Module: soma.aims

Here are listed members (classes, functions) of the soma.aims module. Note that this module is mainly a binding of the C++ aimsdata library, and corresponds to a C++ namespace. Thus once soma.aimsalgo is also imported, the namespace is fed with more classes. As a result the list here includes members from both libraries.

The aims module allows access to the AIMS library in python.

• organization: NeuroSpin and former IFR 49

• license: CeCILL-B (a free licence comparable to BSD)

Comptibility and requirements

Since version 4.5.1 both Python 2 (2.7 and higher) and Python 3 (3.4 and higher) are supported. However as the module contains compiled code (python / C++ bindings) using specific python C interfaces (APIs/ABIs), PyAIMS has to be compiled separately for a given version of python.

PyAIMS also has bindings to the numpy library, allowing easy array manipulations. This also involves constraints on the Numpy ABI version: once PyAims is compiled, it is not possible to swith numpy to a different version featuring a different ABI (which pip often does without warning, unfortunately).

Most of it is a set of direct bindings to the AIMS C++ library API. But a few classes have been customized or specially written to make easy links to the python world. See also the small AIMS C++ developer doc.

aims contains mainly the AIMS and carto data structures and IO system. It covers several C++ libraries: cartobase, cartodata, graph, aimsdata, plus some C++ classes from the standard library (like std::vector)

Main classes

• Reader and Writer for the generic IO system, which allows to read and write everything, and which can be, in most cases, replaced with the more convenient global read() and write() functions. Finder is also part of the IO system to identify files and get information about them.

• Volume_<type>: volumes. An important feature of Volumes is the link with the numpy.ndarray arrays, so all the power of numpy can be used to work on volumes. See for instance Volume_FLOAT. Volumes of various types can be build using the convenience factory function Volume(). Note that the older classes AimsData are deprecated in the C++ library and have been removed from the python bindings in Aims 5.1.

• carto.GenericObject: the dynamic C++ generic object which behaves much like a python object, and its proxy Object which should always be used to access a GenericObject

• AimsVector_<type>_<size> for fixed-size vectors, and their aliases for points: Point3df, Point2df, Point3d

• vector_<type>, set_<type>, list_<type>, map_<type1>_<type2> provide bindings to the C++ std::vector, std::list, std::set, std::map template classes and easy conversions from / to python lists

• rc_ptr_<type>: bridge with C++ reference counters, which should interact quite well, and most of the time transparently, with python reference counting

• BucketMap_VOID: list of voxels. Created using the factory function BucketMap()

• AimsTimeSurface_<polygons_size>_<texture_type=VOID>: meshes, and the factory function AimsTimeSurface(). See for instance AimsTimeSurface_3_VOID.

• TimeTexture_<type>: textures to map on meshes, and the factory function TimeTexture().

• Graph

• Tree

• AffineTransformation3d: the transformation class that allows referential conversions

• Converter_<type1>_<type2> and ShallowConverter_<type1>_<type2>: conversions between data types (mainly volume types). See the factory functions Converter() and ShallowConverter()

• a few algorithms will be added

class soma.aims.AffineTransformation3d(*args)

Bases: Transformation3d

affine()

fromColumnVector()

fromMatrix(value)

header()

inverse()

isDirect()

isIdentity()

Test if the transformation can safely be omitted

This method must only return true if the transformation behaves exactly like an identity transformation (notably, the transform methods will always return the input coordinates unchanged).

NOTE: Implementors of derived classes may choose to always return false if a test would be difficult to implement or expensive to run.

rotation()

rotationaroundx()

rotationaroundy()

rotationaroundz()

scale()

setRotationAffine()

setToIdentity()

setTranslation()

toColumnVector()

toMatrix()

This function return a copy of the transformation matrix

toVector()

transformDouble()

transformFloat()

transformNormal()

transformNormalDouble()

transformNormalFloat()

transformNormalPoint3dd()

transformNormalPoint3df()

transformPoint3d()

transformPoint3dd()

transformPoint3df()

transformUnitNormal()

transformVector()

transformVectorDouble()

transformVectorFloat()

transformVectorPoint3dd()

transformVectorPoint3df()

translation()

class soma.aims.AimsApplication

Bases: wrapper

initialize()

verbose()

soma.aims.AimsConnectedComponent()

void AimsConnectedComponent(data, connectivity, valids, backgrnd=0,

bin=True, minSize=0, numMax=0, verbose=True)

Connected components extraction. The function modifies the input data, and does not return a new one.

Parameters:

• data (Volume_S16 instance) – data will be modified during the process.

• connectivity (Connectivity.Type enum code) –

• valids (dict short: size_t) –

• backgrnd (short) –

• bin (bool (optional)) –

• minSize (size_t (optional)) –

• numMax (size_t (optional)) –

• verbose (bool (optional)) –

void AimsConnectedComponent(data, connectivity, backgrnd=0, bin=True,

minSize=0, maxSize=0, numMax=0, verbose=True)

Connected components extraction. The function modifies the input data, and does not return a new one.

Parameters:

• data (Volume_S16 instance) – data will be modified during the process.

• connectivity (Connectivity.Type enum code) –

• backgrnd (short) –

• bin (bool (optional)) –

• minsize (size_t (optional)) –

• maxSize (size_t (optional)) –

• numMax (size_t (optional)) –

• verbose (bool (optional)) –

void AimsConnectedComponent(data, connectivity, backgrnd=0, bin=True,

minSize=0, maxSize=0, numMax=0, verbose=True)

Connected components extraction, Bucket version. The function modifies the input data, and does not return a new one.

Parameters:

• data (BucketMap_S16 instance) – data will be modified during the process.

• connectivity (Connectivity.Type enum code) –

• backgrnd (short) –

• bin (bool (optional)) –

• minsize (size_t (optional)) –

• maxsize (size_t (optional)) –

• numMax (size_t (optional)) –

• verbose (bool (optional)) –

void AimsConnectedComponent(data, connectivity, valids, backgrnd=0,

bin=True, minSize=0, numMax=0, verbose=True)

Connected components extraction. The function modifies the input data, and does not return a new one.

Parameters:

• data (Volume_U16 instance) – data will be modified during the process.

• connectivity (Connectivity.Type enum code) –

• valids (dict unsigned short: size_t) –

• backgrnd (unsigned short) –

• bin (bool (optional)) –

• minSize (size_t (optional)) –

• numMax (size_t (optional)) –

• verbose (bool (optional)) –

void AimsConnectedComponent(data, connectivity, backgrnd=0, bin=True,

minSize=0, maxSize=0, numMax=0, verbose=True)

Connected components extraction. The function modifies the input data, and does not return a new one.

Parameters:

• data (Volume_U16 instance) – data will be modified during the process.

• connectivity (Connectivity.Type enum code) –

• backgrnd (unsigned short) –

• bin (bool (optional)) –

• minsize (size_t (optional)) –

• maxSize (size_t (optional)) –

• numMax (size_t (optional)) –

• verbose (bool (optional)) –

void AimsConnectedComponent(data, connectivity, backgrnd=0, bin=True,

minSize=0, maxSize=0, numMax=0, verbose=True)

Connected components extraction, Bucket version. The function modifies the input data, and does not return a new one.

Parameters:

• data (BucketMap_U16 instance) – data will be modified during the process.

• connectivity (Connectivity.Type enum code) –

• backgrnd (unsigned short) –

• bin (bool (optional)) –

• minsize (size_t (optional)) –

• maxsize (size_t (optional)) –

• numMax (size_t (optional)) –

• verbose (bool (optional)) –

void AimsConnectedComponent(data, connectivity, valids, backgrnd=0,

bin=True, minSize=0, numMax=0, verbose=True)

Connected components extraction. The function modifies the input data, and does not return a new one.

Parameters:

• data (Volume_S32 instance) – data will be modified during the process.

• connectivity (Connectivity.Type enum code) –

• valids (dict int: size_t) –

• backgrnd (int) –

• bin (bool (optional)) –

• minSize (size_t (optional)) –

• numMax (size_t (optional)) –

• verbose (bool (optional)) –

void AimsConnectedComponent(data, connectivity, backgrnd=0, bin=True,

minSize=0, maxSize=0, numMax=0, verbose=True)

Connected components extraction. The function modifies the input data, and does not return a new one.

Parameters:

• data (Volume_S32 instance) – data will be modified during the process.

• connectivity (Connectivity.Type enum code) –

• backgrnd (int) –

• bin (bool (optional)) –

• minsize (size_t (optional)) –

• maxSize (size_t (optional)) –

• numMax (size_t (optional)) –

• verbose (bool (optional)) –

void AimsConnectedComponent(data, connectivity, backgrnd=0, bin=True,

minSize=0, maxSize=0, numMax=0, verbose=True)

Connected components extraction, Bucket version. The function modifies the input data, and does not return a new one.

Parameters:

• data (BucketMap_S32 instance) – data will be modified during the process.

• connectivity (Connectivity.Type enum code) –

• backgrnd (int) –

• bin (bool (optional)) –

• minsize (size_t (optional)) –

• maxsize (size_t (optional)) –

• numMax (size_t (optional)) –

• verbose (bool (optional)) –

void AimsConnectedComponent(data, connectivity, valids, backgrnd=0,

bin=True, minSize=0, numMax=0, verbose=True)

Connected components extraction. The function modifies the input data, and does not return a new one.

Parameters:

• data (Volume_U32 instance) – data will be modified during the process.

• connectivity (Connectivity.Type enum code) –

• valids (dict unsigned: size_t) –

• backgrnd (unsigned) –

• bin (bool (optional)) –

• minSize (size_t (optional)) –

• numMax (size_t (optional)) –

• verbose (bool (optional)) –

void AimsConnectedComponent(data, connectivity, backgrnd=0, bin=True,

minSize=0, maxSize=0, numMax=0, verbose=True)

Connected components extraction. The function modifies the input data, and does not return a new one.

Parameters:

• data (Volume_U32 instance) – data will be modified during the process.

• connectivity (Connectivity.Type enum code) –

• backgrnd (unsigned) –

• bin (bool (optional)) –

• minsize (size_t (optional)) –

• maxSize (size_t (optional)) –

• numMax (size_t (optional)) –

• verbose (bool (optional)) –

void AimsConnectedComponent(data, connectivity, backgrnd=0, bin=True,

minSize=0, maxSize=0, numMax=0, verbose=True)

Connected components extraction, Bucket version. The function modifies the input data, and does not return a new one.

Parameters:

• data (BucketMap_U32 instance) – data will be modified during the process.

• connectivity (Connectivity.Type enum code) –

• backgrnd (unsigned) –

• bin (bool (optional)) –

• minsize (size_t (optional)) –

• maxsize (size_t (optional)) –

• numMax (size_t (optional)) –

• verbose (bool (optional)) –

class soma.aims.AimsGraphReader

Bases: wrapper

readElements()

setExcludeFilter()

setReadFilter()

class soma.aims.AimsGraphWriter

Bases: wrapper

Global = 1

Keep = 0

Local = 2

class SavingMode

Bases: int

writeElements()

class soma.aims.AimsHSV

Bases: wrapper

hue()

saturation()

value()

class soma.aims.AimsMerge_S16_S16

Bases: wrapper

class soma.aims.AimsRGB

Bases: wrapper

blue()

green()

red()

class soma.aims.AimsRGBA

Bases: wrapper

alpha()

blue()

green()

red()

soma.aims.AimsSurfaceTriangle

alias of AimsTimeSurface_3_VOID

soma.aims.AimsThreshold(*args, **kwargs)

Create a AimsThreshold instance from input and output types. Types may be passed as keyword arguments intype and outtype, or dtype if both are the same. Otherwise the arguments are parsed to find types arguments. Types may be specified as allowed by typeCode().

Other arguments are otherwise passed to the constructor of the underlying threshold object. See for instance: soma.aims.AimsThreshold_S16_S16.

class soma.aims.AimsThreshold_FLOAT_S16

Bases: wrapper

AimsThreshold_FLOAT_S16(ttype, th1, th2=0,

background=0)

Thresholding types are specified as the soma.aims.threshold_t enum. Values are:

• AIMS_LOWER_THAN

• AIMS_LOWER_OR_EQUAL_TO

• AIMS_GREATER_THAN

• AIMS_GREATER_OR_EQUAL_TO

• AIMS_EQUAL_TO

• AIMS_DIFFER

• AIMS_BETWEEN

• AIMS_OUTSIDE

• AIMS_BETWEEN_EXCLUDE_LOWER_BOUND

• AIMS_BETWEEN_EXCLUDE_HIGHER_BOUND

• AIMS_BETWEEN_EXCLUDE_BOUNDS

• AIMS_OUTSIDE_INCLUDE_LOWER_BOUND

• AIMS_OUTSIDE_INCLUDE_HIGHER_BOUND

• AIMS_OUTSIDE_INCLUDE_BOUNDS

Use:

thresholded_vol = threshold(volume)

Apply non-binary thresholding: voxels passing the theshold are left with their initial value.

thresholded_vol = threshold.bin(volume)

Apply binary thresholding: voxels passing the theshold are set to a constant value – which one ?

Parameters:

• ttype (soma.aims.threshold_t enum) – thresholding type (see above)

• th1 (float) – first (main) threshold

• th2 (float) – second threshold (in case of double thresholding)

• background (float) – value set to elements not passing the threshold condition

• volume (Volume_S16) – input volume to be thresholded

Returns:

thresholded_vol – thresholded volume

Return type:

rc_ptr_Volume_FLOAT

thresholded_vol = threshold(volume)

Apply non-binary thresholding: voxels passing the theshold are left with their initial value.

Parameters:

volume (Volume_S16) – input volume to be thresholded

Returns:

thresholded_vol – thresholded volume

Return type:

rc_ptr_Volume_FLOAT

bin()

thresholded_vol = threshold.bin(volume)

Apply binary thresholding: voxels passing the theshold are set to a constant value – which one ?

Parameters:

volume (Volume_FLOAT) – input volume to be thresholded

Returns:

thresholded_vol – thresholded volume

Return type:

rc_ptr_Volume_S16

class soma.aims.AimsThreshold_S16_S16

Bases: wrapper

AimsThreshold_S16_S16(ttype, th1, th2=0,

background=0)

Thresholding types are specified as the soma.aims.threshold_t enum. Values are:

• AIMS_LOWER_THAN

• AIMS_LOWER_OR_EQUAL_TO

• AIMS_GREATER_THAN

• AIMS_GREATER_OR_EQUAL_TO

• AIMS_EQUAL_TO

• AIMS_DIFFER

• AIMS_BETWEEN

• AIMS_OUTSIDE

• AIMS_BETWEEN_EXCLUDE_LOWER_BOUND

• AIMS_BETWEEN_EXCLUDE_HIGHER_BOUND

• AIMS_BETWEEN_EXCLUDE_BOUNDS

• AIMS_OUTSIDE_INCLUDE_LOWER_BOUND

• AIMS_OUTSIDE_INCLUDE_HIGHER_BOUND

• AIMS_OUTSIDE_INCLUDE_BOUNDS

Use:

thresholded_vol = threshold(volume)

Apply non-binary thresholding: voxels passing the theshold are left with their initial value.

thresholded_vol = threshold.bin(volume)

Apply binary thresholding: voxels passing the theshold are set to a constant value – which one ?

Parameters:

• ttype (soma.aims.threshold_t enum) – thresholding type (see above)

• th1 (short) – first (main) threshold

• th2 (short) – second threshold (in case of double thresholding)

• background (short) – value set to elements not passing the threshold condition

• volume (Volume_S16) – input volume to be thresholded

Returns:

thresholded_vol – thresholded volume

Return type:

rc_ptr_Volume_S16

thresholded_vol = threshold(volume)

Apply non-binary thresholding: voxels passing the theshold are left with their initial value.

Parameters:

volume (Volume_S16) – input volume to be thresholded

Returns:

thresholded_vol – thresholded volume

Return type:

rc_ptr_Volume_S16

bin()

thresholded_vol = threshold.bin(volume)

Apply binary thresholding: voxels passing the theshold are set to a constant value – which one ?

Parameters:

volume (Volume_S16) – input volume to be thresholded

Returns:

thresholded_vol – thresholded volume

Return type:

rc_ptr_Volume_S16

soma.aims.AimsTimeSurface(*args, **kwargs)

Create an instance of Aims mesh (AimsTimeSurface_<dim>_<dtype>) from a dimension parameter, or copies a mesh, or build it from arrays.

See for instance AimsTimeSurface_3_VOID

Usages:

mesh1 = AimsTimeSurface()
mesh2 = AimsTimeSurface(3)
mesh3 = AimsTimeSurface(3, 'VOID')
mesh4 = AimsTimeSurface(3, dtype='VOID')
mesh5 = AimsTimeSurface(dim=3, dtype='VOID')

mesh6 = AimsTimeSurface(mesh)

mesh7 = AimsTimeSurface(vertices=[[1,2,3], [3,4,5.6]],
                        polygons=[[0,1]])
mesh8 = AimsTimeSurface([[1,2,3], [3,4,5.6]], polygons=[[0,1]])
mesh9 = AimsTimeSurface([[1,2,3], [3,4,5.6]], None, [[0,1]])
mesh10 = AimsTimeSurface([[1,2,3], [3,4,5.6]], [[0,1]], normals=[])

soma.aims.AimsTimeSurface_2

alias of AimsTimeSurface_2_VOID

class soma.aims.AimsTimeSurface_2_FLOAT(*args)

Bases: RCObject

erase()

fromObject()

header()

The header contains all meta-data.

keys()

normal()

polygon()

size()

texture()

updateNormals()

vertex()

class soma.aims.AimsTimeSurface_2_POINT2DF(*args)

Bases: RCObject

erase()

fromObject()

header()

The header contains all meta-data.

keys()

normal()

polygon()

size()

texture()

updateNormals()

vertex()

class soma.aims.AimsTimeSurface_2_VOID(*args)

Bases: RCObject

erase()

fromObject()

header()

The header contains all meta-data.

keys()

normal()

polygon()

size()

texture()

updateNormals()

vertex()

soma.aims.AimsTimeSurface_3

alias of AimsTimeSurface_3_VOID

class soma.aims.AimsTimeSurface_3_FLOAT(*args)

Bases: RCObject

erase()

fromObject()

header()

The header contains all meta-data.

keys()

normal()

polygon()

size()

texture()

updateNormals()

vertex()

class soma.aims.AimsTimeSurface_3_POINT2DF(*args)

Bases: RCObject

erase()

fromObject()

header()

The header contains all meta-data.

keys()

normal()

polygon()

size()

texture()

updateNormals()

vertex()

class soma.aims.AimsTimeSurface_3_VOID(*args)

Bases: RCObject

erase()

fromObject()

header()

The header contains all meta-data.

keys()

normal()

polygon()

size()

texture()

updateNormals()

vertex()

soma.aims.AimsTimeSurface_4

alias of AimsTimeSurface_4_VOID

class soma.aims.AimsTimeSurface_4_FLOAT(*args)

Bases: RCObject

erase()

fromObject()

header()

The header contains all meta-data.

keys()

normal()

polygon()

size()

texture()

updateNormals()

vertex()

class soma.aims.AimsTimeSurface_4_POINT2DF(*args)

Bases: RCObject

erase()

fromObject()

header()

The header contains all meta-data.

keys()

normal()

polygon()

size()

texture()

updateNormals()

vertex()

class soma.aims.AimsTimeSurface_4_VOID(*args)

Bases: RCObject

erase()

fromObject()

header()

The header contains all meta-data.

keys()

normal()

polygon()

size()

texture()

updateNormals()

vertex()

soma.aims.AimsVector(*args, **kwargs)

Create an AimsVector instance from type and dimension arguments. Types may be passed as the keyword argument dtype. Otherwise the arguments are parsed to find types arguments. Dimension should be passed as the keyword argument dim, or is guessed from the input value(s).

Types may be specified as allowed by typeCode().

If unspecified, type is guessed from the 1st element of the vector data.

class soma.aims.AimsVector_DOUBLE_2

Bases: wrapper

arraydata()

assign()

crossed()

dnorm()

dnorm2()

dot()

fromObject()

isNull()

item()

items()

list()

norm()

norm2()

normalize()

property np

The np property is a shortcut to the __array__ method. Thus:

something.np

is a handier equivalent to:

numpy.asarray(something)

setItems()

class soma.aims.AimsVector_DOUBLE_3

Bases: wrapper

arraydata()

assign()

crossed()

dnorm()

dnorm2()

dot()

fromObject()

isNull()

item()

items()

list()

norm()

norm2()

normalize()

property np

The np property is a shortcut to the __array__ method. Thus:

something.np

is a handier equivalent to:

numpy.asarray(something)

setItems()

class soma.aims.AimsVector_DOUBLE_4

Bases: wrapper

arraydata()

assign()

crossed()

dnorm()

dnorm2()

dot()

fromObject()

isNull()

item()

items()

list()

norm()

norm2()

normalize()

property np

The np property is a shortcut to the __array__ method. Thus:

something.np

is a handier equivalent to:

numpy.asarray(something)

setItems()

class soma.aims.AimsVector_FLOAT_2

Bases: wrapper

arraydata()

assign()

crossed()

dnorm()

dnorm2()

dot()

fromObject()

isNull()

item()

items()

list()

norm()

norm2()

normalize()

property np

The np property is a shortcut to the __array__ method. Thus:

something.np

is a handier equivalent to:

numpy.asarray(something)

setItems()

class soma.aims.AimsVector_FLOAT_3

Bases: wrapper

This class wraps an aims Point3df aka AimsVector<3, float> use the method items() to get a tuple out of it use setItems(Point3df) to affect new values

arraydata()

assign()

crossed()

dnorm()

dnorm2()

dot()

fromObject()

isNull()

item()

items()

list()

norm()

norm2()

normalize()

property np

The np property is a shortcut to the __array__ method. Thus:

something.np

is a handier equivalent to:

numpy.asarray(something)

setItems()

class soma.aims.AimsVector_FLOAT_4

Bases: wrapper

arraydata()

assign()

crossed()

dnorm()

dnorm2()

dot()

fromObject()

isNull()

item()

items()

list()

norm()

norm2()

normalize()

property np

The np property is a shortcut to the __array__ method. Thus:

something.np

is a handier equivalent to:

numpy.asarray(something)

setItems()

class soma.aims.AimsVector_S16_2

Bases: wrapper

arraydata()

assign()

crossed()

dnorm()

dnorm2()

dot()

fromObject()

isNull()

item()

items()

list()

norm()

norm2()

normalize()

property np

The np property is a shortcut to the __array__ method. Thus:

something.np

is a handier equivalent to:

numpy.asarray(something)

setItems()

class soma.aims.AimsVector_S16_3

Bases: wrapper

arraydata()

assign()

crossed()

dnorm()

dnorm2()

dot()

fromObject()

isNull()

item()

items()

list()

norm()

norm2()

normalize()

property np

The np property is a shortcut to the __array__ method. Thus:

something.np

is a handier equivalent to:

numpy.asarray(something)

setItems()

class soma.aims.AimsVector_S16_4

Bases: wrapper

arraydata()

assign()

crossed()

dnorm()

dnorm2()

dot()

fromObject()

isNull()

item()

items()

list()

norm()

norm2()

normalize()

property np

The np property is a shortcut to the __array__ method. Thus:

something.np

is a handier equivalent to:

numpy.asarray(something)

setItems()

class soma.aims.AimsVector_S32_2

Bases: wrapper

arraydata()

assign()

crossed()

dnorm()

dnorm2()

dot()

fromObject()

isNull()

item()

items()

list()

norm()

norm2()

normalize()

property np

The np property is a shortcut to the __array__ method. Thus:

something.np

is a handier equivalent to:

numpy.asarray(something)

setItems()

class soma.aims.AimsVector_S32_3

Bases: wrapper

arraydata()

assign()

crossed()

dnorm()

dnorm2()

dot()

fromObject()

isNull()

item()

items()

list()

norm()

norm2()

normalize()

property np

The np property is a shortcut to the __array__ method. Thus:

something.np

is a handier equivalent to:

numpy.asarray(something)

setItems()

class soma.aims.AimsVector_S32_4

Bases: wrapper

arraydata()

assign()

crossed()

dnorm()

dnorm2()

dot()

fromObject()

isNull()

item()

items()

list()

norm()

norm2()

normalize()

property np

The np property is a shortcut to the __array__ method. Thus:

something.np

is a handier equivalent to:

numpy.asarray(something)

setItems()

class soma.aims.AimsVector_S64_2

Bases: wrapper

arraydata()

assign()

crossed()

dnorm()

dnorm2()

dot()

fromObject()

isNull()

item()

items()

list()

norm()

norm2()

normalize()

property np

The np property is a shortcut to the __array__ method. Thus:

something.np

is a handier equivalent to:

numpy.asarray(something)

setItems()

class soma.aims.AimsVector_S64_3

Bases: wrapper

arraydata()

assign()

crossed()

dnorm()

dnorm2()

dot()

fromObject()

isNull()

item()

items()

list()

norm()

norm2()

normalize()

property np

The np property is a shortcut to the __array__ method. Thus:

something.np

is a handier equivalent to:

numpy.asarray(something)

setItems()

class soma.aims.AimsVector_S64_4

Bases: wrapper

arraydata()

assign()

crossed()

dnorm()

dnorm2()

dot()

fromObject()

isNull()

item()

items()

list()

norm()

norm2()

normalize()

property np

The np property is a shortcut to the __array__ method. Thus:

something.np

is a handier equivalent to:

numpy.asarray(something)

setItems()

class soma.aims.AimsVector_U32_2

Bases: wrapper

arraydata()

assign()

crossed()

dnorm()

dnorm2()

dot()

fromObject()

isNull()

item()

items()

list()

norm()

norm2()

normalize()

property np

The np property is a shortcut to the __array__ method. Thus:

something.np

is a handier equivalent to:

numpy.asarray(something)

setItems()

class soma.aims.AimsVector_U32_3

Bases: wrapper

arraydata()

assign()

crossed()

dnorm()

dnorm2()

dot()

fromObject()

isNull()

item()

items()

list()

norm()

norm2()

normalize()

property np

The np property is a shortcut to the __array__ method. Thus:

something.np

is a handier equivalent to:

numpy.asarray(something)

setItems()

class soma.aims.AimsVector_U32_4

Bases: wrapper

arraydata()

assign()

crossed()

dnorm()

dnorm2()

dot()

fromObject()

isNull()

item()

items()

list()

norm()

norm2()

normalize()

property np

The np property is a shortcut to the __array__ method. Thus:

something.np

is a handier equivalent to:

numpy.asarray(something)

setItems()

exception soma.aims.AssertionError

Bases: StdException

class soma.aims.BorderFiller_BOOL

Bases: wrapper

fillConstant()

static void fillConstant( rc_ptr_Volume_BOOL data,

const bool & value = 0, bool unread_only = false )

Fills volume border with a constant value. The function modifies the input data, and does not return a new one.

Parameters:

• data (Volume_BOOL instance to fill border.) –

• value (bool value to fill border with (optional)) – Default is 0.

• unread_only (bool (optional)) – For partial reading, fill the data only where it has not been read. Default is False

fillMedian()

static void fillMedian( rc_ptr_Volume_BOOL data,

Point4dl size = Point4dl(-1,-1,-1,-1), bool unreadOnly = false )

Fills the border with a median value. The median value is processed in the inside border. The function modifies the input data, and does not return a new one.

Parameters:

• data (Volume_BOOL instance to fill border.) –

• size (Point4dl size of inside border to use to define median value) – [-1,-1,-1,-1] means that the median value is processed in the inside border of equal outside border size. if the outside border is of size (2, 2, 0) in dimensions x, y, z, the inside border is also of size (2, 2, 0) (optional). Default is [-1,-1,-1,-1].

• unread_only (bool (optional)) – For partial reading, fill the data only where it has not been read. Default is False.

fillMirror()

static void fillMirror( rc_ptr_Volume_BOOL data,

bool unreadOnly = false )

Fills the border mirroring the inside border. The function modifies the input data, and does not return a new one.

Parameters:

• data (Volume_BOOL instance to fill border.) –

• unread_only (bool (optional)) – For partial reading, fill the data only where it has not been read. Default is False.

fillNearest()

static void fillNearest( rc_ptr_Volume_BOOL data,

bool unreadOnly = false )

Fills the border with the nearest inside voxel value. The function modifies the input data, and does not return a new one.

Parameters:

• data (Volume_BOOL instance to fill border.) –

• unread_only (bool (optional)) – For partial reading, fill the data only where it has not been read. Default is False.

class soma.aims.BorderFiller_DOUBLE

Bases: wrapper

fillConstant()

static void fillConstant( rc_ptr_Volume_DOUBLE data,

const double & value = 0, bool unread_only = false )

Fills volume border with a constant value. The function modifies the input data, and does not return a new one.

Parameters:

• data (Volume_DOUBLE instance to fill border.) –

• value (double value to fill border with (optional)) – Default is 0.

• unread_only (bool (optional)) – For partial reading, fill the data only where it has not been read. Default is False

fillMedian()

static void fillMedian( rc_ptr_Volume_DOUBLE data,

Point4dl size = Point4dl(-1,-1,-1,-1), bool unreadOnly = false )

Fills the border with a median value. The median value is processed in the inside border. The function modifies the input data, and does not return a new one.

Parameters:

• data (Volume_DOUBLE instance to fill border.) –

• size (Point4dl size of inside border to use to define median value) – [-1,-1,-1,-1] means that the median value is processed in the inside border of equal outside border size. if the outside border is of size (2, 2, 0) in dimensions x, y, z, the inside border is also of size (2, 2, 0) (optional). Default is [-1,-1,-1,-1].

• unread_only (bool (optional)) – For partial reading, fill the data only where it has not been read. Default is False.

fillMirror()

static void fillMirror( rc_ptr_Volume_DOUBLE data,

bool unreadOnly = false )

Fills the border mirroring the inside border. The function modifies the input data, and does not return a new one.

Parameters:

• data (Volume_DOUBLE instance to fill border.) –

• unread_only (bool (optional)) – For partial reading, fill the data only where it has not been read. Default is False.

fillNearest()

static void fillNearest( rc_ptr_Volume_DOUBLE data,

bool unreadOnly = false )

Fills the border with the nearest inside voxel value. The function modifies the input data, and does not return a new one.

Parameters:

• data (Volume_DOUBLE instance to fill border.) –

• unread_only (bool (optional)) – For partial reading, fill the data only where it has not been read. Default is False.

class soma.aims.BorderFiller_FLOAT

Bases: wrapper

fillConstant()

static void fillConstant( rc_ptr_Volume_FLOAT data,

const float & value = 0, bool unread_only = false )

Fills volume border with a constant value. The function modifies the input data, and does not return a new one.

Parameters:

• data (Volume_FLOAT instance to fill border.) –

• value (float value to fill border with (optional)) – Default is 0.

• unread_only (bool (optional)) – For partial reading, fill the data only where it has not been read. Default is False

fillMedian()

static void fillMedian( rc_ptr_Volume_FLOAT data,

Point4dl size = Point4dl(-1,-1,-1,-1), bool unreadOnly = false )

Fills the border with a median value. The median value is processed in the inside border. The function modifies the input data, and does not return a new one.

Parameters:

• data (Volume_FLOAT instance to fill border.) –

• size (Point4dl size of inside border to use to define median value) – [-1,-1,-1,-1] means that the median value is processed in the inside border of equal outside border size. if the outside border is of size (2, 2, 0) in dimensions x, y, z, the inside border is also of size (2, 2, 0) (optional). Default is [-1,-1,-1,-1].

• unread_only (bool (optional)) – For partial reading, fill the data only where it has not been read. Default is False.

fillMirror()

static void fillMirror( rc_ptr_Volume_FLOAT data,

bool unreadOnly = false )

Fills the border mirroring the inside border. The function modifies the input data, and does not return a new one.

Parameters:

• data (Volume_FLOAT instance to fill border.) –

• unread_only (bool (optional)) – For partial reading, fill the data only where it has not been read. Default is False.

fillNearest()

static void fillNearest( rc_ptr_Volume_FLOAT data,

bool unreadOnly = false )

Fills the border with the nearest inside voxel value. The function modifies the input data, and does not return a new one.

Parameters:

• data (Volume_FLOAT instance to fill border.) –

• unread_only (bool (optional)) – For partial reading, fill the data only where it has not been read. Default is False.

class soma.aims.BorderFiller_RGB

Bases: wrapper

fillConstant()

static void fillConstant( rc_ptr_Volume_RGB data,

const AimsRGB & value = 0, bool unread_only = false )

Fills volume border with a constant value. The function modifies the input data, and does not return a new one.

Parameters:

• data (Volume_RGB instance to fill border.) –

• value (AimsRGB value to fill border with (optional)) – Default is 0.

• unread_only (bool (optional)) – For partial reading, fill the data only where it has not been read. Default is False

fillMedian()

static void fillMedian( rc_ptr_Volume_RGB data,

Point4dl size = Point4dl(-1,-1,-1,-1), bool unreadOnly = false )

Fills the border with a median value. The median value is processed in the inside border. The function modifies the input data, and does not return a new one.

Parameters:

• data (Volume_RGB instance to fill border.) –

• size (Point4dl size of inside border to use to define median value) – [-1,-1,-1,-1] means that the median value is processed in the inside border of equal outside border size. if the outside border is of size (2, 2, 0) in dimensions x, y, z, the inside border is also of size (2, 2, 0) (optional). Default is [-1,-1,-1,-1].

• unread_only (bool (optional)) – For partial reading, fill the data only where it has not been read. Default is False.

fillMirror()

static void fillMirror( rc_ptr_Volume_RGB data,

bool unreadOnly = false )

Fills the border mirroring the inside border. The function modifies the input data, and does not return a new one.

Parameters:

• data (Volume_RGB instance to fill border.) –

• unread_only (bool (optional)) – For partial reading, fill the data only where it has not been read. Default is False.

fillNearest()

static void fillNearest( rc_ptr_Volume_RGB data,

bool unreadOnly = false )

Fills the border with the nearest inside voxel value. The function modifies the input data, and does not return a new one.

Parameters:

• data (Volume_RGB instance to fill border.) –

• unread_only (bool (optional)) – For partial reading, fill the data only where it has not been read. Default is False.

class soma.aims.BorderFiller_RGBA

Bases: wrapper

fillConstant()

static void fillConstant( rc_ptr_Volume_RGBA data,

const AimsRGBA & value = 0, bool unread_only = false )

Fills volume border with a constant value. The function modifies the input data, and does not return a new one.

Parameters:

• data (Volume_RGBA instance to fill border.) –

• value (AimsRGBA value to fill border with (optional)) – Default is 0.

• unread_only (bool (optional)) – For partial reading, fill the data only where it has not been read. Default is False

fillMedian()

static void fillMedian( rc_ptr_Volume_RGBA data,

Point4dl size = Point4dl(-1,-1,-1,-1), bool unreadOnly = false )

Fills the border with a median value. The median value is processed in the inside border. The function modifies the input data, and does not return a new one.

Parameters:

• data (Volume_RGBA instance to fill border.) –

• size (Point4dl size of inside border to use to define median value) – [-1,-1,-1,-1] means that the median value is processed in the inside border of equal outside border size. if the outside border is of size (2, 2, 0) in dimensions x, y, z, the inside border is also of size (2, 2, 0) (optional). Default is [-1,-1,-1,-1].

• unread_only (bool (optional)) – For partial reading, fill the data only where it has not been read. Default is False.

fillMirror()

static void fillMirror( rc_ptr_Volume_RGBA data,

bool unreadOnly = false )

Fills the border mirroring the inside border. The function modifies the input data, and does not return a new one.

Parameters:

• data (Volume_RGBA instance to fill border.) –

• unread_only (bool (optional)) – For partial reading, fill the data only where it has not been read. Default is False.

fillNearest()

static void fillNearest( rc_ptr_Volume_RGBA data,

bool unreadOnly = false )

Fills the border with the nearest inside voxel value. The function modifies the input data, and does not return a new one.

Parameters:

• data (Volume_RGBA instance to fill border.) –

• unread_only (bool (optional)) – For partial reading, fill the data only where it has not been read. Default is False.

class soma.aims.BorderFiller_S16

Bases: wrapper

fillConstant()

static void fillConstant( rc_ptr_Volume_S16 data,

const short & value = 0, bool unread_only = false )

Fills volume border with a constant value. The function modifies the input data, and does not return a new one.

Parameters:

• data (Volume_S16 instance to fill border.) –

• value (short value to fill border with (optional)) – Default is 0.

• unread_only (bool (optional)) – For partial reading, fill the data only where it has not been read. Default is False

fillMedian()

static void fillMedian( rc_ptr_Volume_S16 data,

Point4dl size = Point4dl(-1,-1,-1,-1), bool unreadOnly = false )

Fills the border with a median value. The median value is processed in the inside border. The function modifies the input data, and does not return a new one.

Parameters:

• data (Volume_S16 instance to fill border.) –

• size (Point4dl size of inside border to use to define median value) – [-1,-1,-1,-1] means that the median value is processed in the inside border of equal outside border size. if the outside border is of size (2, 2, 0) in dimensions x, y, z, the inside border is also of size (2, 2, 0) (optional). Default is [-1,-1,-1,-1].

• unread_only (bool (optional)) – For partial reading, fill the data only where it has not been read. Default is False.

fillMirror()

static void fillMirror( rc_ptr_Volume_S16 data,

bool unreadOnly = false )

Fills the border mirroring the inside border. The function modifies the input data, and does not return a new one.

Parameters:

• data (Volume_S16 instance to fill border.) –

• unread_only (bool (optional)) – For partial reading, fill the data only where it has not been read. Default is False.

fillNearest()

static void fillNearest( rc_ptr_Volume_S16 data,

bool unreadOnly = false )

Fills the border with the nearest inside voxel value. The function modifies the input data, and does not return a new one.

Parameters:

• data (Volume_S16 instance to fill border.) –

• unread_only (bool (optional)) – For partial reading, fill the data only where it has not been read. Default is False.

class soma.aims.BorderFiller_S32

Bases: wrapper

fillConstant()

static void fillConstant( rc_ptr_Volume_S32 data,

const int & value = 0, bool unread_only = false )

Fills volume border with a constant value. The function modifies the input data, and does not return a new one.

Parameters:

• data (Volume_S32 instance to fill border.) –

• value (int value to fill border with (optional)) – Default is 0.

• unread_only (bool (optional)) – For partial reading, fill the data only where it has not been read. Default is False

fillMedian()

static void fillMedian( rc_ptr_Volume_S32 data,

Point4dl size = Point4dl(-1,-1,-1,-1), bool unreadOnly = false )

Fills the border with a median value. The median value is processed in the inside border. The function modifies the input data, and does not return a new one.

Parameters:

• data (Volume_S32 instance to fill border.) –

• size (Point4dl size of inside border to use to define median value) – [-1,-1,-1,-1] means that the median value is processed in the inside border of equal outside border size. if the outside border is of size (2, 2, 0) in dimensions x, y, z, the inside border is also of size (2, 2, 0) (optional). Default is [-1,-1,-1,-1].

• unread_only (bool (optional)) – For partial reading, fill the data only where it has not been read. Default is False.

fillMirror()

static void fillMirror( rc_ptr_Volume_S32 data,

bool unreadOnly = false )

Fills the border mirroring the inside border. The function modifies the input data, and does not return a new one.

Parameters:

• data (Volume_S32 instance to fill border.) –

• unread_only (bool (optional)) – For partial reading, fill the data only where it has not been read. Default is False.

fillNearest()

static void fillNearest( rc_ptr_Volume_S32 data,

bool unreadOnly = false )

Fills the border with the nearest inside voxel value. The function modifies the input data, and does not return a new one.

Parameters:

• data (Volume_S32 instance to fill border.) –

• unread_only (bool (optional)) – For partial reading, fill the data only where it has not been read. Default is False.

class soma.aims.BorderFiller_U16

Bases: wrapper

fillConstant()

static void fillConstant( rc_ptr_Volume_U16 data,

const unsigned short & value = 0, bool unread_only = false )

Fills volume border with a constant value. The function modifies the input data, and does not return a new one.

Parameters:

• data (Volume_U16 instance to fill border.) –

• value (unsigned short value to fill border with (optional)) – Default is 0.

• unread_only (bool (optional)) – For partial reading, fill the data only where it has not been read. Default is False

fillMedian()

static void fillMedian( rc_ptr_Volume_U16 data,

Point4dl size = Point4dl(-1,-1,-1,-1), bool unreadOnly = false )

Fills the border with a median value. The median value is processed in the inside border. The function modifies the input data, and does not return a new one.

Parameters:

• data (Volume_U16 instance to fill border.) –

• size (Point4dl size of inside border to use to define median value) – [-1,-1,-1,-1] means that the median value is processed in the inside border of equal outside border size. if the outside border is of size (2, 2, 0) in dimensions x, y, z, the inside border is also of size (2, 2, 0) (optional). Default is [-1,-1,-1,-1].

• unread_only (bool (optional)) – For partial reading, fill the data only where it has not been read. Default is False.

fillMirror()

static void fillMirror( rc_ptr_Volume_U16 data,

bool unreadOnly = false )

Fills the border mirroring the inside border. The function modifies the input data, and does not return a new one.

Parameters:

• data (Volume_U16 instance to fill border.) –

• unread_only (bool (optional)) – For partial reading, fill the data only where it has not been read. Default is False.

fillNearest()

static void fillNearest( rc_ptr_Volume_U16 data,

bool unreadOnly = false )

Fills the border with the nearest inside voxel value. The function modifies the input data, and does not return a new one.

Parameters:

• data (Volume_U16 instance to fill border.) –

• unread_only (bool (optional)) – For partial reading, fill the data only where it has not been read. Default is False.

class soma.aims.BorderFiller_U32

Bases: wrapper

fillConstant()

static void fillConstant( rc_ptr_Volume_U32 data,

const unsigned & value = 0, bool unread_only = false )

Fills volume border with a constant value. The function modifies the input data, and does not return a new one.

Parameters:

• data (Volume_U32 instance to fill border.) –

• value (unsigned value to fill border with (optional)) – Default is 0.

• unread_only (bool (optional)) – For partial reading, fill the data only where it has not been read. Default is False

fillMedian()

static void fillMedian( rc_ptr_Volume_U32 data,

Point4dl size = Point4dl(-1,-1,-1,-1), bool unreadOnly = false )

Fills the border with a median value. The median value is processed in the inside border. The function modifies the input data, and does not return a new one.

Parameters:

• data (Volume_U32 instance to fill border.) –

• size (Point4dl size of inside border to use to define median value) – [-1,-1,-1,-1] means that the median value is processed in the inside border of equal outside border size. if the outside border is of size (2, 2, 0) in dimensions x, y, z, the inside border is also of size (2, 2, 0) (optional). Default is [-1,-1,-1,-1].

• unread_only (bool (optional)) – For partial reading, fill the data only where it has not been read. Default is False.

fillMirror()

static void fillMirror( rc_ptr_Volume_U32 data,

bool unreadOnly = false )

Fills the border mirroring the inside border. The function modifies the input data, and does not return a new one.

Parameters:

• data (Volume_U32 instance to fill border.) –

• unread_only (bool (optional)) – For partial reading, fill the data only where it has not been read. Default is False.

fillNearest()

static void fillNearest( rc_ptr_Volume_U32 data,

bool unreadOnly = false )

Fills the border with the nearest inside voxel value. The function modifies the input data, and does not return a new one.

Parameters:

• data (Volume_U32 instance to fill border.) –

• unread_only (bool (optional)) – For partial reading, fill the data only where it has not been read. Default is False.

class soma.aims.BorderFiller_U8

Bases: wrapper

fillConstant()

static void fillConstant( rc_ptr_Volume_U8 data,

const unsigned char & value = 0, bool unread_only = false )

Fills volume border with a constant value. The function modifies the input data, and does not return a new one.

Parameters:

• data (Volume_U8 instance to fill border.) –

• value (unsigned char value to fill border with (optional)) – Default is 0.

• unread_only (bool (optional)) – For partial reading, fill the data only where it has not been read. Default is False

fillMedian()

static void fillMedian( rc_ptr_Volume_U8 data,

Point4dl size = Point4dl(-1,-1,-1,-1), bool unreadOnly = false )

Fills the border with a median value. The median value is processed in the inside border. The function modifies the input data, and does not return a new one.

Parameters:

• data (Volume_U8 instance to fill border.) –

• size (Point4dl size of inside border to use to define median value) – [-1,-1,-1,-1] means that the median value is processed in the inside border of equal outside border size. if the outside border is of size (2, 2, 0) in dimensions x, y, z, the inside border is also of size (2, 2, 0) (optional). Default is [-1,-1,-1,-1].

• unread_only (bool (optional)) – For partial reading, fill the data only where it has not been read. Default is False.

fillMirror()

static void fillMirror( rc_ptr_Volume_U8 data,

bool unreadOnly = false )

Fills the border mirroring the inside border. The function modifies the input data, and does not return a new one.

Parameters:

• data (Volume_U8 instance to fill border.) –

• unread_only (bool (optional)) – For partial reading, fill the data only where it has not been read. Default is False.

fillNearest()

static void fillNearest( rc_ptr_Volume_U8 data,

bool unreadOnly = false )

Fills the border with the nearest inside voxel value. The function modifies the input data, and does not return a new one.

Parameters:

• data (Volume_U8 instance to fill border.) –

• unread_only (bool (optional)) – For partial reading, fill the data only where it has not been read. Default is False.

soma.aims.BucketMap(*args, **kwargs)

Create an instance of Aims bucket (BucketMap_<type>) from a type parameter, which may be specified as the dtype keyword argument, or as one of the arguments if one is identitied as a type.

The default type is ‘VOID’.

Type definitions should match those accepted by typeCode().

class soma.aims.BucketMap_DOUBLE(*args)

Bases: RCObject

class Bucket

Bases: wrapper

clear()

has_key()

items()

iteritems()

keys()

size()

clear()

erase()

fromObject()

header()

The header contains all meta-data.

insert()

items()

iteritems()

keys()

merge()

rcToObject()

setSizeT()

setSizeX()

setSizeXYZT()

setSizeY()

setSizeZ()

size()

sizeT()

sizeX()

sizeY()

sizeZ()

class soma.aims.BucketMap_FLOAT(*args)

Bases: RCObject

class Bucket

Bases: wrapper

clear()

has_key()

items()

iteritems()

keys()

size()

clear()

erase()

fromObject()

header()

The header contains all meta-data.

insert()

items()

iteritems()

keys()

merge()

rcToObject()

setSizeT()

setSizeX()

setSizeXYZT()

setSizeY()

setSizeZ()

size()

sizeT()

sizeX()

sizeY()

sizeZ()

class soma.aims.BucketMap_S16(*args)

Bases: RCObject

class Bucket

Bases: wrapper

clear()

has_key()

items()

iteritems()

keys()

size()

clear()

erase()

fromObject()

header()

The header contains all meta-data.

insert()

items()

iteritems()

keys()

merge()

rcToObject()

setSizeT()

setSizeX()

setSizeXYZT()

setSizeY()

setSizeZ()

size()

sizeT()

sizeX()

sizeY()

sizeZ()

class soma.aims.BucketMap_S32(*args)

Bases: RCObject

class Bucket

Bases: wrapper

clear()

has_key()

items()

iteritems()

keys()

size()

clear()

erase()

fromObject()

header()

The header contains all meta-data.

insert()

items()

iteritems()

keys()

merge()

rcToObject()

setSizeT()

setSizeX()

setSizeXYZT()

setSizeY()

setSizeZ()

size()

sizeT()

sizeX()

sizeY()

sizeZ()

class soma.aims.BucketMap_U16(*args)

Bases: RCObject

class Bucket

Bases: wrapper

clear()

has_key()

items()

iteritems()

keys()

size()

clear()

erase()

fromObject()

header()

The header contains all meta-data.

insert()

items()

iteritems()

keys()

merge()

rcToObject()

setSizeT()

setSizeX()

setSizeXYZT()

setSizeY()

setSizeZ()

size()

sizeT()

sizeX()

sizeY()

sizeZ()

class soma.aims.BucketMap_U32(*args)

Bases: RCObject

class Bucket

Bases: wrapper

clear()

has_key()

items()

iteritems()

keys()

size()

clear()

erase()

fromObject()

header()

The header contains all meta-data.

insert()

items()

iteritems()

keys()

merge()

rcToObject()

setSizeT()

setSizeX()

setSizeXYZT()

setSizeY()

setSizeZ()

size()

sizeT()

sizeX()

sizeY()

sizeZ()

class soma.aims.BucketMap_VOID(*args)

Bases: RCObject

class Bucket

Bases: wrapper

clear()

has_key()

items()

iteritems()

keys()

size()

clear()

erase()

fromObject()

header()

The header contains all meta-data.

insert()

items()

iteritems()

keys()

merge()

rcToObject()

setSizeT()

setSizeX()

setSizeXYZT()

setSizeY()

setSizeZ()

size()

sizeT()

sizeX()

sizeY()

sizeZ()

class soma.aims.BucketUtil

Bases: wrapper

Utility class related to buckets

volumeFromBucket()

volume, offser = BucketUtil.volumeFromBucket(bucket, borderwidth=0,

enable_shift=True)

Bucket to volume conversion. Compared to Converter_BucketMap_Volume, this function has options to handle min bounding box, and allows to have borders.

If enable_shift is False, the volume will start at coordinates (0, 0, 0), without an offset (thus the volume may be much lager than needed, or may not contain the whole bucket if it has negative coordinates). In such case, pos is not used (thus passing 0 is OK).

volume = BucketUtil.volumeFromBucket(bucket, bbmin, bmax, borderwidth=0)

Bucket to volume conversion. Compared to Converter_BucketMap_Volume, this function has options to handle bounding box, and allows to have borders.

class soma.aims.BundleInfo

Bases: wrapper

id()

name()

class soma.aims.BundleListener

Bases: wrapper

Serial processing of bundles.

BundleListener listens events from a BundleProducer object, typically emitted when a new bundle starts or ends, a fiber starts or ends etc.

To use it, BundleListener has to be subclassed and some of the following methods overloaded: * bundleStarted * bundleTerminated * fiberStarted * fiberTerminated * newFiberPoint * noMoreBundle

To connect the listener to a producer, use BundleProducer::addBundleListener().

Inherited classes may inherit both BundleListener and BundleProducer, if they are part of a processing chain.

bundleStarted(producer, bundle_info)

bundleTerminated(producer, bundle_info)

fiberStarted(producer, bundle_info, fiber_info)

fiberTerminated(producer, bundle_info, fiber_info)

newFiberPoint(producer, bundle_info, fiber_info, point)

noMoreBundle(producer)

class soma.aims.BundleMotion

Bases: BundleProducer, BundleListener

addFiberPoint()

bundleStarted(producer, bundle_info)

bundleTerminated(producer, bundle_info)

fiberStarted(producer, bundle_info, fiber_info)

fiberTerminated(producer, bundle_info, fiber_info)

newFiberPoint(producer, bundle_info, fiber_info, point)

noMoreBundle(producer)

startBundle()

startFiber()

terminateBundle()

terminateFiber()

class soma.aims.BundleProducer

Bases: wrapper

Serial processing of bundles.

BundleProducer emits events to a BundleListener object while walking through a bundles set structure (or a bundles file), typically when a new bundle starts or ends, a fiber starts or ends etc.

To connect the listener to a producer, use BundleProducer::addBundleListener().

Inherited classes may inherit both BundleListener and BundleProducer, if they are part of a processing chain.

addBundleListener(listener)

Connects a BundleProducer to a BunsdleListener.

addFiberPoint()

noMoreBundle()

startBundle()

startFiber()

terminateBundle()

terminateFiber()

class soma.aims.BundleROISelect

Bases: BundleProducer, BundleListener

addFiberPoint()

bundleStarted(producer, bundle_info)

bundleTerminated(producer, bundle_info)

fiberStarted(producer, bundle_info, fiber_info)

fiberTerminated(producer, bundle_info, fiber_info)

newFiberPoint(producer, bundle_info, fiber_info, point)

noMoreBundle(producer)

startBundle()

startFiber()

terminateBundle()

terminateFiber()

class soma.aims.BundleROISplit

Bases: BundleProducer, BundleListener

addFiberPoint()

bundleStarted(producer, bundle_info)

bundleTerminated(producer, bundle_info)

fiberStarted(producer, bundle_info, fiber_info)

fiberTerminated(producer, bundle_info, fiber_info)

newFiberPoint(producer, bundle_info, fiber_info, point)

noMoreBundle(producer)

startBundle()

startFiber()

terminateBundle()

terminateFiber()

class soma.aims.BundleReader

Bases: BundleProducer

Reads a bundles file, and emits events while walking through its data.

BundleReader is a BundleProducer, so can be listened by any BundleListener. It may read several bundles/fibers formats, using a lower-level BundleProducer dedicated to a specific format.

Currently .bundles (AIMS/Connectomist) and .trk (Trackvis) formats are supported.

addFiberPoint()

formatExtensions(format='ALL')

return a set of file extensions associated with the given format. If the format is “ALL” (default) then all extensions of all supported formats are returned. If the format does not exist, an empty set is returned, and no error is issued.

noMoreBundle()

read()

read() is the entry point to fibers processing, and triggers the producer machinery.

startBundle()

startFiber()

supportedFormats()

return a set of fiber tracts formats names supported by the BundlesReader.

terminateBundle()

terminateFiber()

class soma.aims.BundleSampler

Bases: BundleProducer, BundleListener

addFiberPoint()

bundleStarted(producer, bundle_info)

bundleTerminated(producer, bundle_info)

fiberStarted(producer, bundle_info, fiber_info)

fiberTerminated(producer, bundle_info, fiber_info)

newFiberPoint(producer, bundle_info, fiber_info, point)

noMoreBundle(producer)

startBundle()

startFiber()

terminateBundle()

terminateFiber()

class soma.aims.BundleToGraph

Bases: BundleListener, PropertySet

Bundles structure building as a Graph

The Graph structure is used to represent bundles and fibers when we need to keep their complete structure in memory. This structure is especially used for 3D rendering in Anatomist.

BundleToGraph is a BundleListener, thus has to be connected to a BundleProducer to work (typically, a BundleReader).

Note that the BundleProducer / BundleListener system work as processing chains, and allows to keep only a small set of data in memory at one time. The Graph structure, on the contrary, keeps all information in memory, so may need a large amount of memory.

bundleStarted(producer, bundle_info)

bundleTerminated(producer, bundle_info)

fiberStarted(producer, bundle_info, fiber_info)

fiberTerminated(producer, bundle_info, fiber_info)

newFiberPoint(producer, bundle_info, fiber_info, point)

noMoreBundle(producer)

class soma.aims.BundleToGraphWriter

Bases: BundleToGraph

bundleStarted(producer, bundle_info)

bundleTerminated(producer, bundle_info)

fiberStarted(producer, bundle_info, fiber_info)

fiberTerminated(producer, bundle_info, fiber_info)

newFiberPoint(producer, bundle_info, fiber_info, point)

noMoreBundle(producer)

setFileString()

class soma.aims.BundleWriter

Bases: BundleListener, PropertySet

Writes bundles information to a bundles file.

BundleWriter is a BundleListener, thus must be connected to a BundleProducer, and is fed by it.

It will write the .bundles format.

bundleStarted(producer, bundle_info)

bundleTerminated(producer, bundle_info)

fiberStarted(producer, bundle_info, fiber_info)

fiberTerminated(producer, bundle_info, fiber_info)

newFiberPoint(producer, bundle_info, fiber_info, point)

noMoreBundle(producer)

setFileString(filename)

Set the output file name.

class soma.aims.BundlesSlicer

Bases: BundleListener

addBundlesSlicerListener()

bundleStarted(producer, bundle_info)

bundleTerminated(producer, bundle_info)

fiberStarted(producer, bundle_info, fiber_info)

fiberTerminated(producer, bundle_info, fiber_info)

newFiberPoint(producer, bundle_info, fiber_info, point)

noMoreBundle(producer)

class soma.aims.BundlesSlicerListener

Bases: wrapper

newBundleSlice()

noMoreBundleSlice()

startBundleSlicing()

terminateBundleSlicing()

class soma.aims.CiftiTools(matrix, smap={})

Bases: wrapper

Parameters:

• mat (rc_ptr_SparseOrDenseMatrix) – matrix with CIFTI header (typically, read from CIFTI format via aims.read())

• smap (map_STRING_S32) – brain structure name to mesh number map: defaults to the result of defaultBrainStructureToMeshMap()

CIFTI-2 shaped matrices manipulation tools.

This class eases manipulation of matrices (SparseOrDenseMatrix) with CIFTI information in their header. CIFTI information specify the nature of data contained in the matrix, and can bring ROIs or parcellations information.

Mainly one can obtain textures to map matrix information onto meshes. Textures may be ROI information (label textures, TimeTexture_S32), or matrix values textures, possibly expanded onto brain regions (TimeTexture_FLOAT in this case).

brainStructureMap()

buildDimensionObjectFromLabelsTexture()

defaultBrainStructureToMeshMap()

Define the brain structure to mesh mapping: several meshes may be involved in CIFTI data mapping (typically a left hemisphere mesh and a right

Returns:

mesh_map – mesh identifier to index mapping

Return type:

map_STRING_S32

dimensionType()

expandedValueTextureFromDimension(dim, other_dim_index_pos)

Get matrix data in textures, possibly expanded to regions if needed.

Parcels data will be expanded to all vertices of each parcel, etc. The resulting textures can be mapped on appropriate brain meshes.

Parameters:

• dim (int) – dimension in the matrix to get info for

• other_dim_index_pos (vector_S32) – position in fixed dimensions. Actually all dimensions must be specified (the size of this list must match the number of dimensions) but the specified dimension position will not be used (since all values will be extracted in textures), and possibly another one (scalars, series, labels dimension will be extracted in time steps or several textures).

Returns:

textures – Scalar or time series data will be stored in texture timepoints. Labels data will be stored in separate textures because they provide possibly different colormaps. In this case the returned list will have the size meshes_number * labels_number, and will be stored in this order: [mesh0_label0, mesh1_label0, .. meshN_label0, mesh0_label1, ..

meshN_label1, .. mesh0_label0, .. meshN_labelM]

Return type:

list of TimeTexture_FLOAT

getBrainStructureMeshNumberOfNodes()

getBrainStructures(dim, keepSurfaces=True, keepVoxels=True)

Retreive brain structures list in a brain models dimension

Parameters:

• dim (int) – dimension in Cifti matrix

• keepSurfaces (bool) – keep or filter out surface models

• keepVoxels (bool) – keep or filter out voxesl models

Returns:

brain_structures – brain structures names list

Return type:

list of string

getDimensionObject()

getIndicesForBrainStructure(dim, struct_name)

Get the list of indices corresponding to a given brain structure in the matrix, on a given dimension.

getIndicesForSurfaceIndices(dim, surface_num, roi_indices)

Get the list of matrix indices corresponding to a given region on a mesh, for a given dimension.

Parameters:

• dim (int) – matrix dimension

• surface_num (int) – surface number (same as given by brainStructureMap())

• roi_indices (list or array of int) – indices in the surface mesh of vertices if interest

Returns:

indices – list of indices in the matrix

Return type:

vector_S32

isMatchingSurface()

isMatchingSurfaceOrTexture()

isMatchingTexture()

matrix()

roiTextureFromDimension(dim)

Get ROI information for a given matrix dimension.

If the matrix dimension defines ROIs (parcels, brain regions), textures defining these regions are built.

If the matrix dimension defines labels, an empty texture will be created, with appropriate colormap information

If the matrix dimensions defines scalars or series, this function will probably not be useful.

Parameters:

dim (int) – dimension in the matrix to get info for

Returns:

textures – textures of regions, possibly with colormaps in headers, for regions, parcels etc. One texture per mesh. For scalars or series, the list will be empty since no particular ROI description is contained in the header for this dimension.

Return type:

list of TimeTexture_S32

setBrainStructureMap()

setMatrix()

valuesDimNum()

valuesDimSize()

class soma.aims.Connectivity

Bases: wrapper

CONNECTIVITY_18_XYZ = 7

CONNECTIVITY_26_XYZ = 8

CONNECTIVITY_4_XY = 0

CONNECTIVITY_4_XYdiag = 28

CONNECTIVITY_4_XZ = 1

CONNECTIVITY_4_XZdiag = 29

CONNECTIVITY_4_YZ = 2

CONNECTIVITY_4_YZdiag = 30

CONNECTIVITY_5_XYminus = 17

CONNECTIVITY_5_XYplus = 18

CONNECTIVITY_5_XZminus = 21

CONNECTIVITY_5_XZplus = 22

CONNECTIVITY_5_XminusY = 15

CONNECTIVITY_5_XminusZ = 19

CONNECTIVITY_5_XplusY = 16

CONNECTIVITY_5_XplusZ = 20

CONNECTIVITY_5_YZminus = 25

CONNECTIVITY_5_YZplus = 26

CONNECTIVITY_5_YminusZ = 23

CONNECTIVITY_5_YplusZ = 24

CONNECTIVITY_6_XYZ = 3

CONNECTIVITY_8_XY = 4

CONNECTIVITY_8_XYZ = 27

CONNECTIVITY_8_XZ = 5

CONNECTIVITY_8_YZ = 6

CONNECTIVITY_9_XY_Zminus = 9

CONNECTIVITY_9_XY_Zplus = 10

CONNECTIVITY_9_XZ_Yminus = 11

CONNECTIVITY_9_XZ_Yplus = 12

CONNECTIVITY_9_YZ_Xminus = 13

CONNECTIVITY_9_YZ_Xplus = 14

class Type

Bases: int

dir()

nbNeighbors()

offset()

type()

type_from_string()

type_string()

type_to_string()

xyzOffset()

soma.aims.Converter(*args, **kwargs)

Create a Converter instance from input and output types. Types may be passed as keyword arguments intype and outtype, or dtype if both are the same (not very useful for a converter). Otherwise the arguments are parsed to find types arguments.

Types may be specified as allowed by typeCode().

Note that for volumes, the method astype is often more convenient than using a Converter object (with the same result).

class soma.aims.Converter_BucketMap_DOUBLE_rc_ptr_Volume_DOUBLE

Bases: wrapper

Converter classes can be used using the convert() method, or as a callable object:

result = converter(input_data)

Parameters:

input_data (BucketMap_DOUBLE) – data to be converted

Returns:

output data – converted data

Return type:

rc_ptr_Volume_DOUBLE

convert(input_data, output_data)

In-place converson inside existing allocated data

Parameters:

• input_data (BucketMap_DOUBLE) – data to be converted

• output_data (rc_ptr_Volume_DOUBLE) – conversion output will be done into this data

Return type:

None

class soma.aims.Converter_BucketMap_DOUBLE_rc_ptr_Volume_FLOAT

Bases: wrapper

Converter classes can be used using the convert() method, or as a callable object:

result = converter(input_data)

Parameters:

input_data (BucketMap_DOUBLE) – data to be converted

Returns:

output data – converted data

Return type:

rc_ptr_Volume_FLOAT

convert(input_data, output_data)

In-place converson inside existing allocated data

Parameters:

• input_data (BucketMap_DOUBLE) – data to be converted

• output_data (rc_ptr_Volume_FLOAT) – conversion output will be done into this data

Return type:

None

class soma.aims.Converter_BucketMap_DOUBLE_rc_ptr_Volume_S16

Bases: wrapper

Converter classes can be used using the convert() method, or as a callable object:

result = converter(input_data)

Parameters:

input_data (BucketMap_DOUBLE) – data to be converted

Returns:

output data – converted data

Return type:

rc_ptr_Volume_S16

convert(input_data, output_data)

In-place converson inside existing allocated data

Parameters:

• input_data (BucketMap_DOUBLE) – data to be converted

• output_data (rc_ptr_Volume_S16) – conversion output will be done into this data

Return type:

None

class soma.aims.Converter_BucketMap_DOUBLE_rc_ptr_Volume_S32

Bases: wrapper

Converter classes can be used using the convert() method, or as a callable object:

result = converter(input_data)

Parameters:

input_data (BucketMap_DOUBLE) – data to be converted

Returns:

output data – converted data

Return type:

rc_ptr_Volume_S32

convert(input_data, output_data)

In-place converson inside existing allocated data

Parameters:

• input_data (BucketMap_DOUBLE) – data to be converted

• output_data (rc_ptr_Volume_S32) – conversion output will be done into this data

Return type:

None

class soma.aims.Converter_BucketMap_DOUBLE_rc_ptr_Volume_U16

Bases: wrapper

Converter classes can be used using the convert() method, or as a callable object:

result = converter(input_data)

Parameters:

input_data (BucketMap_DOUBLE) – data to be converted

Returns:

output data – converted data

Return type:

rc_ptr_Volume_U16

convert(input_data, output_data)

In-place converson inside existing allocated data

Parameters:

• input_data (BucketMap_DOUBLE) – data to be converted

• output_data (rc_ptr_Volume_U16) – conversion output will be done into this data

Return type:

None

class soma.aims.Converter_BucketMap_DOUBLE_rc_ptr_Volume_U32

Bases: wrapper

Converter classes can be used using the convert() method, or as a callable object:

result = converter(input_data)

Parameters:

input_data (BucketMap_DOUBLE) – data to be converted

Returns:

output data – converted data

Return type:

rc_ptr_Volume_U32

convert(input_data, output_data)

In-place converson inside existing allocated data

Parameters:

• input_data (BucketMap_DOUBLE) – data to be converted

• output_data (rc_ptr_Volume_U32) – conversion output will be done into this data

Return type:

None

class soma.aims.Converter_BucketMap_DOUBLE_rc_ptr_Volume_U8

Bases: wrapper

Converter classes can be used using the convert() method, or as a callable object:

result = converter(input_data)

Parameters:

input_data (BucketMap_DOUBLE) – data to be converted

Returns:

output data – converted data

Return type:

rc_ptr_Volume_U8

convert(input_data, output_data)

In-place converson inside existing allocated data

Parameters:

• input_data (BucketMap_DOUBLE) – data to be converted

• output_data (rc_ptr_Volume_U8) – conversion output will be done into this data

Return type:

None

class soma.aims.Converter_BucketMap_FLOAT_rc_ptr_Volume_DOUBLE

Bases: wrapper

Converter classes can be used using the convert() method, or as a callable object:

result = converter(input_data)

Parameters:

input_data (BucketMap_FLOAT) – data to be converted

Returns:

output data – converted data

Return type:

rc_ptr_Volume_DOUBLE

convert(input_data, output_data)

In-place converson inside existing allocated data

Parameters:

• input_data (BucketMap_FLOAT) – data to be converted

• output_data (rc_ptr_Volume_DOUBLE) – conversion output will be done into this data

Return type:

None

class soma.aims.Converter_BucketMap_FLOAT_rc_ptr_Volume_FLOAT

Bases: wrapper

Converter classes can be used using the convert() method, or as a callable object:

result = converter(input_data)

Parameters:

input_data (BucketMap_FLOAT) – data to be converted

Returns:

output data – converted data

Return type:

rc_ptr_Volume_FLOAT

convert(input_data, output_data)

In-place converson inside existing allocated data

Parameters:

• input_data (BucketMap_FLOAT) – data to be converted

• output_data (rc_ptr_Volume_FLOAT) – conversion output will be done into this data

Return type:

None

class soma.aims.Converter_BucketMap_FLOAT_rc_ptr_Volume_S16

Bases: wrapper

Converter classes can be used using the convert() method, or as a callable object:

result = converter(input_data)

Parameters:

input_data (BucketMap_FLOAT) – data to be converted

Returns:

output data – converted data

Return type:

rc_ptr_Volume_S16

convert(input_data, output_data)

In-place converson inside existing allocated data

Parameters:

• input_data (BucketMap_FLOAT) – data to be converted

• output_data (rc_ptr_Volume_S16) – conversion output will be done into this data

Return type:

None

class soma.aims.Converter_BucketMap_FLOAT_rc_ptr_Volume_S32

Bases: wrapper

Converter classes can be used using the convert() method, or as a callable object:

result = converter(input_data)

Parameters:

input_data (BucketMap_FLOAT) – data to be converted

Returns:

output data – converted data

Return type:

rc_ptr_Volume_S32

convert(input_data, output_data)

In-place converson inside existing allocated data

Parameters:

• input_data (BucketMap_FLOAT) – data to be converted

• output_data (rc_ptr_Volume_S32) – conversion output will be done into this data

Return type:

None

class soma.aims.Converter_BucketMap_FLOAT_rc_ptr_Volume_U16

Bases: wrapper

Converter classes can be used using the convert() method, or as a callable object:

result = converter(input_data)

Parameters:

input_data (BucketMap_FLOAT) – data to be converted

Returns:

output data – converted data

Return type:

rc_ptr_Volume_U16

convert(input_data, output_data)

In-place converson inside existing allocated data

Parameters:

• input_data (BucketMap_FLOAT) – data to be converted

• output_data (rc_ptr_Volume_U16) – conversion output will be done into this data

Return type:

None

class soma.aims.Converter_BucketMap_FLOAT_rc_ptr_Volume_U32

Bases: wrapper

Converter classes can be used using the convert() method, or as a callable object:

result = converter(input_data)

Parameters:

input_data (BucketMap_FLOAT) – data to be converted

Returns:

output data – converted data

Return type:

rc_ptr_Volume_U32

convert(input_data, output_data)

In-place converson inside existing allocated data

Parameters:

• input_data (BucketMap_FLOAT) – data to be converted

• output_data (rc_ptr_Volume_U32) – conversion output will be done into this data

Return type:

None

class soma.aims.Converter_BucketMap_FLOAT_rc_ptr_Volume_U8

Bases: wrapper

Converter classes can be used using the convert() method, or as a callable object:

result = converter(input_data)

Parameters:

input_data (BucketMap_FLOAT) – data to be converted

Returns:

output data – converted data

Return type:

rc_ptr_Volume_U8

convert(input_data, output_data)

In-place converson inside existing allocated data

Parameters:

• input_data (BucketMap_FLOAT) – data to be converted

• output_data (rc_ptr_Volume_U8) – conversion output will be done into this data

Return type:

None

class soma.aims.Converter_BucketMap_S16_rc_ptr_Volume_DOUBLE

Bases: wrapper

Converter classes can be used using the convert() method, or as a callable object:

result = converter(input_data)

Parameters:

input_data (BucketMap_S16) – data to be converted

Returns:

output data – converted data

Return type:

rc_ptr_Volume_DOUBLE

convert(input_data, output_data)

In-place converson inside existing allocated data

Parameters:

• input_data (BucketMap_S16) – data to be converted

• output_data (rc_ptr_Volume_DOUBLE) – conversion output will be done into this data

Return type:

None

class soma.aims.Converter_BucketMap_S16_rc_ptr_Volume_FLOAT

Bases: wrapper

Converter classes can be used using the convert() method, or as a callable object:

result = converter(input_data)

Parameters:

input_data (BucketMap_S16) – data to be converted

Returns:

output data – converted data

Return type:

rc_ptr_Volume_FLOAT

convert(input_data, output_data)

In-place converson inside existing allocated data

Parameters:

• input_data (BucketMap_S16) – data to be converted

• output_data (rc_ptr_Volume_FLOAT) – conversion output will be done into this data

Return type:

None

class soma.aims.Converter_BucketMap_S16_rc_ptr_Volume_S16

Bases: wrapper

Converter classes can be used using the convert() method, or as a callable object:

result = converter(input_data)

Parameters:

input_data (BucketMap_S16) – data to be converted

Returns:

output data – converted data

Return type:

rc_ptr_Volume_S16

convert(input_data, output_data)

In-place converson inside existing allocated data

Parameters:

• input_data (BucketMap_S16) – data to be converted

• output_data (rc_ptr_Volume_S16) – conversion output will be done into this data

Return type:

None

class soma.aims.Converter_BucketMap_S16_rc_ptr_Volume_S32

Bases: wrapper

Converter classes can be used using the convert() method, or as a callable object:

result = converter(input_data)

Parameters:

input_data (BucketMap_S16) – data to be converted

Returns:

output data – converted data

Return type:

rc_ptr_Volume_S32

convert(input_data, output_data)

In-place converson inside existing allocated data

Parameters:

• input_data (BucketMap_S16) – data to be converted

• output_data (rc_ptr_Volume_S32) – conversion output will be done into this data

Return type:

None

class soma.aims.Converter_BucketMap_S16_rc_ptr_Volume_U16

Bases: wrapper

Converter classes can be used using the convert() method, or as a callable object:

result = converter(input_data)

Parameters:

input_data (BucketMap_S16) – data to be converted

Returns:

output data – converted data

Return type:

rc_ptr_Volume_U16

convert(input_data, output_data)

In-place converson inside existing allocated data

Parameters:

• input_data (BucketMap_S16) – data to be converted

• output_data (rc_ptr_Volume_U16) – conversion output will be done into this data

Return type:

None

class soma.aims.Converter_BucketMap_S16_rc_ptr_Volume_U32

Bases: wrapper

Converter classes can be used using the convert() method, or as a callable object:

result = converter(input_data)

Parameters:

input_data (BucketMap_S16) – data to be converted

Returns:

output data – converted data

Return type:

rc_ptr_Volume_U32

convert(input_data, output_data)

In-place converson inside existing allocated data

Parameters:

• input_data (BucketMap_S16) – data to be converted

• output_data (rc_ptr_Volume_U32) – conversion output will be done into this data

Return type:

None

class soma.aims.Converter_BucketMap_S16_rc_ptr_Volume_U8

Bases: wrapper

Converter classes can be used using the convert() method, or as a callable object:

result = converter(input_data)

Parameters:

input_data (BucketMap_S16) – data to be converted

Returns:

output data – converted data

Return type:

rc_ptr_Volume_U8

convert(input_data, output_data)

In-place converson inside existing allocated data

Parameters:

• input_data (BucketMap_S16) – data to be converted

• output_data (rc_ptr_Volume_U8) – conversion output will be done into this data

Return type:

None

class soma.aims.Converter_BucketMap_S32_rc_ptr_Volume_DOUBLE

Bases: wrapper

Converter classes can be used using the convert() method, or as a callable object:

result = converter(input_data)

Parameters:

input_data (BucketMap_S32) – data to be converted

Returns:

output data – converted data

Return type:

rc_ptr_Volume_DOUBLE

convert(input_data, output_data)

In-place converson inside existing allocated data

Parameters:

• input_data (BucketMap_S32) – data to be converted

• output_data (rc_ptr_Volume_DOUBLE) – conversion output will be done into this data

Return type:

None

class soma.aims.Converter_BucketMap_S32_rc_ptr_Volume_FLOAT

Bases: wrapper

Converter classes can be used using the convert() method, or as a callable object:

result = converter(input_data)

Parameters:

input_data (BucketMap_S32) – data to be converted

Returns:

output data – converted data

Return type:

rc_ptr_Volume_FLOAT

convert(input_data, output_data)

In-place converson inside existing allocated data

Parameters:

• input_data (BucketMap_S32) – data to be converted

• output_data (rc_ptr_Volume_FLOAT) – conversion output will be done into this data

Return type:

None

class soma.aims.Converter_BucketMap_S32_rc_ptr_Volume_S16

Bases: wrapper

Converter classes can be used using the convert() method, or as a callable object:

result = converter(input_data)

Parameters:

input_data (BucketMap_S32) – data to be converted

Returns:

output data – converted data

Return type:

rc_ptr_Volume_S16

convert(input_data, output_data)

In-place converson inside existing allocated data

Parameters:

• input_data (BucketMap_S32) – data to be converted

• output_data (rc_ptr_Volume_S16) – conversion output will be done into this data

Return type:

None

class soma.aims.Converter_BucketMap_S32_rc_ptr_Volume_S32

Bases: wrapper

Converter classes can be used using the convert() method, or as a callable object:

result = converter(input_data)

Parameters:

input_data (BucketMap_S32) – data to be converted

Returns:

output data – converted data

Return type:

rc_ptr_Volume_S32

convert(input_data, output_data)

In-place converson inside existing allocated data

Parameters:

• input_data (BucketMap_S32) – data to be converted

• output_data (rc_ptr_Volume_S32) – conversion output will be done into this data

Return type:

None

class soma.aims.Converter_BucketMap_S32_rc_ptr_Volume_U16

Bases: wrapper

Converter classes can be used using the convert() method, or as a callable object:

result = converter(input_data)

Parameters:

input_data (BucketMap_S32) – data to be converted

Returns:

output data – converted data

Return type:

rc_ptr_Volume_U16

convert(input_data, output_data)

In-place converson inside existing allocated data

Parameters:

• input_data (BucketMap_S32) – data to be converted

• output_data (rc_ptr_Volume_U16) – conversion output will be done into this data

Return type:

None

class soma.aims.Converter_BucketMap_S32_rc_ptr_Volume_U32

Bases: wrapper

Converter classes can be used using the convert() method, or as a callable object:

result = converter(input_data)

Parameters:

input_data (BucketMap_S32) – data to be converted

Returns:

output data – converted data

Return type:

rc_ptr_Volume_U32

convert(input_data, output_data)

In-place converson inside existing allocated data

Parameters:

• input_data (BucketMap_S32) – data to be converted

• output_data (rc_ptr_Volume_U32) – conversion output will be done into this data

Return type:

None

class soma.aims.Converter_BucketMap_S32_rc_ptr_Volume_U8

Bases: wrapper

Converter classes can be used using the convert() method, or as a callable object:

result = converter(input_data)

Parameters:

input_data (BucketMap_S32) – data to be converted

Returns:

output data – converted data

Return type:

rc_ptr_Volume_U8

convert(input_data, output_data)

In-place converson inside existing allocated data

Parameters:

• input_data (BucketMap_S32) – data to be converted

• output_data (rc_ptr_Volume_U8) – conversion output will be done into this data

Return type:

None

class soma.aims.Converter_BucketMap_U16_rc_ptr_Volume_DOUBLE

Bases: wrapper

Converter classes can be used using the convert() method, or as a callable object:

result = converter(input_data)

Parameters:

input_data (BucketMap_U16) – data to be converted

Returns:

output data – converted data

Return type:

rc_ptr_Volume_DOUBLE

convert(input_data, output_data)

In-place converson inside existing allocated data

Parameters:

• input_data (BucketMap_U16) – data to be converted

• output_data (rc_ptr_Volume_DOUBLE) – conversion output will be done into this data

Return type:

None

class soma.aims.Converter_BucketMap_U16_rc_ptr_Volume_FLOAT

Bases: wrapper

Converter classes can be used using the convert() method, or as a callable object:

result = converter(input_data)

Parameters:

input_data (BucketMap_U16) – data to be converted

Returns:

output data – converted data

Return type:

rc_ptr_Volume_FLOAT

convert(input_data, output_data)

In-place converson inside existing allocated data

Parameters:

• input_data (BucketMap_U16) – data to be converted

• output_data (rc_ptr_Volume_FLOAT) – conversion output will be done into this data

Return type:

None

class soma.aims.Converter_BucketMap_U16_rc_ptr_Volume_S16

Bases: wrapper

Converter classes can be used using the convert() method, or as a callable object:

result = converter(input_data)

Parameters:

input_data (BucketMap_U16) – data to be converted

Returns:

output data – converted data

Return type:

rc_ptr_Volume_S16

convert(input_data, output_data)

In-place converson inside existing allocated data

Parameters:

• input_data (BucketMap_U16) – data to be converted

• output_data (rc_ptr_Volume_S16) – conversion output will be done into this data

Return type:

None

class soma.aims.Converter_BucketMap_U16_rc_ptr_Volume_S32

Bases: wrapper

Converter classes can be used using the convert() method, or as a callable object:

result = converter(input_data)

Parameters:

input_data (BucketMap_U16) – data to be converted

Returns:

output data – converted data

Return type:

rc_ptr_Volume_S32

convert(input_data, output_data)

In-place converson inside existing allocated data

Parameters:

• input_data (BucketMap_U16) – data to be converted

• output_data (rc_ptr_Volume_S32) – conversion output will be done into this data

Return type:

None

class soma.aims.Converter_BucketMap_U16_rc_ptr_Volume_U16

Bases: wrapper

Converter classes can be used using the convert() method, or as a callable object:

result = converter(input_data)

Parameters:

input_data (BucketMap_U16) – data to be converted

Returns:

output data – converted data

Return type:

rc_ptr_Volume_U16

convert(input_data, output_data)

In-place converson inside existing allocated data

Parameters:

• input_data (BucketMap_U16) – data to be converted

• output_data (rc_ptr_Volume_U16) – conversion output will be done into this data

Return type:

None

class soma.aims.Converter_BucketMap_U16_rc_ptr_Volume_U32

Bases: wrapper

Converter classes can be used using the convert() method, or as a callable object:

result = converter(input_data)

Parameters:

input_data (BucketMap_U16) – data to be converted

Returns:

output data – converted data

Return type:

rc_ptr_Volume_U32

convert(input_data, output_data)

In-place converson inside existing allocated data

Parameters:

• input_data (BucketMap_U16) – data to be converted

• output_data (rc_ptr_Volume_U32) – conversion output will be done into this data

Return type:

None

class soma.aims.Converter_BucketMap_U16_rc_ptr_Volume_U8

Bases: wrapper

Converter classes can be used using the convert() method, or as a callable object:

result = converter(input_data)

Parameters:

input_data (BucketMap_U16) – data to be converted

Returns:

output data – converted data

Return type:

rc_ptr_Volume_U8

convert(input_data, output_data)

In-place converson inside existing allocated data

Parameters:

• input_data (BucketMap_U16) – data to be converted

• output_data (rc_ptr_Volume_U8) – conversion output will be done into this data

Return type:

None

class soma.aims.Converter_BucketMap_U32_rc_ptr_Volume_DOUBLE

Bases: wrapper

Converter classes can be used using the convert() method, or as a callable object:

result = converter(input_data)

Parameters:

input_data (BucketMap_U32) – data to be converted

Returns:

output data – converted data

Return type:

rc_ptr_Volume_DOUBLE

convert(input_data, output_data)

In-place converson inside existing allocated data

Parameters:

• input_data (BucketMap_U32) – data to be converted

• output_data (rc_ptr_Volume_DOUBLE) – conversion output will be done into this data

Return type:

None

class soma.aims.Converter_BucketMap_U32_rc_ptr_Volume_FLOAT

Bases: wrapper

Converter classes can be used using the convert() method, or as a callable object:

result = converter(input_data)

Parameters:

input_data (BucketMap_U32) – data to be converted

Returns:

output data – converted data

Return type:

rc_ptr_Volume_FLOAT

convert(input_data, output_data)

In-place converson inside existing allocated data

Parameters:

• input_data (BucketMap_U32) – data to be converted

• output_data (rc_ptr_Volume_FLOAT) – conversion output will be done into this data

Return type:

None

class soma.aims.Converter_BucketMap_U32_rc_ptr_Volume_S16

Bases: wrapper

Converter classes can be used using the convert() method, or as a callable object:

result = converter(input_data)

Parameters:

input_data (BucketMap_U32) – data to be converted

Returns:

output data – converted data

Return type:

rc_ptr_Volume_S16

convert(input_data, output_data)

In-place converson inside existing allocated data

Parameters:

• input_data (BucketMap_U32) – data to be converted

• output_data (rc_ptr_Volume_S16) – conversion output will be done into this data

Return type:

None

class soma.aims.Converter_BucketMap_U32_rc_ptr_Volume_S32

Bases: wrapper

Converter classes can be used using the convert() method, or as a callable object:

result = converter(input_data)

Parameters:

input_data (BucketMap_U32) – data to be converted

Returns:

output data – converted data

Return type:

rc_ptr_Volume_S32

convert(input_data, output_data)

In-place converson inside existing allocated data

Parameters:

• input_data (BucketMap_U32) – data to be converted

• output_data (rc_ptr_Volume_S32) – conversion output will be done into this data

Return type:

None

class soma.aims.Converter_BucketMap_U32_rc_ptr_Volume_U16

Bases: wrapper

Converter classes can be used using the convert() method, or as a callable object:

result = converter(input_data)

Parameters:

input_data (BucketMap_U32) – data to be converted

Returns:

output data – converted data

Return type:

rc_ptr_Volume_U16

convert(input_data, output_data)

In-place converson inside existing allocated data

Parameters:

• input_data (BucketMap_U32) – data to be converted

• output_data (rc_ptr_Volume_U16) – conversion output will be done into this data

Return type:

None

class soma.aims.Converter_BucketMap_U32_rc_ptr_Volume_U32

Bases: wrapper

Converter classes can be used using the convert() method, or as a callable object:

result = converter(input_data)

Parameters:

input_data (BucketMap_U32) – data to be converted

Returns:

output data – converted data

Return type:

rc_ptr_Volume_U32

convert(input_data, output_data)

In-place converson inside existing allocated data

Parameters:

• input_data (BucketMap_U32) – data to be converted

• output_data (rc_ptr_Volume_U32) – conversion output will be done into this data

Return type:

None

class soma.aims.Converter_BucketMap_U32_rc_ptr_Volume_U8

Bases: wrapper

Converter classes can be used using the convert() method, or as a callable object:

result = converter(input_data)

Parameters:

input_data (BucketMap_U32) – data to be converted

Returns:

output data – converted data

Return type:

rc_ptr_Volume_U8

convert(input_data, output_data)

In-place converson inside existing allocated data

Parameters:

• input_data (BucketMap_U32) – data to be converted

• output_data (rc_ptr_Volume_U8) – conversion output will be done into this data

Return type:

None

class soma.aims.Converter_BucketMap_VOID_rc_ptr_Volume_DOUBLE

Bases: wrapper

Converter classes can be used using the convert() method, or as a callable object:

result = converter(input_data)

Parameters:

input_data (BucketMap_VOID) – data to be converted

Returns:

output data – converted data

Return type:

rc_ptr_Volume_DOUBLE

convert(input_data, output_data)

In-place converson inside existing allocated data

Parameters:

• input_data (BucketMap_VOID) – data to be converted

• output_data (rc_ptr_Volume_DOUBLE) – conversion output will be done into this data

Return type:

None

class soma.aims.Converter_BucketMap_VOID_rc_ptr_Volume_FLOAT

Bases: wrapper

Converter classes can be used using the convert() method, or as a callable object:

result = converter(input_data)

Parameters:

input_data (BucketMap_VOID) – data to be converted

Returns:

output data – converted data

Return type:

rc_ptr_Volume_FLOAT

convert(input_data, output_data)

In-place converson inside existing allocated data

Parameters:

• input_data (BucketMap_VOID) – data to be converted

• output_data (rc_ptr_Volume_FLOAT) – conversion output will be done into this data

Return type:

None

class soma.aims.Converter_BucketMap_VOID_rc_ptr_Volume_S16

Bases: wrapper

Converter classes can be used using the convert() method, or as a callable object:

result = converter(input_data)

Parameters:

input_data (BucketMap_VOID) – data to be converted

Returns:

output data – converted data

Return type:

rc_ptr_Volume_S16

convert(input_data, output_data)

In-place converson inside existing allocated data

Parameters:

• input_data (BucketMap_VOID) – data to be converted

• output_data (rc_ptr_Volume_S16) – conversion output will be done into this data

Return type:

None

class soma.aims.Converter_BucketMap_VOID_rc_ptr_Volume_S32

Bases: wrapper

Converter classes can be used using the convert() method, or as a callable object:

result = converter(input_data)

Parameters:

input_data (BucketMap_VOID) – data to be converted

Returns:

output data – converted data

Return type:

rc_ptr_Volume_S32

convert(input_data, output_data)

In-place converson inside existing allocated data

Parameters:

• input_data (BucketMap_VOID) – data to be converted

• output_data (rc_ptr_Volume_S32) – conversion output will be done into this data

Return type:

None

class soma.aims.Converter_BucketMap_VOID_rc_ptr_Volume_U16

Bases: wrapper

Converter classes can be used using the convert() method, or as a callable object:

result = converter(input_data)

Parameters:

input_data (BucketMap_VOID) – data to be converted

Returns:

output data – converted data

Return type:

rc_ptr_Volume_U16

convert(input_data, output_data)

In-place converson inside existing allocated data

Parameters:

• input_data (BucketMap_VOID) – data to be converted

• output_data (rc_ptr_Volume_U16) – conversion output will be done into this data

Return type:

None

class soma.aims.Converter_BucketMap_VOID_rc_ptr_Volume_U32

Bases: wrapper

Converter classes can be used using the convert() method, or as a callable object:

result = converter(input_data)

Parameters:

input_data (BucketMap_VOID) – data to be converted

Returns:

output data – converted data

Return type:

rc_ptr_Volume_U32

convert(input_data, output_data)

In-place converson inside existing allocated data

Parameters:

• input_data (BucketMap_VOID) – data to be converted

• output_data (rc_ptr_Volume_U32) – conversion output will be done into this data

Return type:

None

class soma.aims.Converter_BucketMap_VOID_rc_ptr_Volume_U8

Bases: wrapper

Converter classes can be used using the convert() method, or as a callable object:

result = converter(input_data)

Parameters:

input_data (BucketMap_VOID) – data to be converted

Returns:

output data – converted data

Return type:

rc_ptr_Volume_U8

convert(input_data, output_data)

In-place converson inside existing allocated data

Parameters:

• input_data (BucketMap_VOID) – data to be converted

• output_data (rc_ptr_Volume_U8) – conversion output will be done into this data

Return type:

None

class soma.aims.Converter_Volume_DOUBLE_Volume_DOUBLE

Bases: wrapper

Converter classes can be used using the convert() method, or as a callable object:

result = converter(input_data)

Parameters:

input_data (Volume_DOUBLE) – data to be converted

Returns:

output data – converted data

Return type:

Volume_DOUBLE

convert(input_data, output_data)

In-place converson inside existing allocated data

Parameters:

• input_data (Volume_DOUBLE) – data to be converted

• output_data (Volume_DOUBLE) – conversion output will be done into this data

Return type:

None

class soma.aims.Converter_Volume_DOUBLE_Volume_FLOAT

Bases: wrapper

Converter classes can be used using the convert() method, or as a callable object:

result = converter(input_data)

Parameters:

input_data (Volume_DOUBLE) – data to be converted

Returns:

output data – converted data

Return type:

Volume_FLOAT

convert(input_data, output_data)

In-place converson inside existing allocated data

Parameters:

• input_data (Volume_DOUBLE) – data to be converted

• output_data (Volume_FLOAT) – conversion output will be done into this data

Return type:

None

class soma.aims.Converter_Volume_DOUBLE_Volume_HSV

Bases: wrapper

Converter classes can be used using the convert() method, or as a callable object:

result = converter(input_data)

Parameters:

input_data (Volume_DOUBLE) – data to be converted

Returns:

output data – converted data

Return type:

Volume_HSV

convert(input_data, output_data)

In-place converson inside existing allocated data

Parameters:

• input_data (Volume_DOUBLE) – data to be converted

• output_data (Volume_HSV) – conversion output will be done into this data

Return type:

None

class soma.aims.Converter_Volume_DOUBLE_Volume_RGB

Bases: wrapper

Converter classes can be used using the convert() method, or as a callable object:

result = converter(input_data)

Parameters:

input_data (Volume_DOUBLE) – data to be converted

Returns:

output data – converted data

Return type:

Volume_RGB

convert(input_data, output_data)

In-place converson inside existing allocated data

Parameters:

• input_data (Volume_DOUBLE) – data to be converted

• output_data (Volume_RGB) – conversion output will be done into this data

Return type:

None

class soma.aims.Converter_Volume_DOUBLE_Volume_RGBA

Bases: wrapper

Converter classes can be used using the convert() method, or as a callable object:

result = converter(input_data)

Parameters:

input_data (Volume_DOUBLE) – data to be converted

Returns:

output data – converted data

Return type:

Volume_RGBA

convert(input_data, output_data)

In-place converson inside existing allocated data

Parameters:

• input_data (Volume_DOUBLE) – data to be converted

• output_data (Volume_RGBA) – conversion output will be done into this data

Return type:

None

class soma.aims.Converter_Volume_DOUBLE_Volume_S16

Bases: wrapper

Converter classes can be used using the convert() method, or as a callable object:

result = converter(input_data)

Parameters:

input_data (Volume_DOUBLE) – data to be converted

Returns:

output data – converted data

Return type:

Volume_S16

convert(input_data, output_data)

In-place converson inside existing allocated data

Parameters:

• input_data (Volume_DOUBLE) – data to be converted

• output_data (Volume_S16) – conversion output will be done into this data

Return type:

None

class soma.aims.Converter_Volume_DOUBLE_Volume_S32

Bases: wrapper

Converter classes can be used using the convert() method, or as a callable object:

result = converter(input_data)

Parameters:

input_data (Volume_DOUBLE) – data to be converted

Returns:

output data – converted data

Return type:

Volume_S32

convert(input_data, output_data)

In-place converson inside existing allocated data

Parameters:

• input_data (Volume_DOUBLE) – data to be converted

• output_data (Volume_S32) – conversion output will be done into this data

Return type:

None

class soma.aims.Converter_Volume_DOUBLE_Volume_U16

Bases: wrapper

Converter classes can be used using the convert() method, or as a callable object:

result = converter(input_data)

Parameters:

input_data (Volume_DOUBLE) – data to be converted

Returns:

output data – converted data

Return type:

Volume_U16

convert(input_data, output_data)

In-place converson inside existing allocated data

Parameters:

• input_data (Volume_DOUBLE) – data to be converted

• output_data (Volume_U16) – conversion output will be done into this data

Return type:

None

class soma.aims.Converter_Volume_DOUBLE_Volume_U32

Bases: wrapper

Converter classes can be used using the convert() method, or as a callable object:

result = converter(input_data)

Parameters:

input_data (Volume_DOUBLE) – data to be converted

Returns:

output data – converted data

Return type:

Volume_U32

convert(input_data, output_data)

In-place converson inside existing allocated data

Parameters:

• input_data (Volume_DOUBLE) – data to be converted

• output_data (Volume_U32) – conversion output will be done into this data

Return type:

None

class soma.aims.Converter_Volume_DOUBLE_Volume_U8

Bases: wrapper

Converter classes can be used using the convert() method, or as a callable object:

result = converter(input_data)

Parameters:

input_data (Volume_DOUBLE) – data to be converted

Returns:

output data – converted data

Return type:

Volume_U8

convert(input_data, output_data)

In-place converson inside existing allocated data

Parameters:

• input_data (Volume_DOUBLE) – data to be converted

• output_data (Volume_U8) – conversion output will be done into this data

Return type:

None

class soma.aims.Converter_Volume_FLOAT_Volume_DOUBLE

Bases: wrapper

Converter classes can be used using the convert() method, or as a callable object:

result = converter(input_data)

Parameters:

input_data (Volume_FLOAT) – data to be converted

Returns:

output data – converted data

Return type:

Volume_DOUBLE

convert(input_data, output_data)

In-place converson inside existing allocated data

Parameters:

• input_data (Volume_FLOAT) – data to be converted

• output_data (Volume_DOUBLE) – conversion output will be done into this data

Return type:

None

class soma.aims.Converter_Volume_FLOAT_Volume_FLOAT

Bases: wrapper

Converter classes can be used using the convert() method, or as a callable object:

result = converter(input_data)

Parameters:

input_data (Volume_FLOAT) – data to be converted

Returns:

output data – converted data

Return type:

Volume_FLOAT

convert(input_data, output_data)

In-place converson inside existing allocated data

Parameters:

• input_data (Volume_FLOAT) – data to be converted

• output_data (Volume_FLOAT) – conversion output will be done into this data

Return type:

None

class soma.aims.Converter_Volume_FLOAT_Volume_HSV

Bases: wrapper

Converter classes can be used using the convert() method, or as a callable object:

result = converter(input_data)

Parameters:

input_data (Volume_FLOAT) – data to be converted

Returns:

output data – converted data

Return type:

Volume_HSV

convert(input_data, output_data)

In-place converson inside existing allocated data

Parameters:

• input_data (Volume_FLOAT) – data to be converted

• output_data (Volume_HSV) – conversion output will be done into this data

Return type:

None

class soma.aims.Converter_Volume_FLOAT_Volume_RGB

Bases: wrapper

Converter classes can be used using the convert() method, or as a callable object:

result = converter(input_data)

Parameters:

input_data (Volume_FLOAT) – data to be converted

Returns:

output data – converted data

Return type:

Volume_RGB

convert(input_data, output_data)

In-place converson inside existing allocated data

Parameters:

• input_data (Volume_FLOAT) – data to be converted

• output_data (Volume_RGB) – conversion output will be done into this data

Return type:

None

class soma.aims.Converter_Volume_FLOAT_Volume_RGBA

Bases: wrapper

Converter classes can be used using the convert() method, or as a callable object:

result = converter(input_data)

Parameters:

input_data (Volume_FLOAT) – data to be converted

Returns:

output data – converted data

Return type:

Volume_RGBA

convert(input_data, output_data)

In-place converson inside existing allocated data

Parameters:

• input_data (Volume_FLOAT) – data to be converted

• output_data (Volume_RGBA) – conversion output will be done into this data

Return type:

None

class soma.aims.Converter_Volume_FLOAT_Volume_S16

Bases: wrapper

Converter classes can be used using the convert() method, or as a callable object:

result = converter(input_data)

Parameters:

input_data (Volume_FLOAT) – data to be converted

Returns:

output data – converted data

Return type:

Volume_S16

convert(input_data, output_data)

In-place converson inside existing allocated data

Parameters:

• input_data (Volume_FLOAT) – data to be converted

• output_data (Volume_S16) – conversion output will be done into this data

Return type:

None

class soma.aims.Converter_Volume_FLOAT_Volume_S32

Bases: wrapper

Converter classes can be used using the convert() method, or as a callable object:

result = converter(input_data)

Parameters:

input_data (Volume_FLOAT) – data to be converted

Returns:

output data – converted data

Return type:

Volume_S32

convert(input_data, output_data)

In-place converson inside existing allocated data

Parameters:

• input_data (Volume_FLOAT) – data to be converted

• output_data (Volume_S32) – conversion output will be done into this data

Return type:

None

class soma.aims.Converter_Volume_FLOAT_Volume_U16

Bases: wrapper

Converter classes can be used using the convert() method, or as a callable object:

result = converter(input_data)

Parameters:

input_data (Volume_FLOAT) – data to be converted

Returns:

output data – converted data

Return type:

Volume_U16

convert(input_data, output_data)

In-place converson inside existing allocated data

Parameters:

• input_data (Volume_FLOAT) – data to be converted

• output_data (Volume_U16) – conversion output will be done into this data

Return type:

None

class soma.aims.Converter_Volume_FLOAT_Volume_U32

Bases: wrapper

Converter classes can be used using the convert() method, or as a callable object:

result = converter(input_data)

Parameters:

input_data (Volume_FLOAT) – data to be converted

Returns:

output data – converted data

Return type:

Volume_U32

convert(input_data, output_data)

In-place converson inside existing allocated data

Parameters:

• input_data (Volume_FLOAT) – data to be converted

• output_data (Volume_U32) – conversion output will be done into this data

Return type:

None

class soma.aims.Converter_Volume_FLOAT_Volume_U8

Bases: wrapper

Converter classes can be used using the convert() method, or as a callable object:

result = converter(input_data)

Parameters:

input_data (Volume_FLOAT) – data to be converted

Returns:

output data – converted data

Return type:

Volume_U8

convert(input_data, output_data)

In-place converson inside existing allocated data

Parameters:

• input_data (Volume_FLOAT) – data to be converted

• output_data (Volume_U8) – conversion output will be done into this data

Return type:

None

class soma.aims.Converter_Volume_HSV_Volume_DOUBLE

Bases: wrapper

Converter classes can be used using the convert() method, or as a callable object:

result = converter(input_data)

Parameters:

input_data (Volume_HSV) – data to be converted

Returns:

output data – converted data

Return type:

Volume_DOUBLE

convert(input_data, output_data)

In-place converson inside existing allocated data

Parameters:

• input_data (Volume_HSV) – data to be converted

• output_data (Volume_DOUBLE) – conversion output will be done into this data

Return type:

None

class soma.aims.Converter_Volume_HSV_Volume_FLOAT

Bases: wrapper

Converter classes can be used using the convert() method, or as a callable object:

result = converter(input_data)

Parameters:

input_data (Volume_HSV) – data to be converted

Returns:

output data – converted data

Return type:

Volume_FLOAT

convert(input_data, output_data)

In-place converson inside existing allocated data

Parameters:

• input_data (Volume_HSV) – data to be converted

• output_data (Volume_FLOAT) – conversion output will be done into this data

Return type:

None

class soma.aims.Converter_Volume_HSV_Volume_HSV

Bases: wrapper

Converter classes can be used using the convert() method, or as a callable object:

result = converter(input_data)

Parameters:

input_data (Volume_HSV) – data to be converted

Returns:

output data – converted data

Return type:

Volume_HSV

convert(input_data, output_data)

In-place converson inside existing allocated data

Parameters:

• input_data (Volume_HSV) – data to be converted

• output_data (Volume_HSV) – conversion output will be done into this data

Return type:

None

class soma.aims.Converter_Volume_HSV_Volume_RGB

Bases: wrapper

Converter classes can be used using the convert() method, or as a callable object:

result = converter(input_data)

Parameters:

input_data (Volume_HSV) – data to be converted

Returns:

output data – converted data

Return type:

Volume_RGB

convert(input_data, output_data)

In-place converson inside existing allocated data

Parameters:

• input_data (Volume_HSV) – data to be converted

• output_data (Volume_RGB) – conversion output will be done into this data

Return type:

None

class soma.aims.Converter_Volume_HSV_Volume_RGBA

Bases: wrapper

Converter classes can be used using the convert() method, or as a callable object:

result = converter(input_data)

Parameters:

input_data (Volume_HSV) – data to be converted

Returns:

output data – converted data

Return type:

Volume_RGBA

convert(input_data, output_data)

In-place converson inside existing allocated data

Parameters:

• input_data (Volume_HSV) – data to be converted

• output_data (Volume_RGBA) – conversion output will be done into this data

Return type:

None

class soma.aims.Converter_Volume_HSV_Volume_S16

Bases: wrapper

Converter classes can be used using the convert() method, or as a callable object:

result = converter(input_data)

Parameters:

input_data (Volume_HSV) – data to be converted

Returns:

output data – converted data

Return type:

Volume_S16

convert(input_data, output_data)

In-place converson inside existing allocated data

Parameters:

• input_data (Volume_HSV) – data to be converted

• output_data (Volume_S16) – conversion output will be done into this data

Return type:

None

class soma.aims.Converter_Volume_HSV_Volume_S32

Bases: wrapper

Converter classes can be used using the convert() method, or as a callable object:

result = converter(input_data)

Parameters:

input_data (Volume_HSV) – data to be converted

Returns:

output data – converted data

Return type:

Volume_S32

convert(input_data, output_data)

In-place converson inside existing allocated data

Parameters:

• input_data (Volume_HSV) – data to be converted

• output_data (Volume_S32) – conversion output will be done into this data

Return type:

None

class soma.aims.Converter_Volume_HSV_Volume_U16

Bases: wrapper

Converter classes can be used using the convert() method, or as a callable object:

result = converter(input_data)

Parameters:

input_data (Volume_HSV) – data to be converted

Returns:

output data – converted data

Return type:

Volume_U16

convert(input_data, output_data)

In-place converson inside existing allocated data

Parameters:

• input_data (Volume_HSV) – data to be converted

• output_data (Volume_U16) – conversion output will be done into this data

Return type:

None

class soma.aims.Converter_Volume_HSV_Volume_U32

Bases: wrapper

Converter classes can be used using the convert() method, or as a callable object:

result = converter(input_data)

Parameters:

input_data (Volume_HSV) – data to be converted

Returns:

output data – converted data

Return type:

Volume_U32

convert(input_data, output_data)

In-place converson inside existing allocated data

Parameters:

• input_data (Volume_HSV) – data to be converted

• output_data (Volume_U32) – conversion output will be done into this data

Return type:

None

class soma.aims.Converter_Volume_HSV_Volume_U8

Bases: wrapper

Converter classes can be used using the convert() method, or as a callable object:

result = converter(input_data)

Parameters:

input_data (Volume_HSV) – data to be converted

Returns:

output data – converted data

Return type:

Volume_U8

convert(input_data, output_data)

In-place converson inside existing allocated data

Parameters:

• input_data (Volume_HSV) – data to be converted

• output_data (Volume_U8) – conversion output will be done into this data

Return type:

None

class soma.aims.Converter_Volume_RGBA_Volume_DOUBLE

Bases: wrapper

Converter classes can be used using the convert() method, or as a callable object:

result = converter(input_data)

Parameters:

input_data (Volume_RGBA) – data to be converted

Returns:

output data – converted data

Return type:

Volume_DOUBLE

convert(input_data, output_data)

In-place converson inside existing allocated data

Parameters:

• input_data (Volume_RGBA) – data to be converted

• output_data (Volume_DOUBLE) – conversion output will be done into this data

Return type:

None

class soma.aims.Converter_Volume_RGBA_Volume_FLOAT

Bases: wrapper

Converter classes can be used using the convert() method, or as a callable object:

result = converter(input_data)

Parameters:

input_data (Volume_RGBA) – data to be converted

Returns:

output data – converted data

Return type:

Volume_FLOAT

convert(input_data, output_data)

In-place converson inside existing allocated data

Parameters:

• input_data (Volume_RGBA) – data to be converted

• output_data (Volume_FLOAT) – conversion output will be done into this data

Return type:

None

class soma.aims.Converter_Volume_RGBA_Volume_HSV

Bases: wrapper

Converter classes can be used using the convert() method, or as a callable object:

result = converter(input_data)

Parameters:

input_data (Volume_RGBA) – data to be converted

Returns:

output data – converted data

Return type:

Volume_HSV

convert(input_data, output_data)

In-place converson inside existing allocated data

Parameters:

• input_data (Volume_RGBA) – data to be converted

• output_data (Volume_HSV) – conversion output will be done into this data

Return type:

None

class soma.aims.Converter_Volume_RGBA_Volume_RGB

Bases: wrapper

Converter classes can be used using the convert() method, or as a callable object:

result = converter(input_data)

Parameters:

input_data (Volume_RGBA) – data to be converted

Returns:

output data – converted data

Return type:

Volume_RGB

convert(input_data, output_data)

In-place converson inside existing allocated data

Parameters:

• input_data (Volume_RGBA) – data to be converted

• output_data (Volume_RGB) – conversion output will be done into this data

Return type:

None

class soma.aims.Converter_Volume_RGBA_Volume_RGBA

Bases: wrapper

Converter classes can be used using the convert() method, or as a callable object:

result = converter(input_data)

Parameters:

input_data (Volume_RGBA) – data to be converted

Returns:

output data – converted data

Return type:

Volume_RGBA

convert(input_data, output_data)

In-place converson inside existing allocated data

Parameters:

• input_data (Volume_RGBA) – data to be converted

• output_data (Volume_RGBA) – conversion output will be done into this data

Return type:

None

class soma.aims.Converter_Volume_RGBA_Volume_S16

Bases: wrapper

Converter classes can be used using the convert() method, or as a callable object:

result = converter(input_data)

Parameters:

input_data (Volume_RGBA) – data to be converted

Returns:

output data – converted data

Return type:

Volume_S16

convert(input_data, output_data)

In-place converson inside existing allocated data

Parameters:

• input_data (Volume_RGBA) – data to be converted

• output_data (Volume_S16) – conversion output will be done into this data

Return type:

None

class soma.aims.Converter_Volume_RGBA_Volume_S32

Bases: wrapper

Converter classes can be used using the convert() method, or as a callable object:

result = converter(input_data)

Parameters:

input_data (Volume_RGBA) – data to be converted

Returns:

output data – converted data

Return type:

Volume_S32

convert(input_data, output_data)

In-place converson inside existing allocated data

Parameters:

• input_data (Volume_RGBA) – data to be converted

• output_data (Volume_S32) – conversion output will be done into this data

Return type:

None

class soma.aims.Converter_Volume_RGBA_Volume_U16

Bases: wrapper

Converter classes can be used using the convert() method, or as a callable object:

result = converter(input_data)

Parameters:

input_data (Volume_RGBA) – data to be converted

Returns:

output data – converted data

Return type:

Volume_U16

convert(input_data, output_data)

In-place converson inside existing allocated data

Parameters:

• input_data (Volume_RGBA) – data to be converted

• output_data (Volume_U16) – conversion output will be done into this data

Return type:

None

class soma.aims.Converter_Volume_RGBA_Volume_U32

Bases: wrapper

Converter classes can be used using the convert() method, or as a callable object:

result = converter(input_data)

Parameters:

input_data (Volume_RGBA) – data to be converted

Returns:

output data – converted data

Return type:

Volume_U32

convert(input_data, output_data)

In-place converson inside existing allocated data

Parameters:

• input_data (Volume_RGBA) – data to be converted

• output_data (Volume_U32) – conversion output will be done into this data

Return type:

None

class soma.aims.Converter_Volume_RGBA_Volume_U8

Bases: wrapper

Converter classes can be used using the convert() method, or as a callable object:

result = converter(input_data)

Parameters:

input_data (Volume_RGBA) – data to be converted

Returns:

output data – converted data

Return type:

Volume_U8

convert(input_data, output_data)

In-place converson inside existing allocated data

Parameters:

• input_data (Volume_RGBA) – data to be converted

• output_data (Volume_U8) – conversion output will be done into this data

Return type:

None

class soma.aims.Converter_Volume_RGB_Volume_DOUBLE

Bases: wrapper

Converter classes can be used using the convert() method, or as a callable object:

result = converter(input_data)

Parameters:

input_data (Volume_RGB) – data to be converted

Returns:

output data – converted data

Return type:

Volume_DOUBLE

convert(input_data, output_data)

In-place converson inside existing allocated data

Parameters:

• input_data (Volume_RGB) – data to be converted

• output_data (Volume_DOUBLE) – conversion output will be done into this data

Return type:

None

class soma.aims.Converter_Volume_RGB_Volume_FLOAT

Bases: wrapper

Converter classes can be used using the convert() method, or as a callable object:

result = converter(input_data)

Parameters:

input_data (Volume_RGB) – data to be converted

Returns:

output data – converted data

Return type:

Volume_FLOAT

convert(input_data, output_data)

In-place converson inside existing allocated data

Parameters:

• input_data (Volume_RGB) – data to be converted

• output_data (Volume_FLOAT) – conversion output will be done into this data

Return type:

None

class soma.aims.Converter_Volume_RGB_Volume_HSV

Bases: wrapper

Converter classes can be used using the convert() method, or as a callable object:

result = converter(input_data)

Parameters:

input_data (Volume_RGB) – data to be converted

Returns:

output data – converted data

Return type:

Volume_HSV

convert(input_data, output_data)

In-place converson inside existing allocated data

Parameters:

• input_data (Volume_RGB) – data to be converted

• output_data (Volume_HSV) – conversion output will be done into this data

Return type:

None

class soma.aims.Converter_Volume_RGB_Volume_RGB

Bases: wrapper

Converter classes can be used using the convert() method, or as a callable object:

result = converter(input_data)

Parameters:

input_data (Volume_RGB) – data to be converted

Returns:

output data – converted data

Return type:

Volume_RGB

convert(input_data, output_data)

In-place converson inside existing allocated data

Parameters:

• input_data (Volume_RGB) – data to be converted

• output_data (Volume_RGB) – conversion output will be done into this data

Return type:

None

class soma.aims.Converter_Volume_RGB_Volume_RGBA

Bases: wrapper

Converter classes can be used using the convert() method, or as a callable object:

result = converter(input_data)

Parameters:

input_data (Volume_RGB) – data to be converted

Returns:

output data – converted data

Return type:

Volume_RGBA

convert(input_data, output_data)

In-place converson inside existing allocated data

Parameters:

• input_data (Volume_RGB) – data to be converted

• output_data (Volume_RGBA) – conversion output will be done into this data

Return type:

None

class soma.aims.Converter_Volume_RGB_Volume_S16

Bases: wrapper

Converter classes can be used using the convert() method, or as a callable object:

result = converter(input_data)

Parameters:

input_data (Volume_RGB) – data to be converted

Returns:

output data – converted data

Return type:

Volume_S16

convert(input_data, output_data)

In-place converson inside existing allocated data

Parameters:

• input_data (Volume_RGB) – data to be converted

• output_data (Volume_S16) – conversion output will be done into this data

Return type:

None

class soma.aims.Converter_Volume_RGB_Volume_S32

Bases: wrapper

Converter classes can be used using the convert() method, or as a callable object:

result = converter(input_data)

Parameters:

input_data (Volume_RGB) – data to be converted

Returns:

output data – converted data

Return type:

Volume_S32

convert(input_data, output_data)

In-place converson inside existing allocated data

Parameters:

• input_data (Volume_RGB) – data to be converted

• output_data (Volume_S32) – conversion output will be done into this data

Return type:

None

class soma.aims.Converter_Volume_RGB_Volume_U16

Bases: wrapper

Converter classes can be used using the convert() method, or as a callable object:

result = converter(input_data)

Parameters:

input_data (Volume_RGB) – data to be converted

Returns:

output data – converted data

Return type:

Volume_U16

convert(input_data, output_data)

In-place converson inside existing allocated data

Parameters:

• input_data (Volume_RGB) – data to be converted

• output_data (Volume_U16) – conversion output will be done into this data

Return type:

None

class soma.aims.Converter_Volume_RGB_Volume_U32

Bases: wrapper

Converter classes can be used using the convert() method, or as a callable object:

result = converter(input_data)

Parameters:

input_data (Volume_RGB) – data to be converted

Returns:

output data – converted data

Return type:

Volume_U32

convert(input_data, output_data)

In-place converson inside existing allocated data

Parameters:

• input_data (Volume_RGB) – data to be converted

• output_data (Volume_U32) – conversion output will be done into this data

Return type:

None

class soma.aims.Converter_Volume_RGB_Volume_U8

Bases: wrapper

Converter classes can be used using the convert() method, or as a callable object:

result = converter(input_data)

Parameters:

input_data (Volume_RGB) – data to be converted

Returns:

output data – converted data

Return type:

Volume_U8

convert(input_data, output_data)

In-place converson inside existing allocated data

Parameters:

• input_data (Volume_RGB) – data to be converted

• output_data (Volume_U8) – conversion output will be done into this data

Return type:

None

class soma.aims.Converter_Volume_S16_Volume_DOUBLE

Bases: wrapper

Converter classes can be used using the convert() method, or as a callable object:

result = converter(input_data)

Parameters:

input_data (Volume_S16) – data to be converted

Returns:

output data – converted data

Return type:

Volume_DOUBLE

convert(input_data, output_data)

In-place converson inside existing allocated data

Parameters:

• input_data (Volume_S16) – data to be converted

• output_data (Volume_DOUBLE) – conversion output will be done into this data

Return type:

None

class soma.aims.Converter_Volume_S16_Volume_FLOAT

Bases: wrapper

Converter classes can be used using the convert() method, or as a callable object:

result = converter(input_data)

Parameters:

input_data (Volume_S16) – data to be converted

Returns:

output data – converted data

Return type:

Volume_FLOAT

convert(input_data, output_data)

In-place converson inside existing allocated data

Parameters:

• input_data (Volume_S16) – data to be converted

• output_data (Volume_FLOAT) – conversion output will be done into this data

Return type:

None

class soma.aims.Converter_Volume_S16_Volume_HSV

Bases: wrapper

Converter classes can be used using the convert() method, or as a callable object:

result = converter(input_data)

Parameters:

input_data (Volume_S16) – data to be converted

Returns:

output data – converted data

Return type:

Volume_HSV

convert(input_data, output_data)

In-place converson inside existing allocated data

Parameters:

• input_data (Volume_S16) – data to be converted

• output_data (Volume_HSV) – conversion output will be done into this data

Return type:

None

class soma.aims.Converter_Volume_S16_Volume_RGB

Bases: wrapper

Converter classes can be used using the convert() method, or as a callable object:

result = converter(input_data)

Parameters:

input_data (Volume_S16) – data to be converted

Returns:

output data – converted data

Return type:

Volume_RGB

convert(input_data, output_data)

In-place converson inside existing allocated data

Parameters:

• input_data (Volume_S16) – data to be converted

• output_data (Volume_RGB) – conversion output will be done into this data

Return type:

None

class soma.aims.Converter_Volume_S16_Volume_RGBA

Bases: wrapper

Converter classes can be used using the convert() method, or as a callable object:

result = converter(input_data)

Parameters:

input_data (Volume_S16) – data to be converted

Returns:

output data – converted data

Return type:

Volume_RGBA

convert(input_data, output_data)

In-place converson inside existing allocated data

Parameters:

• input_data (Volume_S16) – data to be converted

• output_data (Volume_RGBA) – conversion output will be done into this data

Return type:

None

class soma.aims.Converter_Volume_S16_Volume_S16

Bases: wrapper

Converter classes can be used using the convert() method, or as a callable object:

result = converter(input_data)

Parameters:

input_data (Volume_S16) – data to be converted

Returns:

output data – converted data

Return type:

Volume_S16

convert(input_data, output_data)

In-place converson inside existing allocated data

Parameters:

• input_data (Volume_S16) – data to be converted

• output_data (Volume_S16) – conversion output will be done into this data

Return type:

None

class soma.aims.Converter_Volume_S16_Volume_S32

Bases: wrapper

Converter classes can be used using the convert() method, or as a callable object:

result = converter(input_data)

Parameters:

input_data (Volume_S16) – data to be converted

Returns:

output data – converted data

Return type:

Volume_S32

convert(input_data, output_data)

In-place converson inside existing allocated data

Parameters:

• input_data (Volume_S16) – data to be converted

• output_data (Volume_S32) – conversion output will be done into this data

Return type:

None

class soma.aims.Converter_Volume_S16_Volume_U16

Bases: wrapper

Converter classes can be used using the convert() method, or as a callable object:

result = converter(input_data)

Parameters:

input_data (Volume_S16) – data to be converted

Returns:

output data – converted data

Return type:

Volume_U16

convert(input_data, output_data)

In-place converson inside existing allocated data

Parameters:

• input_data (Volume_S16) – data to be converted

• output_data (Volume_U16) – conversion output will be done into this data

Return type:

None

class soma.aims.Converter_Volume_S16_Volume_U32

Bases: wrapper

Converter classes can be used using the convert() method, or as a callable object:

result = converter(input_data)

Parameters:

input_data (Volume_S16) – data to be converted

Returns:

output data – converted data

Return type:

Volume_U32

convert(input_data, output_data)

In-place converson inside existing allocated data

Parameters:

• input_data (Volume_S16) – data to be converted

• output_data (Volume_U32) – conversion output will be done into this data

Return type:

None

class soma.aims.Converter_Volume_S16_Volume_U8

Bases: wrapper

Converter classes can be used using the convert() method, or as a callable object:

result = converter(input_data)

Parameters:

input_data (Volume_S16) – data to be converted

Returns:

output data – converted data

Return type:

Volume_U8

convert(input_data, output_data)

In-place converson inside existing allocated data

Parameters:

• input_data (Volume_S16) – data to be converted

• output_data (Volume_U8) – conversion output will be done into this data

Return type:

None

class soma.aims.Converter_Volume_S32_Volume_DOUBLE

Bases: wrapper

Converter classes can be used using the convert() method, or as a callable object:

result = converter(input_data)

Parameters:

input_data (Volume_S32) – data to be converted

Returns:

output data – converted data

Return type:

Volume_DOUBLE

convert(input_data, output_data)

In-place converson inside existing allocated data

Parameters:

• input_data (Volume_S32) – data to be converted

• output_data (Volume_DOUBLE) – conversion output will be done into this data

Return type:

None

class soma.aims.Converter_Volume_S32_Volume_FLOAT

Bases: wrapper

Converter classes can be used using the convert() method, or as a callable object:

result = converter(input_data)

Parameters:

input_data (Volume_S32) – data to be converted

Returns:

output data – converted data

Return type:

Volume_FLOAT

convert(input_data, output_data)

In-place converson inside existing allocated data

Parameters:

• input_data (Volume_S32) – data to be converted

• output_data (Volume_FLOAT) – conversion output will be done into this data

Return type:

None

class soma.aims.Converter_Volume_S32_Volume_HSV

Bases: wrapper

Converter classes can be used using the convert() method, or as a callable object:

result = converter(input_data)

Parameters:

input_data (Volume_S32) – data to be converted

Returns:

output data – converted data

Return type:

Volume_HSV

convert(input_data, output_data)

In-place converson inside existing allocated data

Parameters:

• input_data (Volume_S32) – data to be converted

• output_data (Volume_HSV) – conversion output will be done into this data

Return type:

None

class soma.aims.Converter_Volume_S32_Volume_RGB

Bases: wrapper

Converter classes can be used using the convert() method, or as a callable object:

result = converter(input_data)

Parameters:

input_data (Volume_S32) – data to be converted

Returns:

output data – converted data

Return type:

Volume_RGB

convert(input_data, output_data)

In-place converson inside existing allocated data

Parameters:

• input_data (Volume_S32) – data to be converted

• output_data (Volume_RGB) – conversion output will be done into this data

Return type:

None

class soma.aims.Converter_Volume_S32_Volume_RGBA

Bases: wrapper

Converter classes can be used using the convert() method, or as a callable object:

result = converter(input_data)

Parameters:

input_data (Volume_S32) – data to be converted

Returns:

output data – converted data

Return type:

Volume_RGBA

convert(input_data, output_data)

In-place converson inside existing allocated data

Parameters:

• input_data (Volume_S32) – data to be converted

• output_data (Volume_RGBA) – conversion output will be done into this data

Return type:

None

class soma.aims.Converter_Volume_S32_Volume_S16

Bases: wrapper

Converter classes can be used using the convert() method, or as a callable object:

result = converter(input_data)

Parameters:

input_data (Volume_S32) – data to be converted

Returns:

output data – converted data

Return type:

Volume_S16

convert(input_data, output_data)

In-place converson inside existing allocated data

Parameters:

• input_data (Volume_S32) – data to be converted

• output_data (Volume_S16) – conversion output will be done into this data

Return type:

None

class soma.aims.Converter_Volume_S32_Volume_S32

Bases: wrapper

Converter classes can be used using the convert() method, or as a callable object:

result = converter(input_data)

Parameters:

input_data (Volume_S32) – data to be converted

Returns:

output data – converted data

Return type:

Volume_S32

convert(input_data, output_data)

In-place converson inside existing allocated data

Parameters:

• input_data (Volume_S32) – data to be converted

• output_data (Volume_S32) – conversion output will be done into this data

Return type:

None

class soma.aims.Converter_Volume_S32_Volume_U16

Bases: wrapper

Converter classes can be used using the convert() method, or as a callable object:

result = converter(input_data)

Parameters:

input_data (Volume_S32) – data to be converted

Returns:

output data – converted data

Return type:

Volume_U16

convert(input_data, output_data)

In-place converson inside existing allocated data

Parameters:

• input_data (Volume_S32) – data to be converted

• output_data (Volume_U16) – conversion output will be done into this data

Return type:

None

class soma.aims.Converter_Volume_S32_Volume_U32

Bases: wrapper

Converter classes can be used using the convert() method, or as a callable object:

result = converter(input_data)

Parameters:

input_data (Volume_S32) – data to be converted

Returns:

output data – converted data

Return type:

Volume_U32

convert(input_data, output_data)

In-place converson inside existing allocated data

Parameters:

• input_data (Volume_S32) – data to be converted

• output_data (Volume_U32) – conversion output will be done into this data

Return type:

None

class soma.aims.Converter_Volume_S32_Volume_U8

Bases: wrapper

Converter classes can be used using the convert() method, or as a callable object:

result = converter(input_data)

Parameters:

input_data (Volume_S32) – data to be converted

Returns:

output data – converted data

Return type:

Volume_U8

convert(input_data, output_data)

In-place converson inside existing allocated data

Parameters:

• input_data (Volume_S32) – data to be converted

• output_data (Volume_U8) – conversion output will be done into this data

Return type:

None

class soma.aims.Converter_Volume_U16_Volume_DOUBLE

Bases: wrapper

Converter classes can be used using the convert() method, or as a callable object:

result = converter(input_data)

Parameters:

input_data (Volume_U16) – data to be converted

Returns:

output data – converted data

Return type:

Volume_DOUBLE

convert(input_data, output_data)

In-place converson inside existing allocated data

Parameters:

• input_data (Volume_U16) – data to be converted

• output_data (Volume_DOUBLE) – conversion output will be done into this data

Return type:

None

class soma.aims.Converter_Volume_U16_Volume_FLOAT

Bases: wrapper

Converter classes can be used using the convert() method, or as a callable object:

result = converter(input_data)

Parameters:

input_data (Volume_U16) – data to be converted

Returns:

output data – converted data

Return type:

Volume_FLOAT

convert(input_data, output_data)

In-place converson inside existing allocated data

Parameters:

• input_data (Volume_U16) – data to be converted

• output_data (Volume_FLOAT) – conversion output will be done into this data

Return type:

None

class soma.aims.Converter_Volume_U16_Volume_HSV

Bases: wrapper

Converter classes can be used using the convert() method, or as a callable object:

result = converter(input_data)

Parameters:

input_data (Volume_U16) – data to be converted

Returns:

output data – converted data

Return type:

Volume_HSV

convert(input_data, output_data)

In-place converson inside existing allocated data

Parameters:

• input_data (Volume_U16) – data to be converted

• output_data (Volume_HSV) – conversion output will be done into this data

Return type:

None

class soma.aims.Converter_Volume_U16_Volume_RGB

Bases: wrapper

Converter classes can be used using the convert() method, or as a callable object:

result = converter(input_data)

Parameters:

input_data (Volume_U16) – data to be converted

Returns:

output data – converted data

Return type:

Volume_RGB

convert(input_data, output_data)

In-place converson inside existing allocated data

Parameters:

• input_data (Volume_U16) – data to be converted

• output_data (Volume_RGB) – conversion output will be done into this data

Return type:

None

class soma.aims.Converter_Volume_U16_Volume_RGBA

Bases: wrapper

Converter classes can be used using the convert() method, or as a callable object:

result = converter(input_data)

Parameters:

input_data (Volume_U16) – data to be converted

Returns:

output data – converted data

Return type:

Volume_RGBA

convert(input_data, output_data)

In-place converson inside existing allocated data

Parameters:

• input_data (Volume_U16) – data to be converted

• output_data (Volume_RGBA) – conversion output will be done into this data

Return type:

None

class soma.aims.Converter_Volume_U16_Volume_S16

Bases: wrapper

Converter classes can be used using the convert() method, or as a callable object:

result = converter(input_data)

Parameters:

input_data (Volume_U16) – data to be converted

Returns:

output data – converted data

Return type:

Volume_S16

convert(input_data, output_data)

In-place converson inside existing allocated data

Parameters:

• input_data (Volume_U16) – data to be converted

• output_data (Volume_S16) – conversion output will be done into this data

Return type:

None

class soma.aims.Converter_Volume_U16_Volume_S32

Bases: wrapper

Converter classes can be used using the convert() method, or as a callable object:

result = converter(input_data)

Parameters:

input_data (Volume_U16) – data to be converted

Returns:

output data – converted data

Return type:

Volume_S32

convert(input_data, output_data)

In-place converson inside existing allocated data

Parameters:

• input_data (Volume_U16) – data to be converted

• output_data (Volume_S32) – conversion output will be done into this data

Return type:

None

class soma.aims.Converter_Volume_U16_Volume_U16

Bases: wrapper

Converter classes can be used using the convert() method, or as a callable object:

result = converter(input_data)

Parameters:

input_data (Volume_U16) – data to be converted

Returns:

output data – converted data

Return type:

Volume_U16

convert(input_data, output_data)

In-place converson inside existing allocated data

Parameters:

• input_data (Volume_U16) – data to be converted

• output_data (Volume_U16) – conversion output will be done into this data

Return type:

None

class soma.aims.Converter_Volume_U16_Volume_U32

Bases: wrapper

Converter classes can be used using the convert() method, or as a callable object:

result = converter(input_data)

Parameters:

input_data (Volume_U16) – data to be converted

Returns:

output data – converted data

Return type:

Volume_U32

convert(input_data, output_data)

In-place converson inside existing allocated data

Parameters:

• input_data (Volume_U16) – data to be converted

• output_data (Volume_U32) – conversion output will be done into this data

Return type:

None

class soma.aims.Converter_Volume_U16_Volume_U8

Bases: wrapper

Converter classes can be used using the convert() method, or as a callable object:

result = converter(input_data)

Parameters:

input_data (Volume_U16) – data to be converted

Returns:

output data – converted data

Return type:

Volume_U8

convert(input_data, output_data)

In-place converson inside existing allocated data

Parameters:

• input_data (Volume_U16) – data to be converted

• output_data (Volume_U8) – conversion output will be done into this data

Return type:

None

class soma.aims.Converter_Volume_U32_Volume_DOUBLE

Bases: wrapper

Converter classes can be used using the convert() method, or as a callable object:

result = converter(input_data)

Parameters:

input_data (Volume_U32) – data to be converted

Returns:

output data – converted data

Return type:

Volume_DOUBLE

convert(input_data, output_data)

In-place converson inside existing allocated data

Parameters:

• input_data (Volume_U32) – data to be converted

• output_data (Volume_DOUBLE) – conversion output will be done into this data

Return type:

None

class soma.aims.Converter_Volume_U32_Volume_FLOAT

Bases: wrapper

Converter classes can be used using the convert() method, or as a callable object:

result = converter(input_data)

Parameters:

input_data (Volume_U32) – data to be converted

Returns:

output data – converted data

Return type:

Volume_FLOAT

convert(input_data, output_data)

In-place converson inside existing allocated data

Parameters:

• input_data (Volume_U32) – data to be converted

• output_data (Volume_FLOAT) – conversion output will be done into this data

Return type:

None

class soma.aims.Converter_Volume_U32_Volume_HSV

Bases: wrapper

Converter classes can be used using the convert() method, or as a callable object:

result = converter(input_data)

Parameters:

input_data (Volume_U32) – data to be converted

Returns:

output data – converted data

Return type:

Volume_HSV

convert(input_data, output_data)

In-place converson inside existing allocated data

Parameters:

• input_data (Volume_U32) – data to be converted

• output_data (Volume_HSV) – conversion output will be done into this data

Return type:

None

class soma.aims.Converter_Volume_U32_Volume_RGB

Bases: wrapper

Converter classes can be used using the convert() method, or as a callable object:

result = converter(input_data)

Parameters:

input_data (Volume_U32) – data to be converted

Returns:

output data – converted data

Return type:

Volume_RGB

convert(input_data, output_data)

In-place converson inside existing allocated data

Parameters:

• input_data (Volume_U32) – data to be converted

• output_data (Volume_RGB) – conversion output will be done into this data

Return type:

None

class soma.aims.Converter_Volume_U32_Volume_RGBA

Bases: wrapper

Converter classes can be used using the convert() method, or as a callable object:

result = converter(input_data)

Parameters:

input_data (Volume_U32) – data to be converted

Returns:

output data – converted data

Return type:

Volume_RGBA

convert(input_data, output_data)

In-place converson inside existing allocated data

Parameters:

• input_data (Volume_U32) – data to be converted

• output_data (Volume_RGBA) – conversion output will be done into this data

Return type:

None

class soma.aims.Converter_Volume_U32_Volume_S16

Bases: wrapper

Converter classes can be used using the convert() method, or as a callable object:

result = converter(input_data)

Parameters:

input_data (Volume_U32) – data to be converted

Returns:

output data – converted data

Return type:

Volume_S16

convert(input_data, output_data)

In-place converson inside existing allocated data

Parameters:

• input_data (Volume_U32) – data to be converted

• output_data (Volume_S16) – conversion output will be done into this data

Return type:

None

class soma.aims.Converter_Volume_U32_Volume_S32

Bases: wrapper

Converter classes can be used using the convert() method, or as a callable object:

result = converter(input_data)

Parameters:

input_data (Volume_U32) – data to be converted

Returns:

output data – converted data

Return type:

Volume_S32

convert(input_data, output_data)

In-place converson inside existing allocated data

Parameters:

• input_data (Volume_U32) – data to be converted

• output_data (Volume_S32) – conversion output will be done into this data

Return type:

None

class soma.aims.Converter_Volume_U32_Volume_U16

Bases: wrapper

Converter classes can be used using the convert() method, or as a callable object:

result = converter(input_data)

Parameters:

input_data (Volume_U32) – data to be converted

Returns:

output data – converted data

Return type:

Volume_U16

convert(input_data, output_data)

In-place converson inside existing allocated data

Parameters:

• input_data (Volume_U32) – data to be converted

• output_data (Volume_U16) – conversion output will be done into this data

Return type:

None

class soma.aims.Converter_Volume_U32_Volume_U32

Bases: wrapper

Converter classes can be used using the convert() method, or as a callable object:

result = converter(input_data)

Parameters:

input_data (Volume_U32) – data to be converted

Returns:

output data – converted data

Return type:

Volume_U32

convert(input_data, output_data)

In-place converson inside existing allocated data

Parameters:

• input_data (Volume_U32) – data to be converted

• output_data (Volume_U32) – conversion output will be done into this data

Return type:

None

class soma.aims.Converter_Volume_U32_Volume_U8

Bases: wrapper

Converter classes can be used using the convert() method, or as a callable object:

result = converter(input_data)

Parameters:

input_data (Volume_U32) – data to be converted

Returns:

output data – converted data

Return type:

Volume_U8

convert(input_data, output_data)

In-place converson inside existing allocated data

Parameters:

• input_data (Volume_U32) – data to be converted

• output_data (Volume_U8) – conversion output will be done into this data

Return type:

None

class soma.aims.Converter_Volume_U8_Volume_DOUBLE

Bases: wrapper

Converter classes can be used using the convert() method, or as a callable object:

result = converter(input_data)

Parameters:

input_data (Volume_U8) – data to be converted

Returns:

output data – converted data

Return type:

Volume_DOUBLE

convert(input_data, output_data)

In-place converson inside existing allocated data

Parameters:

• input_data (Volume_U8) – data to be converted

• output_data (Volume_DOUBLE) – conversion output will be done into this data

Return type:

None

class soma.aims.Converter_Volume_U8_Volume_FLOAT

Bases: wrapper

Converter classes can be used using the convert() method, or as a callable object:

result = converter(input_data)

Parameters:

input_data (Volume_U8) – data to be converted

Returns:

output data – converted data

Return type:

Volume_FLOAT

convert(input_data, output_data)

In-place converson inside existing allocated data

Parameters:

• input_data (Volume_U8) – data to be converted

• output_data (Volume_FLOAT) – conversion output will be done into this data

Return type:

None

class soma.aims.Converter_Volume_U8_Volume_HSV

Bases: wrapper

Converter classes can be used using the convert() method, or as a callable object:

result = converter(input_data)

Parameters:

input_data (Volume_U8) – data to be converted

Returns:

output data – converted data

Return type:

Volume_HSV

convert(input_data, output_data)

In-place converson inside existing allocated data

Parameters:

• input_data (Volume_U8) – data to be converted

• output_data (Volume_HSV) – conversion output will be done into this data

Return type:

None

class soma.aims.Converter_Volume_U8_Volume_RGB

Bases: wrapper

Converter classes can be used using the convert() method, or as a callable object:

result = converter(input_data)

Parameters:

input_data (Volume_U8) – data to be converted

Returns:

output data – converted data

Return type:

Volume_RGB

convert(input_data, output_data)

In-place converson inside existing allocated data

Parameters:

• input_data (Volume_U8) – data to be converted

• output_data (Volume_RGB) – conversion output will be done into this data

Return type:

None

class soma.aims.Converter_Volume_U8_Volume_RGBA

Bases: wrapper

Converter classes can be used using the convert() method, or as a callable object:

result = converter(input_data)

Parameters:

input_data (Volume_U8) – data to be converted

Returns:

output data – converted data

Return type:

Volume_RGBA

convert(input_data, output_data)

In-place converson inside existing allocated data

Parameters:

• input_data (Volume_U8) – data to be converted

• output_data (Volume_RGBA) – conversion output will be done into this data

Return type:

None

class soma.aims.Converter_Volume_U8_Volume_S16

Bases: wrapper

Converter classes can be used using the convert() method, or as a callable object:

result = converter(input_data)

Parameters:

input_data (Volume_U8) – data to be converted

Returns:

output data – converted data

Return type:

Volume_S16

convert(input_data, output_data)

In-place converson inside existing allocated data

Parameters:

• input_data (Volume_U8) – data to be converted

• output_data (Volume_S16) – conversion output will be done into this data

Return type:

None

class soma.aims.Converter_Volume_U8_Volume_S32

Bases: wrapper

Converter classes can be used using the convert() method, or as a callable object:

result = converter(input_data)

Parameters:

input_data (Volume_U8) – data to be converted

Returns:

output data – converted data

Return type:

Volume_S32

convert(input_data, output_data)

In-place converson inside existing allocated data

Parameters:

• input_data (Volume_U8) – data to be converted

• output_data (Volume_S32) – conversion output will be done into this data

Return type:

None

class soma.aims.Converter_Volume_U8_Volume_U16

Bases: wrapper

Converter classes can be used using the convert() method, or as a callable object:

result = converter(input_data)

Parameters:

input_data (Volume_U8) – data to be converted

Returns:

output data – converted data

Return type:

Volume_U16

convert(input_data, output_data)

In-place converson inside existing allocated data

Parameters:

• input_data (Volume_U8) – data to be converted

• output_data (Volume_U16) – conversion output will be done into this data

Return type:

None

class soma.aims.Converter_Volume_U8_Volume_U32

Bases: wrapper

Converter classes can be used using the convert() method, or as a callable object:

result = converter(input_data)

Parameters:

input_data (Volume_U8) – data to be converted

Returns:

output data – converted data

Return type:

Volume_U32

convert(input_data, output_data)

In-place converson inside existing allocated data

Parameters:

• input_data (Volume_U8) – data to be converted

• output_data (Volume_U32) – conversion output will be done into this data

Return type:

None

class soma.aims.Converter_Volume_U8_Volume_U8

Bases: wrapper

Converter classes can be used using the convert() method, or as a callable object:

result = converter(input_data)

Parameters:

input_data (Volume_U8) – data to be converted

Returns:

output data – converted data

Return type:

Volume_U8

convert(input_data, output_data)

In-place converson inside existing allocated data

Parameters:

• input_data (Volume_U8) – data to be converted

• output_data (Volume_U8) – conversion output will be done into this data

Return type:

None

class soma.aims.Converter_rc_ptr_Volume_DOUBLE_BucketMap_DOUBLE

Bases: wrapper

Converter classes can be used using the convert() method, or as a callable object:

result = converter(input_data)

Parameters:

input_data (rc_ptr_Volume_DOUBLE) – data to be converted

Returns:

output data – converted data

Return type:

BucketMap_DOUBLE

convert(input_data, output_data)

In-place converson inside existing allocated data

Parameters:

• input_data (rc_ptr_Volume_DOUBLE) – data to be converted

• output_data (BucketMap_DOUBLE) – conversion output will be done into this data

Return type:

None

class soma.aims.Converter_rc_ptr_Volume_DOUBLE_BucketMap_FLOAT

Bases: wrapper

Converter classes can be used using the convert() method, or as a callable object:

result = converter(input_data)

Parameters:

input_data (rc_ptr_Volume_DOUBLE) – data to be converted

Returns:

output data – converted data

Return type:

BucketMap_FLOAT

convert(input_data, output_data)

In-place converson inside existing allocated data

Parameters:

• input_data (rc_ptr_Volume_DOUBLE) – data to be converted

• output_data (BucketMap_FLOAT) – conversion output will be done into this data

Return type:

None

class soma.aims.Converter_rc_ptr_Volume_DOUBLE_BucketMap_S16

Bases: wrapper

Converter classes can be used using the convert() method, or as a callable object:

result = converter(input_data)

Parameters:

input_data (rc_ptr_Volume_DOUBLE) – data to be converted

Returns:

output data – converted data

Return type:

BucketMap_S16

convert(input_data, output_data)

In-place converson inside existing allocated data

Parameters:

• input_data (rc_ptr_Volume_DOUBLE) – data to be converted

• output_data (BucketMap_S16) – conversion output will be done into this data

Return type:

None

class soma.aims.Converter_rc_ptr_Volume_DOUBLE_BucketMap_S32

Bases: wrapper

Converter classes can be used using the convert() method, or as a callable object:

result = converter(input_data)

Parameters:

input_data (rc_ptr_Volume_DOUBLE) – data to be converted

Returns:

output data – converted data

Return type:

BucketMap_S32

convert(input_data, output_data)

In-place converson inside existing allocated data

Parameters:

• input_data (rc_ptr_Volume_DOUBLE) – data to be converted

• output_data (BucketMap_S32) – conversion output will be done into this data

Return type:

None

class soma.aims.Converter_rc_ptr_Volume_DOUBLE_BucketMap_U16

Bases: wrapper

Converter classes can be used using the convert() method, or as a callable object:

result = converter(input_data)

Parameters:

input_data (rc_ptr_Volume_DOUBLE) – data to be converted

Returns:

output data – converted data

Return type:

BucketMap_U16

convert(input_data, output_data)

In-place converson inside existing allocated data

Parameters:

• input_data (rc_ptr_Volume_DOUBLE) – data to be converted

• output_data (BucketMap_U16) – conversion output will be done into this data

Return type:

None

class soma.aims.Converter_rc_ptr_Volume_DOUBLE_BucketMap_U32

Bases: wrapper

Converter classes can be used using the convert() method, or as a callable object:

result = converter(input_data)

Parameters:

input_data (rc_ptr_Volume_DOUBLE) – data to be converted

Returns:

output data – converted data

Return type:

BucketMap_U32

convert(input_data, output_data)

In-place converson inside existing allocated data

Parameters:

• input_data (rc_ptr_Volume_DOUBLE) – data to be converted

• output_data (BucketMap_U32) – conversion output will be done into this data

Return type:

None

class soma.aims.Converter_rc_ptr_Volume_DOUBLE_BucketMap_VOID

Bases: wrapper

Converter classes can be used using the convert() method, or as a callable object:

result = converter(input_data)

Parameters:

input_data (rc_ptr_Volume_DOUBLE) – data to be converted

Returns:

output data – converted data

Return type:

BucketMap_VOID

convert(input_data, output_data)

In-place converson inside existing allocated data

Parameters:

• input_data (rc_ptr_Volume_DOUBLE) – data to be converted

• output_data (BucketMap_VOID) – conversion output will be done into this data

Return type:

None

class soma.aims.Converter_rc_ptr_Volume_FLOAT_BucketMap_DOUBLE

Bases: wrapper

Converter classes can be used using the convert() method, or as a callable object:

result = converter(input_data)

Parameters:

input_data (rc_ptr_Volume_FLOAT) – data to be converted

Returns:

output data – converted data

Return type:

BucketMap_DOUBLE

convert(input_data, output_data)

In-place converson inside existing allocated data

Parameters:

• input_data (rc_ptr_Volume_FLOAT) – data to be converted

• output_data (BucketMap_DOUBLE) – conversion output will be done into this data

Return type:

None

class soma.aims.Converter_rc_ptr_Volume_FLOAT_BucketMap_FLOAT

Bases: wrapper

Converter classes can be used using the convert() method, or as a callable object:

result = converter(input_data)

Parameters:

input_data (rc_ptr_Volume_FLOAT) – data to be converted

Returns:

output data – converted data

Return type:

BucketMap_FLOAT

convert(input_data, output_data)

In-place converson inside existing allocated data

Parameters:

• input_data (rc_ptr_Volume_FLOAT) – data to be converted

• output_data (BucketMap_FLOAT) – conversion output will be done into this data

Return type:

None

class soma.aims.Converter_rc_ptr_Volume_FLOAT_BucketMap_S16

Bases: wrapper

Converter classes can be used using the convert() method, or as a callable object:

result = converter(input_data)

Parameters:

input_data (rc_ptr_Volume_FLOAT) – data to be converted

Returns:

output data – converted data

Return type:

BucketMap_S16

convert(input_data, output_data)

In-place converson inside existing allocated data

Parameters:

• input_data (rc_ptr_Volume_FLOAT) – data to be converted

• output_data (BucketMap_S16) – conversion output will be done into this data

Return type:

None

class soma.aims.Converter_rc_ptr_Volume_FLOAT_BucketMap_S32

Bases: wrapper

Converter classes can be used using the convert() method, or as a callable object:

result = converter(input_data)

Parameters:

input_data (rc_ptr_Volume_FLOAT) – data to be converted

Returns:

output data – converted data

Return type:

BucketMap_S32

convert(input_data, output_data)

In-place converson inside existing allocated data

Parameters:

• input_data (rc_ptr_Volume_FLOAT) – data to be converted

• output_data (BucketMap_S32) – conversion output will be done into this data

Return type:

None

class soma.aims.Converter_rc_ptr_Volume_FLOAT_BucketMap_U16

Bases: wrapper

Converter classes can be used using the convert() method, or as a callable object:

result = converter(input_data)

Parameters:

input_data (rc_ptr_Volume_FLOAT) – data to be converted

Returns:

output data – converted data

Return type:

BucketMap_U16

convert(input_data, output_data)

In-place converson inside existing allocated data

Parameters:

• input_data (rc_ptr_Volume_FLOAT) – data to be converted

• output_data (BucketMap_U16) – conversion output will be done into this data

Return type:

None

class soma.aims.Converter_rc_ptr_Volume_FLOAT_BucketMap_U32

Bases: wrapper

Converter classes can be used using the convert() method, or as a callable object:

result = converter(input_data)

Parameters:

input_data (rc_ptr_Volume_FLOAT) – data to be converted

Returns:

output data – converted data

Return type:

BucketMap_U32

convert(input_data, output_data)

In-place converson inside existing allocated data

Parameters:

• input_data (rc_ptr_Volume_FLOAT) – data to be converted

• output_data (BucketMap_U32) – conversion output will be done into this data

Return type:

None

class soma.aims.Converter_rc_ptr_Volume_FLOAT_BucketMap_VOID

Bases: wrapper

Converter classes can be used using the convert() method, or as a callable object:

result = converter(input_data)

Parameters:

input_data (rc_ptr_Volume_FLOAT) – data to be converted

Returns:

output data – converted data

Return type:

BucketMap_VOID

convert(input_data, output_data)

In-place converson inside existing allocated data

Parameters:

• input_data (rc_ptr_Volume_FLOAT) – data to be converted

• output_data (BucketMap_VOID) – conversion output will be done into this data

Return type:

None

class soma.aims.Converter_rc_ptr_Volume_S16_BucketMap_DOUBLE

Bases: wrapper

Converter classes can be used using the convert() method, or as a callable object:

result = converter(input_data)

Parameters:

input_data (rc_ptr_Volume_S16) – data to be converted

Returns:

output data – converted data

Return type:

BucketMap_DOUBLE

convert(input_data, output_data)

In-place converson inside existing allocated data

Parameters:

• input_data (rc_ptr_Volume_S16) – data to be converted

• output_data (BucketMap_DOUBLE) – conversion output will be done into this data

Return type:

None

class soma.aims.Converter_rc_ptr_Volume_S16_BucketMap_FLOAT

Bases: wrapper

Converter classes can be used using the convert() method, or as a callable object:

result = converter(input_data)

Parameters:

input_data (rc_ptr_Volume_S16) – data to be converted

Returns:

output data – converted data

Return type:

BucketMap_FLOAT

convert(input_data, output_data)

In-place converson inside existing allocated data

Parameters:

• input_data (rc_ptr_Volume_S16) – data to be converted

• output_data (BucketMap_FLOAT) – conversion output will be done into this data

Return type:

None

class soma.aims.Converter_rc_ptr_Volume_S16_BucketMap_S16

Bases: wrapper

Converter classes can be used using the convert() method, or as a callable object:

result = converter(input_data)

Parameters:

input_data (rc_ptr_Volume_S16) – data to be converted

Returns:

output data – converted data

Return type:

BucketMap_S16

convert(input_data, output_data)

In-place converson inside existing allocated data

Parameters:

• input_data (rc_ptr_Volume_S16) – data to be converted

• output_data (BucketMap_S16) – conversion output will be done into this data

Return type:

None

class soma.aims.Converter_rc_ptr_Volume_S16_BucketMap_S32

Bases: wrapper

Converter classes can be used using the convert() method, or as a callable object:

result = converter(input_data)

Parameters:

input_data (rc_ptr_Volume_S16) – data to be converted

Returns:

output data – converted data

Return type:

BucketMap_S32

convert(input_data, output_data)

In-place converson inside existing allocated data

Parameters:

• input_data (rc_ptr_Volume_S16) – data to be converted

• output_data (BucketMap_S32) – conversion output will be done into this data

Return type:

None

class soma.aims.Converter_rc_ptr_Volume_S16_BucketMap_U16

Bases: wrapper

Converter classes can be used using the convert() method, or as a callable object:

result = converter(input_data)

Parameters:

input_data (rc_ptr_Volume_S16) – data to be converted

Returns:

output data – converted data

Return type:

BucketMap_U16

convert(input_data, output_data)

In-place converson inside existing allocated data

Parameters:

• input_data (rc_ptr_Volume_S16) – data to be converted

• output_data (BucketMap_U16) – conversion output will be done into this data

Return type:

None

class soma.aims.Converter_rc_ptr_Volume_S16_BucketMap_U32

Bases: wrapper

Converter classes can be used using the convert() method, or as a callable object:

result = converter(input_data)

Parameters:

input_data (rc_ptr_Volume_S16) – data to be converted

Returns:

output data – converted data

Return type:

BucketMap_U32

convert(input_data, output_data)

In-place converson inside existing allocated data

Parameters:

• input_data (rc_ptr_Volume_S16) – data to be converted

• output_data (BucketMap_U32) – conversion output will be done into this data

Return type:

None

class soma.aims.Converter_rc_ptr_Volume_S16_BucketMap_VOID

Bases: wrapper

Converter classes can be used using the convert() method, or as a callable object:

result = converter(input_data)

Parameters:

input_data (rc_ptr_Volume_S16) – data to be converted

Returns:

output data – converted data

Return type:

BucketMap_VOID

convert(input_data, output_data)

In-place converson inside existing allocated data

Parameters:

• input_data (rc_ptr_Volume_S16) – data to be converted

• output_data (BucketMap_VOID) – conversion output will be done into this data

Return type:

None

class soma.aims.Converter_rc_ptr_Volume_S32_BucketMap_DOUBLE

Bases: wrapper

Converter classes can be used using the convert() method, or as a callable object:

result = converter(input_data)

Parameters:

input_data (rc_ptr_Volume_S32) – data to be converted

Returns:

output data – converted data

Return type:

BucketMap_DOUBLE

convert(input_data, output_data)

In-place converson inside existing allocated data

Parameters:

• input_data (rc_ptr_Volume_S32) – data to be converted

• output_data (BucketMap_DOUBLE) – conversion output will be done into this data

Return type:

None

class soma.aims.Converter_rc_ptr_Volume_S32_BucketMap_FLOAT

Bases: wrapper

Converter classes can be used using the convert() method, or as a callable object:

result = converter(input_data)

Parameters:

input_data (rc_ptr_Volume_S32) – data to be converted

Returns:

output data – converted data

Return type:

BucketMap_FLOAT

convert(input_data, output_data)

In-place converson inside existing allocated data

Parameters:

• input_data (rc_ptr_Volume_S32) – data to be converted

• output_data (BucketMap_FLOAT) – conversion output will be done into this data

Return type:

None

class soma.aims.Converter_rc_ptr_Volume_S32_BucketMap_S16

Bases: wrapper

Converter classes can be used using the convert() method, or as a callable object:

result = converter(input_data)

Parameters:

input_data (rc_ptr_Volume_S32) – data to be converted

Returns:

output data – converted data

Return type:

BucketMap_S16

convert(input_data, output_data)

In-place converson inside existing allocated data

Parameters:

• input_data (rc_ptr_Volume_S32) – data to be converted

• output_data (BucketMap_S16) – conversion output will be done into this data

Return type:

None

class soma.aims.Converter_rc_ptr_Volume_S32_BucketMap_S32

Bases: wrapper

Converter classes can be used using the convert() method, or as a callable object:

result = converter(input_data)

Parameters:

input_data (rc_ptr_Volume_S32) – data to be converted

Returns:

output data – converted data

Return type:

BucketMap_S32

convert(input_data, output_data)

In-place converson inside existing allocated data

Parameters:

• input_data (rc_ptr_Volume_S32) – data to be converted

• output_data (BucketMap_S32) – conversion output will be done into this data

Return type:

None

class soma.aims.Converter_rc_ptr_Volume_S32_BucketMap_U16

Bases: wrapper

Converter classes can be used using the convert() method, or as a callable object:

result = converter(input_data)

Parameters:

input_data (rc_ptr_Volume_S32) – data to be converted

Returns:

output data – converted data

Return type:

BucketMap_U16

convert(input_data, output_data)

In-place converson inside existing allocated data

Parameters:

• input_data (rc_ptr_Volume_S32) – data to be converted

• output_data (BucketMap_U16) – conversion output will be done into this data

Return type:

None

class soma.aims.Converter_rc_ptr_Volume_S32_BucketMap_U32

Bases: wrapper

Converter classes can be used using the convert() method, or as a callable object:

result = converter(input_data)

Parameters:

input_data (rc_ptr_Volume_S32) – data to be converted

Returns:

output data – converted data

Return type:

BucketMap_U32

convert(input_data, output_data)

In-place converson inside existing allocated data

Parameters:

• input_data (rc_ptr_Volume_S32) – data to be converted

• output_data (BucketMap_U32) – conversion output will be done into this data

Return type:

None

class soma.aims.Converter_rc_ptr_Volume_S32_BucketMap_VOID

Bases: wrapper

Converter classes can be used using the convert() method, or as a callable object:

result = converter(input_data)

Parameters:

input_data (rc_ptr_Volume_S32) – data to be converted

Returns:

output data – converted data

Return type:

BucketMap_VOID

convert(input_data, output_data)

In-place converson inside existing allocated data

Parameters:

• input_data (rc_ptr_Volume_S32) – data to be converted

• output_data (BucketMap_VOID) – conversion output will be done into this data

Return type:

None

class soma.aims.Converter_rc_ptr_Volume_U16_BucketMap_DOUBLE

Bases: wrapper

Converter classes can be used using the convert() method, or as a callable object:

result = converter(input_data)

Parameters:

input_data (rc_ptr_Volume_U16) – data to be converted

Returns:

output data – converted data

Return type:

BucketMap_DOUBLE

convert(input_data, output_data)

In-place converson inside existing allocated data

Parameters:

• input_data (rc_ptr_Volume_U16) – data to be converted

• output_data (BucketMap_DOUBLE) – conversion output will be done into this data

Return type:

None

class soma.aims.Converter_rc_ptr_Volume_U16_BucketMap_FLOAT

Bases: wrapper

Converter classes can be used using the convert() method, or as a callable object:

result = converter(input_data)

Parameters:

input_data (rc_ptr_Volume_U16) – data to be converted

Returns:

output data – converted data

Return type:

BucketMap_FLOAT

convert(input_data, output_data)

In-place converson inside existing allocated data

Parameters:

• input_data (rc_ptr_Volume_U16) – data to be converted

• output_data (BucketMap_FLOAT) – conversion output will be done into this data

Return type:

None

class soma.aims.Converter_rc_ptr_Volume_U16_BucketMap_S16

Bases: wrapper

Converter classes can be used using the convert() method, or as a callable object:

result = converter(input_data)

Parameters:

input_data (rc_ptr_Volume_U16) – data to be converted

Returns:

output data – converted data

Return type:

BucketMap_S16

convert(input_data, output_data)

In-place converson inside existing allocated data

Parameters:

• input_data (rc_ptr_Volume_U16) – data to be converted

• output_data (BucketMap_S16) – conversion output will be done into this data

Return type:

None

class soma.aims.Converter_rc_ptr_Volume_U16_BucketMap_S32

Bases: wrapper

Converter classes can be used using the convert() method, or as a callable object:

result = converter(input_data)

Parameters:

input_data (rc_ptr_Volume_U16) – data to be converted

Returns:

output data – converted data

Return type:

BucketMap_S32

convert(input_data, output_data)

In-place converson inside existing allocated data

Parameters:

• input_data (rc_ptr_Volume_U16) – data to be converted

• output_data (BucketMap_S32) – conversion output will be done into this data

Return type:

None

class soma.aims.Converter_rc_ptr_Volume_U16_BucketMap_U16

Bases: wrapper

Converter classes can be used using the convert() method, or as a callable object:

result = converter(input_data)

Parameters:

input_data (rc_ptr_Volume_U16) – data to be converted

Returns:

output data – converted data

Return type:

BucketMap_U16

convert(input_data, output_data)

In-place converson inside existing allocated data

Parameters:

• input_data (rc_ptr_Volume_U16) – data to be converted

• output_data (BucketMap_U16) – conversion output will be done into this data

Return type:

None

class soma.aims.Converter_rc_ptr_Volume_U16_BucketMap_U32

Bases: wrapper

Converter classes can be used using the convert() method, or as a callable object:

result = converter(input_data)

Parameters:

input_data (rc_ptr_Volume_U16) – data to be converted

Returns:

output data – converted data

Return type:

BucketMap_U32

convert(input_data, output_data)

In-place converson inside existing allocated data

Parameters:

• input_data (rc_ptr_Volume_U16) – data to be converted

• output_data (BucketMap_U32) – conversion output will be done into this data

Return type:

None

class soma.aims.Converter_rc_ptr_Volume_U16_BucketMap_VOID

Bases: wrapper

Converter classes can be used using the convert() method, or as a callable object:

result = converter(input_data)

Parameters:

input_data (rc_ptr_Volume_U16) – data to be converted

Returns:

output data – converted data

Return type:

BucketMap_VOID

convert(input_data, output_data)

In-place converson inside existing allocated data

Parameters:

• input_data (rc_ptr_Volume_U16) – data to be converted

• output_data (BucketMap_VOID) – conversion output will be done into this data

Return type:

None

class soma.aims.Converter_rc_ptr_Volume_U32_BucketMap_DOUBLE

Bases: wrapper

Converter classes can be used using the convert() method, or as a callable object:

result = converter(input_data)

Parameters:

input_data (rc_ptr_Volume_U32) – data to be converted

Returns:

output data – converted data

Return type:

BucketMap_DOUBLE

convert(input_data, output_data)

In-place converson inside existing allocated data

Parameters:

• input_data (rc_ptr_Volume_U32) – data to be converted

• output_data (BucketMap_DOUBLE) – conversion output will be done into this data

Return type:

None

class soma.aims.Converter_rc_ptr_Volume_U32_BucketMap_FLOAT

Bases: wrapper

Converter classes can be used using the convert() method, or as a callable object:

result = converter(input_data)

Parameters:

input_data (rc_ptr_Volume_U32) – data to be converted

Returns:

output data – converted data

Return type:

BucketMap_FLOAT

convert(input_data, output_data)

In-place converson inside existing allocated data

Parameters:

• input_data (rc_ptr_Volume_U32) – data to be converted

• output_data (BucketMap_FLOAT) – conversion output will be done into this data

Return type:

None

class soma.aims.Converter_rc_ptr_Volume_U32_BucketMap_S16

Bases: wrapper

Converter classes can be used using the convert() method, or as a callable object:

result = converter(input_data)

Parameters:

input_data (rc_ptr_Volume_U32) – data to be converted

Returns:

output data – converted data

Return type:

BucketMap_S16

convert(input_data, output_data)

In-place converson inside existing allocated data

Parameters:

• input_data (rc_ptr_Volume_U32) – data to be converted

• output_data (BucketMap_S16) – conversion output will be done into this data

Return type:

None

class soma.aims.Converter_rc_ptr_Volume_U32_BucketMap_S32

Bases: wrapper

Converter classes can be used using the convert() method, or as a callable object:

result = converter(input_data)

Parameters:

input_data (rc_ptr_Volume_U32) – data to be converted

Returns:

output data – converted data

Return type:

BucketMap_S32

convert(input_data, output_data)

In-place converson inside existing allocated data

Parameters:

• input_data (rc_ptr_Volume_U32) – data to be converted

• output_data (BucketMap_S32) – conversion output will be done into this data

Return type:

None

class soma.aims.Converter_rc_ptr_Volume_U32_BucketMap_U16

Bases: wrapper

Converter classes can be used using the convert() method, or as a callable object:

result = converter(input_data)

Parameters:

input_data (rc_ptr_Volume_U32) – data to be converted

Returns:

output data – converted data

Return type:

BucketMap_U16

convert(input_data, output_data)

In-place converson inside existing allocated data

Parameters:

• input_data (rc_ptr_Volume_U32) – data to be converted

• output_data (BucketMap_U16) – conversion output will be done into this data

Return type:

None

class soma.aims.Converter_rc_ptr_Volume_U32_BucketMap_U32

Bases: wrapper

Converter classes can be used using the convert() method, or as a callable object:

result = converter(input_data)

Parameters:

input_data (rc_ptr_Volume_U32) – data to be converted

Returns:

output data – converted data

Return type:

BucketMap_U32

convert(input_data, output_data)

In-place converson inside existing allocated data

Parameters:

• input_data (rc_ptr_Volume_U32) – data to be converted

• output_data (BucketMap_U32) – conversion output will be done into this data

Return type:

None

class soma.aims.Converter_rc_ptr_Volume_U32_BucketMap_VOID

Bases: wrapper

Converter classes can be used using the convert() method, or as a callable object:

result = converter(input_data)

Parameters:

input_data (rc_ptr_Volume_U32) – data to be converted

Returns:

output data – converted data

Return type:

BucketMap_VOID

convert(input_data, output_data)

In-place converson inside existing allocated data

Parameters:

• input_data (rc_ptr_Volume_U32) – data to be converted

• output_data (BucketMap_VOID) – conversion output will be done into this data

Return type:

None

class soma.aims.Converter_rc_ptr_Volume_U8_BucketMap_DOUBLE

Bases: wrapper

Converter classes can be used using the convert() method, or as a callable object:

result = converter(input_data)

Parameters:

input_data (rc_ptr_Volume_U8) – data to be converted

Returns:

output data – converted data

Return type:

BucketMap_DOUBLE

convert(input_data, output_data)

In-place converson inside existing allocated data

Parameters:

• input_data (rc_ptr_Volume_U8) – data to be converted

• output_data (BucketMap_DOUBLE) – conversion output will be done into this data

Return type:

None

class soma.aims.Converter_rc_ptr_Volume_U8_BucketMap_FLOAT

Bases: wrapper

Converter classes can be used using the convert() method, or as a callable object:

result = converter(input_data)

Parameters:

input_data (rc_ptr_Volume_U8) – data to be converted

Returns:

output data – converted data

Return type:

BucketMap_FLOAT

convert(input_data, output_data)

In-place converson inside existing allocated data

Parameters:

• input_data (rc_ptr_Volume_U8) – data to be converted

• output_data (BucketMap_FLOAT) – conversion output will be done into this data

Return type:

None

class soma.aims.Converter_rc_ptr_Volume_U8_BucketMap_S16

Bases: wrapper

Converter classes can be used using the convert() method, or as a callable object:

result = converter(input_data)

Parameters:

input_data (rc_ptr_Volume_U8) – data to be converted

Returns:

output data – converted data

Return type:

BucketMap_S16

convert(input_data, output_data)

In-place converson inside existing allocated data

Parameters:

• input_data (rc_ptr_Volume_U8) – data to be converted

• output_data (BucketMap_S16) – conversion output will be done into this data

Return type:

None

class soma.aims.Converter_rc_ptr_Volume_U8_BucketMap_S32

Bases: wrapper

Converter classes can be used using the convert() method, or as a callable object:

result = converter(input_data)

Parameters:

input_data (rc_ptr_Volume_U8) – data to be converted

Returns:

output data – converted data

Return type:

BucketMap_S32

convert(input_data, output_data)

In-place converson inside existing allocated data

Parameters:

• input_data (rc_ptr_Volume_U8) – data to be converted

• output_data (BucketMap_S32) – conversion output will be done into this data

Return type:

None

class soma.aims.Converter_rc_ptr_Volume_U8_BucketMap_U16

Bases: wrapper

Converter classes can be used using the convert() method, or as a callable object:

result = converter(input_data)

Parameters:

input_data (rc_ptr_Volume_U8) – data to be converted

Returns:

output data – converted data

Return type:

BucketMap_U16

convert(input_data, output_data)

In-place converson inside existing allocated data

Parameters:

• input_data (rc_ptr_Volume_U8) – data to be converted

• output_data (BucketMap_U16) – conversion output will be done into this data

Return type:

None

class soma.aims.Converter_rc_ptr_Volume_U8_BucketMap_U32

Bases: wrapper

Converter classes can be used using the convert() method, or as a callable object:

result = converter(input_data)

Parameters:

input_data (rc_ptr_Volume_U8) – data to be converted

Returns:

output data – converted data

Return type:

BucketMap_U32

convert(input_data, output_data)

In-place converson inside existing allocated data

Parameters:

• input_data (rc_ptr_Volume_U8) – data to be converted

• output_data (BucketMap_U32) – conversion output will be done into this data

Return type:

None

class soma.aims.Converter_rc_ptr_Volume_U8_BucketMap_VOID

Bases: wrapper

Converter classes can be used using the convert() method, or as a callable object:

result = converter(input_data)

Parameters:

input_data (rc_ptr_Volume_U8) – data to be converted

Returns:

output data – converted data

Return type:

BucketMap_VOID

convert(input_data, output_data)

In-place converson inside existing allocated data

Parameters:

• input_data (rc_ptr_Volume_U8) – data to be converted

• output_data (BucketMap_VOID) – conversion output will be done into this data

Return type:

None

class soma.aims.CurveSelection

Bases: BundleProducer, BundleListener

addFiberPoint()

bundleStarted(producer, bundle_info)

bundleTerminated(producer, bundle_info)

fiberStarted(producer, bundle_info, fiber_info)

fiberTerminated(producer, bundle_info, fiber_info)

newFiberPoint(producer, bundle_info, fiber_info, point)

noMoreBundle(producer)

startBundle()

startFiber()

terminateBundle()

terminateFiber()

class soma.aims.CutMesh

Bases: wrapper

Cut meshes by a plane. The output of the operation is one cut mesh per input mesh, and possibly a border polygon mesh, and a plane intersection mesh.

The plane mesh is not always correct, it is now preferred to use GLU’s tesselation algorithm.

To use it:

• initialize using a constructor and/or set input parameters (see also the CutTexturedMesh subclasses to handle textured meshes)

• call cut() or cutBorder(), these are the methods actually doing things

• get outputs using cutMeshes(), borderLine(), planeMesh() and CutTexturedMesh.cutTextures()

borderLine()

cut()

cutBorder()

cutMeshes()

planeMesh()

class soma.aims.Edge(*args, **kwargs)

Bases: GraphObject

clone()

currentValue()

getScalar()

getString()

hasSyntax()

hasVertex()

has_key()

intKey()

isArray()

isDictionary()

isDictionaryIterator()

isDynArray()

isIterable()

isIterator()

isValid()

key()

objectIterator()

setSyntax()

size()

type()

vertices()

verticesSize()

exception soma.aims.ErrnoError

Bases: RuntimeError

class soma.aims.FiberInfo

Bases: wrapper

id()

exception soma.aims.FileError

Bases: RuntimeError

class soma.aims.FileFormatDictionary_AimsTimeSurface_2_VOID

Bases: wrapper

fileExtension()

fileFormat()

formats()

init()

registerBaseFormats()

registerFormat()

unregisterFormat()

class soma.aims.FileFormatDictionary_AimsTimeSurface_3_VOID

Bases: wrapper

fileExtension()

fileFormat()

formats()

init()

registerBaseFormats()

registerFormat()

unregisterFormat()

class soma.aims.FileFormatDictionary_Object

Bases: wrapper

fileExtension()

fileFormat()

formats()

init()

registerBaseFormats()

registerFormat()

unregisterFormat()

class soma.aims.FileFormatDictionary_SparseOrDenseMatrix

Bases: wrapper

fileExtension()

fileFormat()

formats()

init()

registerBaseFormats()

registerFormat()

unregisterFormat()

class soma.aims.FileFormatDictionary_Transformation3d

Bases: wrapper

fileExtension()

fileFormat()

formats()

init()

registerBaseFormats()

registerFormat()

unregisterFormat()

class soma.aims.FileFormatDictionary_TransformationGraph3d

Bases: wrapper

fileExtension()

fileFormat()

formats()

init()

registerBaseFormats()

registerFormat()

unregisterFormat()

class soma.aims.FileFormat_AimsTimeSurface_2_VOID

Bases: wrapper

read()

write()

class soma.aims.FileFormat_AimsTimeSurface_3_VOID

Bases: wrapper

read()

write()

class soma.aims.FileFormat_Object

Bases: wrapper

read()

write()

class soma.aims.FileFormat_SparseOrDenseMatrix

Bases: wrapper

read()

write()

class soma.aims.FileFormat_Transformation3d

Bases: wrapper

read()

write()

class soma.aims.FileFormat_TransformationGraph3d

Bases: wrapper

read()

write()

class soma.aims.Finder

Bases: wrapper

check()

dataType()

extensions()

finderFormat()

format()

header()

objectType()

possibleDataTypes()

registerFormat()

setDataType()

setFormat()

setHeader()

setObjectType()

setPossibleDataTypes()

unregisterFormat()

class soma.aims.FinderFormat

Bases: wrapper

check()

class soma.aims.GenericHandlers

Bases: object

Static generic handlers used as import rules.

static moveChildren(namespace, extendedModule, referedModule)

This static method is used to move child objects of a refered module to the extended module.

Parameters:

• namespace (string) – namespace of the referedModule to get objects to move from.

• extendedModule (ExtendedModule) – ExtendedModule object into which move objects.

• referedModule (module) – refered module object to get objects to move from.

static removeChildren(namespace, prefixes, extendedModule, referedModule)

This static method is used to remove children from the extended module.

Parameters:

• namespace (string) – namespace of the referedModule.

• prefixes (list) – list of prefixes of objects to remove.

• extendedModule (ExtendedModule) – ExtendedModule object to remove objects from.

• referedModule (module) – refered module object.

class soma.aims.Graph(*args, **kwargs)

Bases: GraphObject

addDirectedEdge()

addEdge()

addVertex()

clear()

clone()

cloneVertex()

currentValue()

edges()

edgesSize()

extract()

getScalar()

getString()

hasSyntax()

hasVertex()

has_key()

intKey()

isArray()

isDictionary()

isDictionaryIterator()

isDirected()

isDynArray()

isIterable()

isIterator()

isUndirected()

isValid()

key()

loadAllMissingElements()

objectIterator()

order()

randomVertex()

removeEdge()

removeVertex()

setSyntax()

size()

type()

vertices()

class soma.aims.GraphManip

Bases: wrapper

attributeColor()

buckets2Volume()

completeGraph()

getICBM2009cTemplateTransform()

transform = aims.GraphManip.getICBM2009cTemplateTransform(graph)

Extract the transformation to the MNI ICBM152 space, shifted to the “most standard” field of view of the template image, the one from the ICBM2009c_nlin_asym template from the MNI. Actually we find various fields of view for the templates. The one we use here is (193, 229, 193). The transform to the “real” ICBM space (0 roughly at AC) is provided in the output transformation header. This space has a fixed transformation with our Aims Talairach, along with the template volume size and voxel size. This space has a fixed transformation with our Aims Talairach. Includes shifts and axes inversions.

getICBMTransform()

transform = aims.GraphManip.getICBMTransform(graph)

Extract the transformation to the MNI ICBM152 space. This space has a fixed transformation with our Aims Talairach.

getPath()

get_element_table()

Get the GraphElementTable as a dict. The dict has the following shape:

{
    syntax_name: {
        id_name: GraphElementCode_object
    }
}

GraphElementCode objects are given as dicts (str, str):

{
    'id': <same_as_key: filename (globals) or attribute for filename (locals)>,
    'attribute': <attribute_name_in_graph_element>,
    'objectType': <type of object>,
    'dataType': <data type of object>,
    'storageType': <'Global', 'Local', or 'GlobalPacked'>,
    'local_file_attribute': <attribute giving the filename for local storage in each graph elememt>,
    'global_index_attribute': <attribute giving the index for global storage in each graph elememt>,
    'global_filename': <filename for global storage>,
    'global_attribute': <attribute>,
    'syntax': <syntax_name>
}

graphFromVolume()

graph = graphFromVolume(vol, background=0, trans=None) graphFromVolume(vol, graph, background=0, trans=None,

automaticBackgroundSearch=True)

builds a ROI graph from a volume of labels

printGraphElementTable()

setAttributeColor()

storeAims()

storeTalairach()

talairach()

volume2Buckets()

class soma.aims.GraphObject(*args, **kwargs)

Bases: GenericObject

clone()

currentValue()

getScalar()

getString()

hasSyntax()

has_key()

intKey()

isArray()

isDictionary()

isDictionaryIterator()

isDynArray()

isIterable()

isIterator()

isNone()

isScalar()

isString()

isValid()

key()

objectIterator()

setSyntax()

size()

type()

class soma.aims.Hierarchy(*args, **kwargs)

Bases: Tree

find(name)

find_color(name, default_color=<class 'KeyError'>)

hasSyntax()

setSyntax()

exception soma.aims.IOError

Bases: RuntimeError

class soma.aims.IOObjectTypesDictionary

Bases: wrapper

formats()

hasType()

objectsTypes()

exception soma.aims.IndexError

Bases: StdException

class soma.aims.Interpolator(*args)

Bases: RCObject

isValid()

value()

values()

class soma.aims.MaskIterator(*args)

Bases: RCObject

contains()

isValid()

next()

regionName()

restart()

value()

valueMillimeters()

volumeDimension()

voxelSize()

soma.aims.Motion

alias of AffineTransformation3d

class soma.aims.Object

Bases: rc_ptr_GenericObject

Generic dynamic polymorphic object proxy.

Object is a proxy and a reference counter to a GenericObject. In most cases, Object and GenericObject are interchangeable and play the same role, there are two objects for technical reasons in the C++ layer, but in Python it whould make no difference.

The C++ generic object is an implementation of a mutable dynamic container which can hold any type of concrete data, with a generic access API which abstracts the concrete type of the object stored within it.

According to the underlying object type, Object can behave like a number, a string, or a container: sequence or dictionary. The python bindings can therefore support the sequence protocol, or the dictionary protocol, like a ‘real’ python object.

The only part which makes it visibly different from a python object is the conversions with stored objects, which are generally C++ objects (but can also be any python objects). Transparent conversions are done when possible.

We will take an example to show how to use it: a volume header. Suppose the files volume.img/volume.hdr[/volume.img.minf] represent a 3D volume (a MRI volume, typically, here in Analyze/SPM or Nifti format). We will read it using aims, and access its header data, which comes as a generic object.

>>> from __future__ import print_function # work using python 2 or 3
>>> from soma import aims
>>> vol = aims.read('volume.img')
>>> hdr = vol.header()

Now vol is the volume, and hdr its header, of type Object.

>>> type(hdr)
<class 'soma.aims.Object'>
>>> print(hdr)
{ 'voxel_size' : [ 1.875, 1.875, 4, 1 ], 'file_type' : 'SPM',
'byte_swapping' : 0, 'volume_dimension' : [ 128, 128, 16, 1 ],
'vox_units' : 'mm  ', 'cal_units' : '', 'data_type' : 'S16',
'disk_data_type' : 'S16', 'bits_allocated' : 2, 'tr' : 1,
'minimum' : 0, 'maximum' : 13645, 'scale_factor' : 1,
'scale_factor_applied' : 0, 'db_name' : '',
'aux_file' : '', 'orient' : 3, 'generated' : '', 'scannum' : '',
'patient_id' : '', 'exp_date' : '', 'exp_time' : '', 'views' : 0,
'start_field' : 32768, 'field_skip' : 8192, 'omax' : 0,
'omin' : 0, 'smax' : 32, 'smin' : 0, 'SPM_data_type' : '',
'possible_data_types' : [ 'S16' ], 'spm_radio_convention' : 1,
'spm_origin' : [ 65, 65, 9 ], 'origin' : [ 64, 63, 7 ] }

hdr prints like a dictionary, but is not really a python dictionary object. However it behaves like a dictionary:

>>> print(hdr['voxel_size'])
[ 1.875, 1.875, 4, 1 ]
>>> print(hdr['data_type'])
S16
>>> print(hdr['voxel_size'][0])
1.875
>>> for x in hdr:
>>>     print(x)
>>>
voxel_size
file_type
byte_swapping
volume_dimension
vox_units
cal_units
data_type
disk_data_type
bits_allocated
tr
minimum
maximum
scale_factor
scale_factor_applied
db_name
aux_file
orient
generated
scannum
patient_id
exp_date
exp_time
views
start_field
field_skip
omax
omin
smax
smin
SPM_data_type
possible_data_types
spm_radio_convention
spm_origin
origin
>>> for x,y in hdr.items():
>>>     print(x, ':', y)
>>>
voxel_size : [ 1.875, 1.875, 4, 1 ]
file_type : 'SPM'
byte_swapping : 0
volume_dimension : [ 128, 128, 16, 1 ]
vox_units : 'mm  '
cal_units : ''
data_type : 'S16'
disk_data_type : 'S16'
bits_allocated : 2
tr : 1
minimum : 0
maximum : 13645
scale_factor : 1
scale_factor_applied : 0
db_name : ''
aux_file : ''
orient : 3
generated : ''
scannum : ''
patient_id : ''
exp_date : ''
exp_time : ''
views : 0
start_field : 32768
field_skip : 8192
omax : 0
omin : 0
smax : 32
smin : 0
SPM_data_type : ''
possible_data_types : [ 'S16' ]
spm_radio_convention : 1
spm_origin : [ 65, 65, 9 ]
origin : [ 64, 63, 7 ]

Elements returned by the dictionary queries can have various types, althrough they are all stored internally in a C++ structure through soma.aims.Object wrappers. But when the underlying type of the element is known and can be retreived as a python object (either a standard python type or a python binding of a C++ class), it is done automatically. Such conversion is not possible when the underlying object has no python binding and is a pure C++ object, or when there is no conversion function. In this case, an Object is returned and contains the selected data.

Conversions are done using conversion methods that you generally do not need to call by hand: getScalar(), getString(), or the more general conversion method soma.aims.Object.getPython(). Elements types that cannot be converted to python concrete types are retreived in their Object container.

The generic conversion function in Object: getPython, is a static method and can be extended.

Elements in Object containers can generally be read and written:

>>> hdr['data_type'] = 'FLOAT'
>>> hdr['data_type']
'FLOAT'

This generally suits your needs. But in a few cases there will be a problem in internal types handling in the C++ layer.

Here, the underlying C++ generic object which did hold a C++ string (std::string) 'S16' is now replaced by another generic object built from the python string 'FLOAT', and which now wraps an element of type PyObject (or PyString). It just behaves the same way, so this operation is perfectly valid, but if C++ programs expect it to be a C++ std::string, they may fail.

Moreover, when writing back to existing concrete objects, some additional conversions may take place: for instance hdr['voxel_size'] is a C++ object of type std::vector<float>, so writing to hdr['voxel_size'][0] needs to enure we are actually writing a float, and if not, convert to it if possible.

You can query a type identifier for a generic object via the type() method:

>>> hdr.type()
'PropertySet'

Objects that can be converted from C++ generic objects to python are not necessarily known in advance. A conversion table is kept in the global variable soma.aims.convertersObjectToPython (in the aims module) and can be extended. Therefore other python modules using aims (such as sigraph) can extend this conversion table.

Details and tricks

There are some limitations and “unexpected behaviours” caused by the underlying C++ implementation of generic objects, and general behaviour differences between Python and C++. The following is expert-level details, so read it only if you have problems or you are a C++ expert with good knowledge of the cartobase C++ library…

Generic object - specialized object conversions

Putting a specific object in a generic Object makes a copy of it the first time it is done, because C++ generic objects contain the specialized elements. Once this has been done once, generic objects are shared and not copied anymore, which is consistent with the normal python behaviour. The non-pythonic thing is the first insertion in a generic object:

>>> a = aims.vector_FLOAT([12.6, -5.7])
>>> print(a)
[ 12.6, -5.7 ]
>>> hdr['foo'] = a # here a is copied into hdr['foo']
>>> a.append( 6.8 ) # a is changed but not hdr
>>> print(a)
[ 12.6, -5.7, 6.8 ]
>>> print(hdr['foo'])
[ 12.6, -5.7 ]
>>> hdr['dummy'] = hdr['foo']
>>> hdr['foo'].append(4.2)
>>> print(hdr['dummy']) # this time hdr['dummy'] is changed
[ 12.6, -5.7, 4.2 ]

To overcome the first copy problem, you may have to reassign the initial variable to the copy instance:

>>> a = aims.vector_FLOAT([1.2, 2.3, 3.4])
>>> hdr['foo'] = a
>>> a = hdr['foo']
>>> print(hdr['foo'])
[ 1.2, 2.3, 3.4 ]
>>> a[1] = 12.8
>>> print(a)
[ 1.2, 12.8, 3.4 ]
>>> print(hdr['foo'])
[ 1.2, 12.8, 3.4 ]

There are exceptions to this behaviour:

• pure python objects, like lists or dictionaries are never copied since it is only a pointer to them (the C PyObject * pointer) which is stored.

• small builtin types: numbers and strings are always copied since they are always converted and copied, not wrapped, when passed from python to C++ and vice versa.

The get() method

On Object the get method is ambiguous and has 2 meanings:

• get() without arguments is a wrapping to the C++ rc_ptr::get() which returns the underlying wrapped object (here, a GenericObject)

• get(key, default=None) is the dict-like method that is available on GenericObject since aims 4.6.1.

Depending on the arguments the Object method will redirect to the right one, thus:

myobject.get()            # gets the GenericObject
myobject.get('key')       # gets the dict item under keyt 'key'
myobject.get().get('key') # does both, but this is what the previous line
                          # already does, so the result is the same

To avoid this ambiguity, Object.get() and rc_ptr.get() have been renamed _get() years ago (in aims 4.0 I think) but get() is still present for compatibility. This use (without argument) is obsolete and may be removed in the future.

getPython()

Conversion to python types: extracts what is in the Object (when possible). The global dictionary soma.aims.convertersObjectToPython stores converters

isNone()

static ptrToObject(x)

static rcToObject(x)

static toObject(x)

soma.aims.Point2d

alias of AimsVector_S16_2

soma.aims.Point2dd

alias of AimsVector_DOUBLE_2

soma.aims.Point2df

alias of AimsVector_FLOAT_2

soma.aims.Point2dl

alias of AimsVector_S64_2

soma.aims.Point2du

alias of AimsVector_U32_2

soma.aims.Point3d

alias of AimsVector_S16_3

soma.aims.Point3dd

alias of AimsVector_DOUBLE_3

soma.aims.Point3df

alias of AimsVector_FLOAT_3

soma.aims.Point3dl

alias of AimsVector_S64_3

soma.aims.Point3du

alias of AimsVector_U32_3

soma.aims.Point4d

alias of AimsVector_S16_4

soma.aims.Point4dd

alias of AimsVector_DOUBLE_4

soma.aims.Point4df

alias of AimsVector_FLOAT_4

soma.aims.Point4dl

alias of AimsVector_S64_4

soma.aims.Point4du

alias of AimsVector_U32_4

class soma.aims.Quaternion

Bases: wrapper

angle()

axis()

buildFromMatrix(m)

Parameters:

m (vector_FLOAT) – 4x4 matrix in columns (OpenGL-style). Be careful that it is not the expected order for a numpy array using ravel(), which have to be transposed.

buildFromMotion()

compose(value, /)

Return self*value.

fromAxis()

inverse()

norm()

normalized()

setVector()

transform()

transformInverse()

vector()

class soma.aims.RawConverter_BucketMap_VOID_rc_ptr_Volume_S16

Bases: wrapper

convert()

printToVolume()

setTimeIsLabel()

timeIsLabel()

class soma.aims.Reader(typemap=None, allocmode=None, options=None)

Bases: object

Generic reader that can theorerically load any SIP-mapped AIMS or Cartograph object. A translation table can be provided to correctly map readers and objects. For quick and simple operations, you can also use the gloabl soma.aims.read() and soma.aims.write() functions, which use a Reader object internally.

typemap can be provided to specify which reader may be used to load objects whose type has been read. A default internal map is present but can be replaced.

The map has 2 modes:

• object_type : object_type (ex: {'Volume' : 'Volume'} )

• object_type : dict( data_type : full_type ) (ex: 'Mesh' : { 'VOID' : 'AimsSurfaceTriangle' } )

  A default object_type can be specified if the data_type is not found:

  'Mesh' : { 'VOID' : 'AimsSurfaceTriangle',
              'default_object_type' : 'AimsTimeSurface_3_VOID' }
  

  (and this example corresponds to the default internal map if none is specified)

Parameters:

• typemap (dict (optional)) – described above

• allocmode ((optional)) – carto.AllocatorContext or carto.AllocatorStrategy.DataAccess constant: allocation specification.

mapType(iotype, aimstype)

Get the translated type correspondance between identified data type (from IO system) and the data type that will actually be read. This is generally the identity, but a few IO/types allow some variations.

read(filename, border=0, frame=-1, dtype=None, object=None)

Reads the object contained in the file <filename>, whatever the type of the contents of the file. All objects types supported by Aims IO system can be read. A border width and a frame number may be specified and will be only used by formats that support them. If <dtype> is specified, the corresponding object/data type is forced. It may be useful to force reading a volume with float voxels for instance. It is only supported by a few formats. <dtype> may contain a string or a type object, as accepted by soma.aims.typeCode(). The read function may follow other object/data types rules, allocators and options, as specified in the Reader constructor.

Parameters:

• filename (str) –

• border (int) –

• frame (int) –

• dtype –

• object (existing object to be read/filled) – If not specified the function will return a new object. If specified, this is considered the existing object to be read and filled by the reader.

class soma.aims.RoiDiff

Bases: wrapper

class DiffStat

Bases: wrapper

dice

g2_bucket

matching_voxels

unmatching_voxels

diff()

globalStats()

graph2LabelVolume()

mismatch_bucket()

roiNames()

roiNamesInv()

statsByLabel()

writeCSV()

class soma.aims.RoiIterator(*args)

Bases: RCObject

count()

isValid()

maskIterator()

next()

regionName()

restart()

setRegionNameAttributes(attributes)

set region name attribute in graph. Normally “name” or “label”. If several values are provided, attributes are searched in each graph vertex, in that order. If the attributes list is empty, then the graph “label_property” attribute will be used, and if it is not specified there, the default search list (“name”, “label”) will be used.

exception soma.aims.RuntimeError

Bases: StdException

soma.aims.ShallowConverter(*args, **kwargs)

Create a ShallowConverter instance from input and output types. Types may be passed as keyword arguments intype and outtype, or dtype if both are the same (not very useful for a converter). Otherwise the arguments are parsed to find types arguments.

Types may be specified as allowed by typeCode().

Note that for volumes, the method astype is often more convenient than using a Converter object (with the same result).

class soma.aims.ShallowConverter_BucketMap_DOUBLE_rc_ptr_Volume_DOUBLE

Bases: wrapper

convert()

class soma.aims.ShallowConverter_BucketMap_DOUBLE_rc_ptr_Volume_FLOAT

Bases: wrapper

convert()

class soma.aims.ShallowConverter_BucketMap_DOUBLE_rc_ptr_Volume_S16

Bases: wrapper

convert()

class soma.aims.ShallowConverter_BucketMap_DOUBLE_rc_ptr_Volume_S32

Bases: wrapper

convert()

class soma.aims.ShallowConverter_BucketMap_DOUBLE_rc_ptr_Volume_U16

Bases: wrapper

convert()

class soma.aims.ShallowConverter_BucketMap_DOUBLE_rc_ptr_Volume_U32

Bases: wrapper

convert()

class soma.aims.ShallowConverter_BucketMap_DOUBLE_rc_ptr_Volume_U8

Bases: wrapper

convert()

class soma.aims.ShallowConverter_BucketMap_FLOAT_rc_ptr_Volume_DOUBLE

Bases: wrapper

convert()

class soma.aims.ShallowConverter_BucketMap_FLOAT_rc_ptr_Volume_FLOAT

Bases: wrapper

convert()

class soma.aims.ShallowConverter_BucketMap_FLOAT_rc_ptr_Volume_S16

Bases: wrapper

convert()

class soma.aims.ShallowConverter_BucketMap_FLOAT_rc_ptr_Volume_S32

Bases: wrapper

convert()

class soma.aims.ShallowConverter_BucketMap_FLOAT_rc_ptr_Volume_U16

Bases: wrapper

convert()

class soma.aims.ShallowConverter_BucketMap_FLOAT_rc_ptr_Volume_U32

Bases: wrapper

convert()

class soma.aims.ShallowConverter_BucketMap_FLOAT_rc_ptr_Volume_U8

Bases: wrapper

convert()

class soma.aims.ShallowConverter_BucketMap_S16_rc_ptr_Volume_DOUBLE

Bases: wrapper

convert()

class soma.aims.ShallowConverter_BucketMap_S16_rc_ptr_Volume_FLOAT

Bases: wrapper

convert()

class soma.aims.ShallowConverter_BucketMap_S16_rc_ptr_Volume_S16

Bases: wrapper

convert()

class soma.aims.ShallowConverter_BucketMap_S16_rc_ptr_Volume_S32

Bases: wrapper

convert()

class soma.aims.ShallowConverter_BucketMap_S16_rc_ptr_Volume_U16

Bases: wrapper

convert()

class soma.aims.ShallowConverter_BucketMap_S16_rc_ptr_Volume_U32

Bases: wrapper

convert()

class soma.aims.ShallowConverter_BucketMap_S16_rc_ptr_Volume_U8

Bases: wrapper

convert()

class soma.aims.ShallowConverter_BucketMap_S32_rc_ptr_Volume_DOUBLE

Bases: wrapper

convert()

class soma.aims.ShallowConverter_BucketMap_S32_rc_ptr_Volume_FLOAT

Bases: wrapper

convert()

class soma.aims.ShallowConverter_BucketMap_S32_rc_ptr_Volume_S16

Bases: wrapper

convert()

class soma.aims.ShallowConverter_BucketMap_S32_rc_ptr_Volume_S32

Bases: wrapper

convert()

class soma.aims.ShallowConverter_BucketMap_S32_rc_ptr_Volume_U16

Bases: wrapper

convert()

class soma.aims.ShallowConverter_BucketMap_S32_rc_ptr_Volume_U32

Bases: wrapper

convert()

class soma.aims.ShallowConverter_BucketMap_S32_rc_ptr_Volume_U8

Bases: wrapper

convert()

class soma.aims.ShallowConverter_BucketMap_U16_rc_ptr_Volume_DOUBLE

Bases: wrapper

convert()

class soma.aims.ShallowConverter_BucketMap_U16_rc_ptr_Volume_FLOAT

Bases: wrapper

convert()

class soma.aims.ShallowConverter_BucketMap_U16_rc_ptr_Volume_S16

Bases: wrapper

convert()

class soma.aims.ShallowConverter_BucketMap_U16_rc_ptr_Volume_S32

Bases: wrapper

convert()

class soma.aims.ShallowConverter_BucketMap_U16_rc_ptr_Volume_U16

Bases: wrapper

convert()

class soma.aims.ShallowConverter_BucketMap_U16_rc_ptr_Volume_U32

Bases: wrapper

convert()

class soma.aims.ShallowConverter_BucketMap_U16_rc_ptr_Volume_U8

Bases: wrapper

convert()

class soma.aims.ShallowConverter_BucketMap_U32_rc_ptr_Volume_DOUBLE

Bases: wrapper

convert()

class soma.aims.ShallowConverter_BucketMap_U32_rc_ptr_Volume_FLOAT

Bases: wrapper

convert()

class soma.aims.ShallowConverter_BucketMap_U32_rc_ptr_Volume_S16

Bases: wrapper

convert()

class soma.aims.ShallowConverter_BucketMap_U32_rc_ptr_Volume_S32

Bases: wrapper

convert()

class soma.aims.ShallowConverter_BucketMap_U32_rc_ptr_Volume_U16

Bases: wrapper

convert()

class soma.aims.ShallowConverter_BucketMap_U32_rc_ptr_Volume_U32

Bases: wrapper

convert()

class soma.aims.ShallowConverter_BucketMap_U32_rc_ptr_Volume_U8

Bases: wrapper

convert()

class soma.aims.ShallowConverter_BucketMap_VOID_rc_ptr_Volume_DOUBLE

Bases: wrapper

convert()

class soma.aims.ShallowConverter_BucketMap_VOID_rc_ptr_Volume_FLOAT

Bases: wrapper

convert()

class soma.aims.ShallowConverter_BucketMap_VOID_rc_ptr_Volume_S16

Bases: wrapper

convert()

class soma.aims.ShallowConverter_BucketMap_VOID_rc_ptr_Volume_S32

Bases: wrapper

convert()

class soma.aims.ShallowConverter_BucketMap_VOID_rc_ptr_Volume_U16

Bases: wrapper

convert()

class soma.aims.ShallowConverter_BucketMap_VOID_rc_ptr_Volume_U32

Bases: wrapper

convert()

class soma.aims.ShallowConverter_BucketMap_VOID_rc_ptr_Volume_U8

Bases: wrapper

convert()

class soma.aims.ShallowConverter_Volume_DOUBLE_Volume_DOUBLE

Bases: wrapper

convert()

class soma.aims.ShallowConverter_Volume_DOUBLE_Volume_FLOAT

Bases: wrapper

convert()

class soma.aims.ShallowConverter_Volume_DOUBLE_Volume_HSV

Bases: wrapper

convert()

class soma.aims.ShallowConverter_Volume_DOUBLE_Volume_RGB

Bases: wrapper

convert()

class soma.aims.ShallowConverter_Volume_DOUBLE_Volume_RGBA

Bases: wrapper

convert()

class soma.aims.ShallowConverter_Volume_DOUBLE_Volume_S16

Bases: wrapper

convert()

class soma.aims.ShallowConverter_Volume_DOUBLE_Volume_S32

Bases: wrapper

convert()

class soma.aims.ShallowConverter_Volume_DOUBLE_Volume_U16

Bases: wrapper

convert()

class soma.aims.ShallowConverter_Volume_DOUBLE_Volume_U32

Bases: wrapper

convert()

class soma.aims.ShallowConverter_Volume_DOUBLE_Volume_U8

Bases: wrapper

convert()

class soma.aims.ShallowConverter_Volume_FLOAT_Volume_DOUBLE

Bases: wrapper

convert()

class soma.aims.ShallowConverter_Volume_FLOAT_Volume_FLOAT

Bases: wrapper

convert()

class soma.aims.ShallowConverter_Volume_FLOAT_Volume_HSV

Bases: wrapper

convert()

class soma.aims.ShallowConverter_Volume_FLOAT_Volume_RGB

Bases: wrapper

convert()

class soma.aims.ShallowConverter_Volume_FLOAT_Volume_RGBA

Bases: wrapper

convert()

class soma.aims.ShallowConverter_Volume_FLOAT_Volume_S16

Bases: wrapper

convert()

class soma.aims.ShallowConverter_Volume_FLOAT_Volume_S32

Bases: wrapper

convert()

class soma.aims.ShallowConverter_Volume_FLOAT_Volume_U16

Bases: wrapper

convert()

class soma.aims.ShallowConverter_Volume_FLOAT_Volume_U32

Bases: wrapper

convert()

class soma.aims.ShallowConverter_Volume_FLOAT_Volume_U8

Bases: wrapper

convert()

class soma.aims.ShallowConverter_Volume_HSV_Volume_DOUBLE

Bases: wrapper

convert()

class soma.aims.ShallowConverter_Volume_HSV_Volume_FLOAT

Bases: wrapper

convert()

class soma.aims.ShallowConverter_Volume_HSV_Volume_HSV

Bases: wrapper

convert()

class soma.aims.ShallowConverter_Volume_HSV_Volume_RGB

Bases: wrapper

convert()

class soma.aims.ShallowConverter_Volume_HSV_Volume_RGBA

Bases: wrapper

convert()

class soma.aims.ShallowConverter_Volume_HSV_Volume_S16

Bases: wrapper

convert()

class soma.aims.ShallowConverter_Volume_HSV_Volume_S32

Bases: wrapper

convert()

class soma.aims.ShallowConverter_Volume_HSV_Volume_U16

Bases: wrapper

convert()

class soma.aims.ShallowConverter_Volume_HSV_Volume_U32

Bases: wrapper

convert()

class soma.aims.ShallowConverter_Volume_HSV_Volume_U8

Bases: wrapper

convert()

class soma.aims.ShallowConverter_Volume_RGBA_Volume_DOUBLE

Bases: wrapper

convert()

class soma.aims.ShallowConverter_Volume_RGBA_Volume_FLOAT

Bases: wrapper

convert()

class soma.aims.ShallowConverter_Volume_RGBA_Volume_HSV

Bases: wrapper

convert()

class soma.aims.ShallowConverter_Volume_RGBA_Volume_RGB

Bases: wrapper

convert()

class soma.aims.ShallowConverter_Volume_RGBA_Volume_RGBA

Bases: wrapper

convert()

class soma.aims.ShallowConverter_Volume_RGBA_Volume_S16

Bases: wrapper

convert()

class soma.aims.ShallowConverter_Volume_RGBA_Volume_S32

Bases: wrapper

convert()

class soma.aims.ShallowConverter_Volume_RGBA_Volume_U16

Bases: wrapper

convert()

class soma.aims.ShallowConverter_Volume_RGBA_Volume_U32

Bases: wrapper

convert()

class soma.aims.ShallowConverter_Volume_RGBA_Volume_U8

Bases: wrapper

convert()

class soma.aims.ShallowConverter_Volume_RGB_Volume_DOUBLE

Bases: wrapper

convert()

class soma.aims.ShallowConverter_Volume_RGB_Volume_FLOAT

Bases: wrapper

convert()

class soma.aims.ShallowConverter_Volume_RGB_Volume_HSV

Bases: wrapper

convert()

class soma.aims.ShallowConverter_Volume_RGB_Volume_RGB

Bases: wrapper

convert()

class soma.aims.ShallowConverter_Volume_RGB_Volume_RGBA

Bases: wrapper

convert()

class soma.aims.ShallowConverter_Volume_RGB_Volume_S16

Bases: wrapper

convert()

class soma.aims.ShallowConverter_Volume_RGB_Volume_S32

Bases: wrapper

convert()

class soma.aims.ShallowConverter_Volume_RGB_Volume_U16

Bases: wrapper

convert()

class soma.aims.ShallowConverter_Volume_RGB_Volume_U32

Bases: wrapper

convert()

class soma.aims.ShallowConverter_Volume_RGB_Volume_U8

Bases: wrapper

convert()

class soma.aims.ShallowConverter_Volume_S16_Volume_DOUBLE

Bases: wrapper

convert()

class soma.aims.ShallowConverter_Volume_S16_Volume_FLOAT

Bases: wrapper

convert()

class soma.aims.ShallowConverter_Volume_S16_Volume_HSV

Bases: wrapper

convert()

class soma.aims.ShallowConverter_Volume_S16_Volume_RGB

Bases: wrapper

convert()

class soma.aims.ShallowConverter_Volume_S16_Volume_RGBA

Bases: wrapper

convert()

class soma.aims.ShallowConverter_Volume_S16_Volume_S16

Bases: wrapper

convert()

class soma.aims.ShallowConverter_Volume_S16_Volume_S32

Bases: wrapper

convert()

class soma.aims.ShallowConverter_Volume_S16_Volume_U16

Bases: wrapper

convert()

class soma.aims.ShallowConverter_Volume_S16_Volume_U32

Bases: wrapper

convert()

class soma.aims.ShallowConverter_Volume_S16_Volume_U8

Bases: wrapper

convert()

class soma.aims.ShallowConverter_Volume_S32_Volume_DOUBLE

Bases: wrapper

convert()

class soma.aims.ShallowConverter_Volume_S32_Volume_FLOAT

Bases: wrapper

convert()

class soma.aims.ShallowConverter_Volume_S32_Volume_HSV

Bases: wrapper

convert()

class soma.aims.ShallowConverter_Volume_S32_Volume_RGB

Bases: wrapper

convert()

class soma.aims.ShallowConverter_Volume_S32_Volume_RGBA

Bases: wrapper

convert()

class soma.aims.ShallowConverter_Volume_S32_Volume_S16

Bases: wrapper

convert()

class soma.aims.ShallowConverter_Volume_S32_Volume_S32

Bases: wrapper

convert()

class soma.aims.ShallowConverter_Volume_S32_Volume_U16

Bases: wrapper

convert()

class soma.aims.ShallowConverter_Volume_S32_Volume_U32

Bases: wrapper

convert()

class soma.aims.ShallowConverter_Volume_S32_Volume_U8

Bases: wrapper

convert()

class soma.aims.ShallowConverter_Volume_U16_Volume_DOUBLE

Bases: wrapper

convert()

class soma.aims.ShallowConverter_Volume_U16_Volume_FLOAT

Bases: wrapper

convert()

class soma.aims.ShallowConverter_Volume_U16_Volume_HSV

Bases: wrapper

convert()

class soma.aims.ShallowConverter_Volume_U16_Volume_RGB

Bases: wrapper

convert()

class soma.aims.ShallowConverter_Volume_U16_Volume_RGBA

Bases: wrapper

convert()

class soma.aims.ShallowConverter_Volume_U16_Volume_S16

Bases: wrapper

convert()

class soma.aims.ShallowConverter_Volume_U16_Volume_S32

Bases: wrapper

convert()

class soma.aims.ShallowConverter_Volume_U16_Volume_U16

Bases: wrapper

convert()

class soma.aims.ShallowConverter_Volume_U16_Volume_U32

Bases: wrapper

convert()

class soma.aims.ShallowConverter_Volume_U16_Volume_U8

Bases: wrapper

convert()

class soma.aims.ShallowConverter_Volume_U32_Volume_DOUBLE

Bases: wrapper

convert()

class soma.aims.ShallowConverter_Volume_U32_Volume_FLOAT

Bases: wrapper

convert()

class soma.aims.ShallowConverter_Volume_U32_Volume_HSV

Bases: wrapper

convert()

class soma.aims.ShallowConverter_Volume_U32_Volume_RGB

Bases: wrapper

convert()

class soma.aims.ShallowConverter_Volume_U32_Volume_RGBA

Bases: wrapper

convert()

class soma.aims.ShallowConverter_Volume_U32_Volume_S16

Bases: wrapper

convert()

class soma.aims.ShallowConverter_Volume_U32_Volume_S32

Bases: wrapper

convert()

class soma.aims.ShallowConverter_Volume_U32_Volume_U16

Bases: wrapper

convert()

class soma.aims.ShallowConverter_Volume_U32_Volume_U32

Bases: wrapper

convert()

class soma.aims.ShallowConverter_Volume_U32_Volume_U8

Bases: wrapper

convert()

class soma.aims.ShallowConverter_Volume_U8_Volume_DOUBLE

Bases: wrapper

convert()

class soma.aims.ShallowConverter_Volume_U8_Volume_FLOAT

Bases: wrapper

convert()

class soma.aims.ShallowConverter_Volume_U8_Volume_HSV

Bases: wrapper

convert()

class soma.aims.ShallowConverter_Volume_U8_Volume_RGB

Bases: wrapper

convert()

class soma.aims.ShallowConverter_Volume_U8_Volume_RGBA

Bases: wrapper

convert()

class soma.aims.ShallowConverter_Volume_U8_Volume_S16

Bases: wrapper

convert()

class soma.aims.ShallowConverter_Volume_U8_Volume_S32

Bases: wrapper

convert()

class soma.aims.ShallowConverter_Volume_U8_Volume_U16

Bases: wrapper

convert()

class soma.aims.ShallowConverter_Volume_U8_Volume_U32

Bases: wrapper

convert()

class soma.aims.ShallowConverter_Volume_U8_Volume_U8

Bases: wrapper

convert()

class soma.aims.ShallowConverter_rc_ptr_Volume_DOUBLE_BucketMap_DOUBLE

Bases: wrapper

convert()

class soma.aims.ShallowConverter_rc_ptr_Volume_DOUBLE_BucketMap_FLOAT

Bases: wrapper

convert()

class soma.aims.ShallowConverter_rc_ptr_Volume_DOUBLE_BucketMap_S16

Bases: wrapper

convert()

class soma.aims.ShallowConverter_rc_ptr_Volume_DOUBLE_BucketMap_S32

Bases: wrapper

convert()

class soma.aims.ShallowConverter_rc_ptr_Volume_DOUBLE_BucketMap_U16

Bases: wrapper

convert()

class soma.aims.ShallowConverter_rc_ptr_Volume_DOUBLE_BucketMap_U32

Bases: wrapper

convert()

class soma.aims.ShallowConverter_rc_ptr_Volume_DOUBLE_BucketMap_VOID

Bases: wrapper

convert()

class soma.aims.ShallowConverter_rc_ptr_Volume_FLOAT_BucketMap_DOUBLE

Bases: wrapper

convert()

class soma.aims.ShallowConverter_rc_ptr_Volume_FLOAT_BucketMap_FLOAT

Bases: wrapper

convert()

class soma.aims.ShallowConverter_rc_ptr_Volume_FLOAT_BucketMap_S16

Bases: wrapper

convert()

class soma.aims.ShallowConverter_rc_ptr_Volume_FLOAT_BucketMap_S32

Bases: wrapper

convert()

class soma.aims.ShallowConverter_rc_ptr_Volume_FLOAT_BucketMap_U16

Bases: wrapper

convert()

class soma.aims.ShallowConverter_rc_ptr_Volume_FLOAT_BucketMap_U32

Bases: wrapper

convert()

class soma.aims.ShallowConverter_rc_ptr_Volume_FLOAT_BucketMap_VOID

Bases: wrapper

convert()

class soma.aims.ShallowConverter_rc_ptr_Volume_S16_BucketMap_DOUBLE

Bases: wrapper

convert()

class soma.aims.ShallowConverter_rc_ptr_Volume_S16_BucketMap_FLOAT

Bases: wrapper

convert()

class soma.aims.ShallowConverter_rc_ptr_Volume_S16_BucketMap_S16

Bases: wrapper

convert()

class soma.aims.ShallowConverter_rc_ptr_Volume_S16_BucketMap_S32

Bases: wrapper

convert()

class soma.aims.ShallowConverter_rc_ptr_Volume_S16_BucketMap_U16

Bases: wrapper

convert()

class soma.aims.ShallowConverter_rc_ptr_Volume_S16_BucketMap_U32

Bases: wrapper

convert()

class soma.aims.ShallowConverter_rc_ptr_Volume_S16_BucketMap_VOID

Bases: wrapper

convert()

class soma.aims.ShallowConverter_rc_ptr_Volume_S32_BucketMap_DOUBLE

Bases: wrapper

convert()

class soma.aims.ShallowConverter_rc_ptr_Volume_S32_BucketMap_FLOAT

Bases: wrapper

convert()

class soma.aims.ShallowConverter_rc_ptr_Volume_S32_BucketMap_S16

Bases: wrapper

convert()

class soma.aims.ShallowConverter_rc_ptr_Volume_S32_BucketMap_S32

Bases: wrapper

convert()

class soma.aims.ShallowConverter_rc_ptr_Volume_S32_BucketMap_U16

Bases: wrapper

convert()

class soma.aims.ShallowConverter_rc_ptr_Volume_S32_BucketMap_U32

Bases: wrapper

convert()

class soma.aims.ShallowConverter_rc_ptr_Volume_S32_BucketMap_VOID

Bases: wrapper

convert()

class soma.aims.ShallowConverter_rc_ptr_Volume_U16_BucketMap_DOUBLE

Bases: wrapper

convert()

class soma.aims.ShallowConverter_rc_ptr_Volume_U16_BucketMap_FLOAT

Bases: wrapper

convert()

class soma.aims.ShallowConverter_rc_ptr_Volume_U16_BucketMap_S16

Bases: wrapper

convert()

class soma.aims.ShallowConverter_rc_ptr_Volume_U16_BucketMap_S32

Bases: wrapper

convert()

class soma.aims.ShallowConverter_rc_ptr_Volume_U16_BucketMap_U16

Bases: wrapper

convert()

class soma.aims.ShallowConverter_rc_ptr_Volume_U16_BucketMap_U32

Bases: wrapper

convert()

class soma.aims.ShallowConverter_rc_ptr_Volume_U16_BucketMap_VOID

Bases: wrapper

convert()

class soma.aims.ShallowConverter_rc_ptr_Volume_U32_BucketMap_DOUBLE

Bases: wrapper

convert()

class soma.aims.ShallowConverter_rc_ptr_Volume_U32_BucketMap_FLOAT

Bases: wrapper

convert()

class soma.aims.ShallowConverter_rc_ptr_Volume_U32_BucketMap_S16

Bases: wrapper

convert()

class soma.aims.ShallowConverter_rc_ptr_Volume_U32_BucketMap_S32

Bases: wrapper

convert()

class soma.aims.ShallowConverter_rc_ptr_Volume_U32_BucketMap_U16

Bases: wrapper

convert()

class soma.aims.ShallowConverter_rc_ptr_Volume_U32_BucketMap_U32

Bases: wrapper

convert()

class soma.aims.ShallowConverter_rc_ptr_Volume_U32_BucketMap_VOID

Bases: wrapper

convert()

class soma.aims.ShallowConverter_rc_ptr_Volume_U8_BucketMap_DOUBLE

Bases: wrapper

convert()

class soma.aims.ShallowConverter_rc_ptr_Volume_U8_BucketMap_FLOAT

Bases: wrapper

convert()

class soma.aims.ShallowConverter_rc_ptr_Volume_U8_BucketMap_S16

Bases: wrapper

convert()

class soma.aims.ShallowConverter_rc_ptr_Volume_U8_BucketMap_S32

Bases: wrapper

convert()

class soma.aims.ShallowConverter_rc_ptr_Volume_U8_BucketMap_U16

Bases: wrapper

convert()

class soma.aims.ShallowConverter_rc_ptr_Volume_U8_BucketMap_U32

Bases: wrapper

convert()

class soma.aims.ShallowConverter_rc_ptr_Volume_U8_BucketMap_VOID

Bases: wrapper

convert()

class soma.aims.SimpleBundlesSlicer

Bases: BundlesSlicer

bundleStarted(producer, bundle_info)

bundleTerminated(producer, bundle_info)

fiberStarted(producer, bundle_info, fiber_info)

fiberTerminated(producer, bundle_info, fiber_info)

newFiberPoint(producer, bundle_info, fiber_info, point)

noMoreBundle(producer)

class soma.aims.SparseMatrix(*args)

Bases: RCObject

erase_element()

fill()

getColumn()

getComposition()

getNonZeroElementCount()

getRow()

getSize1()

getSize2()

getTrace()

getTransposition()

hasElement()

header()

isSquare()

read()

reallocate()

setColumn()

setDiagonal()

setIdentity()

setRow()

setZero()

transpose()

write()

class soma.aims.SparseOrDenseMatrix(*args)

Bases: RCObject

asDense()

asSparse()

denseMatrix()

erase_element()

freeColumn()

freeRow()

getColumn()

getNonZeroElementCount()

getRow()

getSize()

getSize1()

getSize2()

hasElement()

header()

isDense()

isOptimalShape()

muteToDense()

muteToOptimalShape()

muteToSparse()

read()

readAll()

readColumn()

readRow()

reallocate()

setColumn()

setHeader()

setMatrix()

setRow()

set_element()

sparseMatrix()

subMatrix()

write()

class soma.aims.StandardReferentials

Bases: wrapper

acPcReferential()

identifer (str) for the Taialairach/AIMS space

acPcReferentialID()

identifer (UUID str) for the Talairach/AIMS space

commonScannerBasedReferential()

commonScannerBasedReferentialID()

icbm2009cTemplateHeader()

hdr = aims.StandardReferentials.icbm2009cTemplateHeader() Return a header with size and characteristics of the ICBM2009c MNI template volume.

mniTemplateReferential()

identifer (str) for the MNI/ICBM space

mniTemplateReferentialID()

identifer (UUID str) for the MNI/ICBM space

talairachReferential()

identifer (str) for the Talairach/CIFTI space

talairachToICBM()

talairachToICBM2009cTemplate()

trans = aims.StandardReferentials.talairachToICBM2009cTemplate()

Transformation between the ICBM152 standard space and the ICBM152 template space.

includes shifts and axes inversions.

This is the “most standard” field of view of the template image, the one from the ICBM2009c_nlin_asym template from the MNI. Actually we find various fields of view for the templates. The one we use here is (193, 229, 193). The transform to the “real” ICBM space (0 roughly at AC) is provided in the output transformation header. This space has a fixed transformation with our Aims Talairach, along with the template volume size and voxel size. This space has a fixed transformation with our Aims Talairach.

exception soma.aims.StdException

Bases: Exception

class soma.aims.StdOutInhibitorFix

Bases: ResetCallback

class soma.aims.SurfaceGenerator

Bases: wrapper

Surface Generator Object. Available Methods are :

• cube(center_p, radius_f, smoothnormal_b=false)

• cylinder(p1_p, p2_p, radius1_f, radius2_f, nfacets_i, closed_b, smooth_b=false)

• cone(arrow_p, base_p, radius_f, nfacets_i, closed_b, smooth_b=false)

• arrow(arrow_p, base_p, radius_f, arrowradius_f, nfacets_i, arrowlengthfract_f)

• icosahedron(center_p, radius_f)

• sphere(center_p, radius_f, nfacets_i)

• icosphere(center_p, radius_f, nfacets_i)

With arguments suffix _f:float, _i:int, _b:bool, _p: Point3df or 3-tuple

Alternatively, all those may be called with a GenericObject as only parameter.

This doc might not be up-to-date, use the printDescription() method for more info.

arrow()

static arrow( dictionary ) See the description() and printDescription() methods for more information.

static arrow( Point3df arrowhead, Point3df base, float headradius, float arrowradius, unsigned nfaces, float arrowlengthfactor )

circle_wireframe()

Circle, or part of circle.

center, radius are classical. nseg is the number of segments in the circle polygon normal is a normal vector to the circle plane. startdir is a vector in the circle plane determining the beginning of angles (circle ray). startangle, stopangle are meant to make parts of circle

cone()

static cone( dictionary ) See the description() and printDescription() methods for more information.

static cone( Point3df arrowhead, Point3df base, float radius, unsigned nfaces, bool closed, bool smooth=False )

cube()

static cube( dictionary ) See the description() and printDescription() methods for more information.

static cube( Point3df center, float radius, bool smoothnormals=False )

cylinder()

static cylinder( dictionary ) See the description() and printDescription() methods for more information.

static cylinder( Point3df center1, Point3df center2, float radius1, float radius2, unsigned nfaces, bool closed, bool smooth=False )

description()

description_wireframe()

ellipse()

static ellipse( dictionary ) See the description() and printDescription() methods for more information.

static ellipse( Point3df center, float radius1, float radius2, unsigned nfaces, bool uniquevertices=False )

generate()

generate_wireframe()

grid(dict)

See the description() and printDescription() methods for more information.

grid(Point3df boundingbox_min, Point3df boundingbox_max, Point3df grid_sampling) Regular, wireframe grid

icosahedron()

static icosahedron( dictionary ) See the description() and printDescription() methods for more information.

static icosahedron( Point3df center, float radius )

icosphere(dictionary)

See the description() and printDescription() methods for more information.

icosphere( Point3df center, float radius, unsigned nfaces=320 )

Compared to sphere() which performs meridian / parallels tesselation, icosphere over-segments an icosahedron to get equal, equilateral triangles.

parallelepiped(boundingbox_min, boundingbox_max, smooth=False)

Parameters:

• boundingbox_min (Point3df) – “lower bound” corner position

• boundingbox_min – “upper bound” corner position

• smooth (bool) – if True, make smooth faces and shared vertices in corners

parallelepiped_wireframe(Point3df boundingbox_min, Point3df boundingbox_max)

printDescription()

printDescription_wireframe()

sphere()

static sphere( dictionary ) See the description() and printDescription() methods for more information.

static sphere( Point3df center, float radius, unsigned nfaces, bool uniquevertices=False )

class soma.aims.SurfaceManip

Bases: wrapper

Surface Manipulation Object. All mehtods are static in this class, it is just a means of grouping functions.

checkMeshIntersect()

cutMesh(in_mesh, plane, cut_mesh, border_line)

Cut a mesh by a plane and that’s all.

Parameters:

• in_mesh (AimsSurfaceTriangle) – Triangular mesh to be cut.

• plane (Point4df) – cut plane equation (4 coefs)

• cut_mesh (AimsSurfaceTriangle) – output cut mesh (the part satisfying the plane equation). Polygons crossing the plane will be cut into smaller ones.

• border_line (AimsTimeSurface_2_VOID) – output cut section polygon

Return type:

None

invertSurfacePolygons(mesh)

Invert polygons order (flips 2 vertex indices in each triangle) to flip its interior / exterior notions (used by OpenGL rendering). The input mesh is modified in-place.

joinTexturedMesh()

Join a mesh and a texture into a textured mesh

lineDirections(segments_mesh)

calculate directions of a line mesh, for each vertex

Parameters:

segments_mesh (AimsTimeSurface_2_VOID) –

Returns:

directions

Return type:

vector_POINT3DF

meshArea()

Surface area of a triangular mesh, in mm^2

Surface areas of regions of a triangular mesh, in mm^2. Regions are given as a texture.

meshDensity(mesh, as_distance=False)

Calculate a mesh density: inverse of the average edges distance.

Parameters:

• mesh (AimsSurfaceTriangle) –

• as_distance (bool (optional)) – if True, the average distance is not inverted, thus the output is an average distance map.

Returns:

density_texture

Return type:

TimeTexture_FLOAT

meshEdgeLengthRatioTexture(numerator_mesh, denominator_mesh)

Calculate an edge length ratio in edges of two meshes with the same topology. The max length ratios of edges is kept for each vertex.

Parameters:

• numerator_mesh (AimsSurfaceTriangle) –

• denominator_mesh (AimsSurfaceTriangle) –

Returns:

ratio_texture

Return type:

TimeTexture_FLOAT

meshExtract(mesh, texture, label_value)

Extracts a sub-mesh defined by a texture label value.

Returns:

• sub_mesh (AimsTimeSurface_3_VOID) – extracted sub-mesh

• vertices (vector_ULONG) – indices of extracted vertices

meshMerge(input_output_mesh, input_mesh)

Concatenates the second mesh to the first one. The first argument will be modified.

Parameters:

• input_output_mesh (AimsTimeSurface_3_VOID) – first mesh. Will be modified to be the output.

• input_mesh (AimsTimeSurface_3_VOID) – second mesh to be appended to the first one.

Return type:

None

meshPlanarPolygon(plane, polygon)

Tesselate a planar polygon to fill it by a triangular mesh

Parameters:

• plane (Point4df) – plane equation

• polygon (AimsTimeSurface_2_VOID) – planar polygon to tesselate. Typically, the output of cutMesh()

Returns:

planar_mesh – the mesh filling the polygon

Return type:

AimsSurfaceTriangle

meshTextureBoundary(mesh, label_texture, region_value)

Extracts the boundary of region of value <region_value> of the input texture, on the mesh.

If region_value is negative, take boundaries of all regions. The input texture is a label texture.

Parameters:

• mesh (AimsSurfaceTriangle) – input mesh to extract boundary on

• label_texture (TimeTexture_S16, TimeTexture_S32, or TimeTexture_FLOAT) – label texture defining regions on the mesh

• region_value (int16, int32 or float) – label of the desired region

Returns:

boundary – output segments mesh (filar mesh) for the boundary

Return type:

AimsTimeSurface_2_VOID

meshTransform(mesh, transformation)

Apply linear coordinates transformation to a mesh. The input mesh will be modified in-place.

Parameters:

• mesh (AimsTimeSurface_3_VOID or AimsTimeSurface_2_VOID) – mesh to be transformed. Will be modified.

• transformation (AffineTransformation3d) – Linear transformation matrix

Return type:

None

meshVolume(mesh)

Volume inside a triangular mesh, in mm^3. The mesh must enclode a closed volume, with no holes, otherwise the volume processing will “leak” and will be wrong.

nearestPointToMesh()

rasterizeMesh(mesh, volume, value=2)

Rasterize polygons into a volume.

Parameters:

• mesh (AimsTimeSurface_*) –

• volume (Volume_S16) – Volume to write mesh imprint to

• value (int) – label value used to write the mesh imprint in the volume

rasterizeMeshWireframe(mesh, volume, value=1)

Rasterize polygons edges into a volume.

Parameters:

• mesh (AimsTimeSurface_*) –

• volume (Volume_S16) – Volume to write mesh imprint to

• value (int) – label value used to write the mesh imprint in the volume

refineMeshTri4(mesh, selected_polygons=None)

Refine a mesh by subdivising every triangle into 4 smaller ones.

Parameters:

• mesh (AimsSurfaceTriangle) – mesh to be refined

• selected_polygons (vector_U32) – optional list of polygons indices to be selectively refined. Others will not be changed, unless they are at the border of a refined one, in which case they have to be split in some way.

Returns:

refined_mesh – refined mesh

Return type:

AimsSurfaceTriangle

sortPolygonsAlongDirection(mesh, timestep, direction)

Sort polygons along a given direction. Polygons centers will be used for sorting. Only one timestep is performed (to be fast).

Parameters:

• mesh (AimsTimeSurface_*) – The mesh will be modified.

• timestep (int) –

• direction (Point3df) –

sortPolygonsAlongDirection(mesh, timestep, direction)

Sort polygons along a given direction. Polygons centers will be used for sorting. Only one timestep is performed (to be fast).

Parameters:

• mesh (AimstimeSurface_*) – The mesh will be modified.

• timestep (int) –

• direction (Point3df) –

sortPolygonsAlongDirection(mesh, timestep, direction)

Sort polygons along a given direction. Polygons centers will be used for sorting. Only one timestep is performed (to be fast).

Parameters:

• mesh (AimstimeSurface_*) – The mesh will be modified.

• timestep (int) –

• direction (Point3df) –

splitTexturedMesh()

Split a textured mesh into a mesh and a texture

surfaceNeighbours()

soma.aims.Texture(*args, **kwargs)

Create an instance of Aims low-level texture (Texture_<type>) from a type parameter, which may be specified as the dtype keyword argument, or as one of the arguments if one is identitied as a type.

The default type is ‘FLOAT’.

Type definitions should match those accepted by typeCode().

Texture may also use a numpy array, or another Textrue_* as unique argument.

class soma.aims.Texture_DOUBLE

Bases: wrapper

append()

array_struct()

arraydata()

assign()

checkResize()

data()

erase()

item()

list()

nItem()

property np

The np property is a shortcut to the __array__ method. Thus:

something.np

is a handier equivalent to:

numpy.asarray(something)

push_back()

reserve()

resize()

size()

class soma.aims.Texture_FLOAT

Bases: wrapper

append()

array_struct()

arraydata()

assign()

checkResize()

data()

erase()

item()

list()

nItem()

property np

The np property is a shortcut to the __array__ method. Thus:

something.np

is a handier equivalent to:

numpy.asarray(something)

push_back()

reserve()

resize()

size()

class soma.aims.Texture_POINT2DF

Bases: wrapper

append()

array_struct()

arraydata()

assign()

checkResize()

data()

erase()

item()

list()

nItem()

property np

The np property is a shortcut to the __array__ method. Thus:

something.np

is a handier equivalent to:

numpy.asarray(something)

push_back()

reserve()

resize()

size()

class soma.aims.Texture_S16

Bases: wrapper

append()

array_struct()

arraydata()

assign()

checkResize()

data()

erase()

item()

list()

nItem()

property np

The np property is a shortcut to the __array__ method. Thus:

something.np

is a handier equivalent to:

numpy.asarray(something)

push_back()

reserve()

resize()

size()

class soma.aims.Texture_S32

Bases: wrapper

append()

array_struct()

arraydata()

assign()

checkResize()

data()

erase()

item()

list()

nItem()

property np

The np property is a shortcut to the __array__ method. Thus:

something.np

is a handier equivalent to:

numpy.asarray(something)

push_back()

reserve()

resize()

size()

class soma.aims.Texture_U16

Bases: wrapper

append()

array_struct()

arraydata()

assign()

checkResize()

data()

erase()

item()

list()

nItem()

property np

The np property is a shortcut to the __array__ method. Thus:

something.np

is a handier equivalent to:

numpy.asarray(something)

push_back()

reserve()

resize()

size()

class soma.aims.Texture_U32

Bases: wrapper

append()

array_struct()

arraydata()

assign()

checkResize()

data()

erase()

item()

list()

nItem()

property np

The np property is a shortcut to the __array__ method. Thus:

something.np

is a handier equivalent to:

numpy.asarray(something)

push_back()

reserve()

resize()

size()

class soma.aims.Texture_U8

Bases: wrapper

append()

array_struct()

arraydata()

assign()

checkResize()

data()

erase()

item()

list()

nItem()

property np

The np property is a shortcut to the __array__ method. Thus:

something.np

is a handier equivalent to:

numpy.asarray(something)

push_back()

reserve()

resize()

size()

soma.aims.TimeSurface(*args, **kwargs)

same as AimsTimeSurface(dim, dtype)

soma.aims.TimeTexture(*args, **kwargs)

Create an instance of Aims texture (TimeTexture_<type>) from a type parameter, which may be specified as the dtype keyword argument, or as one of the arguments if one is identitied as a type.

The default type is ‘FLOAT’.

Type definitions should match those accepted by typeCode(). TimeTexture may also use a numpy array, or another TimeTexture_* or Textrue_* as unique argument.

Building from a numpy arrays uses the 1st dimension as vertex, the 2nd as time (if any).

class soma.aims.TimeTexture_DOUBLE(*args)

Bases: RCObject

erase()

fromObject()

has_key()

header()

items()

iteritems()

keys()

nItem()

push_back()

reserve()

size()

class soma.aims.TimeTexture_FLOAT(*args)

Bases: RCObject

erase()

fromObject()

has_key()

header()

items()

iteritems()

keys()

nItem()

push_back()

reserve()

size()

class soma.aims.TimeTexture_POINT2DF(*args)

Bases: RCObject

erase()

fromObject()

has_key()

header()

items()

iteritems()

keys()

nItem()

push_back()

reserve()

size()

class soma.aims.TimeTexture_S16(*args)

Bases: RCObject

erase()

fromObject()

has_key()

header()

items()

iteritems()

keys()

nItem()

push_back()

reserve()

size()

class soma.aims.TimeTexture_S32(*args)

Bases: RCObject

erase()

fromObject()

has_key()

header()

items()

iteritems()

keys()

nItem()

push_back()

reserve()

size()

class soma.aims.TimeTexture_U16(*args)

Bases: RCObject

erase()

fromObject()

has_key()

header()

items()

iteritems()

keys()

nItem()

push_back()

reserve()

size()

class soma.aims.TimeTexture_U32(*args)

Bases: RCObject

erase()

fromObject()

has_key()

header()

items()

iteritems()

keys()

nItem()

push_back()

reserve()

size()

class soma.aims.TimeTexture_U8(*args)

Bases: RCObject

erase()

fromObject()

has_key()

header()

items()

iteritems()

keys()

nItem()

push_back()

reserve()

size()

class soma.aims.Transformation(*args)

Bases: RCObject

Base class for spatial transformations.

header()

isIdentity()

Test if the transformation can safely be omitted

This method must only return true if the transformation behaves exactly like an identity transformation (notably, the transform methods will always return the input coordinates unchanged).

NOTE: Implementors of derived classes may choose to always return false if a test would be difficult to implement or expensive to run.

setHeader()

class soma.aims.Transformation3d(*args)

Bases: Transformation

Base class for spatial transformations in 3D.

fromObject()

toObject()

transform()

transformDouble()

transformFloat()

transformPoint3d()

transformPoint3dd()

transformPoint3df()

transformPoints()

class soma.aims.TransformationChain3d(*args)

Bases: Transformation3d

Container for a composition of multiple transformations.

This container holds a list of transformations, and acts as the composition of all transformations. Transformations are composed from the front to the back of the list:

chain = TransformationChain3d()
chain.push_back(t1)
chain.push_back(t2)
# chain->transform(p) == t2.transform(t1.transform(p))

warning: Do not modify the transformations once you have passed them to push_back() or push_front(): it is unspecified if the changes will be noticed by TransformationChain3d (a reference to the same object may be kept internally, or a copy could be made). This behaviour will allow optimizations to be implemented (e.g. composing adjacent affine transformations by multiplying their matrices).

getInverse()

invertible()

isIdentity()

Test if the transformation can safely be omitted

This method must only return true if the transformation behaves exactly like an identity transformation (notably, the transform methods will always return the input coordinates unchanged).

NOTE: Implementors of derived classes may choose to always return false if a test would be difficult to implement or expensive to run.

pop_back()

Remove the last transformation from the list

pop_front()

Remove the first transformation from the list

push_back(transformation)

Add a transformation to the back of the list (applied last)

push_front(transformation)

Add a transformation to the front of the list (applied first)

simplify()

Compute a simpler transformation that is equivalent to the chain.

The transformation chain is simplified by applying the following rules, so that it should provide equivalent results to the original chain, up to numerical precision:

• The simplification is applied recursively to any sub-chain.

• Transformations of the simplified sub-chains are inserted at the top level (i.e. the simplified chain is flat, it contains no sub-chains).

• Consecutive affine transformations are composed using matrix multiplication.

• Identity transforms (i.e. transforms for which Transformation::isIdentity() returns true) are removed from the list.

• If the simplified chain consists of only one transformation, no chain is returned, the contained transformation is returned directly. However, the transformation is not necessarily the same instance that was inserted in the chain (it will be a copy if it is an AffineTransformation3d).

• If the simplified chain is empty, an empty chain is returned.

No deep copy is made, so the result can contain pointers to the same transformations as the original chain.

size()

transformDouble()

transformFloat()

transformPoint3d()

transformPoint3dd()

transformPoint3df()

class soma.aims.TransformationGraph3d(*args, **kwargs)

Bases: Graph

Manage transformations (affine and non-linear) transformations graph.

It maintains a graph of directed transformations (vertices are referentials, edges are 3D transformations).

It can be populated from a dictionary (Object) which can be read from a JSON or YAML file, and performs lazy-loading: transformations are actually loaded when they are used, more precisely in getTransformation() and when building a chain of composed transformations.

The graph is oriented, and does not manage inverse transforms. We could thing this could be done automatically for affine or other inversible transformations, but the lazy loading feature does not allow to know if a not yet loaded transform will be inversible or not. So this has to be done manually for now.

The graph populates with composed transforms when they are used: indirect paths from a referential to another are generated when needed, and stored in the graph as “deduced” transforms. Later access will thus use this cache instead of reccomputing it. A drawback, thus, is that the graph has to be used “statically”: any modification in the graph structure, or in any of its transformations, should invalidate a number of deduced, cached ones, which we do not handle for now (it’s a quite difficult problem to manage it efficiently). To date the only solution is to completely clear the cached transforms (clearCache()) after any modification.

The TransformationGraph3d structure is a Graph, and its elements are Vertex or Edge objects. To manipulate transformations, the API generally allows to use identifiers (generally UUIDs) for elements, and the Transformation objects are accessed through the “transformation” property of edges, or using the transformation() convenience method:

ref1 = tgraph.referentialById(“23df7ce8-e405-bc31-3863-d543e3cc89e5”) trans_edge = tgraph.getTransformation(

“23df7ce8-e405-bc31-3863-d543e3cc89e5”, “52929a27-6838-1d08-d6fc-7905ed9413a0”)

if trans_edge:

trans = tgraph.transformation(trans_edge)

see also: https://hbp-spatial-backend.apps.hbp.eu/swagger-ui#/api_v1/get_v1_transform_point

asDict()

convert to a dict-like structure compatible with loadTransformationsGraph()

Parameters:

• affine_only (bool) – if true, inclue only affine transformations

• allow_read (bool) – if true, and if affine_only or embed_affines is also true, all affine transformations will be read in order to determine which are affine. Otherwise only those already loaded in memory (via the lazy reading mechanism) will be known to be affine. This parameter has no effect on non-affine transformations.

• embed_affines (bool) –

  if true, affine transformations are not recorded as a

  file name (.trm format), but as an embedded 4x4 matrix.

clearCache(chain_only=False)

remove deduced transformations (built from composition).

If chain_only is true, then inverses of direct transforms are not removed.

clone()

currentValue()

getScalar()

getString()

getTransformChain()

Get a transformation chain between two vertices.

You normally don’t need to call this method directly, il is called through getTransformation( src_ref, dst_ref, true ). This method however does not modify the transformations graph and does not register the combined transformation. It will, however, load lazy-loading transformations.

getTransformation()

edge = tgraph.getTransformation(src_ref, dst_ref, allow_compose=False)

Get the transformation between source_ref and dst_ref. If it is not a registered transformation, return None. src_ref annd dst_ref may be string IDs or Vertex objects.

If allow_compose is True and the transformation is not found, then a transformations chain path is looked for. If a matching one is found, it is then registered in the graph to allow fast access later. The drawback of this register operation is that it cannot react to changes in the transformation chain (if a new transformation is added and could make a shorter path, it will not be taken into account).

getTransformation_raw(src_ref, dst_ref)

same as getTransformation(), but do not perform lazy loading

hasSyntax()

has_key()

intKey()

isArray()

isDictionary()

isDictionaryIterator()

isDynArray()

isIterable()

isIterator()

isValid()

key()

loadAffineTransformations()

Load all affine transformations.

loadTransformationsGraph()

Load a full transformations graph from a dict-like object.

The description dict may typically be read from a .json or a .yaml file.

The description is organized as a 2-level dictionary:

{
    source_ref_id: {
        dest_ref_id1: transformation_filename1,
        dest_ref_id2: transformation_filename2,
    },
    ...
}

A referential ID is a string which may represent an UUID, or a name.

A transformatioon filename may be an affine (.trm) or non-linear (.ima) transformation file, or an empty string to represent an identity transformation.

The transformation files are found relatively to the directory given as the dirname parameter.

Alternatively to file names, an affine transformation may be given directly as its 4x4 matrix, written as a line vector (all 16 coefficients in a vecotr, describing the matrix horizontally). Ex:

{
    source_ref_id: {
        dest_ref_id1: [1, 0, 0, 0,
                       0, 1, 0, 0,
                       0, 0, 1, 0,
                       0, 0, 0, 1],
    },
    ...
}

objectIterator()

referentialById()

Get the vertex (referential) with given ID

registerInverseTransformations(loadAffines=False)

register inverse transformations when they can be obtained.

This can be done only for loaded transformations. So the lazy loading feature will prevent for it to work on not already loaded transformations, since we cannot know if they are invertible before they are loaded.

For this reason, the loadAffines parameter allows to load affine transforms and register their inverses.

registerTransformation()

Add (or register) the given transformation in the transformations graph.

transform may be a filename, or a Transformation instance. a Transformation is supposed to be a non-linear FFD (Free Form Deformation), not a linear transformation. If transform is a string, it may be: - an empty string will be an identity transformation - a .trm file will be an affine transformation, and will be passed to

the builtin Anatomist system

• another file (.ima) will be a FFD transformation file and will be registered as its filename. Loading will happen only when the transformation is used, in get_transformation().

setSyntax()

size()

transformation()

Get the Transformation3d object inside an edge. The returned reference counting pointer may contain a null pointer.

Get the Transformation3d object for the given UUID. The returned reference counting pointer may contain a null pointer.

transformationById()

Get the edge (transformation) with given ID

type()

updateIds()

Update the internal UUIDs cache. Needs to be done after changes in elements UUIDs or insertion / deletions

class soma.aims.Tree(*args, **kwargs)

Bases: GenericObject

children()

childrenSize()

clone()

currentValue()

getScalar()

getString()

hasSyntax()

has_key()

insert()

intKey()

isArray()

isDictionary()

isDictionaryIterator()

isDynArray()

isIterable()

isIterator()

isNone()

isScalar()

isString()

isValid()

key()

objectIterator()

remove()

setSyntax()

size()

type()

class soma.aims.TreeReader

Bases: wrapper

name()

read()

exception soma.aims.ValueError

Bases: StdException

class soma.aims.Vertex(*args, **kwargs)

Bases: GraphObject

clone()

currentValue()

edges()

edgesSize()

getScalar()

getString()

hasSyntax()

has_key()

intKey()

isArray()

isDictionary()

isDictionaryIterator()

isDynArray()

isIterable()

isIterator()

isValid()

key()

neighbours()

objectIterator()

randomNeighbour()

setSyntax()

size()

type()

soma.aims.Volume(*args, **kwargs)

Create an instance of Aims Volume (Volume_<type>) from a type parameter, which may be specified as the dtype keyword argument, or as one of the arguments if one is identitied as a type. The default type is ‘FLOAT’. Type definitions should match those accepted by typeCode(). Volume may also use a numpy array, or another Volume as unique argument.

Note that Volume( Volume_* ) actually performs a copy of the data, whereas Volume( rc_ptr_Volume_* ) share the input data.

soma.aims.VolumeView(volume, position, size)

Create a view in an existing volume. The returned volume is of the same type and shares data with its “parent”.

class soma.aims.Volume_BOOL(*args)

Bases: RCObject

Generalities

The various Volume_<type> classes are bindings to the C++ template classes carto::Volume. It represents a 4D volume (1D to 4D, actually) storing a specific type of data: for instance S16 is signed 16 bit short ints, FLOAT is 32 bit floats, etc.

Volumes are read and written using the Reader and Writer classes, which are in turn used by the simple read() and write() functions.

A volume of a given type can be built either using its specialized class constructor, or the general Volume() function which can take a voxel type in its arguments: the following are equivalent:

>>> v = aims.Volume_S16(100, 100, 10)
>>> v = aims.Volume('S16', 100, 100, 10)
>>> v = aims.Volume(100, 100, 10, dtype='S16')
>>> v = aims.Volume([100, 100, 10], dtype='S16')
>>> import numpy
>>> v = aims.Volume(numpy.int16, 100, 100, 10)

Numpy arrays and volumes

A volume is an array of voxels, which can be accessed via the at() method. For standard numeric types, it is also possible to get the voxels array as a numpy array, using the __array__() method, or more conveniently, numpy.asarray(volume) or numpy.array(volume, copy=False). In aims >= 5.0.2, a more concise shortcut is also available: volume.np (this is available on all types providing numpy bindings actually).

The array returned is a reference to the actual data block, so any modification to its contents also affects the Volume contents, so it is generally an easy way of manipulating volume voxels because all the power of the numpy module can be used on Volumes. The obsoloete arraydata() method used to return a numpy array just like it is in memory, that is a 4D (or more) array generally indexed by [t][z][y][x] (but it depands how it has been built), which is generally not what you like and is not consistent with AIMS indexing. Contrarily, using volume.np sets strides in the returned numpy array, so that indexing is in the “normal” order [x][y][z][t], while still sharing the same memory block. The Volume object now also wraps the numpy accessors to the volume object itself, so that volume[x, y, z, t] is the same as nupmy.asarray(volume)[x, y, z, t].

new in PyAims 4.7

Since PyAims 4.7 the numpy arrays bindings have notably improved, and are now able to bind arrays to voxels types which are not scalar numeric types. Volumes of RGB, RGBA, HSV, or Point3df now have numpy bindings. The bound object have generally a “numpy struct” binding, that is not the usual C++/python object binding, but instead a structure managed by numpy which also supports indexing. For most objects we are using, they also have an array stucture (a RGB is an array with 3 int8 items), and are bound under a sturcture with a unique field, named “v” (for “vector”):

>>> v = aims.Volume('RGB', 100, 100, 10)
>>> v[0, 0, 0, 0]
([0, 0, 0],)

Such an array may be indexed by the field name, which returns another array with scalar values and additional dimensions:

>>> v['v'].dtype
dtype('uint8')
>>> v['v'].shape
(100, 100, 10, 1, 3)

Both arrays share their memory with the aims volume.

See also

Precisions about aims / numpy bindings

Header

Volumes also store a header which can contain various information (including sizes and voxel sizes). The header is a dictionary-like generic object (Object) which can be accessed by the header() method. This header object also has a read-write access with some restrictions inherent to the Object mechanism. It will be saved with the volume contents when the volume is saved on disk.

Volumes support a number of arithmetic operators like +, - etc. when the operands types and sizes match: for instance:

>>> # V1 and V2 are two volumes
>>> V3 = V1 + V2  # adds two volumes
>>> V2 -= V1
>>> V3 = V1 + 3   # adds 3 to aceh voxel
>>> V3 = V1 * V2  # itemwise multiplication

Some type conversions can be performed on volumes, for istance to convert a Volume_S16 to a Volume_FLOAT. The simplest, to convert to another data type, is to use the astype() method.

To convert a volume into diffent structure types, such as Buckets, use the converter classes Converter_<type1>_<type2> and ShallowConverter_<type1>_<type2> with <type1> and <type2> being volume or other object types: for instance Converter_Volume_S16_Volume_FLOAT. The converter can also be called using type arguments:

>>> vol1 = aims.AimsData('S16', 100, 100, 10)
>>> c = aims.Converter(intype=vol1, outtype='BucketMap_VOID')
>>> vol2 = c(vol1)

Volume from a numpy array

It is also possible to build a Volume from a numpy array:

>>> v = aims.Volume(numpy.zeros((100, 100, 10)))

Note that passing a 1D numpy array of ints will build a volume mapping the array contents, whereas passing a python list or tuple of ints will interpret the list as a shape for the volume:

>>> v = aims.Volume(numpy.array([100, 100, 10]).astype('int32'))
>>> print(v.getSize())
[ 3, 1, 1, 1 ]
>>> print(v.np)
[100 100  10]
>>> v = aims.Volume([100, 100, 10])
>>> print(v.getSize())
[ 100, 100, 10, 1 ]

Array ordering:

In pyaims <= 5.0.x the Volume classes were only working with the X axis (the first) being contiguous, and, for numpy, should be interpreted as “Fortran-contiguous”. So to convert a numpy array into a Volume and keep the same axes ordering, you had to convert it to Fortran order first:

>>> v = aims.Volume(numpy.zeros((2, 3, 4, dtype='int32')))
# v.getSize() used to return [4, 3, 2, 1]
>>> v = aims.Volume(np.asfortranarray(numpy.zeros((2, 3, 4), dtype='int32')))
>>> print(v.getSize())
[2, 3, 4, 1]

In pyaims 5.1 this limitation is gone, you can omit the fortran order conversion. Strides are taken into account in the C++ volume. But you have to be careful with such volumes as many C++ programs assume internally that the X axis is contiguous in memory, which is not true in this situation. These programs and functions may not work, crash, or produce incorrect results when used with non-contiguous X axis volumes.

class Position4Di

Bases: wrapper

4 ints for position or size, used for Volume views.

all()

allocatorContext()

any()

arraydata()

Note

arraydata() returns a numpy array to the internal memory block, with “inverted” shape and strides.

WARNING: this is an obsolete method, which behaviour has changed. Most of the time you need numpy.asarray(volume), or more simply: volume.np, which actually provides an array with the same indices ordering. Here it is a transposed one.

Given the internal ordering of Aims Volumes, the resulting numpy array is indexed as [t][z][y][x]. This order corresponds to the numpy “fortran” order: order='F' If you need the inverse, more natural, [x][y][z][t] ordering, use the following:

>>> volarray = volume.np

or:

>>> volarray = numpy.array(volume, copy=False)

or:

>>> volarray = numpy.asarray(volume)

Using arraydata(), as the indices are reversed, if you do something like:

vol2 = aims.Volume(vol.arraydata())

You will build a transposed volume.

astype(dtype, copy=False)

Easy conversion method for volumes. Works in a similar was as numpy arrays astype() methods, except that the “copy” parameter defaults to False.

Parameters:

• dtype (string or type object) – may be a volume or voxel type, specified either as a type oject (int, aims.Volume_S32, numpy.int16), or as a string (“S16”…).

• copy (bool) – if False, a ShallowConverter will be used: if dtype matches the current volume type, a shared reference to self will be returned. Otherwise a new copy will be returned.

Return type:

A volume of the converted type

at(posx, posy=0, posz=0, post=0)

Returns the volume value for the selected voxel.

at(posx1, posx2, posx3, posx4, posx5, posx6=0, posx7=0, posx8=0)

Returns the volume value for the selected voxel.

at(vector_int)

Returns the volume value for the selected voxel.

checkResize()

copyHeaderFrom()

fill(value)

Fill Volume_BOOL using the given value.

fillBorder(value)

Fill the surrounding of the volume view in the reference volume (if any) using the given value.

fromObject()

getBorders()

getSize()

Number of voxels in each dimension (list of 4 ints)

getSizeT()

getSizeX()

getSizeY()

getSizeZ()

getStrides()

getVoxelSize()

Voxel sizes in mm (list of 4 floats)

header()

The header contains all meta-data.

max()

min()

property np

The np property is a shortcut to the __array__ method. Thus:

something.np

is a handier equivalent to:

numpy.asarray(something)

posInRefVolume()

If the volume is a view into another (larger) one, this returns the position in “parent” one.

refVolume()

If the volume is a view into another (larger) one, this returns the “parent” one.

setPosInRefVolume()

Set position in parent volume

setValue(value, x, y=0, z=0, t=0)

Set the voxel value at the given position.

setValue(value, [x1, x2, x3, x4, x5, x6…])

Set the voxel value at the given position.

setVoxelSize(vs_list)

setVoxelSize(vx, vy=1., vz=1., vt=1.) → None

Set voxel sizes in mm (list of at least 4 floats)

property shape

value(posx, posy=0, posz=0, post=0)

value is an alias to at(): returns the volume value for the selected voxel.

class soma.aims.Volume_CDOUBLE(*args)

Bases: RCObject

Generalities

The various Volume_<type> classes are bindings to the C++ template classes carto::Volume. It represents a 4D volume (1D to 4D, actually) storing a specific type of data: for instance S16 is signed 16 bit short ints, FLOAT is 32 bit floats, etc.

Volumes are read and written using the Reader and Writer classes, which are in turn used by the simple read() and write() functions.

A volume of a given type can be built either using its specialized class constructor, or the general Volume() function which can take a voxel type in its arguments: the following are equivalent:

>>> v = aims.Volume_S16(100, 100, 10)
>>> v = aims.Volume('S16', 100, 100, 10)
>>> v = aims.Volume(100, 100, 10, dtype='S16')
>>> v = aims.Volume([100, 100, 10], dtype='S16')
>>> import numpy
>>> v = aims.Volume(numpy.int16, 100, 100, 10)

Numpy arrays and volumes

A volume is an array of voxels, which can be accessed via the at() method. For standard numeric types, it is also possible to get the voxels array as a numpy array, using the __array__() method, or more conveniently, numpy.asarray(volume) or numpy.array(volume, copy=False). In aims >= 5.0.2, a more concise shortcut is also available: volume.np (this is available on all types providing numpy bindings actually).

The array returned is a reference to the actual data block, so any modification to its contents also affects the Volume contents, so it is generally an easy way of manipulating volume voxels because all the power of the numpy module can be used on Volumes. The obsoloete arraydata() method used to return a numpy array just like it is in memory, that is a 4D (or more) array generally indexed by [t][z][y][x] (but it depands how it has been built), which is generally not what you like and is not consistent with AIMS indexing. Contrarily, using volume.np sets strides in the returned numpy array, so that indexing is in the “normal” order [x][y][z][t], while still sharing the same memory block. The Volume object now also wraps the numpy accessors to the volume object itself, so that volume[x, y, z, t] is the same as nupmy.asarray(volume)[x, y, z, t].

new in PyAims 4.7

Since PyAims 4.7 the numpy arrays bindings have notably improved, and are now able to bind arrays to voxels types which are not scalar numeric types. Volumes of RGB, RGBA, HSV, or Point3df now have numpy bindings. The bound object have generally a “numpy struct” binding, that is not the usual C++/python object binding, but instead a structure managed by numpy which also supports indexing. For most objects we are using, they also have an array stucture (a RGB is an array with 3 int8 items), and are bound under a sturcture with a unique field, named “v” (for “vector”):

>>> v = aims.Volume('RGB', 100, 100, 10)
>>> v[0, 0, 0, 0]
([0, 0, 0],)

Such an array may be indexed by the field name, which returns another array with scalar values and additional dimensions:

>>> v['v'].dtype
dtype('uint8')
>>> v['v'].shape
(100, 100, 10, 1, 3)

Both arrays share their memory with the aims volume.

See also

Precisions about aims / numpy bindings

Header

Volumes also store a header which can contain various information (including sizes and voxel sizes). The header is a dictionary-like generic object (Object) which can be accessed by the header() method. This header object also has a read-write access with some restrictions inherent to the Object mechanism. It will be saved with the volume contents when the volume is saved on disk.

Volumes support a number of arithmetic operators like +, - etc. when the operands types and sizes match: for instance:

>>> # V1 and V2 are two volumes
>>> V3 = V1 + V2  # adds two volumes
>>> V2 -= V1
>>> V3 = V1 + 3   # adds 3 to aceh voxel
>>> V3 = V1 * V2  # itemwise multiplication

Some type conversions can be performed on volumes, for istance to convert a Volume_S16 to a Volume_FLOAT. The simplest, to convert to another data type, is to use the astype() method.

To convert a volume into diffent structure types, such as Buckets, use the converter classes Converter_<type1>_<type2> and ShallowConverter_<type1>_<type2> with <type1> and <type2> being volume or other object types: for instance Converter_Volume_S16_Volume_FLOAT. The converter can also be called using type arguments:

>>> vol1 = aims.AimsData('S16', 100, 100, 10)
>>> c = aims.Converter(intype=vol1, outtype='BucketMap_VOID')
>>> vol2 = c(vol1)

Volume from a numpy array

It is also possible to build a Volume from a numpy array:

>>> v = aims.Volume(numpy.zeros((100, 100, 10)))

Note that passing a 1D numpy array of ints will build a volume mapping the array contents, whereas passing a python list or tuple of ints will interpret the list as a shape for the volume:

>>> v = aims.Volume(numpy.array([100, 100, 10]).astype('int32'))
>>> print(v.getSize())
[ 3, 1, 1, 1 ]
>>> print(v.np)
[100 100  10]
>>> v = aims.Volume([100, 100, 10])
>>> print(v.getSize())
[ 100, 100, 10, 1 ]

Array ordering:

In pyaims <= 5.0.x the Volume classes were only working with the X axis (the first) being contiguous, and, for numpy, should be interpreted as “Fortran-contiguous”. So to convert a numpy array into a Volume and keep the same axes ordering, you had to convert it to Fortran order first:

>>> v = aims.Volume(numpy.zeros((2, 3, 4, dtype='int32')))
# v.getSize() used to return [4, 3, 2, 1]
>>> v = aims.Volume(np.asfortranarray(numpy.zeros((2, 3, 4), dtype='int32')))
>>> print(v.getSize())
[2, 3, 4, 1]

In pyaims 5.1 this limitation is gone, you can omit the fortran order conversion. Strides are taken into account in the C++ volume. But you have to be careful with such volumes as many C++ programs assume internally that the X axis is contiguous in memory, which is not true in this situation. These programs and functions may not work, crash, or produce incorrect results when used with non-contiguous X axis volumes.

class Position4Di

Bases: wrapper

4 ints for position or size, used for Volume views.

all()

allocatorContext()

any()

arraydata()

Note

arraydata() returns a numpy array to the internal memory block, with “inverted” shape and strides.

WARNING: this is an obsolete method, which behaviour has changed. Most of the time you need numpy.asarray(volume), or more simply: volume.np, which actually provides an array with the same indices ordering. Here it is a transposed one.

Given the internal ordering of Aims Volumes, the resulting numpy array is indexed as [t][z][y][x]. This order corresponds to the numpy “fortran” order: order='F' If you need the inverse, more natural, [x][y][z][t] ordering, use the following:

>>> volarray = volume.np

or:

>>> volarray = numpy.array(volume, copy=False)

or:

>>> volarray = numpy.asarray(volume)

Using arraydata(), as the indices are reversed, if you do something like:

vol2 = aims.Volume(vol.arraydata())

You will build a transposed volume.

astype(dtype, copy=False)

Easy conversion method for volumes. Works in a similar was as numpy arrays astype() methods, except that the “copy” parameter defaults to False.

Parameters:

• dtype (string or type object) – may be a volume or voxel type, specified either as a type oject (int, aims.Volume_S32, numpy.int16), or as a string (“S16”…).

• copy (bool) – if False, a ShallowConverter will be used: if dtype matches the current volume type, a shared reference to self will be returned. Otherwise a new copy will be returned.

Return type:

A volume of the converted type

at(posx, posy=0, posz=0, post=0)

Returns the volume value for the selected voxel.

at(posx1, posx2, posx3, posx4, posx5, posx6=0, posx7=0, posx8=0)

Returns the volume value for the selected voxel.

at(vector_int)

Returns the volume value for the selected voxel.

checkResize()

copyHeaderFrom()

fill(value)

Fill Volume_CDOUBLE using the given value.

fillBorder(value)

Fill the surrounding of the volume view in the reference volume (if any) using the given value.

fromObject()

getBorders()

getSize()

Number of voxels in each dimension (list of 4 ints)

getSizeT()

getSizeX()

getSizeY()

getSizeZ()

getStrides()

getVoxelSize()

Voxel sizes in mm (list of 4 floats)

header()

The header contains all meta-data.

max()

min()

property np

The np property is a shortcut to the __array__ method. Thus:

something.np

is a handier equivalent to:

numpy.asarray(something)

posInRefVolume()

If the volume is a view into another (larger) one, this returns the position in “parent” one.

refVolume()

If the volume is a view into another (larger) one, this returns the “parent” one.

setPosInRefVolume()

Set position in parent volume

setValue(value, x, y=0, z=0, t=0)

Set the voxel value at the given position.

setValue(value, [x1, x2, x3, x4, x5, x6…])

Set the voxel value at the given position.

setVoxelSize(vs_list)

setVoxelSize(vx, vy=1., vz=1., vt=1.) → None

Set voxel sizes in mm (list of at least 4 floats)

property shape

value(posx, posy=0, posz=0, post=0)

value is an alias to at(): returns the volume value for the selected voxel.

class soma.aims.Volume_CFLOAT(*args)

Bases: RCObject

Generalities

The various Volume_<type> classes are bindings to the C++ template classes carto::Volume. It represents a 4D volume (1D to 4D, actually) storing a specific type of data: for instance S16 is signed 16 bit short ints, FLOAT is 32 bit floats, etc.

Volumes are read and written using the Reader and Writer classes, which are in turn used by the simple read() and write() functions.

A volume of a given type can be built either using its specialized class constructor, or the general Volume() function which can take a voxel type in its arguments: the following are equivalent:

>>> v = aims.Volume_S16(100, 100, 10)
>>> v = aims.Volume('S16', 100, 100, 10)
>>> v = aims.Volume(100, 100, 10, dtype='S16')
>>> v = aims.Volume([100, 100, 10], dtype='S16')
>>> import numpy
>>> v = aims.Volume(numpy.int16, 100, 100, 10)

Numpy arrays and volumes

A volume is an array of voxels, which can be accessed via the at() method. For standard numeric types, it is also possible to get the voxels array as a numpy array, using the __array__() method, or more conveniently, numpy.asarray(volume) or numpy.array(volume, copy=False). In aims >= 5.0.2, a more concise shortcut is also available: volume.np (this is available on all types providing numpy bindings actually).

The array returned is a reference to the actual data block, so any modification to its contents also affects the Volume contents, so it is generally an easy way of manipulating volume voxels because all the power of the numpy module can be used on Volumes. The obsoloete arraydata() method used to return a numpy array just like it is in memory, that is a 4D (or more) array generally indexed by [t][z][y][x] (but it depands how it has been built), which is generally not what you like and is not consistent with AIMS indexing. Contrarily, using volume.np sets strides in the returned numpy array, so that indexing is in the “normal” order [x][y][z][t], while still sharing the same memory block. The Volume object now also wraps the numpy accessors to the volume object itself, so that volume[x, y, z, t] is the same as nupmy.asarray(volume)[x, y, z, t].

new in PyAims 4.7

Since PyAims 4.7 the numpy arrays bindings have notably improved, and are now able to bind arrays to voxels types which are not scalar numeric types. Volumes of RGB, RGBA, HSV, or Point3df now have numpy bindings. The bound object have generally a “numpy struct” binding, that is not the usual C++/python object binding, but instead a structure managed by numpy which also supports indexing. For most objects we are using, they also have an array stucture (a RGB is an array with 3 int8 items), and are bound under a sturcture with a unique field, named “v” (for “vector”):

>>> v = aims.Volume('RGB', 100, 100, 10)
>>> v[0, 0, 0, 0]
([0, 0, 0],)

Such an array may be indexed by the field name, which returns another array with scalar values and additional dimensions:

>>> v['v'].dtype
dtype('uint8')
>>> v['v'].shape
(100, 100, 10, 1, 3)

Both arrays share their memory with the aims volume.

See also

Precisions about aims / numpy bindings

Header

Volumes also store a header which can contain various information (including sizes and voxel sizes). The header is a dictionary-like generic object (Object) which can be accessed by the header() method. This header object also has a read-write access with some restrictions inherent to the Object mechanism. It will be saved with the volume contents when the volume is saved on disk.

Volumes support a number of arithmetic operators like +, - etc. when the operands types and sizes match: for instance:

>>> # V1 and V2 are two volumes
>>> V3 = V1 + V2  # adds two volumes
>>> V2 -= V1
>>> V3 = V1 + 3   # adds 3 to aceh voxel
>>> V3 = V1 * V2  # itemwise multiplication

Some type conversions can be performed on volumes, for istance to convert a Volume_S16 to a Volume_FLOAT. The simplest, to convert to another data type, is to use the astype() method.

To convert a volume into diffent structure types, such as Buckets, use the converter classes Converter_<type1>_<type2> and ShallowConverter_<type1>_<type2> with <type1> and <type2> being volume or other object types: for instance Converter_Volume_S16_Volume_FLOAT. The converter can also be called using type arguments:

>>> vol1 = aims.AimsData('S16', 100, 100, 10)
>>> c = aims.Converter(intype=vol1, outtype='BucketMap_VOID')
>>> vol2 = c(vol1)

Volume from a numpy array

It is also possible to build a Volume from a numpy array:

>>> v = aims.Volume(numpy.zeros((100, 100, 10)))

Note that passing a 1D numpy array of ints will build a volume mapping the array contents, whereas passing a python list or tuple of ints will interpret the list as a shape for the volume:

>>> v = aims.Volume(numpy.array([100, 100, 10]).astype('int32'))
>>> print(v.getSize())
[ 3, 1, 1, 1 ]
>>> print(v.np)
[100 100  10]
>>> v = aims.Volume([100, 100, 10])
>>> print(v.getSize())
[ 100, 100, 10, 1 ]

Array ordering:

In pyaims <= 5.0.x the Volume classes were only working with the X axis (the first) being contiguous, and, for numpy, should be interpreted as “Fortran-contiguous”. So to convert a numpy array into a Volume and keep the same axes ordering, you had to convert it to Fortran order first:

>>> v = aims.Volume(numpy.zeros((2, 3, 4, dtype='int32')))
# v.getSize() used to return [4, 3, 2, 1]
>>> v = aims.Volume(np.asfortranarray(numpy.zeros((2, 3, 4), dtype='int32')))
>>> print(v.getSize())
[2, 3, 4, 1]

In pyaims 5.1 this limitation is gone, you can omit the fortran order conversion. Strides are taken into account in the C++ volume. But you have to be careful with such volumes as many C++ programs assume internally that the X axis is contiguous in memory, which is not true in this situation. These programs and functions may not work, crash, or produce incorrect results when used with non-contiguous X axis volumes.

class Position4Di

Bases: wrapper

4 ints for position or size, used for Volume views.

all()

allocatorContext()

any()

arraydata()

Note

arraydata() returns a numpy array to the internal memory block, with “inverted” shape and strides.

WARNING: this is an obsolete method, which behaviour has changed. Most of the time you need numpy.asarray(volume), or more simply: volume.np, which actually provides an array with the same indices ordering. Here it is a transposed one.

Given the internal ordering of Aims Volumes, the resulting numpy array is indexed as [t][z][y][x]. This order corresponds to the numpy “fortran” order: order='F' If you need the inverse, more natural, [x][y][z][t] ordering, use the following:

>>> volarray = volume.np

or:

>>> volarray = numpy.array(volume, copy=False)

or:

>>> volarray = numpy.asarray(volume)

Using arraydata(), as the indices are reversed, if you do something like:

vol2 = aims.Volume(vol.arraydata())

You will build a transposed volume.

astype(dtype, copy=False)

Easy conversion method for volumes. Works in a similar was as numpy arrays astype() methods, except that the “copy” parameter defaults to False.

Parameters:

• dtype (string or type object) – may be a volume or voxel type, specified either as a type oject (int, aims.Volume_S32, numpy.int16), or as a string (“S16”…).

• copy (bool) – if False, a ShallowConverter will be used: if dtype matches the current volume type, a shared reference to self will be returned. Otherwise a new copy will be returned.

Return type:

A volume of the converted type

at(posx, posy=0, posz=0, post=0)

Returns the volume value for the selected voxel.

at(posx1, posx2, posx3, posx4, posx5, posx6=0, posx7=0, posx8=0)

Returns the volume value for the selected voxel.

at(vector_int)

Returns the volume value for the selected voxel.

checkResize()

copyHeaderFrom()

fill(value)

Fill Volume_CFLOAT using the given value.

fillBorder(value)

Fill the surrounding of the volume view in the reference volume (if any) using the given value.

fromObject()

getBorders()

getSize()

Number of voxels in each dimension (list of 4 ints)

getSizeT()

getSizeX()

getSizeY()

getSizeZ()

getStrides()

getVoxelSize()

Voxel sizes in mm (list of 4 floats)

header()

The header contains all meta-data.

max()

min()

property np

The np property is a shortcut to the __array__ method. Thus:

something.np

is a handier equivalent to:

numpy.asarray(something)

posInRefVolume()

If the volume is a view into another (larger) one, this returns the position in “parent” one.

refVolume()

If the volume is a view into another (larger) one, this returns the “parent” one.

setPosInRefVolume()

Set position in parent volume

setValue(value, x, y=0, z=0, t=0)

Set the voxel value at the given position.

setValue(value, [x1, x2, x3, x4, x5, x6…])

Set the voxel value at the given position.

setVoxelSize(vs_list)

setVoxelSize(vx, vy=1., vz=1., vt=1.) → None

Set voxel sizes in mm (list of at least 4 floats)

property shape

value(posx, posy=0, posz=0, post=0)

value is an alias to at(): returns the volume value for the selected voxel.

class soma.aims.Volume_DOUBLE(*args)

Bases: RCObject

Generalities

The various Volume_<type> classes are bindings to the C++ template classes carto::Volume. It represents a 4D volume (1D to 4D, actually) storing a specific type of data: for instance S16 is signed 16 bit short ints, FLOAT is 32 bit floats, etc.

Volumes are read and written using the Reader and Writer classes, which are in turn used by the simple read() and write() functions.

A volume of a given type can be built either using its specialized class constructor, or the general Volume() function which can take a voxel type in its arguments: the following are equivalent:

>>> v = aims.Volume_S16(100, 100, 10)
>>> v = aims.Volume('S16', 100, 100, 10)
>>> v = aims.Volume(100, 100, 10, dtype='S16')
>>> v = aims.Volume([100, 100, 10], dtype='S16')
>>> import numpy
>>> v = aims.Volume(numpy.int16, 100, 100, 10)

Numpy arrays and volumes

A volume is an array of voxels, which can be accessed via the at() method. For standard numeric types, it is also possible to get the voxels array as a numpy array, using the __array__() method, or more conveniently, numpy.asarray(volume) or numpy.array(volume, copy=False). In aims >= 5.0.2, a more concise shortcut is also available: volume.np (this is available on all types providing numpy bindings actually).

The array returned is a reference to the actual data block, so any modification to its contents also affects the Volume contents, so it is generally an easy way of manipulating volume voxels because all the power of the numpy module can be used on Volumes. The obsoloete arraydata() method used to return a numpy array just like it is in memory, that is a 4D (or more) array generally indexed by [t][z][y][x] (but it depands how it has been built), which is generally not what you like and is not consistent with AIMS indexing. Contrarily, using volume.np sets strides in the returned numpy array, so that indexing is in the “normal” order [x][y][z][t], while still sharing the same memory block. The Volume object now also wraps the numpy accessors to the volume object itself, so that volume[x, y, z, t] is the same as nupmy.asarray(volume)[x, y, z, t].

new in PyAims 4.7

Since PyAims 4.7 the numpy arrays bindings have notably improved, and are now able to bind arrays to voxels types which are not scalar numeric types. Volumes of RGB, RGBA, HSV, or Point3df now have numpy bindings. The bound object have generally a “numpy struct” binding, that is not the usual C++/python object binding, but instead a structure managed by numpy which also supports indexing. For most objects we are using, they also have an array stucture (a RGB is an array with 3 int8 items), and are bound under a sturcture with a unique field, named “v” (for “vector”):

>>> v = aims.Volume('RGB', 100, 100, 10)
>>> v[0, 0, 0, 0]
([0, 0, 0],)

Such an array may be indexed by the field name, which returns another array with scalar values and additional dimensions:

>>> v['v'].dtype
dtype('uint8')
>>> v['v'].shape
(100, 100, 10, 1, 3)

Both arrays share their memory with the aims volume.

See also

Precisions about aims / numpy bindings

Header

Volumes also store a header which can contain various information (including sizes and voxel sizes). The header is a dictionary-like generic object (Object) which can be accessed by the header() method. This header object also has a read-write access with some restrictions inherent to the Object mechanism. It will be saved with the volume contents when the volume is saved on disk.

Volumes support a number of arithmetic operators like +, - etc. when the operands types and sizes match: for instance:

>>> # V1 and V2 are two volumes
>>> V3 = V1 + V2  # adds two volumes
>>> V2 -= V1
>>> V3 = V1 + 3   # adds 3 to aceh voxel
>>> V3 = V1 * V2  # itemwise multiplication

Some type conversions can be performed on volumes, for istance to convert a Volume_S16 to a Volume_FLOAT. The simplest, to convert to another data type, is to use the astype() method.

To convert a volume into diffent structure types, such as Buckets, use the converter classes Converter_<type1>_<type2> and ShallowConverter_<type1>_<type2> with <type1> and <type2> being volume or other object types: for instance Converter_Volume_S16_Volume_FLOAT. The converter can also be called using type arguments:

>>> vol1 = aims.AimsData('S16', 100, 100, 10)
>>> c = aims.Converter(intype=vol1, outtype='BucketMap_VOID')
>>> vol2 = c(vol1)

Volume from a numpy array

It is also possible to build a Volume from a numpy array:

>>> v = aims.Volume(numpy.zeros((100, 100, 10)))

Note that passing a 1D numpy array of ints will build a volume mapping the array contents, whereas passing a python list or tuple of ints will interpret the list as a shape for the volume:

>>> v = aims.Volume(numpy.array([100, 100, 10]).astype('int32'))
>>> print(v.getSize())
[ 3, 1, 1, 1 ]
>>> print(v.np)
[100 100  10]
>>> v = aims.Volume([100, 100, 10])
>>> print(v.getSize())
[ 100, 100, 10, 1 ]

Array ordering:

In pyaims <= 5.0.x the Volume classes were only working with the X axis (the first) being contiguous, and, for numpy, should be interpreted as “Fortran-contiguous”. So to convert a numpy array into a Volume and keep the same axes ordering, you had to convert it to Fortran order first:

>>> v = aims.Volume(numpy.zeros((2, 3, 4, dtype='int32')))
# v.getSize() used to return [4, 3, 2, 1]
>>> v = aims.Volume(np.asfortranarray(numpy.zeros((2, 3, 4), dtype='int32')))
>>> print(v.getSize())
[2, 3, 4, 1]

In pyaims 5.1 this limitation is gone, you can omit the fortran order conversion. Strides are taken into account in the C++ volume. But you have to be careful with such volumes as many C++ programs assume internally that the X axis is contiguous in memory, which is not true in this situation. These programs and functions may not work, crash, or produce incorrect results when used with non-contiguous X axis volumes.

class Position4Di

Bases: wrapper

4 ints for position or size, used for Volume views.

all()

allocatorContext()

any()

arraydata()

Note

arraydata() returns a numpy array to the internal memory block, with “inverted” shape and strides.

WARNING: this is an obsolete method, which behaviour has changed. Most of the time you need numpy.asarray(volume), or more simply: volume.np, which actually provides an array with the same indices ordering. Here it is a transposed one.

Given the internal ordering of Aims Volumes, the resulting numpy array is indexed as [t][z][y][x]. This order corresponds to the numpy “fortran” order: order='F' If you need the inverse, more natural, [x][y][z][t] ordering, use the following:

>>> volarray = volume.np

or:

>>> volarray = numpy.array(volume, copy=False)

or:

>>> volarray = numpy.asarray(volume)

Using arraydata(), as the indices are reversed, if you do something like:

vol2 = aims.Volume(vol.arraydata())

You will build a transposed volume.

astype(dtype, copy=False)

Easy conversion method for volumes. Works in a similar was as numpy arrays astype() methods, except that the “copy” parameter defaults to False.

Parameters:

• dtype (string or type object) – may be a volume or voxel type, specified either as a type oject (int, aims.Volume_S32, numpy.int16), or as a string (“S16”…).

• copy (bool) – if False, a ShallowConverter will be used: if dtype matches the current volume type, a shared reference to self will be returned. Otherwise a new copy will be returned.

Return type:

A volume of the converted type

at(posx, posy=0, posz=0, post=0)

Returns the volume value for the selected voxel.

at(posx1, posx2, posx3, posx4, posx5, posx6=0, posx7=0, posx8=0)

Returns the volume value for the selected voxel.

at(vector_int)

Returns the volume value for the selected voxel.

checkResize()

copyHeaderFrom()

fill(value)

Fill Volume_DOUBLE using the given value.

fillBorder(value)

Fill the surrounding of the volume view in the reference volume (if any) using the given value.

fromObject()

getBorders()

getSize()

Number of voxels in each dimension (list of 4 ints)

getSizeT()

getSizeX()

getSizeY()

getSizeZ()

getStrides()

getVoxelSize()

Voxel sizes in mm (list of 4 floats)

header()

The header contains all meta-data.

max()

min()

property np

The np property is a shortcut to the __array__ method. Thus:

something.np

is a handier equivalent to:

numpy.asarray(something)

posInRefVolume()

If the volume is a view into another (larger) one, this returns the position in “parent” one.

refVolume()

If the volume is a view into another (larger) one, this returns the “parent” one.

setPosInRefVolume()

Set position in parent volume

setValue(value, x, y=0, z=0, t=0)

Set the voxel value at the given position.

setValue(value, [x1, x2, x3, x4, x5, x6…])

Set the voxel value at the given position.

setVoxelSize(vs_list)

setVoxelSize(vx, vy=1., vz=1., vt=1.) → None

Set voxel sizes in mm (list of at least 4 floats)

property shape

value(posx, posy=0, posz=0, post=0)

value is an alias to at(): returns the volume value for the selected voxel.

class soma.aims.Volume_FLOAT(*args)

Bases: RCObject

Generalities

The various Volume_<type> classes are bindings to the C++ template classes carto::Volume. It represents a 4D volume (1D to 4D, actually) storing a specific type of data: for instance S16 is signed 16 bit short ints, FLOAT is 32 bit floats, etc.

Volumes are read and written using the Reader and Writer classes, which are in turn used by the simple read() and write() functions.

A volume of a given type can be built either using its specialized class constructor, or the general Volume() function which can take a voxel type in its arguments: the following are equivalent:

>>> v = aims.Volume_S16(100, 100, 10)
>>> v = aims.Volume('S16', 100, 100, 10)
>>> v = aims.Volume(100, 100, 10, dtype='S16')
>>> v = aims.Volume([100, 100, 10], dtype='S16')
>>> import numpy
>>> v = aims.Volume(numpy.int16, 100, 100, 10)

Numpy arrays and volumes

A volume is an array of voxels, which can be accessed via the at() method. For standard numeric types, it is also possible to get the voxels array as a numpy array, using the __array__() method, or more conveniently, numpy.asarray(volume) or numpy.array(volume, copy=False). In aims >= 5.0.2, a more concise shortcut is also available: volume.np (this is available on all types providing numpy bindings actually).

The array returned is a reference to the actual data block, so any modification to its contents also affects the Volume contents, so it is generally an easy way of manipulating volume voxels because all the power of the numpy module can be used on Volumes. The obsoloete arraydata() method used to return a numpy array just like it is in memory, that is a 4D (or more) array generally indexed by [t][z][y][x] (but it depands how it has been built), which is generally not what you like and is not consistent with AIMS indexing. Contrarily, using volume.np sets strides in the returned numpy array, so that indexing is in the “normal” order [x][y][z][t], while still sharing the same memory block. The Volume object now also wraps the numpy accessors to the volume object itself, so that volume[x, y, z, t] is the same as nupmy.asarray(volume)[x, y, z, t].

new in PyAims 4.7

Since PyAims 4.7 the numpy arrays bindings have notably improved, and are now able to bind arrays to voxels types which are not scalar numeric types. Volumes of RGB, RGBA, HSV, or Point3df now have numpy bindings. The bound object have generally a “numpy struct” binding, that is not the usual C++/python object binding, but instead a structure managed by numpy which also supports indexing. For most objects we are using, they also have an array stucture (a RGB is an array with 3 int8 items), and are bound under a sturcture with a unique field, named “v” (for “vector”):

>>> v = aims.Volume('RGB', 100, 100, 10)
>>> v[0, 0, 0, 0]
([0, 0, 0],)

Such an array may be indexed by the field name, which returns another array with scalar values and additional dimensions:

>>> v['v'].dtype
dtype('uint8')
>>> v['v'].shape
(100, 100, 10, 1, 3)

Both arrays share their memory with the aims volume.

See also

Precisions about aims / numpy bindings

Header

Volumes also store a header which can contain various information (including sizes and voxel sizes). The header is a dictionary-like generic object (Object) which can be accessed by the header() method. This header object also has a read-write access with some restrictions inherent to the Object mechanism. It will be saved with the volume contents when the volume is saved on disk.

Volumes support a number of arithmetic operators like +, - etc. when the operands types and sizes match: for instance:

>>> # V1 and V2 are two volumes
>>> V3 = V1 + V2  # adds two volumes
>>> V2 -= V1
>>> V3 = V1 + 3   # adds 3 to aceh voxel
>>> V3 = V1 * V2  # itemwise multiplication

Some type conversions can be performed on volumes, for istance to convert a Volume_S16 to a Volume_FLOAT. The simplest, to convert to another data type, is to use the astype() method.

To convert a volume into diffent structure types, such as Buckets, use the converter classes Converter_<type1>_<type2> and ShallowConverter_<type1>_<type2> with <type1> and <type2> being volume or other object types: for instance Converter_Volume_S16_Volume_FLOAT. The converter can also be called using type arguments:

>>> vol1 = aims.AimsData('S16', 100, 100, 10)
>>> c = aims.Converter(intype=vol1, outtype='BucketMap_VOID')
>>> vol2 = c(vol1)

Volume from a numpy array

It is also possible to build a Volume from a numpy array:

>>> v = aims.Volume(numpy.zeros((100, 100, 10)))

Note that passing a 1D numpy array of ints will build a volume mapping the array contents, whereas passing a python list or tuple of ints will interpret the list as a shape for the volume:

>>> v = aims.Volume(numpy.array([100, 100, 10]).astype('int32'))
>>> print(v.getSize())
[ 3, 1, 1, 1 ]
>>> print(v.np)
[100 100  10]
>>> v = aims.Volume([100, 100, 10])
>>> print(v.getSize())
[ 100, 100, 10, 1 ]

Array ordering:

In pyaims <= 5.0.x the Volume classes were only working with the X axis (the first) being contiguous, and, for numpy, should be interpreted as “Fortran-contiguous”. So to convert a numpy array into a Volume and keep the same axes ordering, you had to convert it to Fortran order first:

>>> v = aims.Volume(numpy.zeros((2, 3, 4, dtype='int32')))
# v.getSize() used to return [4, 3, 2, 1]
>>> v = aims.Volume(np.asfortranarray(numpy.zeros((2, 3, 4), dtype='int32')))
>>> print(v.getSize())
[2, 3, 4, 1]

In pyaims 5.1 this limitation is gone, you can omit the fortran order conversion. Strides are taken into account in the C++ volume. But you have to be careful with such volumes as many C++ programs assume internally that the X axis is contiguous in memory, which is not true in this situation. These programs and functions may not work, crash, or produce incorrect results when used with non-contiguous X axis volumes.

class Position4Di

Bases: wrapper

4 ints for position or size, used for Volume views.

all()

allocatorContext()

any()

arraydata()

Note

arraydata() returns a numpy array to the internal memory block, with “inverted” shape and strides.

WARNING: this is an obsolete method, which behaviour has changed. Most of the time you need numpy.asarray(volume), or more simply: volume.np, which actually provides an array with the same indices ordering. Here it is a transposed one.

Given the internal ordering of Aims Volumes, the resulting numpy array is indexed as [t][z][y][x]. This order corresponds to the numpy “fortran” order: order='F' If you need the inverse, more natural, [x][y][z][t] ordering, use the following:

>>> volarray = volume.np

or:

>>> volarray = numpy.array(volume, copy=False)

or:

>>> volarray = numpy.asarray(volume)

Using arraydata(), as the indices are reversed, if you do something like:

vol2 = aims.Volume(vol.arraydata())

You will build a transposed volume.

astype(dtype, copy=False)

Easy conversion method for volumes. Works in a similar was as numpy arrays astype() methods, except that the “copy” parameter defaults to False.

Parameters:

• dtype (string or type object) – may be a volume or voxel type, specified either as a type oject (int, aims.Volume_S32, numpy.int16), or as a string (“S16”…).

• copy (bool) – if False, a ShallowConverter will be used: if dtype matches the current volume type, a shared reference to self will be returned. Otherwise a new copy will be returned.

Return type:

A volume of the converted type

at(posx, posy=0, posz=0, post=0)

Returns the volume value for the selected voxel.

at(posx1, posx2, posx3, posx4, posx5, posx6=0, posx7=0, posx8=0)

Returns the volume value for the selected voxel.

at(vector_int)

Returns the volume value for the selected voxel.

checkResize()

copyHeaderFrom()

fill(value)

Fill Volume_FLOAT using the given value.

fillBorder(value)

Fill the surrounding of the volume view in the reference volume (if any) using the given value.

fromObject()

getBorders()

getSize()

Number of voxels in each dimension (list of 4 ints)

getSizeT()

getSizeX()

getSizeY()

getSizeZ()

getStrides()

getVoxelSize()

Voxel sizes in mm (list of 4 floats)

header()

The header contains all meta-data.

max()

min()

property np

The np property is a shortcut to the __array__ method. Thus:

something.np

is a handier equivalent to:

numpy.asarray(something)

posInRefVolume()

If the volume is a view into another (larger) one, this returns the position in “parent” one.

refVolume()

If the volume is a view into another (larger) one, this returns the “parent” one.

setPosInRefVolume()

Set position in parent volume

setValue(value, x, y=0, z=0, t=0)

Set the voxel value at the given position.

setValue(value, [x1, x2, x3, x4, x5, x6…])

Set the voxel value at the given position.

setVoxelSize(vs_list)

setVoxelSize(vx, vy=1., vz=1., vt=1.) → None

Set voxel sizes in mm (list of at least 4 floats)

property shape

value(posx, posy=0, posz=0, post=0)

value is an alias to at(): returns the volume value for the selected voxel.

class soma.aims.Volume_HSV(*args)

Bases: RCObject

Generalities

The various Volume_<type> classes are bindings to the C++ template classes carto::Volume. It represents a 4D volume (1D to 4D, actually) storing a specific type of data: for instance S16 is signed 16 bit short ints, FLOAT is 32 bit floats, etc.

Volumes are read and written using the Reader and Writer classes, which are in turn used by the simple read() and write() functions.

A volume of a given type can be built either using its specialized class constructor, or the general Volume() function which can take a voxel type in its arguments: the following are equivalent:

>>> v = aims.Volume_S16(100, 100, 10)
>>> v = aims.Volume('S16', 100, 100, 10)
>>> v = aims.Volume(100, 100, 10, dtype='S16')
>>> v = aims.Volume([100, 100, 10], dtype='S16')
>>> import numpy
>>> v = aims.Volume(numpy.int16, 100, 100, 10)

Numpy arrays and volumes

A volume is an array of voxels, which can be accessed via the at() method. For standard numeric types, it is also possible to get the voxels array as a numpy array, using the __array__() method, or more conveniently, numpy.asarray(volume) or numpy.array(volume, copy=False). In aims >= 5.0.2, a more concise shortcut is also available: volume.np (this is available on all types providing numpy bindings actually).

The array returned is a reference to the actual data block, so any modification to its contents also affects the Volume contents, so it is generally an easy way of manipulating volume voxels because all the power of the numpy module can be used on Volumes. The obsoloete arraydata() method used to return a numpy array just like it is in memory, that is a 4D (or more) array generally indexed by [t][z][y][x] (but it depands how it has been built), which is generally not what you like and is not consistent with AIMS indexing. Contrarily, using volume.np sets strides in the returned numpy array, so that indexing is in the “normal” order [x][y][z][t], while still sharing the same memory block. The Volume object now also wraps the numpy accessors to the volume object itself, so that volume[x, y, z, t] is the same as nupmy.asarray(volume)[x, y, z, t].

new in PyAims 4.7

Since PyAims 4.7 the numpy arrays bindings have notably improved, and are now able to bind arrays to voxels types which are not scalar numeric types. Volumes of RGB, RGBA, HSV, or Point3df now have numpy bindings. The bound object have generally a “numpy struct” binding, that is not the usual C++/python object binding, but instead a structure managed by numpy which also supports indexing. For most objects we are using, they also have an array stucture (a RGB is an array with 3 int8 items), and are bound under a sturcture with a unique field, named “v” (for “vector”):

>>> v = aims.Volume('RGB', 100, 100, 10)
>>> v[0, 0, 0, 0]
([0, 0, 0],)

Such an array may be indexed by the field name, which returns another array with scalar values and additional dimensions:

>>> v['v'].dtype
dtype('uint8')
>>> v['v'].shape
(100, 100, 10, 1, 3)

Both arrays share their memory with the aims volume.

See also

Precisions about aims / numpy bindings

Header

Volumes also store a header which can contain various information (including sizes and voxel sizes). The header is a dictionary-like generic object (Object) which can be accessed by the header() method. This header object also has a read-write access with some restrictions inherent to the Object mechanism. It will be saved with the volume contents when the volume is saved on disk.

Volumes support a number of arithmetic operators like +, - etc. when the operands types and sizes match: for instance:

>>> # V1 and V2 are two volumes
>>> V3 = V1 + V2  # adds two volumes
>>> V2 -= V1
>>> V3 = V1 + 3   # adds 3 to aceh voxel
>>> V3 = V1 * V2  # itemwise multiplication

Some type conversions can be performed on volumes, for istance to convert a Volume_S16 to a Volume_FLOAT. The simplest, to convert to another data type, is to use the astype() method.

To convert a volume into diffent structure types, such as Buckets, use the converter classes Converter_<type1>_<type2> and ShallowConverter_<type1>_<type2> with <type1> and <type2> being volume or other object types: for instance Converter_Volume_S16_Volume_FLOAT. The converter can also be called using type arguments:

>>> vol1 = aims.AimsData('S16', 100, 100, 10)
>>> c = aims.Converter(intype=vol1, outtype='BucketMap_VOID')
>>> vol2 = c(vol1)

Volume from a numpy array

It is also possible to build a Volume from a numpy array:

>>> v = aims.Volume(numpy.zeros((100, 100, 10)))

Note that passing a 1D numpy array of ints will build a volume mapping the array contents, whereas passing a python list or tuple of ints will interpret the list as a shape for the volume:

>>> v = aims.Volume(numpy.array([100, 100, 10]).astype('int32'))
>>> print(v.getSize())
[ 3, 1, 1, 1 ]
>>> print(v.np)
[100 100  10]
>>> v = aims.Volume([100, 100, 10])
>>> print(v.getSize())
[ 100, 100, 10, 1 ]

Array ordering:

In pyaims <= 5.0.x the Volume classes were only working with the X axis (the first) being contiguous, and, for numpy, should be interpreted as “Fortran-contiguous”. So to convert a numpy array into a Volume and keep the same axes ordering, you had to convert it to Fortran order first:

>>> v = aims.Volume(numpy.zeros((2, 3, 4, dtype='int32')))
# v.getSize() used to return [4, 3, 2, 1]
>>> v = aims.Volume(np.asfortranarray(numpy.zeros((2, 3, 4), dtype='int32')))
>>> print(v.getSize())
[2, 3, 4, 1]

In pyaims 5.1 this limitation is gone, you can omit the fortran order conversion. Strides are taken into account in the C++ volume. But you have to be careful with such volumes as many C++ programs assume internally that the X axis is contiguous in memory, which is not true in this situation. These programs and functions may not work, crash, or produce incorrect results when used with non-contiguous X axis volumes.

class Position4Di

Bases: wrapper

4 ints for position or size, used for Volume views.

all()

allocatorContext()

any()

arraydata()

Note

arraydata() returns a numpy array to the internal memory block, with “inverted” shape and strides.

WARNING: this is an obsolete method, which behaviour has changed. Most of the time you need numpy.asarray(volume), or more simply: volume.np, which actually provides an array with the same indices ordering. Here it is a transposed one.

Given the internal ordering of Aims Volumes, the resulting numpy array is indexed as [t][z][y][x]. This order corresponds to the numpy “fortran” order: order='F' If you need the inverse, more natural, [x][y][z][t] ordering, use the following:

>>> volarray = volume.np

or:

>>> volarray = numpy.array(volume, copy=False)

or:

>>> volarray = numpy.asarray(volume)

Using arraydata(), as the indices are reversed, if you do something like:

vol2 = aims.Volume(vol.arraydata())

You will build a transposed volume.

astype(dtype, copy=False)

Easy conversion method for volumes. Works in a similar was as numpy arrays astype() methods, except that the “copy” parameter defaults to False.

Parameters:

• dtype (string or type object) – may be a volume or voxel type, specified either as a type oject (int, aims.Volume_S32, numpy.int16), or as a string (“S16”…).

• copy (bool) – if False, a ShallowConverter will be used: if dtype matches the current volume type, a shared reference to self will be returned. Otherwise a new copy will be returned.

Return type:

A volume of the converted type

at(posx, posy=0, posz=0, post=0)

Returns the volume value for the selected voxel.

at(posx1, posx2, posx3, posx4, posx5, posx6=0, posx7=0, posx8=0)

Returns the volume value for the selected voxel.

at(vector_int)

Returns the volume value for the selected voxel.

checkResize()

copyHeaderFrom()

fill(value)

Fill Volume_HSV using the given value.

fillBorder(value)

Fill the surrounding of the volume view in the reference volume (if any) using the given value.

fromObject()

getBorders()

getSize()

Number of voxels in each dimension (list of 4 ints)

getSizeT()

getSizeX()

getSizeY()

getSizeZ()

getStrides()

getVoxelSize()

Voxel sizes in mm (list of 4 floats)

header()

The header contains all meta-data.

max()

min()

property np

The np property is a shortcut to the __array__ method. Thus:

something.np

is a handier equivalent to:

numpy.asarray(something)

posInRefVolume()

If the volume is a view into another (larger) one, this returns the position in “parent” one.

refVolume()

If the volume is a view into another (larger) one, this returns the “parent” one.

setPosInRefVolume()

Set position in parent volume

setValue(value, x, y=0, z=0, t=0)

Set the voxel value at the given position.

setValue(value, [x1, x2, x3, x4, x5, x6…])

Set the voxel value at the given position.

setVoxelSize(vs_list)

setVoxelSize(vx, vy=1., vz=1., vt=1.) → None

Set voxel sizes in mm (list of at least 4 floats)

property shape

value(posx, posy=0, posz=0, post=0)

value is an alias to at(): returns the volume value for the selected voxel.

class soma.aims.Volume_POINT3DF(*args)

Bases: RCObject

Generalities

The various Volume_<type> classes are bindings to the C++ template classes carto::Volume. It represents a 4D volume (1D to 4D, actually) storing a specific type of data: for instance S16 is signed 16 bit short ints, FLOAT is 32 bit floats, etc.

Volumes are read and written using the Reader and Writer classes, which are in turn used by the simple read() and write() functions.

A volume of a given type can be built either using its specialized class constructor, or the general Volume() function which can take a voxel type in its arguments: the following are equivalent:

>>> v = aims.Volume_S16(100, 100, 10)
>>> v = aims.Volume('S16', 100, 100, 10)
>>> v = aims.Volume(100, 100, 10, dtype='S16')
>>> v = aims.Volume([100, 100, 10], dtype='S16')
>>> import numpy
>>> v = aims.Volume(numpy.int16, 100, 100, 10)

Numpy arrays and volumes

A volume is an array of voxels, which can be accessed via the at() method. For standard numeric types, it is also possible to get the voxels array as a numpy array, using the __array__() method, or more conveniently, numpy.asarray(volume) or numpy.array(volume, copy=False). In aims >= 5.0.2, a more concise shortcut is also available: volume.np (this is available on all types providing numpy bindings actually).

The array returned is a reference to the actual data block, so any modification to its contents also affects the Volume contents, so it is generally an easy way of manipulating volume voxels because all the power of the numpy module can be used on Volumes. The obsoloete arraydata() method used to return a numpy array just like it is in memory, that is a 4D (or more) array generally indexed by [t][z][y][x] (but it depands how it has been built), which is generally not what you like and is not consistent with AIMS indexing. Contrarily, using volume.np sets strides in the returned numpy array, so that indexing is in the “normal” order [x][y][z][t], while still sharing the same memory block. The Volume object now also wraps the numpy accessors to the volume object itself, so that volume[x, y, z, t] is the same as nupmy.asarray(volume)[x, y, z, t].

new in PyAims 4.7

Since PyAims 4.7 the numpy arrays bindings have notably improved, and are now able to bind arrays to voxels types which are not scalar numeric types. Volumes of RGB, RGBA, HSV, or Point3df now have numpy bindings. The bound object have generally a “numpy struct” binding, that is not the usual C++/python object binding, but instead a structure managed by numpy which also supports indexing. For most objects we are using, they also have an array stucture (a RGB is an array with 3 int8 items), and are bound under a sturcture with a unique field, named “v” (for “vector”):

>>> v = aims.Volume('RGB', 100, 100, 10)
>>> v[0, 0, 0, 0]
([0, 0, 0],)

Such an array may be indexed by the field name, which returns another array with scalar values and additional dimensions:

>>> v['v'].dtype
dtype('uint8')
>>> v['v'].shape
(100, 100, 10, 1, 3)

Both arrays share their memory with the aims volume.

See also

Precisions about aims / numpy bindings

Header

Volumes also store a header which can contain various information (including sizes and voxel sizes). The header is a dictionary-like generic object (Object) which can be accessed by the header() method. This header object also has a read-write access with some restrictions inherent to the Object mechanism. It will be saved with the volume contents when the volume is saved on disk.

Volumes support a number of arithmetic operators like +, - etc. when the operands types and sizes match: for instance:

>>> # V1 and V2 are two volumes
>>> V3 = V1 + V2  # adds two volumes
>>> V2 -= V1
>>> V3 = V1 + 3   # adds 3 to aceh voxel
>>> V3 = V1 * V2  # itemwise multiplication

Some type conversions can be performed on volumes, for istance to convert a Volume_S16 to a Volume_FLOAT. The simplest, to convert to another data type, is to use the astype() method.

To convert a volume into diffent structure types, such as Buckets, use the converter classes Converter_<type1>_<type2> and ShallowConverter_<type1>_<type2> with <type1> and <type2> being volume or other object types: for instance Converter_Volume_S16_Volume_FLOAT. The converter can also be called using type arguments:

>>> vol1 = aims.AimsData('S16', 100, 100, 10)
>>> c = aims.Converter(intype=vol1, outtype='BucketMap_VOID')
>>> vol2 = c(vol1)

Volume from a numpy array

It is also possible to build a Volume from a numpy array:

>>> v = aims.Volume(numpy.zeros((100, 100, 10)))

Note that passing a 1D numpy array of ints will build a volume mapping the array contents, whereas passing a python list or tuple of ints will interpret the list as a shape for the volume:

>>> v = aims.Volume(numpy.array([100, 100, 10]).astype('int32'))
>>> print(v.getSize())
[ 3, 1, 1, 1 ]
>>> print(v.np)
[100 100  10]
>>> v = aims.Volume([100, 100, 10])
>>> print(v.getSize())
[ 100, 100, 10, 1 ]

Array ordering:

In pyaims <= 5.0.x the Volume classes were only working with the X axis (the first) being contiguous, and, for numpy, should be interpreted as “Fortran-contiguous”. So to convert a numpy array into a Volume and keep the same axes ordering, you had to convert it to Fortran order first:

>>> v = aims.Volume(numpy.zeros((2, 3, 4, dtype='int32')))
# v.getSize() used to return [4, 3, 2, 1]
>>> v = aims.Volume(np.asfortranarray(numpy.zeros((2, 3, 4), dtype='int32')))
>>> print(v.getSize())
[2, 3, 4, 1]

In pyaims 5.1 this limitation is gone, you can omit the fortran order conversion. Strides are taken into account in the C++ volume. But you have to be careful with such volumes as many C++ programs assume internally that the X axis is contiguous in memory, which is not true in this situation. These programs and functions may not work, crash, or produce incorrect results when used with non-contiguous X axis volumes.

class Position4Di

Bases: wrapper

4 ints for position or size, used for Volume views.

all()

allocatorContext()

any()

arraydata()

Note

arraydata() returns a numpy array to the internal memory block, with “inverted” shape and strides.

WARNING: this is an obsolete method, which behaviour has changed. Most of the time you need numpy.asarray(volume), or more simply: volume.np, which actually provides an array with the same indices ordering. Here it is a transposed one.

Given the internal ordering of Aims Volumes, the resulting numpy array is indexed as [t][z][y][x]. This order corresponds to the numpy “fortran” order: order='F' If you need the inverse, more natural, [x][y][z][t] ordering, use the following:

>>> volarray = volume.np

or:

>>> volarray = numpy.array(volume, copy=False)

or:

>>> volarray = numpy.asarray(volume)

Using arraydata(), as the indices are reversed, if you do something like:

vol2 = aims.Volume(vol.arraydata())

You will build a transposed volume.

astype(dtype, copy=False)

Easy conversion method for volumes. Works in a similar was as numpy arrays astype() methods, except that the “copy” parameter defaults to False.

Parameters:

• dtype (string or type object) – may be a volume or voxel type, specified either as a type oject (int, aims.Volume_S32, numpy.int16), or as a string (“S16”…).

• copy (bool) – if False, a ShallowConverter will be used: if dtype matches the current volume type, a shared reference to self will be returned. Otherwise a new copy will be returned.

Return type:

A volume of the converted type

at(posx, posy=0, posz=0, post=0)

Returns the volume value for the selected voxel.

at(posx1, posx2, posx3, posx4, posx5, posx6=0, posx7=0, posx8=0)

Returns the volume value for the selected voxel.

at(vector_int)

Returns the volume value for the selected voxel.

checkResize()

copyHeaderFrom()

fill(value)

Fill Volume_POINT3DF using the given value.

fillBorder(value)

Fill the surrounding of the volume view in the reference volume (if any) using the given value.

fromObject()

getBorders()

getSize()

Number of voxels in each dimension (list of 4 ints)

getSizeT()

getSizeX()

getSizeY()

getSizeZ()

getStrides()

getVoxelSize()

Voxel sizes in mm (list of 4 floats)

header()

The header contains all meta-data.

max()

min()

property np

The np property is a shortcut to the __array__ method. Thus:

something.np

is a handier equivalent to:

numpy.asarray(something)

posInRefVolume()

If the volume is a view into another (larger) one, this returns the position in “parent” one.

refVolume()

If the volume is a view into another (larger) one, this returns the “parent” one.

setPosInRefVolume()

Set position in parent volume

setValue(value, x, y=0, z=0, t=0)

Set the voxel value at the given position.

setValue(value, [x1, x2, x3, x4, x5, x6…])

Set the voxel value at the given position.

setVoxelSize(vs_list)

setVoxelSize(vx, vy=1., vz=1., vt=1.) → None

Set voxel sizes in mm (list of at least 4 floats)

property shape

value(posx, posy=0, posz=0, post=0)

value is an alias to at(): returns the volume value for the selected voxel.

class soma.aims.Volume_RGB(*args)

Bases: RCObject

Generalities

The various Volume_<type> classes are bindings to the C++ template classes carto::Volume. It represents a 4D volume (1D to 4D, actually) storing a specific type of data: for instance S16 is signed 16 bit short ints, FLOAT is 32 bit floats, etc.

Volumes are read and written using the Reader and Writer classes, which are in turn used by the simple read() and write() functions.

A volume of a given type can be built either using its specialized class constructor, or the general Volume() function which can take a voxel type in its arguments: the following are equivalent:

>>> v = aims.Volume_S16(100, 100, 10)
>>> v = aims.Volume('S16', 100, 100, 10)
>>> v = aims.Volume(100, 100, 10, dtype='S16')
>>> v = aims.Volume([100, 100, 10], dtype='S16')
>>> import numpy
>>> v = aims.Volume(numpy.int16, 100, 100, 10)

Numpy arrays and volumes

A volume is an array of voxels, which can be accessed via the at() method. For standard numeric types, it is also possible to get the voxels array as a numpy array, using the __array__() method, or more conveniently, numpy.asarray(volume) or numpy.array(volume, copy=False). In aims >= 5.0.2, a more concise shortcut is also available: volume.np (this is available on all types providing numpy bindings actually).

The array returned is a reference to the actual data block, so any modification to its contents also affects the Volume contents, so it is generally an easy way of manipulating volume voxels because all the power of the numpy module can be used on Volumes. The obsoloete arraydata() method used to return a numpy array just like it is in memory, that is a 4D (or more) array generally indexed by [t][z][y][x] (but it depands how it has been built), which is generally not what you like and is not consistent with AIMS indexing. Contrarily, using volume.np sets strides in the returned numpy array, so that indexing is in the “normal” order [x][y][z][t], while still sharing the same memory block. The Volume object now also wraps the numpy accessors to the volume object itself, so that volume[x, y, z, t] is the same as nupmy.asarray(volume)[x, y, z, t].

new in PyAims 4.7

Since PyAims 4.7 the numpy arrays bindings have notably improved, and are now able to bind arrays to voxels types which are not scalar numeric types. Volumes of RGB, RGBA, HSV, or Point3df now have numpy bindings. The bound object have generally a “numpy struct” binding, that is not the usual C++/python object binding, but instead a structure managed by numpy which also supports indexing. For most objects we are using, they also have an array stucture (a RGB is an array with 3 int8 items), and are bound under a sturcture with a unique field, named “v” (for “vector”):

>>> v = aims.Volume('RGB', 100, 100, 10)
>>> v[0, 0, 0, 0]
([0, 0, 0],)

Such an array may be indexed by the field name, which returns another array with scalar values and additional dimensions:

>>> v['v'].dtype
dtype('uint8')
>>> v['v'].shape
(100, 100, 10, 1, 3)

Both arrays share their memory with the aims volume.

See also

Precisions about aims / numpy bindings

Header

Volumes also store a header which can contain various information (including sizes and voxel sizes). The header is a dictionary-like generic object (Object) which can be accessed by the header() method. This header object also has a read-write access with some restrictions inherent to the Object mechanism. It will be saved with the volume contents when the volume is saved on disk.

Volumes support a number of arithmetic operators like +, - etc. when the operands types and sizes match: for instance:

>>> # V1 and V2 are two volumes
>>> V3 = V1 + V2  # adds two volumes
>>> V2 -= V1
>>> V3 = V1 + 3   # adds 3 to aceh voxel
>>> V3 = V1 * V2  # itemwise multiplication

Some type conversions can be performed on volumes, for istance to convert a Volume_S16 to a Volume_FLOAT. The simplest, to convert to another data type, is to use the astype() method.

To convert a volume into diffent structure types, such as Buckets, use the converter classes Converter_<type1>_<type2> and ShallowConverter_<type1>_<type2> with <type1> and <type2> being volume or other object types: for instance Converter_Volume_S16_Volume_FLOAT. The converter can also be called using type arguments:

>>> vol1 = aims.AimsData('S16', 100, 100, 10)
>>> c = aims.Converter(intype=vol1, outtype='BucketMap_VOID')
>>> vol2 = c(vol1)

Volume from a numpy array

It is also possible to build a Volume from a numpy array:

>>> v = aims.Volume(numpy.zeros((100, 100, 10)))

Note that passing a 1D numpy array of ints will build a volume mapping the array contents, whereas passing a python list or tuple of ints will interpret the list as a shape for the volume:

>>> v = aims.Volume(numpy.array([100, 100, 10]).astype('int32'))
>>> print(v.getSize())
[ 3, 1, 1, 1 ]
>>> print(v.np)
[100 100  10]
>>> v = aims.Volume([100, 100, 10])
>>> print(v.getSize())
[ 100, 100, 10, 1 ]

Array ordering:

In pyaims <= 5.0.x the Volume classes were only working with the X axis (the first) being contiguous, and, for numpy, should be interpreted as “Fortran-contiguous”. So to convert a numpy array into a Volume and keep the same axes ordering, you had to convert it to Fortran order first:

>>> v = aims.Volume(numpy.zeros((2, 3, 4, dtype='int32')))
# v.getSize() used to return [4, 3, 2, 1]
>>> v = aims.Volume(np.asfortranarray(numpy.zeros((2, 3, 4), dtype='int32')))
>>> print(v.getSize())
[2, 3, 4, 1]

In pyaims 5.1 this limitation is gone, you can omit the fortran order conversion. Strides are taken into account in the C++ volume. But you have to be careful with such volumes as many C++ programs assume internally that the X axis is contiguous in memory, which is not true in this situation. These programs and functions may not work, crash, or produce incorrect results when used with non-contiguous X axis volumes.

class Position4Di

Bases: wrapper

4 ints for position or size, used for Volume views.

all()

allocatorContext()

any()

arraydata()

Note

arraydata() returns a numpy array to the internal memory block, with “inverted” shape and strides.

WARNING: this is an obsolete method, which behaviour has changed. Most of the time you need numpy.asarray(volume), or more simply: volume.np, which actually provides an array with the same indices ordering. Here it is a transposed one.

Given the internal ordering of Aims Volumes, the resulting numpy array is indexed as [t][z][y][x]. This order corresponds to the numpy “fortran” order: order='F' If you need the inverse, more natural, [x][y][z][t] ordering, use the following:

>>> volarray = volume.np

or:

>>> volarray = numpy.array(volume, copy=False)

or:

>>> volarray = numpy.asarray(volume)

Using arraydata(), as the indices are reversed, if you do something like:

vol2 = aims.Volume(vol.arraydata())

You will build a transposed volume.

astype(dtype, copy=False)

Easy conversion method for volumes. Works in a similar was as numpy arrays astype() methods, except that the “copy” parameter defaults to False.

Parameters:

• dtype (string or type object) – may be a volume or voxel type, specified either as a type oject (int, aims.Volume_S32, numpy.int16), or as a string (“S16”…).

• copy (bool) – if False, a ShallowConverter will be used: if dtype matches the current volume type, a shared reference to self will be returned. Otherwise a new copy will be returned.

Return type:

A volume of the converted type

at(posx, posy=0, posz=0, post=0)

Returns the volume value for the selected voxel.

at(posx1, posx2, posx3, posx4, posx5, posx6=0, posx7=0, posx8=0)

Returns the volume value for the selected voxel.

at(vector_int)

Returns the volume value for the selected voxel.

checkResize()

copyHeaderFrom()

fill(value)

Fill Volume_RGB using the given value.

fillBorder(value)

Fill the surrounding of the volume view in the reference volume (if any) using the given value.

fromObject()

getBorders()

getSize()

Number of voxels in each dimension (list of 4 ints)

getSizeT()

getSizeX()

getSizeY()

getSizeZ()

getStrides()

getVoxelSize()

Voxel sizes in mm (list of 4 floats)

header()

The header contains all meta-data.

max()

min()

property np

The np property is a shortcut to the __array__ method. Thus:

something.np

is a handier equivalent to:

numpy.asarray(something)

posInRefVolume()

If the volume is a view into another (larger) one, this returns the position in “parent” one.

refVolume()

If the volume is a view into another (larger) one, this returns the “parent” one.

setPosInRefVolume()

Set position in parent volume

setValue(value, x, y=0, z=0, t=0)

Set the voxel value at the given position.

setValue(value, [x1, x2, x3, x4, x5, x6…])

Set the voxel value at the given position.

setVoxelSize(vs_list)

setVoxelSize(vx, vy=1., vz=1., vt=1.) → None

Set voxel sizes in mm (list of at least 4 floats)

property shape

value(posx, posy=0, posz=0, post=0)

value is an alias to at(): returns the volume value for the selected voxel.

class soma.aims.Volume_RGBA(*args)

Bases: RCObject

Generalities

The various Volume_<type> classes are bindings to the C++ template classes carto::Volume. It represents a 4D volume (1D to 4D, actually) storing a specific type of data: for instance S16 is signed 16 bit short ints, FLOAT is 32 bit floats, etc.

Volumes are read and written using the Reader and Writer classes, which are in turn used by the simple read() and write() functions.

A volume of a given type can be built either using its specialized class constructor, or the general Volume() function which can take a voxel type in its arguments: the following are equivalent:

>>> v = aims.Volume_S16(100, 100, 10)
>>> v = aims.Volume('S16', 100, 100, 10)
>>> v = aims.Volume(100, 100, 10, dtype='S16')
>>> v = aims.Volume([100, 100, 10], dtype='S16')
>>> import numpy
>>> v = aims.Volume(numpy.int16, 100, 100, 10)

Numpy arrays and volumes

A volume is an array of voxels, which can be accessed via the at() method. For standard numeric types, it is also possible to get the voxels array as a numpy array, using the __array__() method, or more conveniently, numpy.asarray(volume) or numpy.array(volume, copy=False). In aims >= 5.0.2, a more concise shortcut is also available: volume.np (this is available on all types providing numpy bindings actually).

The array returned is a reference to the actual data block, so any modification to its contents also affects the Volume contents, so it is generally an easy way of manipulating volume voxels because all the power of the numpy module can be used on Volumes. The obsoloete arraydata() method used to return a numpy array just like it is in memory, that is a 4D (or more) array generally indexed by [t][z][y][x] (but it depands how it has been built), which is generally not what you like and is not consistent with AIMS indexing. Contrarily, using volume.np sets strides in the returned numpy array, so that indexing is in the “normal” order [x][y][z][t], while still sharing the same memory block. The Volume object now also wraps the numpy accessors to the volume object itself, so that volume[x, y, z, t] is the same as nupmy.asarray(volume)[x, y, z, t].

new in PyAims 4.7

Since PyAims 4.7 the numpy arrays bindings have notably improved, and are now able to bind arrays to voxels types which are not scalar numeric types. Volumes of RGB, RGBA, HSV, or Point3df now have numpy bindings. The bound object have generally a “numpy struct” binding, that is not the usual C++/python object binding, but instead a structure managed by numpy which also supports indexing. For most objects we are using, they also have an array stucture (a RGB is an array with 3 int8 items), and are bound under a sturcture with a unique field, named “v” (for “vector”):

>>> v = aims.Volume('RGB', 100, 100, 10)
>>> v[0, 0, 0, 0]
([0, 0, 0],)

Such an array may be indexed by the field name, which returns another array with scalar values and additional dimensions:

>>> v['v'].dtype
dtype('uint8')
>>> v['v'].shape
(100, 100, 10, 1, 3)

Both arrays share their memory with the aims volume.

See also

Precisions about aims / numpy bindings

Header

Volumes also store a header which can contain various information (including sizes and voxel sizes). The header is a dictionary-like generic object (Object) which can be accessed by the header() method. This header object also has a read-write access with some restrictions inherent to the Object mechanism. It will be saved with the volume contents when the volume is saved on disk.

Volumes support a number of arithmetic operators like +, - etc. when the operands types and sizes match: for instance:

>>> # V1 and V2 are two volumes
>>> V3 = V1 + V2  # adds two volumes
>>> V2 -= V1
>>> V3 = V1 + 3   # adds 3 to aceh voxel
>>> V3 = V1 * V2  # itemwise multiplication

Some type conversions can be performed on volumes, for istance to convert a Volume_S16 to a Volume_FLOAT. The simplest, to convert to another data type, is to use the astype() method.

To convert a volume into diffent structure types, such as Buckets, use the converter classes Converter_<type1>_<type2> and ShallowConverter_<type1>_<type2> with <type1> and <type2> being volume or other object types: for instance Converter_Volume_S16_Volume_FLOAT. The converter can also be called using type arguments:

>>> vol1 = aims.AimsData('S16', 100, 100, 10)
>>> c = aims.Converter(intype=vol1, outtype='BucketMap_VOID')
>>> vol2 = c(vol1)

Volume from a numpy array

It is also possible to build a Volume from a numpy array:

>>> v = aims.Volume(numpy.zeros((100, 100, 10)))

Note that passing a 1D numpy array of ints will build a volume mapping the array contents, whereas passing a python list or tuple of ints will interpret the list as a shape for the volume:

>>> v = aims.Volume(numpy.array([100, 100, 10]).astype('int32'))
>>> print(v.getSize())
[ 3, 1, 1, 1 ]
>>> print(v.np)
[100 100  10]
>>> v = aims.Volume([100, 100, 10])
>>> print(v.getSize())
[ 100, 100, 10, 1 ]

Array ordering:

In pyaims <= 5.0.x the Volume classes were only working with the X axis (the first) being contiguous, and, for numpy, should be interpreted as “Fortran-contiguous”. So to convert a numpy array into a Volume and keep the same axes ordering, you had to convert it to Fortran order first:

>>> v = aims.Volume(numpy.zeros((2, 3, 4, dtype='int32')))
# v.getSize() used to return [4, 3, 2, 1]
>>> v = aims.Volume(np.asfortranarray(numpy.zeros((2, 3, 4), dtype='int32')))
>>> print(v.getSize())
[2, 3, 4, 1]

In pyaims 5.1 this limitation is gone, you can omit the fortran order conversion. Strides are taken into account in the C++ volume. But you have to be careful with such volumes as many C++ programs assume internally that the X axis is contiguous in memory, which is not true in this situation. These programs and functions may not work, crash, or produce incorrect results when used with non-contiguous X axis volumes.

class Position4Di

Bases: wrapper

4 ints for position or size, used for Volume views.

all()

allocatorContext()

any()

arraydata()

Note

arraydata() returns a numpy array to the internal memory block, with “inverted” shape and strides.

WARNING: this is an obsolete method, which behaviour has changed. Most of the time you need numpy.asarray(volume), or more simply: volume.np, which actually provides an array with the same indices ordering. Here it is a transposed one.

Given the internal ordering of Aims Volumes, the resulting numpy array is indexed as [t][z][y][x]. This order corresponds to the numpy “fortran” order: order='F' If you need the inverse, more natural, [x][y][z][t] ordering, use the following:

>>> volarray = volume.np

or:

>>> volarray = numpy.array(volume, copy=False)

or:

>>> volarray = numpy.asarray(volume)

Using arraydata(), as the indices are reversed, if you do something like:

vol2 = aims.Volume(vol.arraydata())

You will build a transposed volume.

astype(dtype, copy=False)

Easy conversion method for volumes. Works in a similar was as numpy arrays astype() methods, except that the “copy” parameter defaults to False.

Parameters:

• dtype (string or type object) – may be a volume or voxel type, specified either as a type oject (int, aims.Volume_S32, numpy.int16), or as a string (“S16”…).

• copy (bool) – if False, a ShallowConverter will be used: if dtype matches the current volume type, a shared reference to self will be returned. Otherwise a new copy will be returned.

Return type:

A volume of the converted type

at(posx, posy=0, posz=0, post=0)

Returns the volume value for the selected voxel.

at(posx1, posx2, posx3, posx4, posx5, posx6=0, posx7=0, posx8=0)

Returns the volume value for the selected voxel.

at(vector_int)

Returns the volume value for the selected voxel.

checkResize()

copyHeaderFrom()

fill(value)

Fill Volume_RGBA using the given value.

fillBorder(value)

Fill the surrounding of the volume view in the reference volume (if any) using the given value.

fromObject()

getBorders()

getSize()

Number of voxels in each dimension (list of 4 ints)

getSizeT()

getSizeX()

getSizeY()

getSizeZ()

getStrides()

getVoxelSize()

Voxel sizes in mm (list of 4 floats)

header()

The header contains all meta-data.

max()

min()

property np

The np property is a shortcut to the __array__ method. Thus:

something.np

is a handier equivalent to:

numpy.asarray(something)

posInRefVolume()

If the volume is a view into another (larger) one, this returns the position in “parent” one.

refVolume()

If the volume is a view into another (larger) one, this returns the “parent” one.

setPosInRefVolume()

Set position in parent volume

setValue(value, x, y=0, z=0, t=0)

Set the voxel value at the given position.

setValue(value, [x1, x2, x3, x4, x5, x6…])

Set the voxel value at the given position.

setVoxelSize(vs_list)

setVoxelSize(vx, vy=1., vz=1., vt=1.) → None

Set voxel sizes in mm (list of at least 4 floats)

property shape

value(posx, posy=0, posz=0, post=0)

value is an alias to at(): returns the volume value for the selected voxel.

class soma.aims.Volume_S16(*args)

Bases: RCObject

Generalities

The various Volume_<type> classes are bindings to the C++ template classes carto::Volume. It represents a 4D volume (1D to 4D, actually) storing a specific type of data: for instance S16 is signed 16 bit short ints, FLOAT is 32 bit floats, etc.

Volumes are read and written using the Reader and Writer classes, which are in turn used by the simple read() and write() functions.

A volume of a given type can be built either using its specialized class constructor, or the general Volume() function which can take a voxel type in its arguments: the following are equivalent:

>>> v = aims.Volume_S16(100, 100, 10)
>>> v = aims.Volume('S16', 100, 100, 10)
>>> v = aims.Volume(100, 100, 10, dtype='S16')
>>> v = aims.Volume([100, 100, 10], dtype='S16')
>>> import numpy
>>> v = aims.Volume(numpy.int16, 100, 100, 10)

Numpy arrays and volumes

A volume is an array of voxels, which can be accessed via the at() method. For standard numeric types, it is also possible to get the voxels array as a numpy array, using the __array__() method, or more conveniently, numpy.asarray(volume) or numpy.array(volume, copy=False). In aims >= 5.0.2, a more concise shortcut is also available: volume.np (this is available on all types providing numpy bindings actually).

The array returned is a reference to the actual data block, so any modification to its contents also affects the Volume contents, so it is generally an easy way of manipulating volume voxels because all the power of the numpy module can be used on Volumes. The obsoloete arraydata() method used to return a numpy array just like it is in memory, that is a 4D (or more) array generally indexed by [t][z][y][x] (but it depands how it has been built), which is generally not what you like and is not consistent with AIMS indexing. Contrarily, using volume.np sets strides in the returned numpy array, so that indexing is in the “normal” order [x][y][z][t], while still sharing the same memory block. The Volume object now also wraps the numpy accessors to the volume object itself, so that volume[x, y, z, t] is the same as nupmy.asarray(volume)[x, y, z, t].

new in PyAims 4.7

Since PyAims 4.7 the numpy arrays bindings have notably improved, and are now able to bind arrays to voxels types which are not scalar numeric types. Volumes of RGB, RGBA, HSV, or Point3df now have numpy bindings. The bound object have generally a “numpy struct” binding, that is not the usual C++/python object binding, but instead a structure managed by numpy which also supports indexing. For most objects we are using, they also have an array stucture (a RGB is an array with 3 int8 items), and are bound under a sturcture with a unique field, named “v” (for “vector”):

>>> v = aims.Volume('RGB', 100, 100, 10)
>>> v[0, 0, 0, 0]
([0, 0, 0],)

Such an array may be indexed by the field name, which returns another array with scalar values and additional dimensions:

>>> v['v'].dtype
dtype('uint8')
>>> v['v'].shape
(100, 100, 10, 1, 3)

Both arrays share their memory with the aims volume.

See also

Precisions about aims / numpy bindings

Header

Volumes also store a header which can contain various information (including sizes and voxel sizes). The header is a dictionary-like generic object (Object) which can be accessed by the header() method. This header object also has a read-write access with some restrictions inherent to the Object mechanism. It will be saved with the volume contents when the volume is saved on disk.

Volumes support a number of arithmetic operators like +, - etc. when the operands types and sizes match: for instance:

>>> # V1 and V2 are two volumes
>>> V3 = V1 + V2  # adds two volumes
>>> V2 -= V1
>>> V3 = V1 + 3   # adds 3 to aceh voxel
>>> V3 = V1 * V2  # itemwise multiplication

Some type conversions can be performed on volumes, for istance to convert a Volume_S16 to a Volume_FLOAT. The simplest, to convert to another data type, is to use the astype() method.

To convert a volume into diffent structure types, such as Buckets, use the converter classes Converter_<type1>_<type2> and ShallowConverter_<type1>_<type2> with <type1> and <type2> being volume or other object types: for instance Converter_Volume_S16_Volume_FLOAT. The converter can also be called using type arguments:

>>> vol1 = aims.AimsData('S16', 100, 100, 10)
>>> c = aims.Converter(intype=vol1, outtype='BucketMap_VOID')
>>> vol2 = c(vol1)

Volume from a numpy array

It is also possible to build a Volume from a numpy array:

>>> v = aims.Volume(numpy.zeros((100, 100, 10)))

Note that passing a 1D numpy array of ints will build a volume mapping the array contents, whereas passing a python list or tuple of ints will interpret the list as a shape for the volume:

>>> v = aims.Volume(numpy.array([100, 100, 10]).astype('int32'))
>>> print(v.getSize())
[ 3, 1, 1, 1 ]
>>> print(v.np)
[100 100  10]
>>> v = aims.Volume([100, 100, 10])
>>> print(v.getSize())
[ 100, 100, 10, 1 ]

Array ordering:

In pyaims <= 5.0.x the Volume classes were only working with the X axis (the first) being contiguous, and, for numpy, should be interpreted as “Fortran-contiguous”. So to convert a numpy array into a Volume and keep the same axes ordering, you had to convert it to Fortran order first:

>>> v = aims.Volume(numpy.zeros((2, 3, 4, dtype='int32')))
# v.getSize() used to return [4, 3, 2, 1]
>>> v = aims.Volume(np.asfortranarray(numpy.zeros((2, 3, 4), dtype='int32')))
>>> print(v.getSize())
[2, 3, 4, 1]

In pyaims 5.1 this limitation is gone, you can omit the fortran order conversion. Strides are taken into account in the C++ volume. But you have to be careful with such volumes as many C++ programs assume internally that the X axis is contiguous in memory, which is not true in this situation. These programs and functions may not work, crash, or produce incorrect results when used with non-contiguous X axis volumes.

class Position4Di

Bases: wrapper

4 ints for position or size, used for Volume views.

all()

allocatorContext()

any()

arraydata()

Note

arraydata() returns a numpy array to the internal memory block, with “inverted” shape and strides.

WARNING: this is an obsolete method, which behaviour has changed. Most of the time you need numpy.asarray(volume), or more simply: volume.np, which actually provides an array with the same indices ordering. Here it is a transposed one.

Given the internal ordering of Aims Volumes, the resulting numpy array is indexed as [t][z][y][x]. This order corresponds to the numpy “fortran” order: order='F' If you need the inverse, more natural, [x][y][z][t] ordering, use the following:

>>> volarray = volume.np

or:

>>> volarray = numpy.array(volume, copy=False)

or:

>>> volarray = numpy.asarray(volume)

Using arraydata(), as the indices are reversed, if you do something like:

vol2 = aims.Volume(vol.arraydata())

You will build a transposed volume.

astype(dtype, copy=False)

Easy conversion method for volumes. Works in a similar was as numpy arrays astype() methods, except that the “copy” parameter defaults to False.

Parameters:

• dtype (string or type object) – may be a volume or voxel type, specified either as a type oject (int, aims.Volume_S32, numpy.int16), or as a string (“S16”…).

• copy (bool) – if False, a ShallowConverter will be used: if dtype matches the current volume type, a shared reference to self will be returned. Otherwise a new copy will be returned.

Return type:

A volume of the converted type

at(posx, posy=0, posz=0, post=0)

Returns the volume value for the selected voxel.

at(posx1, posx2, posx3, posx4, posx5, posx6=0, posx7=0, posx8=0)

Returns the volume value for the selected voxel.

at(vector_int)

Returns the volume value for the selected voxel.

checkResize()

copyHeaderFrom()

fill(value)

Fill Volume_S16 using the given value.

fillBorder(value)

Fill the surrounding of the volume view in the reference volume (if any) using the given value.

fromObject()

getBorders()

getSize()

Number of voxels in each dimension (list of 4 ints)

getSizeT()

getSizeX()

getSizeY()

getSizeZ()

getStrides()

getVoxelSize()

Voxel sizes in mm (list of 4 floats)

header()

The header contains all meta-data.

max()

min()

property np

The np property is a shortcut to the __array__ method. Thus:

something.np

is a handier equivalent to:

numpy.asarray(something)

posInRefVolume()

If the volume is a view into another (larger) one, this returns the position in “parent” one.

refVolume()

If the volume is a view into another (larger) one, this returns the “parent” one.

setPosInRefVolume()

Set position in parent volume

setValue(value, x, y=0, z=0, t=0)

Set the voxel value at the given position.

setValue(value, [x1, x2, x3, x4, x5, x6…])

Set the voxel value at the given position.

setVoxelSize(vs_list)

setVoxelSize(vx, vy=1., vz=1., vt=1.) → None

Set voxel sizes in mm (list of at least 4 floats)

property shape

value(posx, posy=0, posz=0, post=0)

value is an alias to at(): returns the volume value for the selected voxel.

class soma.aims.Volume_S32(*args)

Bases: RCObject

Generalities

The various Volume_<type> classes are bindings to the C++ template classes carto::Volume. It represents a 4D volume (1D to 4D, actually) storing a specific type of data: for instance S16 is signed 16 bit short ints, FLOAT is 32 bit floats, etc.

Volumes are read and written using the Reader and Writer classes, which are in turn used by the simple read() and write() functions.

A volume of a given type can be built either using its specialized class constructor, or the general Volume() function which can take a voxel type in its arguments: the following are equivalent:

>>> v = aims.Volume_S16(100, 100, 10)
>>> v = aims.Volume('S16', 100, 100, 10)
>>> v = aims.Volume(100, 100, 10, dtype='S16')
>>> v = aims.Volume([100, 100, 10], dtype='S16')
>>> import numpy
>>> v = aims.Volume(numpy.int16, 100, 100, 10)

Numpy arrays and volumes

A volume is an array of voxels, which can be accessed via the at() method. For standard numeric types, it is also possible to get the voxels array as a numpy array, using the __array__() method, or more conveniently, numpy.asarray(volume) or numpy.array(volume, copy=False). In aims >= 5.0.2, a more concise shortcut is also available: volume.np (this is available on all types providing numpy bindings actually).

The array returned is a reference to the actual data block, so any modification to its contents also affects the Volume contents, so it is generally an easy way of manipulating volume voxels because all the power of the numpy module can be used on Volumes. The obsoloete arraydata() method used to return a numpy array just like it is in memory, that is a 4D (or more) array generally indexed by [t][z][y][x] (but it depands how it has been built), which is generally not what you like and is not consistent with AIMS indexing. Contrarily, using volume.np sets strides in the returned numpy array, so that indexing is in the “normal” order [x][y][z][t], while still sharing the same memory block. The Volume object now also wraps the numpy accessors to the volume object itself, so that volume[x, y, z, t] is the same as nupmy.asarray(volume)[x, y, z, t].

new in PyAims 4.7

Since PyAims 4.7 the numpy arrays bindings have notably improved, and are now able to bind arrays to voxels types which are not scalar numeric types. Volumes of RGB, RGBA, HSV, or Point3df now have numpy bindings. The bound object have generally a “numpy struct” binding, that is not the usual C++/python object binding, but instead a structure managed by numpy which also supports indexing. For most objects we are using, they also have an array stucture (a RGB is an array with 3 int8 items), and are bound under a sturcture with a unique field, named “v” (for “vector”):

>>> v = aims.Volume('RGB', 100, 100, 10)
>>> v[0, 0, 0, 0]
([0, 0, 0],)

Such an array may be indexed by the field name, which returns another array with scalar values and additional dimensions:

>>> v['v'].dtype
dtype('uint8')
>>> v['v'].shape
(100, 100, 10, 1, 3)

Both arrays share their memory with the aims volume.

See also

Precisions about aims / numpy bindings

Header

Volumes also store a header which can contain various information (including sizes and voxel sizes). The header is a dictionary-like generic object (Object) which can be accessed by the header() method. This header object also has a read-write access with some restrictions inherent to the Object mechanism. It will be saved with the volume contents when the volume is saved on disk.

Volumes support a number of arithmetic operators like +, - etc. when the operands types and sizes match: for instance:

>>> # V1 and V2 are two volumes
>>> V3 = V1 + V2  # adds two volumes
>>> V2 -= V1
>>> V3 = V1 + 3   # adds 3 to aceh voxel
>>> V3 = V1 * V2  # itemwise multiplication

Some type conversions can be performed on volumes, for istance to convert a Volume_S16 to a Volume_FLOAT. The simplest, to convert to another data type, is to use the astype() method.

To convert a volume into diffent structure types, such as Buckets, use the converter classes Converter_<type1>_<type2> and ShallowConverter_<type1>_<type2> with <type1> and <type2> being volume or other object types: for instance Converter_Volume_S16_Volume_FLOAT. The converter can also be called using type arguments:

>>> vol1 = aims.AimsData('S16', 100, 100, 10)
>>> c = aims.Converter(intype=vol1, outtype='BucketMap_VOID')
>>> vol2 = c(vol1)

Volume from a numpy array

It is also possible to build a Volume from a numpy array:

>>> v = aims.Volume(numpy.zeros((100, 100, 10)))

Note that passing a 1D numpy array of ints will build a volume mapping the array contents, whereas passing a python list or tuple of ints will interpret the list as a shape for the volume:

>>> v = aims.Volume(numpy.array([100, 100, 10]).astype('int32'))
>>> print(v.getSize())
[ 3, 1, 1, 1 ]
>>> print(v.np)
[100 100  10]
>>> v = aims.Volume([100, 100, 10])
>>> print(v.getSize())
[ 100, 100, 10, 1 ]

Array ordering:

In pyaims <= 5.0.x the Volume classes were only working with the X axis (the first) being contiguous, and, for numpy, should be interpreted as “Fortran-contiguous”. So to convert a numpy array into a Volume and keep the same axes ordering, you had to convert it to Fortran order first:

>>> v = aims.Volume(numpy.zeros((2, 3, 4, dtype='int32')))
# v.getSize() used to return [4, 3, 2, 1]
>>> v = aims.Volume(np.asfortranarray(numpy.zeros((2, 3, 4), dtype='int32')))
>>> print(v.getSize())
[2, 3, 4, 1]

In pyaims 5.1 this limitation is gone, you can omit the fortran order conversion. Strides are taken into account in the C++ volume. But you have to be careful with such volumes as many C++ programs assume internally that the X axis is contiguous in memory, which is not true in this situation. These programs and functions may not work, crash, or produce incorrect results when used with non-contiguous X axis volumes.

class Position4Di

Bases: wrapper

4 ints for position or size, used for Volume views.

all()

allocatorContext()

any()

arraydata()

Note

arraydata() returns a numpy array to the internal memory block, with “inverted” shape and strides.

WARNING: this is an obsolete method, which behaviour has changed. Most of the time you need numpy.asarray(volume), or more simply: volume.np, which actually provides an array with the same indices ordering. Here it is a transposed one.

Given the internal ordering of Aims Volumes, the resulting numpy array is indexed as [t][z][y][x]. This order corresponds to the numpy “fortran” order: order='F' If you need the inverse, more natural, [x][y][z][t] ordering, use the following:

>>> volarray = volume.np

or:

>>> volarray = numpy.array(volume, copy=False)

or:

>>> volarray = numpy.asarray(volume)

Using arraydata(), as the indices are reversed, if you do something like:

vol2 = aims.Volume(vol.arraydata())

You will build a transposed volume.

astype(dtype, copy=False)

Easy conversion method for volumes. Works in a similar was as numpy arrays astype() methods, except that the “copy” parameter defaults to False.

Parameters:

• dtype (string or type object) – may be a volume or voxel type, specified either as a type oject (int, aims.Volume_S32, numpy.int16), or as a string (“S16”…).

• copy (bool) – if False, a ShallowConverter will be used: if dtype matches the current volume type, a shared reference to self will be returned. Otherwise a new copy will be returned.

Return type:

A volume of the converted type

at(posx, posy=0, posz=0, post=0)

Returns the volume value for the selected voxel.

at(posx1, posx2, posx3, posx4, posx5, posx6=0, posx7=0, posx8=0)

Returns the volume value for the selected voxel.

at(vector_int)

Returns the volume value for the selected voxel.

checkResize()

copyHeaderFrom()

fill(value)

Fill Volume_S32 using the given value.

fillBorder(value)

Fill the surrounding of the volume view in the reference volume (if any) using the given value.

fromObject()

getBorders()

getSize()

Number of voxels in each dimension (list of 4 ints)

getSizeT()

getSizeX()

getSizeY()

getSizeZ()

getStrides()

getVoxelSize()

Voxel sizes in mm (list of 4 floats)

header()

The header contains all meta-data.

max()

min()

property np

The np property is a shortcut to the __array__ method. Thus:

something.np

is a handier equivalent to:

numpy.asarray(something)

posInRefVolume()

If the volume is a view into another (larger) one, this returns the position in “parent” one.

refVolume()

If the volume is a view into another (larger) one, this returns the “parent” one.

setPosInRefVolume()

Set position in parent volume

setValue(value, x, y=0, z=0, t=0)

Set the voxel value at the given position.

setValue(value, [x1, x2, x3, x4, x5, x6…])

Set the voxel value at the given position.

setVoxelSize(vs_list)

setVoxelSize(vx, vy=1., vz=1., vt=1.) → None

Set voxel sizes in mm (list of at least 4 floats)

property shape

value(posx, posy=0, posz=0, post=0)

value is an alias to at(): returns the volume value for the selected voxel.

class soma.aims.Volume_U16(*args)

Bases: RCObject

Generalities

The various Volume_<type> classes are bindings to the C++ template classes carto::Volume. It represents a 4D volume (1D to 4D, actually) storing a specific type of data: for instance S16 is signed 16 bit short ints, FLOAT is 32 bit floats, etc.

Volumes are read and written using the Reader and Writer classes, which are in turn used by the simple read() and write() functions.

A volume of a given type can be built either using its specialized class constructor, or the general Volume() function which can take a voxel type in its arguments: the following are equivalent:

>>> v = aims.Volume_S16(100, 100, 10)
>>> v = aims.Volume('S16', 100, 100, 10)
>>> v = aims.Volume(100, 100, 10, dtype='S16')
>>> v = aims.Volume([100, 100, 10], dtype='S16')
>>> import numpy
>>> v = aims.Volume(numpy.int16, 100, 100, 10)

Numpy arrays and volumes

A volume is an array of voxels, which can be accessed via the at() method. For standard numeric types, it is also possible to get the voxels array as a numpy array, using the __array__() method, or more conveniently, numpy.asarray(volume) or numpy.array(volume, copy=False). In aims >= 5.0.2, a more concise shortcut is also available: volume.np (this is available on all types providing numpy bindings actually).

The array returned is a reference to the actual data block, so any modification to its contents also affects the Volume contents, so it is generally an easy way of manipulating volume voxels because all the power of the numpy module can be used on Volumes. The obsoloete arraydata() method used to return a numpy array just like it is in memory, that is a 4D (or more) array generally indexed by [t][z][y][x] (but it depands how it has been built), which is generally not what you like and is not consistent with AIMS indexing. Contrarily, using volume.np sets strides in the returned numpy array, so that indexing is in the “normal” order [x][y][z][t], while still sharing the same memory block. The Volume object now also wraps the numpy accessors to the volume object itself, so that volume[x, y, z, t] is the same as nupmy.asarray(volume)[x, y, z, t].

new in PyAims 4.7

Since PyAims 4.7 the numpy arrays bindings have notably improved, and are now able to bind arrays to voxels types which are not scalar numeric types. Volumes of RGB, RGBA, HSV, or Point3df now have numpy bindings. The bound object have generally a “numpy struct” binding, that is not the usual C++/python object binding, but instead a structure managed by numpy which also supports indexing. For most objects we are using, they also have an array stucture (a RGB is an array with 3 int8 items), and are bound under a sturcture with a unique field, named “v” (for “vector”):

>>> v = aims.Volume('RGB', 100, 100, 10)
>>> v[0, 0, 0, 0]
([0, 0, 0],)

Such an array may be indexed by the field name, which returns another array with scalar values and additional dimensions:

>>> v['v'].dtype
dtype('uint8')
>>> v['v'].shape
(100, 100, 10, 1, 3)

Both arrays share their memory with the aims volume.

See also

Precisions about aims / numpy bindings

Header

Volumes also store a header which can contain various information (including sizes and voxel sizes). The header is a dictionary-like generic object (Object) which can be accessed by the header() method. This header object also has a read-write access with some restrictions inherent to the Object mechanism. It will be saved with the volume contents when the volume is saved on disk.

Volumes support a number of arithmetic operators like +, - etc. when the operands types and sizes match: for instance:

>>> # V1 and V2 are two volumes
>>> V3 = V1 + V2  # adds two volumes
>>> V2 -= V1
>>> V3 = V1 + 3   # adds 3 to aceh voxel
>>> V3 = V1 * V2  # itemwise multiplication

Some type conversions can be performed on volumes, for istance to convert a Volume_S16 to a Volume_FLOAT. The simplest, to convert to another data type, is to use the astype() method.

To convert a volume into diffent structure types, such as Buckets, use the converter classes Converter_<type1>_<type2> and ShallowConverter_<type1>_<type2> with <type1> and <type2> being volume or other object types: for instance Converter_Volume_S16_Volume_FLOAT. The converter can also be called using type arguments:

>>> vol1 = aims.AimsData('S16', 100, 100, 10)
>>> c = aims.Converter(intype=vol1, outtype='BucketMap_VOID')
>>> vol2 = c(vol1)

Volume from a numpy array

It is also possible to build a Volume from a numpy array:

>>> v = aims.Volume(numpy.zeros((100, 100, 10)))

Note that passing a 1D numpy array of ints will build a volume mapping the array contents, whereas passing a python list or tuple of ints will interpret the list as a shape for the volume:

>>> v = aims.Volume(numpy.array([100, 100, 10]).astype('int32'))
>>> print(v.getSize())
[ 3, 1, 1, 1 ]
>>> print(v.np)
[100 100  10]
>>> v = aims.Volume([100, 100, 10])
>>> print(v.getSize())
[ 100, 100, 10, 1 ]

Array ordering:

In pyaims <= 5.0.x the Volume classes were only working with the X axis (the first) being contiguous, and, for numpy, should be interpreted as “Fortran-contiguous”. So to convert a numpy array into a Volume and keep the same axes ordering, you had to convert it to Fortran order first:

>>> v = aims.Volume(numpy.zeros((2, 3, 4, dtype='int32')))
# v.getSize() used to return [4, 3, 2, 1]
>>> v = aims.Volume(np.asfortranarray(numpy.zeros((2, 3, 4), dtype='int32')))
>>> print(v.getSize())
[2, 3, 4, 1]

In pyaims 5.1 this limitation is gone, you can omit the fortran order conversion. Strides are taken into account in the C++ volume. But you have to be careful with such volumes as many C++ programs assume internally that the X axis is contiguous in memory, which is not true in this situation. These programs and functions may not work, crash, or produce incorrect results when used with non-contiguous X axis volumes.

class Position4Di

Bases: wrapper

4 ints for position or size, used for Volume views.

all()

allocatorContext()

any()

arraydata()

Note

arraydata() returns a numpy array to the internal memory block, with “inverted” shape and strides.

WARNING: this is an obsolete method, which behaviour has changed. Most of the time you need numpy.asarray(volume), or more simply: volume.np, which actually provides an array with the same indices ordering. Here it is a transposed one.

Given the internal ordering of Aims Volumes, the resulting numpy array is indexed as [t][z][y][x]. This order corresponds to the numpy “fortran” order: order='F' If you need the inverse, more natural, [x][y][z][t] ordering, use the following:

>>> volarray = volume.np

or:

>>> volarray = numpy.array(volume, copy=False)

or:

>>> volarray = numpy.asarray(volume)

Using arraydata(), as the indices are reversed, if you do something like:

vol2 = aims.Volume(vol.arraydata())

You will build a transposed volume.

astype(dtype, copy=False)

Easy conversion method for volumes. Works in a similar was as numpy arrays astype() methods, except that the “copy” parameter defaults to False.

Parameters:

• dtype (string or type object) – may be a volume or voxel type, specified either as a type oject (int, aims.Volume_S32, numpy.int16), or as a string (“S16”…).

• copy (bool) – if False, a ShallowConverter will be used: if dtype matches the current volume type, a shared reference to self will be returned. Otherwise a new copy will be returned.

Return type:

A volume of the converted type

at(posx, posy=0, posz=0, post=0)

Returns the volume value for the selected voxel.

at(posx1, posx2, posx3, posx4, posx5, posx6=0, posx7=0, posx8=0)

Returns the volume value for the selected voxel.

at(vector_int)

Returns the volume value for the selected voxel.

checkResize()

copyHeaderFrom()

fill(value)

Fill Volume_U16 using the given value.

fillBorder(value)

Fill the surrounding of the volume view in the reference volume (if any) using the given value.

fromObject()

getBorders()

getSize()

Number of voxels in each dimension (list of 4 ints)

getSizeT()

getSizeX()

getSizeY()

getSizeZ()

getStrides()

getVoxelSize()

Voxel sizes in mm (list of 4 floats)

header()

The header contains all meta-data.

max()

min()

property np

The np property is a shortcut to the __array__ method. Thus:

something.np

is a handier equivalent to:

numpy.asarray(something)

posInRefVolume()

If the volume is a view into another (larger) one, this returns the position in “parent” one.

refVolume()

If the volume is a view into another (larger) one, this returns the “parent” one.

setPosInRefVolume()

Set position in parent volume

setValue(value, x, y=0, z=0, t=0)

Set the voxel value at the given position.

setValue(value, [x1, x2, x3, x4, x5, x6…])

Set the voxel value at the given position.

setVoxelSize(vs_list)

setVoxelSize(vx, vy=1., vz=1., vt=1.) → None

Set voxel sizes in mm (list of at least 4 floats)

property shape

value(posx, posy=0, posz=0, post=0)

value is an alias to at(): returns the volume value for the selected voxel.

class soma.aims.Volume_U32(*args)

Bases: RCObject

Generalities

The various Volume_<type> classes are bindings to the C++ template classes carto::Volume. It represents a 4D volume (1D to 4D, actually) storing a specific type of data: for instance S16 is signed 16 bit short ints, FLOAT is 32 bit floats, etc.

Volumes are read and written using the Reader and Writer classes, which are in turn used by the simple read() and write() functions.

A volume of a given type can be built either using its specialized class constructor, or the general Volume() function which can take a voxel type in its arguments: the following are equivalent:

>>> v = aims.Volume_S16(100, 100, 10)
>>> v = aims.Volume('S16', 100, 100, 10)
>>> v = aims.Volume(100, 100, 10, dtype='S16')
>>> v = aims.Volume([100, 100, 10], dtype='S16')
>>> import numpy
>>> v = aims.Volume(numpy.int16, 100, 100, 10)

Numpy arrays and volumes

A volume is an array of voxels, which can be accessed via the at() method. For standard numeric types, it is also possible to get the voxels array as a numpy array, using the __array__() method, or more conveniently, numpy.asarray(volume) or numpy.array(volume, copy=False). In aims >= 5.0.2, a more concise shortcut is also available: volume.np (this is available on all types providing numpy bindings actually).

The array returned is a reference to the actual data block, so any modification to its contents also affects the Volume contents, so it is generally an easy way of manipulating volume voxels because all the power of the numpy module can be used on Volumes. The obsoloete arraydata() method used to return a numpy array just like it is in memory, that is a 4D (or more) array generally indexed by [t][z][y][x] (but it depands how it has been built), which is generally not what you like and is not consistent with AIMS indexing. Contrarily, using volume.np sets strides in the returned numpy array, so that indexing is in the “normal” order [x][y][z][t], while still sharing the same memory block. The Volume object now also wraps the numpy accessors to the volume object itself, so that volume[x, y, z, t] is the same as nupmy.asarray(volume)[x, y, z, t].

new in PyAims 4.7

Since PyAims 4.7 the numpy arrays bindings have notably improved, and are now able to bind arrays to voxels types which are not scalar numeric types. Volumes of RGB, RGBA, HSV, or Point3df now have numpy bindings. The bound object have generally a “numpy struct” binding, that is not the usual C++/python object binding, but instead a structure managed by numpy which also supports indexing. For most objects we are using, they also have an array stucture (a RGB is an array with 3 int8 items), and are bound under a sturcture with a unique field, named “v” (for “vector”):

>>> v = aims.Volume('RGB', 100, 100, 10)
>>> v[0, 0, 0, 0]
([0, 0, 0],)

Such an array may be indexed by the field name, which returns another array with scalar values and additional dimensions:

>>> v['v'].dtype
dtype('uint8')
>>> v['v'].shape
(100, 100, 10, 1, 3)

Both arrays share their memory with the aims volume.

See also

Precisions about aims / numpy bindings

Header

Volumes also store a header which can contain various information (including sizes and voxel sizes). The header is a dictionary-like generic object (Object) which can be accessed by the header() method. This header object also has a read-write access with some restrictions inherent to the Object mechanism. It will be saved with the volume contents when the volume is saved on disk.

Volumes support a number of arithmetic operators like +, - etc. when the operands types and sizes match: for instance:

>>> # V1 and V2 are two volumes
>>> V3 = V1 + V2  # adds two volumes
>>> V2 -= V1
>>> V3 = V1 + 3   # adds 3 to aceh voxel
>>> V3 = V1 * V2  # itemwise multiplication

Some type conversions can be performed on volumes, for istance to convert a Volume_S16 to a Volume_FLOAT. The simplest, to convert to another data type, is to use the astype() method.

To convert a volume into diffent structure types, such as Buckets, use the converter classes Converter_<type1>_<type2> and ShallowConverter_<type1>_<type2> with <type1> and <type2> being volume or other object types: for instance Converter_Volume_S16_Volume_FLOAT. The converter can also be called using type arguments:

>>> vol1 = aims.AimsData('S16', 100, 100, 10)
>>> c = aims.Converter(intype=vol1, outtype='BucketMap_VOID')
>>> vol2 = c(vol1)

Volume from a numpy array

It is also possible to build a Volume from a numpy array:

>>> v = aims.Volume(numpy.zeros((100, 100, 10)))

Note that passing a 1D numpy array of ints will build a volume mapping the array contents, whereas passing a python list or tuple of ints will interpret the list as a shape for the volume:

>>> v = aims.Volume(numpy.array([100, 100, 10]).astype('int32'))
>>> print(v.getSize())
[ 3, 1, 1, 1 ]
>>> print(v.np)
[100 100  10]
>>> v = aims.Volume([100, 100, 10])
>>> print(v.getSize())
[ 100, 100, 10, 1 ]

Array ordering:

In pyaims <= 5.0.x the Volume classes were only working with the X axis (the first) being contiguous, and, for numpy, should be interpreted as “Fortran-contiguous”. So to convert a numpy array into a Volume and keep the same axes ordering, you had to convert it to Fortran order first:

>>> v = aims.Volume(numpy.zeros((2, 3, 4, dtype='int32')))
# v.getSize() used to return [4, 3, 2, 1]
>>> v = aims.Volume(np.asfortranarray(numpy.zeros((2, 3, 4), dtype='int32')))
>>> print(v.getSize())
[2, 3, 4, 1]

In pyaims 5.1 this limitation is gone, you can omit the fortran order conversion. Strides are taken into account in the C++ volume. But you have to be careful with such volumes as many C++ programs assume internally that the X axis is contiguous in memory, which is not true in this situation. These programs and functions may not work, crash, or produce incorrect results when used with non-contiguous X axis volumes.

class Position4Di

Bases: wrapper

4 ints for position or size, used for Volume views.

all()

allocatorContext()

any()

arraydata()

Note

arraydata() returns a numpy array to the internal memory block, with “inverted” shape and strides.

WARNING: this is an obsolete method, which behaviour has changed. Most of the time you need numpy.asarray(volume), or more simply: volume.np, which actually provides an array with the same indices ordering. Here it is a transposed one.

Given the internal ordering of Aims Volumes, the resulting numpy array is indexed as [t][z][y][x]. This order corresponds to the numpy “fortran” order: order='F' If you need the inverse, more natural, [x][y][z][t] ordering, use the following:

>>> volarray = volume.np

or:

>>> volarray = numpy.array(volume, copy=False)

or:

>>> volarray = numpy.asarray(volume)

Using arraydata(), as the indices are reversed, if you do something like:

vol2 = aims.Volume(vol.arraydata())

You will build a transposed volume.

astype(dtype, copy=False)

Easy conversion method for volumes. Works in a similar was as numpy arrays astype() methods, except that the “copy” parameter defaults to False.

Parameters:

• dtype (string or type object) – may be a volume or voxel type, specified either as a type oject (int, aims.Volume_S32, numpy.int16), or as a string (“S16”…).

• copy (bool) – if False, a ShallowConverter will be used: if dtype matches the current volume type, a shared reference to self will be returned. Otherwise a new copy will be returned.

Return type:

A volume of the converted type

at(posx, posy=0, posz=0, post=0)

Returns the volume value for the selected voxel.

at(posx1, posx2, posx3, posx4, posx5, posx6=0, posx7=0, posx8=0)

Returns the volume value for the selected voxel.

at(vector_int)

Returns the volume value for the selected voxel.

checkResize()

copyHeaderFrom()

fill(value)

Fill Volume_U32 using the given value.

fillBorder(value)

Fill the surrounding of the volume view in the reference volume (if any) using the given value.

fromObject()

getBorders()

getSize()

Number of voxels in each dimension (list of 4 ints)

getSizeT()

getSizeX()

getSizeY()

getSizeZ()

getStrides()

getVoxelSize()

Voxel sizes in mm (list of 4 floats)

header()

The header contains all meta-data.

max()

min()

property np

The np property is a shortcut to the __array__ method. Thus:

something.np

is a handier equivalent to:

numpy.asarray(something)

posInRefVolume()

If the volume is a view into another (larger) one, this returns the position in “parent” one.

refVolume()

If the volume is a view into another (larger) one, this returns the “parent” one.

setPosInRefVolume()

Set position in parent volume

setValue(value, x, y=0, z=0, t=0)

Set the voxel value at the given position.

setValue(value, [x1, x2, x3, x4, x5, x6…])

Set the voxel value at the given position.

setVoxelSize(vs_list)

setVoxelSize(vx, vy=1., vz=1., vt=1.) → None

Set voxel sizes in mm (list of at least 4 floats)

property shape

value(posx, posy=0, posz=0, post=0)

value is an alias to at(): returns the volume value for the selected voxel.

class soma.aims.Volume_U8(*args)

Bases: RCObject

Generalities

The various Volume_<type> classes are bindings to the C++ template classes carto::Volume. It represents a 4D volume (1D to 4D, actually) storing a specific type of data: for instance S16 is signed 16 bit short ints, FLOAT is 32 bit floats, etc.

Volumes are read and written using the Reader and Writer classes, which are in turn used by the simple read() and write() functions.

A volume of a given type can be built either using its specialized class constructor, or the general Volume() function which can take a voxel type in its arguments: the following are equivalent:

>>> v = aims.Volume_S16(100, 100, 10)
>>> v = aims.Volume('S16', 100, 100, 10)
>>> v = aims.Volume(100, 100, 10, dtype='S16')
>>> v = aims.Volume([100, 100, 10], dtype='S16')
>>> import numpy
>>> v = aims.Volume(numpy.int16, 100, 100, 10)

Numpy arrays and volumes

A volume is an array of voxels, which can be accessed via the at() method. For standard numeric types, it is also possible to get the voxels array as a numpy array, using the __array__() method, or more conveniently, numpy.asarray(volume) or numpy.array(volume, copy=False). In aims >= 5.0.2, a more concise shortcut is also available: volume.np (this is available on all types providing numpy bindings actually).

The array returned is a reference to the actual data block, so any modification to its contents also affects the Volume contents, so it is generally an easy way of manipulating volume voxels because all the power of the numpy module can be used on Volumes. The obsoloete arraydata() method used to return a numpy array just like it is in memory, that is a 4D (or more) array generally indexed by [t][z][y][x] (but it depands how it has been built), which is generally not what you like and is not consistent with AIMS indexing. Contrarily, using volume.np sets strides in the returned numpy array, so that indexing is in the “normal” order [x][y][z][t], while still sharing the same memory block. The Volume object now also wraps the numpy accessors to the volume object itself, so that volume[x, y, z, t] is the same as nupmy.asarray(volume)[x, y, z, t].

new in PyAims 4.7

Since PyAims 4.7 the numpy arrays bindings have notably improved, and are now able to bind arrays to voxels types which are not scalar numeric types. Volumes of RGB, RGBA, HSV, or Point3df now have numpy bindings. The bound object have generally a “numpy struct” binding, that is not the usual C++/python object binding, but instead a structure managed by numpy which also supports indexing. For most objects we are using, they also have an array stucture (a RGB is an array with 3 int8 items), and are bound under a sturcture with a unique field, named “v” (for “vector”):

>>> v = aims.Volume('RGB', 100, 100, 10)
>>> v[0, 0, 0, 0]
([0, 0, 0],)

Such an array may be indexed by the field name, which returns another array with scalar values and additional dimensions:

>>> v['v'].dtype
dtype('uint8')
>>> v['v'].shape
(100, 100, 10, 1, 3)

Both arrays share their memory with the aims volume.

See also

Precisions about aims / numpy bindings

Header

Volumes also store a header which can contain various information (including sizes and voxel sizes). The header is a dictionary-like generic object (Object) which can be accessed by the header() method. This header object also has a read-write access with some restrictions inherent to the Object mechanism. It will be saved with the volume contents when the volume is saved on disk.

Volumes support a number of arithmetic operators like +, - etc. when the operands types and sizes match: for instance:

>>> # V1 and V2 are two volumes
>>> V3 = V1 + V2  # adds two volumes
>>> V2 -= V1
>>> V3 = V1 + 3   # adds 3 to aceh voxel
>>> V3 = V1 * V2  # itemwise multiplication

Some type conversions can be performed on volumes, for istance to convert a Volume_S16 to a Volume_FLOAT. The simplest, to convert to another data type, is to use the astype() method.

To convert a volume into diffent structure types, such as Buckets, use the converter classes Converter_<type1>_<type2> and ShallowConverter_<type1>_<type2> with <type1> and <type2> being volume or other object types: for instance Converter_Volume_S16_Volume_FLOAT. The converter can also be called using type arguments:

>>> vol1 = aims.AimsData('S16', 100, 100, 10)
>>> c = aims.Converter(intype=vol1, outtype='BucketMap_VOID')
>>> vol2 = c(vol1)

Volume from a numpy array

It is also possible to build a Volume from a numpy array:

>>> v = aims.Volume(numpy.zeros((100, 100, 10)))

Note that passing a 1D numpy array of ints will build a volume mapping the array contents, whereas passing a python list or tuple of ints will interpret the list as a shape for the volume:

>>> v = aims.Volume(numpy.array([100, 100, 10]).astype('int32'))
>>> print(v.getSize())
[ 3, 1, 1, 1 ]
>>> print(v.np)
[100 100  10]
>>> v = aims.Volume([100, 100, 10])
>>> print(v.getSize())
[ 100, 100, 10, 1 ]

Array ordering:

In pyaims <= 5.0.x the Volume classes were only working with the X axis (the first) being contiguous, and, for numpy, should be interpreted as “Fortran-contiguous”. So to convert a numpy array into a Volume and keep the same axes ordering, you had to convert it to Fortran order first:

>>> v = aims.Volume(numpy.zeros((2, 3, 4, dtype='int32')))
# v.getSize() used to return [4, 3, 2, 1]
>>> v = aims.Volume(np.asfortranarray(numpy.zeros((2, 3, 4), dtype='int32')))
>>> print(v.getSize())
[2, 3, 4, 1]

In pyaims 5.1 this limitation is gone, you can omit the fortran order conversion. Strides are taken into account in the C++ volume. But you have to be careful with such volumes as many C++ programs assume internally that the X axis is contiguous in memory, which is not true in this situation. These programs and functions may not work, crash, or produce incorrect results when used with non-contiguous X axis volumes.

class Position4Di

Bases: wrapper

4 ints for position or size, used for Volume views.

all()

allocatorContext()

any()

arraydata()

Note

arraydata() returns a numpy array to the internal memory block, with “inverted” shape and strides.

WARNING: this is an obsolete method, which behaviour has changed. Most of the time you need numpy.asarray(volume), or more simply: volume.np, which actually provides an array with the same indices ordering. Here it is a transposed one.

Given the internal ordering of Aims Volumes, the resulting numpy array is indexed as [t][z][y][x]. This order corresponds to the numpy “fortran” order: order='F' If you need the inverse, more natural, [x][y][z][t] ordering, use the following:

>>> volarray = volume.np

or:

>>> volarray = numpy.array(volume, copy=False)

or:

>>> volarray = numpy.asarray(volume)

Using arraydata(), as the indices are reversed, if you do something like:

vol2 = aims.Volume(vol.arraydata())

You will build a transposed volume.

astype(dtype, copy=False)

Easy conversion method for volumes. Works in a similar was as numpy arrays astype() methods, except that the “copy” parameter defaults to False.

Parameters:

• dtype (string or type object) – may be a volume or voxel type, specified either as a type oject (int, aims.Volume_S32, numpy.int16), or as a string (“S16”…).

• copy (bool) – if False, a ShallowConverter will be used: if dtype matches the current volume type, a shared reference to self will be returned. Otherwise a new copy will be returned.

Return type:

A volume of the converted type

at(posx, posy=0, posz=0, post=0)

Returns the volume value for the selected voxel.

at(posx1, posx2, posx3, posx4, posx5, posx6=0, posx7=0, posx8=0)

Returns the volume value for the selected voxel.

at(vector_int)

Returns the volume value for the selected voxel.

checkResize()

copyHeaderFrom()

fill(value)

Fill Volume_U8 using the given value.

fillBorder(value)

Fill the surrounding of the volume view in the reference volume (if any) using the given value.

fromObject()

getBorders()

getSize()

Number of voxels in each dimension (list of 4 ints)

getSizeT()

getSizeX()

getSizeY()

getSizeZ()

getStrides()

getVoxelSize()

Voxel sizes in mm (list of 4 floats)

header()

The header contains all meta-data.

max()

min()

property np

The np property is a shortcut to the __array__ method. Thus:

something.np

is a handier equivalent to:

numpy.asarray(something)

posInRefVolume()

If the volume is a view into another (larger) one, this returns the position in “parent” one.

refVolume()

If the volume is a view into another (larger) one, this returns the “parent” one.

setPosInRefVolume()

Set position in parent volume

setValue(value, x, y=0, z=0, t=0)

Set the voxel value at the given position.

setValue(value, [x1, x2, x3, x4, x5, x6…])

Set the voxel value at the given position.

Set a voxel value at given position

Set a voxel value at given position

setVoxelSize(vs_list)

setVoxelSize(vx, vy=1., vz=1., vt=1.) → None

Set voxel sizes in mm (list of at least 4 floats)

property shape

value(posx, posy=0, posz=0, post=0)

value is an alias to at(): returns the volume value for the selected voxel.

class soma.aims.Writer

Bases: object

write(obj, filename, format=None, options={})

Writes the object <obj> in a file named <filename>, whatever the type of <obj>, as format <format>. All objects types and formats supported by the Aims IO system can be used. <obj> may be a reference-counter to an object type supported by the IO system. Additional specific options may be passed to the underlying IO system in an optional <options> dictionary.

writtenObjectDataType()

Data content type (voxel or texture type…) written (available after writing)

writtenObjectFullType()

Data full type written (available after writing)

writtenObjectType()

Data object type (Volume, Mesh…) written (available after writing)

class soma.aims.aims

Bases: simplewrapper

class AffineTransformation3d(*args)

Bases: Transformation3d

affine()

fromColumnVector()

fromMatrix(value)

header()

inverse()

isDirect()

isIdentity()

Test if the transformation can safely be omitted

This method must only return true if the transformation behaves exactly like an identity transformation (notably, the transform methods will always return the input coordinates unchanged).

NOTE: Implementors of derived classes may choose to always return false if a test would be difficult to implement or expensive to run.

rotation()

rotationaroundx()

rotationaroundy()

rotationaroundz()

scale()

setRotationAffine()

setToIdentity()

setTranslation()

toColumnVector()

toMatrix()

This function return a copy of the transformation matrix

toVector()

transformDouble()

transformFloat()

transformNormal()

transformNormalDouble()

transformNormalFloat()

transformNormalPoint3dd()

transformNormalPoint3df()

transformPoint3d()

transformPoint3dd()

transformPoint3df()

transformUnitNormal()

transformVector()

transformVectorDouble()

transformVectorFloat()

transformVectorPoint3dd()

transformVectorPoint3df()

translation()

class AimsApplication

Bases: wrapper

initialize()

verbose()

AimsConnectedComponent()

void AimsConnectedComponent(data, connectivity, valids, backgrnd=0,

bin=True, minSize=0, numMax=0, verbose=True)

Connected components extraction. The function modifies the input data, and does not return a new one.

Parameters:

• data (Volume_S16 instance) – data will be modified during the process.

• connectivity (Connectivity.Type enum code) –

• valids (dict short: size_t) –

• backgrnd (short) –

• bin (bool (optional)) –

• minSize (size_t (optional)) –

• numMax (size_t (optional)) –

• verbose (bool (optional)) –

void AimsConnectedComponent(data, connectivity, backgrnd=0, bin=True,

minSize=0, maxSize=0, numMax=0, verbose=True)

Connected components extraction. The function modifies the input data, and does not return a new one.

Parameters:

• data (Volume_S16 instance) – data will be modified during the process.

• connectivity (Connectivity.Type enum code) –

• backgrnd (short) –

• bin (bool (optional)) –

• minsize (size_t (optional)) –

• maxSize (size_t (optional)) –

• numMax (size_t (optional)) –

• verbose (bool (optional)) –

void AimsConnectedComponent(data, connectivity, backgrnd=0, bin=True,

minSize=0, maxSize=0, numMax=0, verbose=True)

Connected components extraction, Bucket version. The function modifies the input data, and does not return a new one.

Parameters:

• data (BucketMap_S16 instance) – data will be modified during the process.

• connectivity (Connectivity.Type enum code) –

• backgrnd (short) –

• bin (bool (optional)) –

• minsize (size_t (optional)) –

• maxsize (size_t (optional)) –

• numMax (size_t (optional)) –

• verbose (bool (optional)) –

void AimsConnectedComponent(data, connectivity, valids, backgrnd=0,

bin=True, minSize=0, numMax=0, verbose=True)

Connected components extraction. The function modifies the input data, and does not return a new one.

Parameters:

• data (Volume_U16 instance) – data will be modified during the process.

• connectivity (Connectivity.Type enum code) –

• valids (dict unsigned short: size_t) –

• backgrnd (unsigned short) –

• bin (bool (optional)) –

• minSize (size_t (optional)) –

• numMax (size_t (optional)) –

• verbose (bool (optional)) –

void AimsConnectedComponent(data, connectivity, backgrnd=0, bin=True,

minSize=0, maxSize=0, numMax=0, verbose=True)

Connected components extraction. The function modifies the input data, and does not return a new one.

Parameters:

• data (Volume_U16 instance) – data will be modified during the process.

• connectivity (Connectivity.Type enum code) –

• backgrnd (unsigned short) –

• bin (bool (optional)) –

• minsize (size_t (optional)) –

• maxSize (size_t (optional)) –

• numMax (size_t (optional)) –

• verbose (bool (optional)) –

void AimsConnectedComponent(data, connectivity, backgrnd=0, bin=True,

minSize=0, maxSize=0, numMax=0, verbose=True)

Connected components extraction, Bucket version. The function modifies the input data, and does not return a new one.

Parameters:

• data (BucketMap_U16 instance) – data will be modified during the process.

• connectivity (Connectivity.Type enum code) –

• backgrnd (unsigned short) –

• bin (bool (optional)) –

• minsize (size_t (optional)) –

• maxsize (size_t (optional)) –

• numMax (size_t (optional)) –

• verbose (bool (optional)) –

void AimsConnectedComponent(data, connectivity, valids, backgrnd=0,

bin=True, minSize=0, numMax=0, verbose=True)

Connected components extraction. The function modifies the input data, and does not return a new one.

Parameters:

• data (Volume_S32 instance) – data will be modified during the process.

• connectivity (Connectivity.Type enum code) –

• valids (dict int: size_t) –

• backgrnd (int) –

• bin (bool (optional)) –

• minSize (size_t (optional)) –

• numMax (size_t (optional)) –

• verbose (bool (optional)) –

void AimsConnectedComponent(data, connectivity, backgrnd=0, bin=True,

minSize=0, maxSize=0, numMax=0, verbose=True)

Connected components extraction. The function modifies the input data, and does not return a new one.

Parameters:

• data (Volume_S32 instance) – data will be modified during the process.

• connectivity (Connectivity.Type enum code) –

• backgrnd (int) –

• bin (bool (optional)) –

• minsize (size_t (optional)) –

• maxSize (size_t (optional)) –

• numMax (size_t (optional)) –

• verbose (bool (optional)) –

void AimsConnectedComponent(data, connectivity, backgrnd=0, bin=True,

minSize=0, maxSize=0, numMax=0, verbose=True)

Connected components extraction, Bucket version. The function modifies the input data, and does not return a new one.

Parameters:

• data (BucketMap_S32 instance) – data will be modified during the process.

• connectivity (Connectivity.Type enum code) –

• backgrnd (int) –

• bin (bool (optional)) –

• minsize (size_t (optional)) –

• maxsize (size_t (optional)) –

• numMax (size_t (optional)) –

• verbose (bool (optional)) –

void AimsConnectedComponent(data, connectivity, valids, backgrnd=0,

bin=True, minSize=0, numMax=0, verbose=True)

Connected components extraction. The function modifies the input data, and does not return a new one.

Parameters:

• data (Volume_U32 instance) – data will be modified during the process.

• connectivity (Connectivity.Type enum code) –

• valids (dict unsigned: size_t) –

• backgrnd (unsigned) –

• bin (bool (optional)) –

• minSize (size_t (optional)) –

• numMax (size_t (optional)) –

• verbose (bool (optional)) –

void AimsConnectedComponent(data, connectivity, backgrnd=0, bin=True,

minSize=0, maxSize=0, numMax=0, verbose=True)

Connected components extraction. The function modifies the input data, and does not return a new one.

Parameters:

• data (Volume_U32 instance) – data will be modified during the process.

• connectivity (Connectivity.Type enum code) –

• backgrnd (unsigned) –

• bin (bool (optional)) –

• minsize (size_t (optional)) –

• maxSize (size_t (optional)) –

• numMax (size_t (optional)) –

• verbose (bool (optional)) –

void AimsConnectedComponent(data, connectivity, backgrnd=0, bin=True,

minSize=0, maxSize=0, numMax=0, verbose=True)

Connected components extraction, Bucket version. The function modifies the input data, and does not return a new one.

Parameters:

• data (BucketMap_U32 instance) – data will be modified during the process.

• connectivity (Connectivity.Type enum code) –

• backgrnd (unsigned) –

• bin (bool (optional)) –

• minsize (size_t (optional)) –

• maxsize (size_t (optional)) –

• numMax (size_t (optional)) –

• verbose (bool (optional)) –

class AimsGraphReader

Bases: wrapper

readElements()

setExcludeFilter()

setReadFilter()

class AimsGraphWriter

Bases: wrapper

Global = 1

Keep = 0

Local = 2

class SavingMode

Bases: int

writeElements()

class BarycenterCurvature

Bases: Curvature

doIt()

class BoixCurvature

Bases: Curvature

doIt()

class BoixGaussianCurvature

Bases: Curvature

doIt()

class BucketUtil

Bases: wrapper

Utility class related to buckets

volumeFromBucket()

volume, offser = BucketUtil.volumeFromBucket(bucket, borderwidth=0,

enable_shift=True)

Bucket to volume conversion. Compared to Converter_BucketMap_Volume, this function has options to handle min bounding box, and allows to have borders.

If enable_shift is False, the volume will start at coordinates (0, 0, 0), without an offset (thus the volume may be much lager than needed, or may not contain the whole bucket if it has negative coordinates). In such case, pos is not used (thus passing 0 is OK).

volume = BucketUtil.volumeFromBucket(bucket, bbmin, bmax, borderwidth=0)

Bucket to volume conversion. Compared to Converter_BucketMap_Volume, this function has options to handle bounding box, and allows to have borders.

class BundleInfo

Bases: wrapper

id()

name()

class BundleListener

Bases: wrapper

Serial processing of bundles.

BundleListener listens events from a BundleProducer object, typically emitted when a new bundle starts or ends, a fiber starts or ends etc.

To use it, BundleListener has to be subclassed and some of the following methods overloaded: * bundleStarted * bundleTerminated * fiberStarted * fiberTerminated * newFiberPoint * noMoreBundle

To connect the listener to a producer, use BundleProducer::addBundleListener().

Inherited classes may inherit both BundleListener and BundleProducer, if they are part of a processing chain.

bundleStarted(producer, bundle_info)

bundleTerminated(producer, bundle_info)

fiberStarted(producer, bundle_info, fiber_info)

fiberTerminated(producer, bundle_info, fiber_info)

newFiberPoint(producer, bundle_info, fiber_info, point)

noMoreBundle(producer)

class BundleMotion

Bases: BundleProducer, BundleListener

addFiberPoint()

bundleStarted(producer, bundle_info)

bundleTerminated(producer, bundle_info)

fiberStarted(producer, bundle_info, fiber_info)

fiberTerminated(producer, bundle_info, fiber_info)

newFiberPoint(producer, bundle_info, fiber_info, point)

noMoreBundle(producer)

startBundle()

startFiber()

terminateBundle()

terminateFiber()

class BundleProducer

Bases: wrapper

Serial processing of bundles.

BundleProducer emits events to a BundleListener object while walking through a bundles set structure (or a bundles file), typically when a new bundle starts or ends, a fiber starts or ends etc.

To connect the listener to a producer, use BundleProducer::addBundleListener().

Inherited classes may inherit both BundleListener and BundleProducer, if they are part of a processing chain.

addBundleListener(listener)

Connects a BundleProducer to a BunsdleListener.

addFiberPoint()

noMoreBundle()

startBundle()

startFiber()

terminateBundle()

terminateFiber()

class BundleROISelect

Bases: BundleProducer, BundleListener

addFiberPoint()

bundleStarted(producer, bundle_info)

bundleTerminated(producer, bundle_info)

fiberStarted(producer, bundle_info, fiber_info)

fiberTerminated(producer, bundle_info, fiber_info)

newFiberPoint(producer, bundle_info, fiber_info, point)

noMoreBundle(producer)

startBundle()

startFiber()

terminateBundle()

terminateFiber()

class BundleROISplit

Bases: BundleProducer, BundleListener

addFiberPoint()

bundleStarted(producer, bundle_info)

bundleTerminated(producer, bundle_info)

fiberStarted(producer, bundle_info, fiber_info)

fiberTerminated(producer, bundle_info, fiber_info)

newFiberPoint(producer, bundle_info, fiber_info, point)

noMoreBundle(producer)

startBundle()

startFiber()

terminateBundle()

terminateFiber()

class BundleReader

Bases: BundleProducer

Reads a bundles file, and emits events while walking through its data.

BundleReader is a BundleProducer, so can be listened by any BundleListener. It may read several bundles/fibers formats, using a lower-level BundleProducer dedicated to a specific format.

Currently .bundles (AIMS/Connectomist) and .trk (Trackvis) formats are supported.

addFiberPoint()

formatExtensions(format='ALL')

return a set of file extensions associated with the given format. If the format is “ALL” (default) then all extensions of all supported formats are returned. If the format does not exist, an empty set is returned, and no error is issued.

noMoreBundle()

read()

read() is the entry point to fibers processing, and triggers the producer machinery.

startBundle()

startFiber()

supportedFormats()

return a set of fiber tracts formats names supported by the BundlesReader.

terminateBundle()

terminateFiber()

class BundleSampler

Bases: BundleProducer, BundleListener

addFiberPoint()

bundleStarted(producer, bundle_info)

bundleTerminated(producer, bundle_info)

fiberStarted(producer, bundle_info, fiber_info)

fiberTerminated(producer, bundle_info, fiber_info)

newFiberPoint(producer, bundle_info, fiber_info, point)

noMoreBundle(producer)

startBundle()

startFiber()

terminateBundle()

terminateFiber()

class BundleToGraph

Bases: BundleListener, PropertySet

Bundles structure building as a Graph

The Graph structure is used to represent bundles and fibers when we need to keep their complete structure in memory. This structure is especially used for 3D rendering in Anatomist.

BundleToGraph is a BundleListener, thus has to be connected to a BundleProducer to work (typically, a BundleReader).

Note that the BundleProducer / BundleListener system work as processing chains, and allows to keep only a small set of data in memory at one time. The Graph structure, on the contrary, keeps all information in memory, so may need a large amount of memory.

bundleStarted(producer, bundle_info)

bundleTerminated(producer, bundle_info)

fiberStarted(producer, bundle_info, fiber_info)

fiberTerminated(producer, bundle_info, fiber_info)

newFiberPoint(producer, bundle_info, fiber_info, point)

noMoreBundle(producer)

class BundleToGraphWriter

Bases: BundleToGraph

bundleStarted(producer, bundle_info)

bundleTerminated(producer, bundle_info)

fiberStarted(producer, bundle_info, fiber_info)

fiberTerminated(producer, bundle_info, fiber_info)

newFiberPoint(producer, bundle_info, fiber_info, point)

noMoreBundle(producer)

setFileString()

class BundleTransformer(direct_transformation)

Bases: BundleListener, BundleProducer

Apply a spatial transformation to fiber bundles.

Each point along the bundles is transformed according to the supplied transformation.

This is a BundleListener / BundleProducer stream processing class which applies vector field deformation to bundle data. It can be typically connected to a BundleReader and a BundleWriter.

addFiberPoint()

bundleStarted(producer, bundle_info)

bundleTerminated(producer, bundle_info)

fiberStarted(producer, bundle_info, fiber_info)

fiberTerminated(producer, bundle_info, fiber_info)

newFiberPoint(producer, bundle_info, fiber_info, point)

noMoreBundle(producer)

startBundle()

startFiber()

terminateBundle()

terminateFiber()

class BundleWriter

Bases: BundleListener, PropertySet

Writes bundles information to a bundles file.

BundleWriter is a BundleListener, thus must be connected to a BundleProducer, and is fed by it.

It will write the .bundles format.

bundleStarted(producer, bundle_info)

bundleTerminated(producer, bundle_info)

fiberStarted(producer, bundle_info, fiber_info)

fiberTerminated(producer, bundle_info, fiber_info)

newFiberPoint(producer, bundle_info, fiber_info, point)

noMoreBundle(producer)

setFileString(filename)

Set the output file name.

class BundlesSlicer

Bases: BundleListener

addBundlesSlicerListener()

bundleStarted(producer, bundle_info)

bundleTerminated(producer, bundle_info)

fiberStarted(producer, bundle_info, fiber_info)

fiberTerminated(producer, bundle_info, fiber_info)

newFiberPoint(producer, bundle_info, fiber_info, point)

noMoreBundle(producer)

class BundlesSlicerListener

Bases: wrapper

newBundleSlice()

noMoreBundleSlice()

startBundleSlicing()

terminateBundleSlicing()

class CiftiTools(matrix, smap={})

Bases: wrapper

Parameters:

• mat (rc_ptr_SparseOrDenseMatrix) – matrix with CIFTI header (typically, read from CIFTI format via aims.read())

• smap (map_STRING_S32) – brain structure name to mesh number map: defaults to the result of defaultBrainStructureToMeshMap()

CIFTI-2 shaped matrices manipulation tools.

This class eases manipulation of matrices (SparseOrDenseMatrix) with CIFTI information in their header. CIFTI information specify the nature of data contained in the matrix, and can bring ROIs or parcellations information.

Mainly one can obtain textures to map matrix information onto meshes. Textures may be ROI information (label textures, TimeTexture_S32), or matrix values textures, possibly expanded onto brain regions (TimeTexture_FLOAT in this case).

brainStructureMap()

buildDimensionObjectFromLabelsTexture()

defaultBrainStructureToMeshMap()

Define the brain structure to mesh mapping: several meshes may be involved in CIFTI data mapping (typically a left hemisphere mesh and a right

Returns:

mesh_map – mesh identifier to index mapping

Return type:

map_STRING_S32

dimensionType()

expandedValueTextureFromDimension(dim, other_dim_index_pos)

Get matrix data in textures, possibly expanded to regions if needed.

Parcels data will be expanded to all vertices of each parcel, etc. The resulting textures can be mapped on appropriate brain meshes.

Parameters:

• dim (int) – dimension in the matrix to get info for

• other_dim_index_pos (vector_S32) – position in fixed dimensions. Actually all dimensions must be specified (the size of this list must match the number of dimensions) but the specified dimension position will not be used (since all values will be extracted in textures), and possibly another one (scalars, series, labels dimension will be extracted in time steps or several textures).

Returns:

textures – Scalar or time series data will be stored in texture timepoints. Labels data will be stored in separate textures because they provide possibly different colormaps. In this case the returned list will have the size meshes_number * labels_number, and will be stored in this order: [mesh0_label0, mesh1_label0, .. meshN_label0, mesh0_label1, ..

meshN_label1, .. mesh0_label0, .. meshN_labelM]

Return type:

list of TimeTexture_FLOAT

getBrainStructureMeshNumberOfNodes()

getBrainStructures(dim, keepSurfaces=True, keepVoxels=True)

Retreive brain structures list in a brain models dimension

Parameters:

• dim (int) – dimension in Cifti matrix

• keepSurfaces (bool) – keep or filter out surface models

• keepVoxels (bool) – keep or filter out voxesl models

Returns:

brain_structures – brain structures names list

Return type:

list of string

getDimensionObject()

getIndicesForBrainStructure(dim, struct_name)

Get the list of indices corresponding to a given brain structure in the matrix, on a given dimension.

getIndicesForSurfaceIndices(dim, surface_num, roi_indices)

Get the list of matrix indices corresponding to a given region on a mesh, for a given dimension.

Parameters:

• dim (int) – matrix dimension

• surface_num (int) – surface number (same as given by brainStructureMap())

• roi_indices (list or array of int) – indices in the surface mesh of vertices if interest

Returns:

indices – list of indices in the matrix

Return type:

vector_S32

isMatchingSurface()

isMatchingSurfaceOrTexture()

isMatchingTexture()

matrix()

roiTextureFromDimension(dim)

Get ROI information for a given matrix dimension.

If the matrix dimension defines ROIs (parcels, brain regions), textures defining these regions are built.

If the matrix dimension defines labels, an empty texture will be created, with appropriate colormap information

If the matrix dimensions defines scalars or series, this function will probably not be useful.

Parameters:

dim (int) – dimension in the matrix to get info for

Returns:

textures – textures of regions, possibly with colormaps in headers, for regions, parcels etc. One texture per mesh. For scalars or series, the list will be empty since no particular ROI description is contained in the header for this dimension.

Return type:

list of TimeTexture_S32

setBrainStructureMap()

setMatrix()

valuesDimNum()

valuesDimSize()

class ConeSamplable

Bases: Samplable_FLOAT_3

contains()

class Connectivity

Bases: wrapper

CONNECTIVITY_18_XYZ = 7

CONNECTIVITY_26_XYZ = 8

CONNECTIVITY_4_XY = 0

CONNECTIVITY_4_XYdiag = 28

CONNECTIVITY_4_XZ = 1

CONNECTIVITY_4_XZdiag = 29

CONNECTIVITY_4_YZ = 2

CONNECTIVITY_4_YZdiag = 30

CONNECTIVITY_5_XYminus = 17

CONNECTIVITY_5_XYplus = 18

CONNECTIVITY_5_XZminus = 21

CONNECTIVITY_5_XZplus = 22

CONNECTIVITY_5_XminusY = 15

CONNECTIVITY_5_XminusZ = 19

CONNECTIVITY_5_XplusY = 16

CONNECTIVITY_5_XplusZ = 20

CONNECTIVITY_5_YZminus = 25

CONNECTIVITY_5_YZplus = 26

CONNECTIVITY_5_YminusZ = 23

CONNECTIVITY_5_YplusZ = 24

CONNECTIVITY_6_XYZ = 3

CONNECTIVITY_8_XY = 4

CONNECTIVITY_8_XYZ = 27

CONNECTIVITY_8_XZ = 5

CONNECTIVITY_8_YZ = 6

CONNECTIVITY_9_XY_Zminus = 9

CONNECTIVITY_9_XY_Zplus = 10

CONNECTIVITY_9_XZ_Yminus = 11

CONNECTIVITY_9_XZ_Yplus = 12

CONNECTIVITY_9_YZ_Xminus = 13

CONNECTIVITY_9_YZ_Xplus = 14

class Type

Bases: int

dir()

nbNeighbors()

offset()

type()

type_from_string()

type_string()

type_to_string()

xyzOffset()

class CoordinatesFieldMeshInterpoler

Bases: MeshInterpoler

class Curvature

Bases: GeometricProperties

doIt()

getTextureProperties()

regularize()

class CurvatureFactory

Bases: wrapper

createCurvature()

class CurveSelection

Bases: BundleProducer, BundleListener

addFiberPoint()

bundleStarted(producer, bundle_info)

bundleTerminated(producer, bundle_info)

fiberStarted(producer, bundle_info, fiber_info)

fiberTerminated(producer, bundle_info, fiber_info)

newFiberPoint(producer, bundle_info, fiber_info, point)

noMoreBundle(producer)

startBundle()

startFiber()

terminateBundle()

terminateFiber()

class CutMesh

Bases: wrapper

Cut meshes by a plane. The output of the operation is one cut mesh per input mesh, and possibly a border polygon mesh, and a plane intersection mesh.

The plane mesh is not always correct, it is now preferred to use GLU’s tesselation algorithm.

To use it:

• initialize using a constructor and/or set input parameters (see also the CutTexturedMesh subclasses to handle textured meshes)

• call cut() or cutBorder(), these are the methods actually doing things

• get outputs using cutMeshes(), borderLine(), planeMesh() and CutTexturedMesh.cutTextures()

borderLine()

cut()

cutBorder()

cutMeshes()

planeMesh()

class FastMarching(connectivity='26', process_mid_interface=False)

Bases: wrapper

FastMarching(process_mid_interface)

(2nd form: deprecated constructor, with connectivity 26.)

Parameters:

• connectivity (string) – “26”, “18”, “6”. The connectivity type is only used to build the interfaces between the work region and the seeds: the fast marching itself only uses 6-connectivity.

• process_mid_interface (bool) – If process_mid_interface is false (the default), voronoi boundaries will not be available after propagation.

Fast marching algorithm implementation, for images.

The fast marching is a propagation algorithm which is typically used to perform distance maps. It may use a speed map to locally change the propagation speed and distance. It may also be used to perform a Voronoi diagam, and to get Voronoi regions boundaries.

It is used the following way:

• instantiate a FastMarching object, with specified connectivity

• if needed, set the speed map (or inverse speed map) using setSpeedMap() or setInvSpeedMap()

• propagate using one of the doit() methods. It will return the distanc map.

• Voronoi and boundaries can then be retreived using voronoiVol(), midInterface() or midInterfaceVol()

clearSpeedMap()

doit(vol, worklabel, inlabel, outlabel)

Perform fast marching propagation from a label image “vol”.

This is a simplified interface to the other, more general, doit() method.

Propagation will take place in the region “worklabel”, from seeds “inlabel” and “outlabel”.

Parameters:

• vol (rc_ptr_Volume_S16) – label volume to build distance map from. Contains seeds, propagation (work) region, and possibly forbidden regions

• worklabel (int16) –

• inlabel (int16) –

• outlabel (int16) –

Returns:

distance_map – resulting distance map

Return type:

rc_ptr_Volume_FLOAT

doit(vol, worklabels, seedlabels)

Perform fast marching propagation from a label image “vol”.

Propagation will take place in the regions listed in “worklabels”, from all seeds in the “seedlabels” list.

Parameters:

• vol (rc_ptr_Volume_S16) – label volume to build distance map from. Contains seeds, propagation (work) region, and possibly forbidden regions

• worklabels (set_S16) – WARNING: the propagation labels in worklabels should be positive

• seedlabels (set_S16) –

Returns:

distance_map – resulting distance map

Return type:

rc_ptr_Volume_FLOAT

invSpeedMap()

midInterface(label1, label2)

get the interface between Voronoi regions label1 and label2, as a bucket.

The mid_interface option must have been used when instantiating the FastMarching object, and propagation maust have taken place.

midInterfaceLabels()

Voronoi interfaces labels. Given as a vector of pairs of labels

Returns:

labels – in the shape ((label1, label2), (label3, label4), …)

Return type:

tuple of tuples

midInterfaceVol(label1, label2)

get the interface between Voronoi regions label1 and label2, as a volume.

the mid_interface option must have been used when instantiating the FastMarching object, and propagation maust have taken place.

setInvSpeedMap(invspeed)

Sets an initialized inverse speed map (overrides any previous speed map).

Once a speed map (or inverse speed map) has been setup manually, it will be used during propagation in doit(), for only one run. The speed map data contents will be modified during the process, and the map will not be reusable for other data (seed voxels will be printed in it). The input inverse speed map object will also be modified since it is a shared reference, the algorithm will directly work in it.

Parameters:

invspeed (rc_ptr_Volume_FLOAT) –

setSpeedMap(speed)

Sets an initialized speed map. The inverse speed will be deduced from it.

Once a speed map (or inverse speed map) has been setup manually, it will be used during propagation in doit(), for only one run. The speed map data contents will be modified during the process, and the map will not be reusable for other data (seed voxels will be printed in it).

Parameters:

speed (rc_ptr_Volume_FLOAT) –

setVerbose()

verbose()

voronoiVol()

get the resulting Voronoi regions (after propagation)

class FastMarching_BucketMap_S16(connectivity='26', process_mid_interface=False)

Bases: wrapper

FastMarching_BucketMap_S16(process_mid_interface)

(2nd form: deprecated constructor, with connectivity 26.)

Parameters:

• connectivity (string) – “26”, “18”, “6”. The connectivity type is only used to build the interfaces between the work region and the seeds: the fast marching itself only uses 6-connectivity.

• process_mid_interface (bool) – If process_mid_interface is false (the default), voronoi boundaries will not be available after propagation.

Fast marching algorithm implementation, for buckets.

The fast marching is a propagation algorithm which is typically used to perform distance maps. It may use a speed map to locally change the propagation speed and distance. It may also be used to perform a Voronoi diagam, and to get Voronoi regions boundaries.

It is used the following way:

• instantiate a FastMarching object, with specified connectivity

• if needed, set the speed map (or inverse speed map) using setSpeedMap() or setInvSpeedMap()

• propagate using one of the doit() methods. It will return the distanc map.

• Voronoi and boundaries can then be retreived using voronoiVol(), midInterface() or midInterfaceVol()

clearSpeedMap()

doit(vol, worklabel, inlabel, outlabel)

Perform fast marching propagation from a label bucket “vol”.

This is a simplified interface to the other, more general, doit() method.

Propagation will take place in the region “worklabel”, from seeds “inlabel” and “outlabel”.

Parameters:

• vol (rc_ptr_BucketMap_S16) – label bucket to build distance map from. Contains seeds, propagation (work) region. Propagation outside the bucket will be forbidden.

• worklabel (int16) –

• inlabel (int16) –

• outlabel (int16) –

Returns:

distance_map – resulting distance map

Return type:

rc_ptr_Volume_FLOAT

doit(vol, worklabels, seedlabels)

Perform fast marching propagation from a label bucket “vol”.

Propagation will take place in the regions listed in “worklabels”, from all seeds in the “seedlabels” list.

Parameters:

• vol (rc_ptr_BucketMap_S16) – label bucket to build distance map from. Contains seeds, propagation (work) region, and possibly forbidden regions

• worklabels (set_S16) –

• seedlabels (set_S16) –

Returns:

distance_map – resulting distance map

Return type:

rc_ptr_Volume_FLOAT

midInterface(label1, label2)

get the interface between Voronoi regions label1 and label2, as a bucket.

The mid_interface option must have been used when instantiating the FastMarching object, and propagation maust have taken place.

midInterfaceLabels()

Voronoi interfaces labels. Given as a vector of pairs of labels

Returns:

labels – in the shape ((label1, label2), (label3, label4), …)

Return type:

tuple of tuples

midInterfaceVol(label1, label2)

get the interface between Voronoi regions label1 and label2, as a volume.

the mid_interface option must have been used when instantiating the FastMarching object, and propagation maust have taken place.

setInvSpeedMap(invspeed)

Sets an initialized inverse speed map (overrides any previous speed map).

Parameters:

invspeed (rc_ptr_BucketMap_FLOAT) –

setSpeedMap(speed)

Sets an initialized speed map. The inverse speed will be deduced from it.

Parameters:

speed (rc_ptr_BucketMap_FLOAT) –

setVerbose()

verbose()

voronoiVol()

get the resulting Voronoi regions (after propagation)

class FfdTransformation(*args)

Bases: Transformation3d

FFD vector field deformation transform

Free Form Deformation is the registration technique used to build the vector fields. This class is dedicated to the application of the vector field deformation to transform coordinates.

Vector fields are stored in volumes rc_ptr_Volume_POINT3DF.

ctrlDeformations()

deformation()

dimX()

dimY()

dimZ()

ffdCoord()

getCtrlKnot()

increaseResolution()

isFlat()

isIdentity()

Test if the transformation can safely be omitted

This method must only return true if the transformation behaves exactly like an identity transformation (notably, the transform methods will always return the input coordinates unchanged).

NOTE: Implementors of derived classes may choose to always return false if a test would be difficult to implement or expensive to run.

isXFlat()

isYFlat()

isZFlat()

printControlPointsGrid()

sizeX()

sizeY()

sizeZ()

transformDouble()

transformFloat()

transformPoint3d()

transformPoint3dd()

transformPoint3df()

updateAllCtrlKnot()

updateAllCtrlKnotFromDeformation()

updateCtrlKnot()

updateDimensions()

write()

writeDebugCtrlKnots()

writeDebugDeformations()

class FiberInfo

Bases: wrapper

id()

class Finder

Bases: wrapper

check()

dataType()

extensions()

finderFormat()

format()

header()

objectType()

possibleDataTypes()

registerFormat()

setDataType()

setFormat()

setHeader()

setObjectType()

setPossibleDataTypes()

unregisterFormat()

class FinderFormat

Bases: wrapper

check()

class FiniteElementCurvature

Bases: Curvature

doIt()

class FoldArgOverSegment

Bases: wrapper

dilateBucket()

findSplitLine()

mergeVertices(v1, v2)

merge vertices into v1. v2 is removed from the graph.

printSplitInSkeleton()

splitLineOnBucket()

splitSimpleSurface()

splitVertex()

subdivizeGraph()

subdivizeVertex()

class FoldGraphAttributes

Bases: wrapper

cleanup()

doAll()

getBrainDepth()

getBrainDepthGradX()

getBrainDepthGradY()

getBrainDepthGradZ()

getDepth()

getDepthfactor()

getDilatedDepth()

getDilatedDepthGradX()

getDilatedDepthGradY()

getDilatedDepthGradZ()

getNDepth()

greyAndCSFVolumes()

makeCorticalRelationAttributes()

makeGlobalAttributes()

makeJunctionAttributes()

makeMeshes()

makePliDePassageAttributes()

makeSimpleSurfaceAttributes()

makeSummaryGlobalAttributes()

maxThreads()

mesher()

prepareBrainDepthMap()

prepareDepthMap()

rebuildCorticalRelations()

setMaxThreads()

Sets the maxumum number of threads used in multithreaded-enabled parts. 1 means mono-threaded, 0 means une thread per CPU. A negative value means one thread per CPU, but never use more CPUs than the absolute value of the given number.

thickness()

class GaussianCurvature

Bases: Curvature

doIt()

class GeodesicPath(surface, texCurv, method, strain)

class GeodesicPath(surface, method, strain)

Bases: wrapper

Initializes the geodesic path structures for a given mesh geometry, using a constraint map (curvature, typically). Several methods are available.

Parameters:

• surface (AimsTimeSurface_3_VOID) – mesh to compute geodesic paths or distances on

• texCurv (TimeTexture_FLOAT) – constraint map texture. If not specified, the curvature will be computed and used as constraint.

• method (int) –

  0:

  unconstrained,

  1:

  minimize the constraint map, suitable for sulci using the curvature as constraint,

  2:

  maximize constraint map, suitable for gyri using the curvature as constraint,

  3:

  unconstrained

• strain (int) – weight factor on the constraints map. In practice we use 3 for sulci and gyri.

Geodesic paths or distance maps, using the Dijkstra algorithm

Ex:

from soma import aims, aimsalgo
mesh = aims.read('mesh.gii')
gp = GeodesicPath(mesh, 0, 0)
dmap = TimeTexture('FLOAT')
// get a distance map from vertex no 12
dmax = gp.distanceMap_1_N_ind(12, dmap[0].data(), 0)
aims.write(dmax, 'distance.gii')

It is possible to get distance maps, or paths between two or more points.

distanceMap_1_N_ind()

Compute a distance map from a given point

Parameters:

• source (int) – index of the starting point (vertex number)

• distanceMap (vector_FLOAT) – output distance map, the vector can be empty, it will be filled with as many values as the mesh vertices number.

• type_distance (int) –

  0:

  weighted distance,

  1:

  euclidean distance

Returns:

length – max distance

Return type:

float

longestPath_1_N_ind(source, targets, type_distance)

Parameters:

• source (unsigned) –

• targets (vector_U32) –

• type_distance (int) –

Returns:

• target (unsigned)

• length (float)

longestPath_N_N_ind(points, type_distance)

Parameters:

• points (vector_U32) –

• type_distance (int) –

Returns:

• s (int)

• d (int)

• length (float)

shortestPath_1_1_1_ind(source, middle, target)

Parameters:

• source (unsigned) –

• middle (unsigned) –

• target (unsigned) –

Returns:

path

Return type:

vector_U32

shortestPath_1_1_ind(source, target)

Parameters:

• source (unsigned) –

• target (unsigned) –

Returns:

path

Return type:

vector_U32

shortestPath_1_1_ind(source, target, subset)

Parameters:

• source (unsigned) –

• target (unsigned) –

• subset (TimeTexture_S16) –

Returns:

path

Return type:

vector_U32

shortestPath_1_1_ind_xyz(source, target, indice, coord3D)

Parameters:

• source (unsigned) –

• target (unsigned) –

• indice (vector_U32 (output)) –

• coord3D (vector_POINT3DF (output)) –

shortestPath_1_1_len(source, target)

Parameters:

• source (unsigned) –

• target (unsigned) –

Returns:

length

Return type:

float

shortestPath_1_1_tex(source, target, texturevalue, tex)

Parameters:

• source (unsigned) –

• target (unsigned) –

• texturevalue (float) –

• tex (TimeTexture_S16 (output)) –

shortestPath_1_N_ind(source, targets)

Parameters:

• source (unsigned) –

• targets (vector_U32) –

Returns:

• target (unsigned)

• length (float)

class GeometricProperties

Bases: wrapper

buildSortVerticesNeighborhood()

doAlpha()

doBeta()

doDot()

doGraph()

doNeighbor()

doPhi()

doSimpleAlpha()

doSurface()

doTheta()

getAlpha()

getBeta()

getMesh()

getNeighbor()

getRcMesh()

getSimpleAlpha()

getTriangleNeighbor()

graphToMesh()

sortPolygons()

class GradientAdvection

Bases: wrapper

descend_scalar_field()

doit()

propagate_all_labels()

setPropagationThreshold()

setVerbose()

class GraphManip

Bases: wrapper

attributeColor()

buckets2Volume()

completeGraph()

getICBM2009cTemplateTransform()

transform = aims.GraphManip.getICBM2009cTemplateTransform(graph)

Extract the transformation to the MNI ICBM152 space, shifted to the “most standard” field of view of the template image, the one from the ICBM2009c_nlin_asym template from the MNI. Actually we find various fields of view for the templates. The one we use here is (193, 229, 193). The transform to the “real” ICBM space (0 roughly at AC) is provided in the output transformation header. This space has a fixed transformation with our Aims Talairach, along with the template volume size and voxel size. This space has a fixed transformation with our Aims Talairach. Includes shifts and axes inversions.

getICBMTransform()

transform = aims.GraphManip.getICBMTransform(graph)

Extract the transformation to the MNI ICBM152 space. This space has a fixed transformation with our Aims Talairach.

getPath()

get_element_table()

Get the GraphElementTable as a dict. The dict has the following shape:

{
    syntax_name: {
        id_name: GraphElementCode_object
    }
}

GraphElementCode objects are given as dicts (str, str):

{
    'id': <same_as_key: filename (globals) or attribute for filename (locals)>,
    'attribute': <attribute_name_in_graph_element>,
    'objectType': <type of object>,
    'dataType': <data type of object>,
    'storageType': <'Global', 'Local', or 'GlobalPacked'>,
    'local_file_attribute': <attribute giving the filename for local storage in each graph elememt>,
    'global_index_attribute': <attribute giving the index for global storage in each graph elememt>,
    'global_filename': <filename for global storage>,
    'global_attribute': <attribute>,
    'syntax': <syntax_name>
}

graphFromVolume()

graph = graphFromVolume(vol, background=0, trans=None) graphFromVolume(vol, graph, background=0, trans=None,

automaticBackgroundSearch=True)

builds a ROI graph from a volume of labels

printGraphElementTable()

setAttributeColor()

storeAims()

storeTalairach()

talairach()

volume2Buckets()

class HarmonicCageMeshResampler

Bases: wrapper

computeCoordinates()

coordinate()

coordinates()

getControl()

get_image_coords()

moveControl()

set_keep_image_coords()

class Hierarchy(*args, **kwargs)

Bases: Tree

find(name)

find_color(name, default_color=<class 'KeyError'>)

hasSyntax()

setSyntax()

class IOObjectTypesDictionary

Bases: wrapper

formats()

hasType()

objectsTypes()

class Interpolator(*args)

Bases: RCObject

isValid()

value()

values()

class MaskIterator(*args)

Bases: RCObject

contains()

isValid()

next()

regionName()

restart()

value()

valueMillimeters()

volumeDimension()

voxelSize()

class MeshInterpoler

Bases: wrapper

class InterpolationType

Bases: int

Linear = 0

NearestNeighbour = 1

project()

projectedTriCoord1()

projectedTriCoord2()

projectedTriCoord3()

projectedTriangles()

reloadProjectionParams()

resampleMesh()

resampleTexture()

setDiscontinuityThresholds()

setMeshes()

class PointsDistribution(force=None, move_constaint=None)

Bases: wrapper

Parameters:

• force (aims.PointsDistribution.ForceFunction instance) – force / energy function between 2 points. Takes 2 points and a bool (has_link), and returns the force vector applied to the 1st point. Defaults to a Coulomb force (r_vec/r^3)

• move_constraints (aims.PointsDistribution.MoveConstraints instance) – applies force to a point, and add additional constraints. Takes a point, a force vector, and a step (factor to the force), returns the new point position. Default: projects the force to be tangent to a unit sphere, and renormalizes the resulting point position to stock on the sphere.

Points repartition using forces in a given geometry (on a sphere for instance).

adapted from: http://www.nicoptere.net/blog/index.php/2008/09/20/50-distribution-points-sphere-actionscript http://www.nicoptere.net/AS3/distribution/Distribute.as

Points are moved according to forces, using an energy minimization method.

A few parameters have been added, to allow fitting spheres, or “free” geometries and forces.

Linked points can be defined, with different force behaviours.

class CoulombAndRestoringForce

Bases: ForceFunction

Utility function for sphere_distribution.

Individual Coulomb force between 2 points, plus a restoring force that avoids points expanding away like the universe

energy()

Energy of the force between 2 points

Energy functions are the integral of corresponding forces - they are used to drive the minimization.

force(p1, p2, has_link)

Force between 2 points

Parameters:

• p1 (Point3df) – 1st point

• p2 (Point3df) – 2nd point

• has_link (bool) – True if points p1 and p2 are linked and should be closer

Returns:

force

Return type:

Point3df

class CoulombForce

Bases: ForceFunction

Utility function for sphere_distribution.

Individual Coulomb force between 2 points

energy()

Coulomb energy of the force between 2 points (1/r)

force()

Coulomb electrostatic force between 2 points (r_vec/r^3)

class ForceFunction

Bases: wrapper

Utility force class for sphere_distribution.

Individual force and energy between 2 points

energy()

Energy of the force between 2 points

Energy functions are the integral of corresponding forces - they are used to drive the minimization.

force(p1, p2, has_link)

Force between 2 points

Parameters:

• p1 (Point3df) – 1st point

• p2 (Point3df) – 2nd point

• has_link (bool) – True if points p1 and p2 are linked and should be closer

Returns:

force

Return type:

Point3df

class MoveConstraints

Bases: wrapper

Utility function for sphere_distribution.

Add force f * step to the returned point position pt, and optionally apply some specific position constraints (stick to sphere…)

position(pt, f, step)

The default is unconstrained: just move the requested amount

Parameters:

• pt (Point3df) – point to be moved

• f (Point3df) – force which applies on the point

• step (float) – move step factor

Returns:

new_pos – Position after move and application of constraints

Return type:

Point3df

class SphereMove

Bases: MoveConstraints

Move point constrained to a uinit sphere: project the force to be tangent to the sphere, move the point, then stick it onto the sphere.

position(pt, f, step)

The default is unconstrained: just move the requested amount

Parameters:

• pt (Point3df) – point to be moved

• f (Point3df) – force which applies on the point

• step (float) – move step factor

Returns:

new_pos – Position after move and application of constraints

Return type:

Point3df

distribute(pts, nsteps=100, step=0.01)

get a points distribution on a sphere.

Parameters:

• points (list of 3D points (Point3df)) –

• nsteps (max number of optimization iterations) –

• step (initial move step factor (is adapted during the minimization)) –

distribute(npoints, nsteps=100, step=0.01)

Same as above but point are randomly initialized on a sphere, using the init_points() function

get_coulomb_energy()

get_forces()

init_points(npoints)

Randomly initialize npoints points on a unit sphere

Parameters:

npoints (int) – number of points to initialize

Returns:

points – points 3D positions

Return type:

aims.vector_POINT3DF

setForceFunction(force)

Set the individual force function

Parameters:

force (aims.PointsDistribution.ForceFunction instance) –

setMoveConstraints(move_constaint)

Set the individual move constraints function

Parameters:

move_constaint (aims.PointsDistribution.MoveConstraints instance) –

set_links(links)

Set linked points set

Optional links. Linked points have different forces to make them closer. The links dict maps a point num to a set of linked points: {0: [1, 3], 1: [0, 5], 2: [4], 3: [0]} The map should be symmetrical.

class Quaternion

Bases: wrapper

angle()

axis()

buildFromMatrix(m)

Parameters:

m (vector_FLOAT) – 4x4 matrix in columns (OpenGL-style). Be careful that it is not the expected order for a numpy array using ravel(), which have to be transposed.

buildFromMotion()

compose(value, /)

Return self*value.

fromAxis()

inverse()

norm()

normalized()

setVector()

transform()

transformInverse()

vector()

class RegularBinnedHistogram_DOUBLE

Bases: Histogram_DOUBLE

bins()

doit()

maxDataValue()

minDataValue()

setBins()

unique()

class RegularBinnedHistogram_FLOAT

Bases: Histogram_FLOAT

bins()

doit()

maxDataValue()

minDataValue()

setBins()

unique()

class RegularBinnedHistogram_S16

Bases: Histogram_S16

bins()

doit()

maxDataValue()

minDataValue()

setBins()

unique()

class RegularBinnedHistogram_S32

Bases: Histogram_S32

bins()

doit()

maxDataValue()

minDataValue()

setBins()

unique()

class RegularBinnedHistogram_U16

Bases: Histogram_U16

bins()

doit()

maxDataValue()

minDataValue()

setBins()

unique()

class RegularBinnedHistogram_U32

Bases: Histogram_U32

bins()

doit()

maxDataValue()

minDataValue()

setBins()

unique()

class RegularBinnedHistogram_U8

Bases: Histogram_U8

bins()

doit()

maxDataValue()

minDataValue()

setBins()

unique()

class ResamplerFactory_DOUBLE

Bases: wrapper

ResamplerFactory classes are used to instantiate a Resampler object for the chosen interpolation type. The main method is getResampler().

Cubic = 3

Linear = 1

MajorityLabel = 101

Median = 201

NearestNeighbor = 0

Quadratic = 2

Quartic = 4

Quintic = 5

class ResamplerType

Bases: int

SeventhOrder = 7

SixthOrder = 6

getResampler(order) → resampler

Instantiate a Resampler of the given order.

Parameters:

order (int) – order of interpolation: 0 is nearest neighbour (no interpolation), 1 is linear, 3 is cubic, etc. up to 7th order.

Returns:

result – a new instance of the selected resampler type

Return type:

Resampler_DOUBLE

class ResamplerFactory_FLOAT

Bases: wrapper

ResamplerFactory classes are used to instantiate a Resampler object for the chosen interpolation type. The main method is getResampler().

Cubic = 3

Linear = 1

MajorityLabel = 101

Median = 201

NearestNeighbor = 0

Quadratic = 2

Quartic = 4

Quintic = 5

class ResamplerType

Bases: int

SeventhOrder = 7

SixthOrder = 6

getResampler(order) → resampler

Instantiate a Resampler of the given order.

Parameters:

order (int) – order of interpolation: 0 is nearest neighbour (no interpolation), 1 is linear, 3 is cubic, etc. up to 7th order.

Returns:

result – a new instance of the selected resampler type

Return type:

Resampler_FLOAT

class ResamplerFactory_HSV

Bases: wrapper

ResamplerFactory classes are used to instantiate a Resampler object for the chosen interpolation type. The main method is getResampler().

Cubic = 3

Linear = 1

MajorityLabel = 101

Median = 201

NearestNeighbor = 0

Quadratic = 2

Quartic = 4

Quintic = 5

class ResamplerType

Bases: int

SeventhOrder = 7

SixthOrder = 6

getResampler(order) → resampler

Instantiate a Resampler of the given order.

Parameters:

order (int) – order of interpolation: 0 is nearest neighbour (no interpolation), 1 is linear, 3 is cubic, etc. up to 7th order.

Returns:

result – a new instance of the selected resampler type

Return type:

Resampler_HSV

class ResamplerFactory_POINT3DF

Bases: wrapper

ResamplerFactory classes are used to instantiate a Resampler object for the chosen interpolation type. The main method is getResampler().

Cubic = 3

Linear = 1

MajorityLabel = 101

Median = 201

NearestNeighbor = 0

Quadratic = 2

Quartic = 4

Quintic = 5

class ResamplerType

Bases: int

SeventhOrder = 7

SixthOrder = 6

getResampler(order) → resampler

Instantiate a Resampler of the given order.

Parameters:

order (int) – order of interpolation: 0 is nearest neighbour (no interpolation), 1 is linear, 3 is cubic, etc. up to 7th order.

Returns:

result – a new instance of the selected resampler type

Return type:

Resampler_POINT3DF

class ResamplerFactory_RGB

Bases: wrapper

ResamplerFactory classes are used to instantiate a Resampler object for the chosen interpolation type. The main method is getResampler().

Cubic = 3

Linear = 1

MajorityLabel = 101

Median = 201

NearestNeighbor = 0

Quadratic = 2

Quartic = 4

Quintic = 5

class ResamplerType

Bases: int

SeventhOrder = 7

SixthOrder = 6

getResampler(order) → resampler

Instantiate a Resampler of the given order.

Parameters:

order (int) – order of interpolation: 0 is nearest neighbour (no interpolation), 1 is linear, 3 is cubic, etc. up to 7th order.

Returns:

result – a new instance of the selected resampler type

Return type:

Resampler_RGB

class ResamplerFactory_RGBA

Bases: wrapper

ResamplerFactory classes are used to instantiate a Resampler object for the chosen interpolation type. The main method is getResampler().

Cubic = 3

Linear = 1

MajorityLabel = 101

Median = 201

NearestNeighbor = 0

Quadratic = 2

Quartic = 4

Quintic = 5

class ResamplerType

Bases: int

SeventhOrder = 7

SixthOrder = 6

getResampler(order) → resampler

Instantiate a Resampler of the given order.

Parameters:

order (int) – order of interpolation: 0 is nearest neighbour (no interpolation), 1 is linear, 3 is cubic, etc. up to 7th order.

Returns:

result – a new instance of the selected resampler type

Return type:

Resampler_RGBA

class ResamplerFactory_S16

Bases: wrapper

ResamplerFactory classes are used to instantiate a Resampler object for the chosen interpolation type. The main method is getResampler().

Cubic = 3

Linear = 1

MajorityLabel = 101

Median = 201

NearestNeighbor = 0

Quadratic = 2

Quartic = 4

Quintic = 5

class ResamplerType

Bases: int

SeventhOrder = 7

SixthOrder = 6

getResampler(order) → resampler

Instantiate a Resampler of the given order.

Parameters:

order (int) – order of interpolation: 0 is nearest neighbour (no interpolation), 1 is linear, 3 is cubic, etc. up to 7th order.

Returns:

result – a new instance of the selected resampler type

Return type:

Resampler_S16

class ResamplerFactory_S32

Bases: wrapper

ResamplerFactory classes are used to instantiate a Resampler object for the chosen interpolation type. The main method is getResampler().

Cubic = 3

Linear = 1

MajorityLabel = 101

Median = 201

NearestNeighbor = 0

Quadratic = 2

Quartic = 4

Quintic = 5

class ResamplerType

Bases: int

SeventhOrder = 7

SixthOrder = 6

getResampler(order) → resampler

Instantiate a Resampler of the given order.

Parameters:

order (int) – order of interpolation: 0 is nearest neighbour (no interpolation), 1 is linear, 3 is cubic, etc. up to 7th order.

Returns:

result – a new instance of the selected resampler type

Return type:

Resampler_S32

class ResamplerFactory_U16

Bases: wrapper

ResamplerFactory classes are used to instantiate a Resampler object for the chosen interpolation type. The main method is getResampler().

Cubic = 3

Linear = 1

MajorityLabel = 101

Median = 201

NearestNeighbor = 0

Quadratic = 2

Quartic = 4

Quintic = 5

class ResamplerType

Bases: int

SeventhOrder = 7

SixthOrder = 6

getResampler(order) → resampler

Instantiate a Resampler of the given order.

Parameters:

order (int) – order of interpolation: 0 is nearest neighbour (no interpolation), 1 is linear, 3 is cubic, etc. up to 7th order.

Returns:

result – a new instance of the selected resampler type

Return type:

Resampler_U16

class ResamplerFactory_U32

Bases: wrapper

ResamplerFactory classes are used to instantiate a Resampler object for the chosen interpolation type. The main method is getResampler().

Cubic = 3

Linear = 1

MajorityLabel = 101

Median = 201

NearestNeighbor = 0

Quadratic = 2

Quartic = 4

Quintic = 5

class ResamplerType

Bases: int

SeventhOrder = 7

SixthOrder = 6

getResampler(order) → resampler

Instantiate a Resampler of the given order.

Parameters:

order (int) – order of interpolation: 0 is nearest neighbour (no interpolation), 1 is linear, 3 is cubic, etc. up to 7th order.

Returns:

result – a new instance of the selected resampler type

Return type:

Resampler_U32

class ResamplerFactory_U8

Bases: wrapper

ResamplerFactory classes are used to instantiate a Resampler object for the chosen interpolation type. The main method is getResampler().

Cubic = 3

Linear = 1

MajorityLabel = 101

Median = 201

NearestNeighbor = 0

Quadratic = 2

Quartic = 4

Quintic = 5

class ResamplerType

Bases: int

SeventhOrder = 7

SixthOrder = 6

getResampler(order) → resampler

Instantiate a Resampler of the given order.

Parameters:

order (int) – order of interpolation: 0 is nearest neighbour (no interpolation), 1 is linear, 3 is cubic, etc. up to 7th order.

Returns:

result – a new instance of the selected resampler type

Return type:

Resampler_U8

class RoiDiff

Bases: wrapper

class DiffStat

Bases: wrapper

dice

g2_bucket

matching_voxels

unmatching_voxels

diff()

globalStats()

graph2LabelVolume()

mismatch_bucket()

roiNames()

roiNamesInv()

statsByLabel()

writeCSV()

class RoiIterator(*args)

Bases: RCObject

count()

isValid()

maskIterator()

next()

regionName()

restart()

setRegionNameAttributes(attributes)

set region name attribute in graph. Normally “name” or “label”. If several values are provided, attributes are searched in each graph vertex, in that order. If the attributes list is empty, then the graph “label_property” attribute will be used, and if it is not specified there, the default search list (“name”, “label”) will be used.

class SimpleBundlesSlicer

Bases: BundlesSlicer

bundleStarted(producer, bundle_info)

bundleTerminated(producer, bundle_info)

fiberStarted(producer, bundle_info, fiber_info)

fiberTerminated(producer, bundle_info, fiber_info)

newFiberPoint(producer, bundle_info, fiber_info, point)

noMoreBundle(producer)

class Spam

Bases: SpamBase

class SpamBase

Bases: wrapper

prodlikelihoods()

set_bb_talairach_offset()

set_bb_talairach_size()

set_img_density()

class SpamFromLikelihood

Bases: SpamBase

class SparseMatrix(*args)

Bases: RCObject

erase_element()

fill()

getColumn()

getComposition()

getNonZeroElementCount()

getRow()

getSize1()

getSize2()

getTrace()

getTransposition()

hasElement()

header()

isSquare()

read()

reallocate()

setColumn()

setDiagonal()

setIdentity()

setRow()

setZero()

transpose()

write()

class SparseOrDenseMatrix(*args)

Bases: RCObject

asDense()

asSparse()

denseMatrix()

erase_element()

freeColumn()

freeRow()

getColumn()

getNonZeroElementCount()

getRow()

getSize()

getSize1()

getSize2()

hasElement()

header()

isDense()

isOptimalShape()

muteToDense()

muteToOptimalShape()

muteToSparse()

read()

readAll()

readColumn()

readRow()

reallocate()

setColumn()

setHeader()

setMatrix()

setRow()

set_element()

sparseMatrix()

subMatrix()

write()

class SphereSamplable

Bases: Samplable_FLOAT_3

contains()

class SplineFfd(*args)

Bases: FfdTransformation

FFD vector field deformation transform

Free Form Deformation is the registration technique used to build the vector fields. This class is dedicated to the application of the vector field deformation to transform coordinates.

Vector fields are stored in volumes rc_ptr_Volume_POINT3DF.

This Spline FFD uses cubic spline interpolation between displacement vectors to process transformed coordinates. See TrilinearFfd for a variant using trilinear interpolation.

This class is the “base” vector field deformation class, which can perform point-to-point transformation. It is used by various higher-level classes or functions to work on higher-level objects:

To resample full 2D or 3D images, see the Resampler class and its derived classes (see also ResamplerFactory).

As a Transformation3d specialization, the main method of this class is the transform() method, which actually performs 3D coordinates transformation. The other methods can be seen as “internal machinery”.

see transformMesh, transformBucket, transformGraph and BundleTransformer to apply vector field deformations to various types of objects.

spline3()

transformDouble()

transformFloat()

transformPoint3d()

transformPoint3dd()

transformPoint3df()

class StandardReferentials

Bases: wrapper

acPcReferential()

identifer (str) for the Taialairach/AIMS space

acPcReferentialID()

identifer (UUID str) for the Talairach/AIMS space

commonScannerBasedReferential()

commonScannerBasedReferentialID()

icbm2009cTemplateHeader()

hdr = aims.StandardReferentials.icbm2009cTemplateHeader() Return a header with size and characteristics of the ICBM2009c MNI template volume.

mniTemplateReferential()

identifer (str) for the MNI/ICBM space

mniTemplateReferentialID()

identifer (UUID str) for the MNI/ICBM space

talairachReferential()

identifer (str) for the Talairach/CIFTI space

talairachToICBM()

talairachToICBM2009cTemplate()

trans = aims.StandardReferentials.talairachToICBM2009cTemplate()

Transformation between the ICBM152 standard space and the ICBM152 template space.

includes shifts and axes inversions.

This is the “most standard” field of view of the template image, the one from the ICBM2009c_nlin_asym template from the MNI. Actually we find various fields of view for the templates. The one we use here is (193, 229, 193). The transform to the “real” ICBM space (0 roughly at AC) is provided in the output transformation header. This space has a fixed transformation with our Aims Talairach, along with the template volume size and voxel size. This space has a fixed transformation with our Aims Talairach.

class SurfaceGenerator

Bases: wrapper

Surface Generator Object. Available Methods are :

• cube(center_p, radius_f, smoothnormal_b=false)

• cylinder(p1_p, p2_p, radius1_f, radius2_f, nfacets_i, closed_b, smooth_b=false)

• cone(arrow_p, base_p, radius_f, nfacets_i, closed_b, smooth_b=false)

• arrow(arrow_p, base_p, radius_f, arrowradius_f, nfacets_i, arrowlengthfract_f)

• icosahedron(center_p, radius_f)

• sphere(center_p, radius_f, nfacets_i)

• icosphere(center_p, radius_f, nfacets_i)

With arguments suffix _f:float, _i:int, _b:bool, _p: Point3df or 3-tuple

Alternatively, all those may be called with a GenericObject as only parameter.

This doc might not be up-to-date, use the printDescription() method for more info.

arrow()

static arrow( dictionary ) See the description() and printDescription() methods for more information.

static arrow( Point3df arrowhead, Point3df base, float headradius, float arrowradius, unsigned nfaces, float arrowlengthfactor )

circle_wireframe()

Circle, or part of circle.

center, radius are classical. nseg is the number of segments in the circle polygon normal is a normal vector to the circle plane. startdir is a vector in the circle plane determining the beginning of angles (circle ray). startangle, stopangle are meant to make parts of circle

cone()

static cone( dictionary ) See the description() and printDescription() methods for more information.

static cone( Point3df arrowhead, Point3df base, float radius, unsigned nfaces, bool closed, bool smooth=False )

cube()

static cube( dictionary ) See the description() and printDescription() methods for more information.

static cube( Point3df center, float radius, bool smoothnormals=False )

cylinder()

static cylinder( dictionary ) See the description() and printDescription() methods for more information.

static cylinder( Point3df center1, Point3df center2, float radius1, float radius2, unsigned nfaces, bool closed, bool smooth=False )

description()

description_wireframe()

ellipse()

static ellipse( dictionary ) See the description() and printDescription() methods for more information.

static ellipse( Point3df center, float radius1, float radius2, unsigned nfaces, bool uniquevertices=False )

generate()

generate_wireframe()

grid(dict)

See the description() and printDescription() methods for more information.

grid(Point3df boundingbox_min, Point3df boundingbox_max, Point3df grid_sampling) Regular, wireframe grid

icosahedron()

static icosahedron( dictionary ) See the description() and printDescription() methods for more information.

static icosahedron( Point3df center, float radius )

icosphere(dictionary)

See the description() and printDescription() methods for more information.

icosphere( Point3df center, float radius, unsigned nfaces=320 )

Compared to sphere() which performs meridian / parallels tesselation, icosphere over-segments an icosahedron to get equal, equilateral triangles.

parallelepiped(boundingbox_min, boundingbox_max, smooth=False)

Parameters:

• boundingbox_min (Point3df) – “lower bound” corner position

• boundingbox_min – “upper bound” corner position

• smooth (bool) – if True, make smooth faces and shared vertices in corners

parallelepiped_wireframe(Point3df boundingbox_min, Point3df boundingbox_max)

printDescription()

printDescription_wireframe()

sphere()

static sphere( dictionary ) See the description() and printDescription() methods for more information.

static sphere( Point3df center, float radius, unsigned nfaces, bool uniquevertices=False )

class SurfaceManip

Bases: wrapper

Surface Manipulation Object. All mehtods are static in this class, it is just a means of grouping functions.

checkMeshIntersect()

cutMesh(in_mesh, plane, cut_mesh, border_line)

Cut a mesh by a plane and that’s all.

Parameters:

• in_mesh (AimsSurfaceTriangle) – Triangular mesh to be cut.

• plane (Point4df) – cut plane equation (4 coefs)

• cut_mesh (AimsSurfaceTriangle) – output cut mesh (the part satisfying the plane equation). Polygons crossing the plane will be cut into smaller ones.

• border_line (AimsTimeSurface_2_VOID) – output cut section polygon

Return type:

None

invertSurfacePolygons(mesh)

Invert polygons order (flips 2 vertex indices in each triangle) to flip its interior / exterior notions (used by OpenGL rendering). The input mesh is modified in-place.

joinTexturedMesh()

Join a mesh and a texture into a textured mesh

lineDirections(segments_mesh)

calculate directions of a line mesh, for each vertex

Parameters:

segments_mesh (AimsTimeSurface_2_VOID) –

Returns:

directions

Return type:

vector_POINT3DF

meshArea()

Surface area of a triangular mesh, in mm^2

Surface areas of regions of a triangular mesh, in mm^2. Regions are given as a texture.

meshDensity(mesh, as_distance=False)

Calculate a mesh density: inverse of the average edges distance.

Parameters:

• mesh (AimsSurfaceTriangle) –

• as_distance (bool (optional)) – if True, the average distance is not inverted, thus the output is an average distance map.

Returns:

density_texture

Return type:

TimeTexture_FLOAT

meshEdgeLengthRatioTexture(numerator_mesh, denominator_mesh)

Calculate an edge length ratio in edges of two meshes with the same topology. The max length ratios of edges is kept for each vertex.

Parameters:

• numerator_mesh (AimsSurfaceTriangle) –

• denominator_mesh (AimsSurfaceTriangle) –

Returns:

ratio_texture

Return type:

TimeTexture_FLOAT

meshExtract(mesh, texture, label_value)

Extracts a sub-mesh defined by a texture label value.

Returns:

• sub_mesh (AimsTimeSurface_3_VOID) – extracted sub-mesh

• vertices (vector_ULONG) – indices of extracted vertices

meshMerge(input_output_mesh, input_mesh)

Concatenates the second mesh to the first one. The first argument will be modified.

Parameters:

• input_output_mesh (AimsTimeSurface_3_VOID) – first mesh. Will be modified to be the output.

• input_mesh (AimsTimeSurface_3_VOID) – second mesh to be appended to the first one.

Return type:

None

meshPlanarPolygon(plane, polygon)

Tesselate a planar polygon to fill it by a triangular mesh

Parameters:

• plane (Point4df) – plane equation

• polygon (AimsTimeSurface_2_VOID) – planar polygon to tesselate. Typically, the output of cutMesh()

Returns:

planar_mesh – the mesh filling the polygon

Return type:

AimsSurfaceTriangle

meshTextureBoundary(mesh, label_texture, region_value)

Extracts the boundary of region of value <region_value> of the input texture, on the mesh.

If region_value is negative, take boundaries of all regions. The input texture is a label texture.

Parameters:

• mesh (AimsSurfaceTriangle) – input mesh to extract boundary on

• label_texture (TimeTexture_S16, TimeTexture_S32, or TimeTexture_FLOAT) – label texture defining regions on the mesh

• region_value (int16, int32 or float) – label of the desired region

Returns:

boundary – output segments mesh (filar mesh) for the boundary

Return type:

AimsTimeSurface_2_VOID

meshTransform(mesh, transformation)

Apply linear coordinates transformation to a mesh. The input mesh will be modified in-place.

Parameters:

• mesh (AimsTimeSurface_3_VOID or AimsTimeSurface_2_VOID) – mesh to be transformed. Will be modified.

• transformation (AffineTransformation3d) – Linear transformation matrix

Return type:

None

meshVolume(mesh)

Volume inside a triangular mesh, in mm^3. The mesh must enclode a closed volume, with no holes, otherwise the volume processing will “leak” and will be wrong.

nearestPointToMesh()

rasterizeMesh(mesh, volume, value=2)

Rasterize polygons into a volume.

Parameters:

• mesh (AimsTimeSurface_*) –

• volume (Volume_S16) – Volume to write mesh imprint to

• value (int) – label value used to write the mesh imprint in the volume

rasterizeMeshWireframe(mesh, volume, value=1)

Rasterize polygons edges into a volume.

Parameters:

• mesh (AimsTimeSurface_*) –

• volume (Volume_S16) – Volume to write mesh imprint to

• value (int) – label value used to write the mesh imprint in the volume

refineMeshTri4(mesh, selected_polygons=None)

Refine a mesh by subdivising every triangle into 4 smaller ones.

Parameters:

• mesh (AimsSurfaceTriangle) – mesh to be refined

• selected_polygons (vector_U32) – optional list of polygons indices to be selectively refined. Others will not be changed, unless they are at the border of a refined one, in which case they have to be split in some way.

Returns:

refined_mesh – refined mesh

Return type:

AimsSurfaceTriangle

sortPolygonsAlongDirection(mesh, timestep, direction)

Sort polygons along a given direction. Polygons centers will be used for sorting. Only one timestep is performed (to be fast).

Parameters:

• mesh (AimsTimeSurface_*) – The mesh will be modified.

• timestep (int) –

• direction (Point3df) –

sortPolygonsAlongDirection(mesh, timestep, direction)

Sort polygons along a given direction. Polygons centers will be used for sorting. Only one timestep is performed (to be fast).

Parameters:

• mesh (AimstimeSurface_*) – The mesh will be modified.

• timestep (int) –

• direction (Point3df) –

sortPolygonsAlongDirection(mesh, timestep, direction)

Sort polygons along a given direction. Polygons centers will be used for sorting. Only one timestep is performed (to be fast).

Parameters:

• mesh (AimstimeSurface_*) – The mesh will be modified.

• timestep (int) –

• direction (Point3df) –

splitTexturedMesh()

Split a textured mesh into a mesh and a texture

surfaceNeighbours()

class TransformationChain3d(*args)

Bases: Transformation3d

Container for a composition of multiple transformations.

This container holds a list of transformations, and acts as the composition of all transformations. Transformations are composed from the front to the back of the list:

chain = TransformationChain3d()
chain.push_back(t1)
chain.push_back(t2)
# chain->transform(p) == t2.transform(t1.transform(p))

warning: Do not modify the transformations once you have passed them to push_back() or push_front(): it is unspecified if the changes will be noticed by TransformationChain3d (a reference to the same object may be kept internally, or a copy could be made). This behaviour will allow optimizations to be implemented (e.g. composing adjacent affine transformations by multiplying their matrices).

getInverse()

invertible()

isIdentity()

Test if the transformation can safely be omitted

This method must only return true if the transformation behaves exactly like an identity transformation (notably, the transform methods will always return the input coordinates unchanged).

NOTE: Implementors of derived classes may choose to always return false if a test would be difficult to implement or expensive to run.

pop_back()

Remove the last transformation from the list

pop_front()

Remove the first transformation from the list

push_back(transformation)

Add a transformation to the back of the list (applied last)

push_front(transformation)

Add a transformation to the front of the list (applied first)

simplify()

Compute a simpler transformation that is equivalent to the chain.

The transformation chain is simplified by applying the following rules, so that it should provide equivalent results to the original chain, up to numerical precision:

• The simplification is applied recursively to any sub-chain.

• Transformations of the simplified sub-chains are inserted at the top level (i.e. the simplified chain is flat, it contains no sub-chains).

• Consecutive affine transformations are composed using matrix multiplication.

• Identity transforms (i.e. transforms for which Transformation::isIdentity() returns true) are removed from the list.

• If the simplified chain consists of only one transformation, no chain is returned, the contained transformation is returned directly. However, the transformation is not necessarily the same instance that was inserted in the chain (it will be a copy if it is an AffineTransformation3d).

• If the simplified chain is empty, an empty chain is returned.

No deep copy is made, so the result can contain pointers to the same transformations as the original chain.

size()

transformDouble()

transformFloat()

transformPoint3d()

transformPoint3dd()

transformPoint3df()

class TransformationGraph3d(*args, **kwargs)

Bases: Graph

Manage transformations (affine and non-linear) transformations graph.

It maintains a graph of directed transformations (vertices are referentials, edges are 3D transformations).

It can be populated from a dictionary (Object) which can be read from a JSON or YAML file, and performs lazy-loading: transformations are actually loaded when they are used, more precisely in getTransformation() and when building a chain of composed transformations.

The graph is oriented, and does not manage inverse transforms. We could thing this could be done automatically for affine or other inversible transformations, but the lazy loading feature does not allow to know if a not yet loaded transform will be inversible or not. So this has to be done manually for now.

The graph populates with composed transforms when they are used: indirect paths from a referential to another are generated when needed, and stored in the graph as “deduced” transforms. Later access will thus use this cache instead of reccomputing it. A drawback, thus, is that the graph has to be used “statically”: any modification in the graph structure, or in any of its transformations, should invalidate a number of deduced, cached ones, which we do not handle for now (it’s a quite difficult problem to manage it efficiently). To date the only solution is to completely clear the cached transforms (clearCache()) after any modification.

The TransformationGraph3d structure is a Graph, and its elements are Vertex or Edge objects. To manipulate transformations, the API generally allows to use identifiers (generally UUIDs) for elements, and the Transformation objects are accessed through the “transformation” property of edges, or using the transformation() convenience method:

ref1 = tgraph.referentialById(“23df7ce8-e405-bc31-3863-d543e3cc89e5”) trans_edge = tgraph.getTransformation(

“23df7ce8-e405-bc31-3863-d543e3cc89e5”, “52929a27-6838-1d08-d6fc-7905ed9413a0”)

if trans_edge:

trans = tgraph.transformation(trans_edge)

see also: https://hbp-spatial-backend.apps.hbp.eu/swagger-ui#/api_v1/get_v1_transform_point

asDict()

convert to a dict-like structure compatible with loadTransformationsGraph()

Parameters:

• affine_only (bool) – if true, inclue only affine transformations

• allow_read (bool) – if true, and if affine_only or embed_affines is also true, all affine transformations will be read in order to determine which are affine. Otherwise only those already loaded in memory (via the lazy reading mechanism) will be known to be affine. This parameter has no effect on non-affine transformations.

• embed_affines (bool) –

  if true, affine transformations are not recorded as a

  file name (.trm format), but as an embedded 4x4 matrix.

clearCache(chain_only=False)

remove deduced transformations (built from composition).

If chain_only is true, then inverses of direct transforms are not removed.

clone()

currentValue()

getScalar()

getString()

getTransformChain()

Get a transformation chain between two vertices.

You normally don’t need to call this method directly, il is called through getTransformation( src_ref, dst_ref, true ). This method however does not modify the transformations graph and does not register the combined transformation. It will, however, load lazy-loading transformations.

getTransformation()

edge = tgraph.getTransformation(src_ref, dst_ref, allow_compose=False)

Get the transformation between source_ref and dst_ref. If it is not a registered transformation, return None. src_ref annd dst_ref may be string IDs or Vertex objects.

If allow_compose is True and the transformation is not found, then a transformations chain path is looked for. If a matching one is found, it is then registered in the graph to allow fast access later. The drawback of this register operation is that it cannot react to changes in the transformation chain (if a new transformation is added and could make a shorter path, it will not be taken into account).

getTransformation_raw(src_ref, dst_ref)

same as getTransformation(), but do not perform lazy loading

hasSyntax()

has_key()

intKey()

isArray()

isDictionary()

isDictionaryIterator()

isDynArray()

isIterable()

isIterator()

isValid()

key()

loadAffineTransformations()

Load all affine transformations.

loadTransformationsGraph()

Load a full transformations graph from a dict-like object.

The description dict may typically be read from a .json or a .yaml file.

The description is organized as a 2-level dictionary:

{
    source_ref_id: {
        dest_ref_id1: transformation_filename1,
        dest_ref_id2: transformation_filename2,
    },
    ...
}

A referential ID is a string which may represent an UUID, or a name.

A transformatioon filename may be an affine (.trm) or non-linear (.ima) transformation file, or an empty string to represent an identity transformation.

The transformation files are found relatively to the directory given as the dirname parameter.

Alternatively to file names, an affine transformation may be given directly as its 4x4 matrix, written as a line vector (all 16 coefficients in a vecotr, describing the matrix horizontally). Ex:

{
    source_ref_id: {
        dest_ref_id1: [1, 0, 0, 0,
                       0, 1, 0, 0,
                       0, 0, 1, 0,
                       0, 0, 0, 1],
    },
    ...
}

objectIterator()

referentialById()

Get the vertex (referential) with given ID

registerInverseTransformations(loadAffines=False)

register inverse transformations when they can be obtained.

This can be done only for loaded transformations. So the lazy loading feature will prevent for it to work on not already loaded transformations, since we cannot know if they are invertible before they are loaded.

For this reason, the loadAffines parameter allows to load affine transforms and register their inverses.

registerTransformation()

Add (or register) the given transformation in the transformations graph.

transform may be a filename, or a Transformation instance. a Transformation is supposed to be a non-linear FFD (Free Form Deformation), not a linear transformation. If transform is a string, it may be: - an empty string will be an identity transformation - a .trm file will be an affine transformation, and will be passed to

the builtin Anatomist system

• another file (.ima) will be a FFD transformation file and will be registered as its filename. Loading will happen only when the transformation is used, in get_transformation().

setSyntax()

size()

transformation()

Get the Transformation3d object inside an edge. The returned reference counting pointer may contain a null pointer.

Get the Transformation3d object for the given UUID. The returned reference counting pointer may contain a null pointer.

transformationById()

Get the edge (transformation) with given ID

type()

updateIds()

Update the internal UUIDs cache. Needs to be done after changes in elements UUIDs or insertion / deletions

class TrilinearFfd(*args)

Bases: FfdTransformation

FFD vector field deformation transform

Free Form Deformation is the registration technique used to build the vector fields. This class is dedicated to the application of the vector field deformation to transform coordinates.

This is a variant of SplineFfd which is performing trilinear interpolation between displacement vectors. See SplineFfd for details.

transformDouble()

transformFloat()

transformPoint3d()

transformPoint3dd()

transformPoint3df()

class VertexRemover

Bases: wrapper

A class to remove a vertex from a mesh, and remeshing the hole.

NB: remeshing is not always possible, therefore removing a given point in a mesh is not always possible. Therefore, it may be important to check the return value of operator() to check if the point has actually been removed.

geometricProperties()

floodFill()

getLinearInterpolator()

getMaskIterator()

getRoiIterator()

giftiColormap()

class knn

Bases: simplewrapper

class Database

Bases: wrapper

init()

class Knn

Bases: wrapper

find()

class KnnBruteForce

Bases: Knn

class KnnFriedman

Bases: Knn

precompute()

class KnnGlobalFriedman

Bases: Knn

precompute()

mask()

maskWithVolume()

class meshdistance

Bases: simplewrapper

MeshDilation()

MeshDistance()

dist_tex = MeshDistance(mesh, inittex, allowUnreached)

inittex values have the following meaning:

0: propagation domain n>0: seed (distance 0) -1: forbidden

MeshErosion()

MeshVoronoi(mesh, inittex, background, forbidden, dist, connexity, object)

MeshVoronoi(mesh, inittex, dist, connexity, object) → None

Compute a geodesic voronoi diagram (dist = MAX_FLOAT,object=true ) of objects defined in inittex. The background has the label Back and the objects have a positive label. The distance can be euclidean geodesic (connexity=false) or just the connexity of the triangulation(connexity=true) This function can as well be used for dilation(object=true) / erosion(object=false) using the parameter dist as the size of the structuring element.

Parameters:

• mesh (AimsSurfaceTriangle) –

• inittex (TimeTexture_S16) –

• background (short) –

• forbidden (short) –

• dist (float) –

• connexity (bool) –

• object (bool) –

Returns:

voronoi_texture

Return type:

TimeTexture_S16

MeshVoronoiStepbyStep()

textureMax()

transformBoundingBox()

class soma.aims.carto

Bases: simplewrapper

class AllocatorContext

Bases: wrapper

Allocation context specifications. This object is used when memory must be allocated for large objects (volumes, arrays…), especially for data which will be read from disk. It allows to specify how the memory will be used (read-only, read-write, how much…) to allow to decide whether any memory mapping techniques should be used or not.

accessMode()

allocatorType()

allowsMemoryMapping()

dataSource()

dataSourceInfo()

isAllocated()

setAccessMode()

setAllowsMemoryMapping()

setDataSource()

setDataSourceInfo()

setUseFactor()

useFactor()

class AllocatorStrategy

Bases: wrapper

Memory management strategy helper. Contains mainly constants and a memory query function.

CopyMap = 2

class DataAccess

Bases: int

Data access mode

InternalModif:

random access in memory, disk data (memmapped) should not be overwritten.

ReadOnly:

read only in memory. Accessing data in write mode may cause a crash.

ReadWrite:

read/write both in memory and on disk, if memmapped.

NotOwner:

data is unallocated, or its ownership belongs to a proxy object.

InternalModif = 0

MAP = 1

MAP_COPY = 2

MAP_RO = 3

MAP_RW = 4

MEM = 0

class MappingMode

Bases: int

Memory mapping modes

Memory, (MEM):

in-memory allocation

CopyMap, (MAP, MAP_COPY):

data is copied into a memmaped file (accessed read/write)

ReadOnlyMap, (MAP_RO):

read-only memory mapping

ReadWriteMap, (MAP_RW):

read/write memory mapping: modifying the memory also modifies the file on disk.

Unallocated:

not allocated.

Memory = 0

NotOwner = 3

ReadOnly = 1

ReadOnlyMap = 3

ReadWrite = 2

ReadWriteMap = 4

Unallocated = 5

allocator()

Create an AllocatorContext object with the required mapping mode

memSizes()

Check the current system memory and return the amount of RAM, free RAM, and swap.

class ContinuousRoi(*args)

Bases: Roi

contains()

class DiscreteRoi(*args)

Bases: Roi

count()

getSiteIterator()

holds()

class FormatDictionary_AffineTransformation3d

Bases: wrapper

readExtensions()

readFormats()

writeExtensions()

writeFormats()

class FormatDictionary_AimsTimeSurface_2_FLOAT

Bases: wrapper

readExtensions()

readFormats()

writeExtensions()

writeFormats()

class FormatDictionary_AimsTimeSurface_2_POINT2DF

Bases: wrapper

readExtensions()

readFormats()

writeExtensions()

writeFormats()

class FormatDictionary_AimsTimeSurface_2_VOID

Bases: wrapper

readExtensions()

readFormats()

writeExtensions()

writeFormats()

class FormatDictionary_AimsTimeSurface_3_FLOAT

Bases: wrapper

readExtensions()

readFormats()

writeExtensions()

writeFormats()

class FormatDictionary_AimsTimeSurface_3_POINT2DF

Bases: wrapper

readExtensions()

readFormats()

writeExtensions()

writeFormats()

class FormatDictionary_AimsTimeSurface_3_VOID

Bases: wrapper

readExtensions()

readFormats()

writeExtensions()

writeFormats()

class FormatDictionary_AimsTimeSurface_4_FLOAT

Bases: wrapper

readExtensions()

readFormats()

writeExtensions()

writeFormats()

class FormatDictionary_AimsTimeSurface_4_POINT2DF

Bases: wrapper

readExtensions()

readFormats()

writeExtensions()

writeFormats()

class FormatDictionary_AimsTimeSurface_4_VOID

Bases: wrapper

readExtensions()

readFormats()

writeExtensions()

writeFormats()

class FormatDictionary_BucketMap_DOUBLE

Bases: wrapper

readExtensions()

readFormats()

writeExtensions()

writeFormats()

class FormatDictionary_BucketMap_FLOAT

Bases: wrapper

readExtensions()

readFormats()

writeExtensions()

writeFormats()

class FormatDictionary_BucketMap_S16

Bases: wrapper

readExtensions()

readFormats()

writeExtensions()

writeFormats()

class FormatDictionary_BucketMap_S32

Bases: wrapper

readExtensions()

readFormats()

writeExtensions()

writeFormats()

class FormatDictionary_BucketMap_U16

Bases: wrapper

readExtensions()

readFormats()

writeExtensions()

writeFormats()

class FormatDictionary_BucketMap_U32

Bases: wrapper

readExtensions()

readFormats()

writeExtensions()

writeFormats()

class FormatDictionary_BucketMap_VOID

Bases: wrapper

readExtensions()

readFormats()

writeExtensions()

writeFormats()

class FormatDictionary_Graph

Bases: wrapper

readExtensions()

readFormats()

writeExtensions()

writeFormats()

class FormatDictionary_Hierarchy

Bases: wrapper

readExtensions()

readFormats()

writeExtensions()

writeFormats()

class FormatDictionary_Object

Bases: wrapper

readExtensions()

readFormats()

writeExtensions()

writeFormats()

class FormatDictionary_SparseMatrix

Bases: wrapper

readExtensions()

readFormats()

writeExtensions()

writeFormats()

class FormatDictionary_SparseOrDenseMatrix

Bases: wrapper

readExtensions()

readFormats()

writeExtensions()

writeFormats()

class FormatDictionary_TimeTexture_DOUBLE

Bases: wrapper

readExtensions()

readFormats()

writeExtensions()

writeFormats()

class FormatDictionary_TimeTexture_FLOAT

Bases: wrapper

readExtensions()

readFormats()

writeExtensions()

writeFormats()

class FormatDictionary_TimeTexture_POINT2DF

Bases: wrapper

readExtensions()

readFormats()

writeExtensions()

writeFormats()

class FormatDictionary_TimeTexture_S16

Bases: wrapper

readExtensions()

readFormats()

writeExtensions()

writeFormats()

class FormatDictionary_TimeTexture_S32

Bases: wrapper

readExtensions()

readFormats()

writeExtensions()

writeFormats()

class FormatDictionary_TimeTexture_U16

Bases: wrapper

readExtensions()

readFormats()

writeExtensions()

writeFormats()

class FormatDictionary_TimeTexture_U32

Bases: wrapper

readExtensions()

readFormats()

writeExtensions()

writeFormats()

class FormatDictionary_TimeTexture_U8

Bases: wrapper

readExtensions()

readFormats()

writeExtensions()

writeFormats()

class FormatDictionary_Transformation3d

Bases: wrapper

readExtensions()

readFormats()

writeExtensions()

writeFormats()

class FormatDictionary_TransformationGraph3d

Bases: wrapper

readExtensions()

readFormats()

writeExtensions()

writeFormats()

class FormatDictionary_Volume_CDOUBLE

Bases: wrapper

readExtensions()

readFormats()

writeExtensions()

writeFormats()

class FormatDictionary_Volume_CFLOAT

Bases: wrapper

readExtensions()

readFormats()

writeExtensions()

writeFormats()

class FormatDictionary_Volume_DOUBLE

Bases: wrapper

readExtensions()

readFormats()

writeExtensions()

writeFormats()

class FormatDictionary_Volume_FLOAT

Bases: wrapper

readExtensions()

readFormats()

writeExtensions()

writeFormats()

class FormatDictionary_Volume_HSV

Bases: wrapper

readExtensions()

readFormats()

writeExtensions()

writeFormats()

class FormatDictionary_Volume_POINT3DF

Bases: wrapper

readExtensions()

readFormats()

writeExtensions()

writeFormats()

class FormatDictionary_Volume_RGB

Bases: wrapper

readExtensions()

readFormats()

writeExtensions()

writeFormats()

class FormatDictionary_Volume_RGBA

Bases: wrapper

readExtensions()

readFormats()

writeExtensions()

writeFormats()

class FormatDictionary_Volume_S16

Bases: wrapper

readExtensions()

readFormats()

writeExtensions()

writeFormats()

class FormatDictionary_Volume_S32

Bases: wrapper

readExtensions()

readFormats()

writeExtensions()

writeFormats()

class FormatDictionary_Volume_U16

Bases: wrapper

readExtensions()

readFormats()

writeExtensions()

writeFormats()

class FormatDictionary_Volume_U32

Bases: wrapper

readExtensions()

readFormats()

writeExtensions()

writeFormats()

class FormatDictionary_Volume_U8

Bases: wrapper

readExtensions()

readFormats()

writeExtensions()

writeFormats()

class GenericObject(*args, **kwargs)

Bases: RCObject

Generic dynamic polymorphic object.

GenericObject should not be used directly, but rather through the soma.aims.Object proxy.

See soma.aims.Object for a complete documentation.

append()

currentValue()

get()

getScalar()

getString()

getSyntax()

hasSyntax()

has_key()

index()

intKey()

isArray()

isDictionary()

isDictionaryIterator()

isDynArray()

isIterable()

isIterator()

isNone()

isScalar()

isString()

isValid()

items()

iteritems()

iterkeys()

itervalues()

key()

keys()

objectIterator()

setSyntax()

size()

type()

update(x)

values()

class Headered(*args)

Bases: RCObject

header()

class IOObjectTypesDictionary

Bases: wrapper

hasReadType()

hasWriteType()

readTypes()

writeTypes()

class Info

Bases: wrapper

Information class, which provides information about the AIMS / Cartobase libraries, such as libraries versions, plugins, data paths, etc.

May be used in 2 ways: * use static methods: Info.printVersions(), Info.printInfos() to directly output info on the standard output * get a list of Info objects using Info.infos() then use the specific methods on the Info objects. There may be several Info objects since higher-level libraries and applications may add their own ones.

infos()

Static method. Get a list of Info objects, each library may provide one (or several).

printBuiltins()

Print on the standard output buitin optional features, selected when the library has been built.

printInfos()

Static method. Print all information on the standard output.

printOtherInfo()

Print on the standard output additional information (such as IO properties, settings options, etc).

printPaths()

Print on the standard output configured data paths.

printVersion()

Print on the standard output the library version.

printVersions()

Static method. Print versions of libraries

class Mutex

Bases: wrapper

lock()

unlock()

class MutexedObject(*args)

Bases: RCObject

mutex()

class NumericGenericObjectConverter

Bases: wrapper

asBool()

asInt()

asLong()

class Object

Bases: rc_ptr_GenericObject

Generic dynamic polymorphic object proxy.

Object is a proxy and a reference counter to a GenericObject. In most cases, Object and GenericObject are interchangeable and play the same role, there are two objects for technical reasons in the C++ layer, but in Python it whould make no difference.

The C++ generic object is an implementation of a mutable dynamic container which can hold any type of concrete data, with a generic access API which abstracts the concrete type of the object stored within it.

According to the underlying object type, Object can behave like a number, a string, or a container: sequence or dictionary. The python bindings can therefore support the sequence protocol, or the dictionary protocol, like a ‘real’ python object.

The only part which makes it visibly different from a python object is the conversions with stored objects, which are generally C++ objects (but can also be any python objects). Transparent conversions are done when possible.

We will take an example to show how to use it: a volume header. Suppose the files volume.img/volume.hdr[/volume.img.minf] represent a 3D volume (a MRI volume, typically, here in Analyze/SPM or Nifti format). We will read it using aims, and access its header data, which comes as a generic object.

>>> from __future__ import print_function # work using python 2 or 3
>>> from soma import aims
>>> vol = aims.read('volume.img')
>>> hdr = vol.header()

Now vol is the volume, and hdr its header, of type Object.

>>> type(hdr)
<class 'soma.aims.Object'>
>>> print(hdr)
{ 'voxel_size' : [ 1.875, 1.875, 4, 1 ], 'file_type' : 'SPM',
'byte_swapping' : 0, 'volume_dimension' : [ 128, 128, 16, 1 ],
'vox_units' : 'mm  ', 'cal_units' : '', 'data_type' : 'S16',
'disk_data_type' : 'S16', 'bits_allocated' : 2, 'tr' : 1,
'minimum' : 0, 'maximum' : 13645, 'scale_factor' : 1,
'scale_factor_applied' : 0, 'db_name' : '',
'aux_file' : '', 'orient' : 3, 'generated' : '', 'scannum' : '',
'patient_id' : '', 'exp_date' : '', 'exp_time' : '', 'views' : 0,
'start_field' : 32768, 'field_skip' : 8192, 'omax' : 0,
'omin' : 0, 'smax' : 32, 'smin' : 0, 'SPM_data_type' : '',
'possible_data_types' : [ 'S16' ], 'spm_radio_convention' : 1,
'spm_origin' : [ 65, 65, 9 ], 'origin' : [ 64, 63, 7 ] }

hdr prints like a dictionary, but is not really a python dictionary object. However it behaves like a dictionary:

>>> print(hdr['voxel_size'])
[ 1.875, 1.875, 4, 1 ]
>>> print(hdr['data_type'])
S16
>>> print(hdr['voxel_size'][0])
1.875
>>> for x in hdr:
>>>     print(x)
>>>
voxel_size
file_type
byte_swapping
volume_dimension
vox_units
cal_units
data_type
disk_data_type
bits_allocated
tr
minimum
maximum
scale_factor
scale_factor_applied
db_name
aux_file
orient
generated
scannum
patient_id
exp_date
exp_time
views
start_field
field_skip
omax
omin
smax
smin
SPM_data_type
possible_data_types
spm_radio_convention
spm_origin
origin
>>> for x,y in hdr.items():
>>>     print(x, ':', y)
>>>
voxel_size : [ 1.875, 1.875, 4, 1 ]
file_type : 'SPM'
byte_swapping : 0
volume_dimension : [ 128, 128, 16, 1 ]
vox_units : 'mm  '
cal_units : ''
data_type : 'S16'
disk_data_type : 'S16'
bits_allocated : 2
tr : 1
minimum : 0
maximum : 13645
scale_factor : 1
scale_factor_applied : 0
db_name : ''
aux_file : ''
orient : 3
generated : ''
scannum : ''
patient_id : ''
exp_date : ''
exp_time : ''
views : 0
start_field : 32768
field_skip : 8192
omax : 0
omin : 0
smax : 32
smin : 0
SPM_data_type : ''
possible_data_types : [ 'S16' ]
spm_radio_convention : 1
spm_origin : [ 65, 65, 9 ]
origin : [ 64, 63, 7 ]

Elements returned by the dictionary queries can have various types, althrough they are all stored internally in a C++ structure through soma.aims.Object wrappers. But when the underlying type of the element is known and can be retreived as a python object (either a standard python type or a python binding of a C++ class), it is done automatically. Such conversion is not possible when the underlying object has no python binding and is a pure C++ object, or when there is no conversion function. In this case, an Object is returned and contains the selected data.

Conversions are done using conversion methods that you generally do not need to call by hand: getScalar(), getString(), or the more general conversion method soma.aims.Object.getPython(). Elements types that cannot be converted to python concrete types are retreived in their Object container.

The generic conversion function in Object: getPython, is a static method and can be extended.

Elements in Object containers can generally be read and written:

>>> hdr['data_type'] = 'FLOAT'
>>> hdr['data_type']
'FLOAT'

This generally suits your needs. But in a few cases there will be a problem in internal types handling in the C++ layer.

Here, the underlying C++ generic object which did hold a C++ string (std::string) 'S16' is now replaced by another generic object built from the python string 'FLOAT', and which now wraps an element of type PyObject (or PyString). It just behaves the same way, so this operation is perfectly valid, but if C++ programs expect it to be a C++ std::string, they may fail.

Moreover, when writing back to existing concrete objects, some additional conversions may take place: for instance hdr['voxel_size'] is a C++ object of type std::vector<float>, so writing to hdr['voxel_size'][0] needs to enure we are actually writing a float, and if not, convert to it if possible.

You can query a type identifier for a generic object via the type() method:

>>> hdr.type()
'PropertySet'

Objects that can be converted from C++ generic objects to python are not necessarily known in advance. A conversion table is kept in the global variable soma.aims.convertersObjectToPython (in the aims module) and can be extended. Therefore other python modules using aims (such as sigraph) can extend this conversion table.

Details and tricks

There are some limitations and “unexpected behaviours” caused by the underlying C++ implementation of generic objects, and general behaviour differences between Python and C++. The following is expert-level details, so read it only if you have problems or you are a C++ expert with good knowledge of the cartobase C++ library…

Generic object - specialized object conversions

Putting a specific object in a generic Object makes a copy of it the first time it is done, because C++ generic objects contain the specialized elements. Once this has been done once, generic objects are shared and not copied anymore, which is consistent with the normal python behaviour. The non-pythonic thing is the first insertion in a generic object:

>>> a = aims.vector_FLOAT([12.6, -5.7])
>>> print(a)
[ 12.6, -5.7 ]
>>> hdr['foo'] = a # here a is copied into hdr['foo']
>>> a.append( 6.8 ) # a is changed but not hdr
>>> print(a)
[ 12.6, -5.7, 6.8 ]
>>> print(hdr['foo'])
[ 12.6, -5.7 ]
>>> hdr['dummy'] = hdr['foo']
>>> hdr['foo'].append(4.2)
>>> print(hdr['dummy']) # this time hdr['dummy'] is changed
[ 12.6, -5.7, 4.2 ]

To overcome the first copy problem, you may have to reassign the initial variable to the copy instance:

>>> a = aims.vector_FLOAT([1.2, 2.3, 3.4])
>>> hdr['foo'] = a
>>> a = hdr['foo']
>>> print(hdr['foo'])
[ 1.2, 2.3, 3.4 ]
>>> a[1] = 12.8
>>> print(a)
[ 1.2, 12.8, 3.4 ]
>>> print(hdr['foo'])
[ 1.2, 12.8, 3.4 ]

There are exceptions to this behaviour:

• pure python objects, like lists or dictionaries are never copied since it is only a pointer to them (the C PyObject * pointer) which is stored.

• small builtin types: numbers and strings are always copied since they are always converted and copied, not wrapped, when passed from python to C++ and vice versa.

The get() method

On Object the get method is ambiguous and has 2 meanings:

• get() without arguments is a wrapping to the C++ rc_ptr::get() which returns the underlying wrapped object (here, a GenericObject)

• get(key, default=None) is the dict-like method that is available on GenericObject since aims 4.6.1.

Depending on the arguments the Object method will redirect to the right one, thus:

myobject.get()            # gets the GenericObject
myobject.get('key')       # gets the dict item under keyt 'key'
myobject.get().get('key') # does both, but this is what the previous line
                          # already does, so the result is the same

To avoid this ambiguity, Object.get() and rc_ptr.get() have been renamed _get() years ago (in aims 4.0 I think) but get() is still present for compatibility. This use (without argument) is obsolete and may be removed in the future.

getPython()

Conversion to python types: extracts what is in the Object (when possible). The global dictionary soma.aims.convertersObjectToPython stores converters

isNone()

static ptrToObject(x)

static rcToObject(x)

static toObject(x)

class PSyntaxSet

Bases: wrapper

keys()

semantic()

syntaxKeys()

class Paths

Bases: simplewrapper

findResourceFile()

findResourceFiles()

globalShared()

home()

memmap()

resourceSearchPath()

shfjShared()

tempDir()

class PluginLoader

Bases: wrapper

class PluginFile

Bases: wrapper

filename

loaded

version

load()

loadPluginFile()

pluginFiles()

class PropertySet

Bases: wrapper

clearProperties()

copyBuiltinProperties()

getProperty()

hasProperty()

objectIterator()

removeProperty()

setProperty()

size()

PyObjectfromObject()

class RCObject(*args)

Bases: wrapper

class Roi(*args)

Bases: Headered

class Semantic

Bases: wrapper

internal

needed

type

class SharedObject(*args)

Bases: RCObject

class Site

Bases: wrapper

at()

set()

size()

class SiteIterator

Bases: wrapper

getSite()

isValid()

next()

restart()

writeSite()

class SyntaxReader

Bases: wrapper

read()

debugMessageLevel()

class fdinhibitor(fd, permanent=False)

Bases: wrapper

fd: file descriptor to inhibit, permanent: if false, don’t reopen the stream when deleting the fdinhibitor

usage: from soma import aims fdi = aims.carto.fdinhibitor(sys.stderr.fileno()) fdi.close() # call a function which prints something on stderr which we don’t want to # appear fdi.open() sys.stderr.write(‘after reopenn’) # works again

Temporarily closes a file descriptor (typically, stdout/stderr). Currently, this low-level implementation doesn’t work with all C++ streams: on some systems C++ streams stay in a bad state afterwards and are silent forever. Standard IO streams (cin, cout, cerr) are checked and protected against this problem.

class ResetCallback

Bases: wrapper

close()

hasResetCallback()

notify()

open()

registerResetCallback()

unregisterResetCallback()

none()

Returns a null aims.Object

class rc_ptr_MaskIterator

Bases: wrapper

get(*args, **kwargs)

get() is ambiguous: rc_ptr / Object has the get() method, providing access to the underlying object. GenericObject has the method get(key, default=None) as a dictionary-like object. This proxy calls the right one depending on arguments.

isNull()

release()

reset()

class rc_ptr_RoiIterator

Bases: wrapper

get(*args, **kwargs)

get() is ambiguous: rc_ptr / Object has the get() method, providing access to the underlying object. GenericObject has the method get(key, default=None) as a dictionary-like object. This proxy calls the right one depending on arguments.

isNull()

release()

reset()

setDebugMessageLevel()

setOrientationInformation(header, orient)

force or alter a specific voxels orientation on disk (if the output format supports it), by changing the internal “storage_to_memory” matrix, in a more or less convenient way, with different syntaxes:

• “flipx yflip”: flips orientations of x and y axes.

-“neuro”, “neurological” or “left-to-right”: force neuro orientation. - “radio”, “radiological” or “right-to-left”: force radio orientation. - “-1 1 -1”: set a flip matrix flipping x and z axes (set the diagonal). - “-1 0 0 0 1 0 0 0 -1”: same by specifying the full rotation matrix. - “-1 0 0 255 0 1 0 0 0 0 -1 123 0 0 0 1”: same by specifying

the full 4x4 matrix.

By default, all orientation matrices are applied relatively to the current voxels orientation. To set absolute matrices (from the AIMS conventional orientation), specify “abs:” before the matrix. Ex:

• “abs: -1 1 -1”

• “abs: -1 0 0 255 0 1 0 0 0 0 -1 123 0 0 0 1”

setVerbose()

verbose()

soma.aims.convertersObjectToPython = {'POINT2DF': <built-in function fromObject>, 'POINT3DF': <built-in function fromObject>, 'POINT4DF': <built-in function fromObject>, 'PyObject': <built-in function PyObjectfromObject>, 'S16': <built-in function asInt>, 'S32': <built-in function asInt>, 'U16': <built-in function asInt>, 'U32': <built-in function asInt>, 'boolean': <built-in function asBool>, 'rc_ptr of Mesh of FLOAT': <built-in function fromObject>, 'rc_ptr of Mesh of POINT2DF': <built-in function fromObject>, 'rc_ptr of Mesh of VOID': <built-in function fromObject>, 'rc_ptr of Mesh4 of FLOAT': <built-in function fromObject>, 'rc_ptr of Mesh4 of POINT2DF': <built-in function fromObject>, 'rc_ptr of Mesh4 of VOID': <built-in function fromObject>, 'rc_ptr of Segments of FLOAT': <built-in function fromObject>, 'rc_ptr of Segments of POINT2DF': <built-in function fromObject>, 'rc_ptr of Segments of VOID': <built-in function fromObject>, 'rc_ptr of Transformation3d': <built-in function fromObject>, 'rc_ptr of bucket of DOUBLE': <built-in function fromObject>, 'rc_ptr of bucket of FLOAT': <built-in function fromObject>, 'rc_ptr of bucket of S16': <built-in function fromObject>, 'rc_ptr of bucket of S32': <built-in function fromObject>, 'rc_ptr of bucket of U16': <built-in function fromObject>, 'rc_ptr of bucket of U32': <built-in function fromObject>, 'rc_ptr of bucket of VOID': <built-in function fromObject>, 'rc_ptr of mesh of VOID': <built-in function fromObject>, 'rc_ptr of texture of FLOAT': <built-in function fromObject>, 'rc_ptr of texture of POINT2DF': <built-in function fromObject>, 'rc_ptr of texture of S16': <built-in function fromObject>, 'rc_ptr of texture of S32': <built-in function fromObject>, 'rc_ptr of texture of U32': <built-in function fromObject>, 'string': <function <lambda>>}

Conversion function map. These converters are used to convert between a C++ object inside a generic object to their Python equivalent. They are typically used when accessing a sub-object:

>>> from soma import aims
>>> v = aims.Object(aims.vector_STRING())
>>> v.append('toto')
>>> v.append('bubu')
>>> type(v)
soma.aims.Object
>>> v.type()
'vector of string'
>>> v[0]
'toto'
>>> type(v[0])
str

In this example, v contains a C++ object of type std::vector<std::string>. Its elements are accessed via a wrapping which is using a C++ generic object (carto::Object). But in python we obtain a str (pyton string): the string has been taken out of the generic object using this conversion map (and then converted automatically to str by the SIP tool).

soma.aims.floodFill()

soma.aims.getLinearInterpolator()

soma.aims.getMaskIterator()

soma.aims.getRoiIterator()

soma.aims.get_transform_to(aims_obj, ref)

Get a transformation object in an AIMS object header to the given referential identifier. Objects need to have a header() method following the aims conventions (referentials and transformations elements beingn lists).

Parameters:

• aims_obj (Aims object with a header) – object we want to get the transformation from

• ref (str) – target refetential identifier. May be an UUID string, or a known identifier such as “Talairach-MNI template-SPM” (see aims.StandardReferentials attributes)

Returns:

transform – the transformation object, or None if no matching one is found

Return type:

aims.AffineTransformation3d

soma.aims.giftiColormap()

class soma.aims.list_AimsTimeSurface_3_VOID

Bases: wrapper

append()

assign()

index()

list()

remove()

size()

class soma.aims.list_AimsTimeSurface_3_VOID_iterator

Bases: wrapper

class soma.aims.list_DOUBLE

Bases: wrapper

append()

assign()

index()

list()

remove()

size()

class soma.aims.list_DOUBLE_iterator

Bases: wrapper

class soma.aims.list_EdgePtr

Bases: wrapper

append()

assign()

index()

list()

remove()

size()

class soma.aims.list_EdgePtr_iterator

Bases: wrapper

class soma.aims.list_FLOAT

Bases: wrapper

append()

assign()

index()

list()

remove()

size()

class soma.aims.list_FLOAT_iterator

Bases: wrapper

class soma.aims.list_GraphPtr

Bases: wrapper

append()

assign()

index()

list()

remove()

size()

class soma.aims.list_GraphPtr_iterator

Bases: wrapper

class soma.aims.list_POINT3D

Bases: wrapper

append()

assign()

index()

list()

remove()

size()

class soma.aims.list_POINT3DF

Bases: wrapper

append()

assign()

index()

list()

remove()

size()

class soma.aims.list_POINT3DF_iterator

Bases: wrapper

class soma.aims.list_POINT3D_iterator

Bases: wrapper

class soma.aims.list_PluginFile

Bases: wrapper

append()

assign()

index()

list()

remove()

size()

class soma.aims.list_PluginFile_iterator

Bases: wrapper

class soma.aims.list_S32

Bases: wrapper

append()

assign()

index()

list()

remove()

size()

class soma.aims.list_S32_iterator

Bases: wrapper

class soma.aims.list_STRING

Bases: wrapper

append()

assign()

index()

list()

remove()

size()

class soma.aims.list_STRING_iterator

Bases: wrapper

class soma.aims.list_U32

Bases: wrapper

append()

assign()

index()

list()

remove()

size()

class soma.aims.list_U32_iterator

Bases: wrapper

class soma.aims.list_rc_ptr_Graph

Bases: wrapper

append()

assign()

index()

list()

remove()

size()

class soma.aims.list_rc_ptr_Graph_iterator

Bases: wrapper

class soma.aims.list_vector_POINT3DF

Bases: wrapper

append()

assign()

index()

list()

remove()

size()

class soma.aims.list_vector_POINT3DF_iterator

Bases: wrapper

class soma.aims.list_vector_STRING

Bases: wrapper

append()

assign()

index()

list()

remove()

size()

class soma.aims.list_vector_STRING_iterator

Bases: wrapper

soma.aims.mask()

soma.aims.maskWithVolume()

class soma.aims.merge_t

Bases: int

soma.aims.proxydelitem(self, attr)

soma.aims.proxyiter(self)

class soma.aims.pyaims

Bases: simplewrapper

class DebuggingVolume(*args)

Bases: Volume_S16

created = False

deleted = False

class soma.aims.range(stop)

class soma.aims.range(start, stop[, step]) → range object

Bases: object

Return an object that produces a sequence of integers from start (inclusive) to stop (exclusive) by step. range(i, j) produces i, i+1, i+2, …, j-1. start defaults to 0, and stop is omitted! range(4) produces 0, 1, 2, 3. These are exactly the valid indices for a list of 4 elements. When step is given, it specifies the increment (or decrement).

count(value) → integer -- return number of occurrences of value

index(value) → integer -- return index of value.

Raise ValueError if the value is not present.

start

step

stop

soma.aims.rc_ptr(*args, **kwargs)

Create an instance of aims reference-counting object (rc_ptr_<type>) from a type parameter, which may be specified as the dtype keyword argument, or as one of the arguments if one is identitied as a type.

Type definitions should match those accepted by typeCode().

class soma.aims.rc_ptr_AffineTransformation3d

Bases: wrapper

get(*args, **kwargs)

get() is ambiguous: rc_ptr / Object has the get() method, providing access to the underlying object. GenericObject has the method get(key, default=None) as a dictionary-like object. This proxy calls the right one depending on arguments.

isNull()

release()

reset()

soma.aims.rc_ptr_AimsTimeSurface_2

alias of rc_ptr_AimsTimeSurface_2_VOID

class soma.aims.rc_ptr_AimsTimeSurface_2_FLOAT

Bases: wrapper

get(*args, **kwargs)

get() is ambiguous: rc_ptr / Object has the get() method, providing access to the underlying object. GenericObject has the method get(key, default=None) as a dictionary-like object. This proxy calls the right one depending on arguments.

isNull()

release()

reset()

class soma.aims.rc_ptr_AimsTimeSurface_2_POINT2DF

Bases: wrapper

get(*args, **kwargs)

get() is ambiguous: rc_ptr / Object has the get() method, providing access to the underlying object. GenericObject has the method get(key, default=None) as a dictionary-like object. This proxy calls the right one depending on arguments.

isNull()

release()

reset()

class soma.aims.rc_ptr_AimsTimeSurface_2_VOID

Bases: wrapper

get(*args, **kwargs)

get() is ambiguous: rc_ptr / Object has the get() method, providing access to the underlying object. GenericObject has the method get(key, default=None) as a dictionary-like object. This proxy calls the right one depending on arguments.

isNull()

release()

reset()

soma.aims.rc_ptr_AimsTimeSurface_3

alias of rc_ptr_AimsTimeSurface_3_VOID

class soma.aims.rc_ptr_AimsTimeSurface_3_FLOAT

Bases: wrapper

get(*args, **kwargs)

get() is ambiguous: rc_ptr / Object has the get() method, providing access to the underlying object. GenericObject has the method get(key, default=None) as a dictionary-like object. This proxy calls the right one depending on arguments.

isNull()

release()

reset()

class soma.aims.rc_ptr_AimsTimeSurface_3_POINT2DF

Bases: wrapper

get(*args, **kwargs)

get() is ambiguous: rc_ptr / Object has the get() method, providing access to the underlying object. GenericObject has the method get(key, default=None) as a dictionary-like object. This proxy calls the right one depending on arguments.

isNull()

release()

reset()

class soma.aims.rc_ptr_AimsTimeSurface_3_VOID

Bases: wrapper

get(*args, **kwargs)

get() is ambiguous: rc_ptr / Object has the get() method, providing access to the underlying object. GenericObject has the method get(key, default=None) as a dictionary-like object. This proxy calls the right one depending on arguments.

isNull()

release()

reset()

soma.aims.rc_ptr_AimsTimeSurface_4

alias of rc_ptr_AimsTimeSurface_4_VOID

class soma.aims.rc_ptr_AimsTimeSurface_4_FLOAT

Bases: wrapper

get(*args, **kwargs)

get() is ambiguous: rc_ptr / Object has the get() method, providing access to the underlying object. GenericObject has the method get(key, default=None) as a dictionary-like object. This proxy calls the right one depending on arguments.

isNull()

release()

reset()

class soma.aims.rc_ptr_AimsTimeSurface_4_POINT2DF

Bases: wrapper

get(*args, **kwargs)

get() is ambiguous: rc_ptr / Object has the get() method, providing access to the underlying object. GenericObject has the method get(key, default=None) as a dictionary-like object. This proxy calls the right one depending on arguments.

isNull()

release()

reset()

class soma.aims.rc_ptr_AimsTimeSurface_4_VOID

Bases: wrapper

get(*args, **kwargs)

get() is ambiguous: rc_ptr / Object has the get() method, providing access to the underlying object. GenericObject has the method get(key, default=None) as a dictionary-like object. This proxy calls the right one depending on arguments.

isNull()

release()

reset()

class soma.aims.rc_ptr_BucketMap_DOUBLE

Bases: wrapper

get(*args, **kwargs)

get() is ambiguous: rc_ptr / Object has the get() method, providing access to the underlying object. GenericObject has the method get(key, default=None) as a dictionary-like object. This proxy calls the right one depending on arguments.

isNull()

release()

reset()

class soma.aims.rc_ptr_BucketMap_FLOAT

Bases: wrapper

get(*args, **kwargs)

get() is ambiguous: rc_ptr / Object has the get() method, providing access to the underlying object. GenericObject has the method get(key, default=None) as a dictionary-like object. This proxy calls the right one depending on arguments.

isNull()

release()

reset()

class soma.aims.rc_ptr_BucketMap_S16

Bases: wrapper

get(*args, **kwargs)

get() is ambiguous: rc_ptr / Object has the get() method, providing access to the underlying object. GenericObject has the method get(key, default=None) as a dictionary-like object. This proxy calls the right one depending on arguments.

isNull()

release()

reset()

class soma.aims.rc_ptr_BucketMap_S32

Bases: wrapper

get(*args, **kwargs)

get() is ambiguous: rc_ptr / Object has the get() method, providing access to the underlying object. GenericObject has the method get(key, default=None) as a dictionary-like object. This proxy calls the right one depending on arguments.

isNull()

release()

reset()

class soma.aims.rc_ptr_BucketMap_U16

Bases: wrapper

get(*args, **kwargs)

get() is ambiguous: rc_ptr / Object has the get() method, providing access to the underlying object. GenericObject has the method get(key, default=None) as a dictionary-like object. This proxy calls the right one depending on arguments.

isNull()

release()

reset()

class soma.aims.rc_ptr_BucketMap_U32

Bases: wrapper

get(*args, **kwargs)

get() is ambiguous: rc_ptr / Object has the get() method, providing access to the underlying object. GenericObject has the method get(key, default=None) as a dictionary-like object. This proxy calls the right one depending on arguments.

isNull()

release()

reset()

class soma.aims.rc_ptr_BucketMap_VOID

Bases: wrapper

get(*args, **kwargs)

get() is ambiguous: rc_ptr / Object has the get() method, providing access to the underlying object. GenericObject has the method get(key, default=None) as a dictionary-like object. This proxy calls the right one depending on arguments.

isNull()

release()

reset()

class soma.aims.rc_ptr_DataSource

Bases: wrapper

get(*args, **kwargs)

get() is ambiguous: rc_ptr / Object has the get() method, providing access to the underlying object. GenericObject has the method get(key, default=None) as a dictionary-like object. This proxy calls the right one depending on arguments.

isNull()

release()

reset()

class soma.aims.rc_ptr_DataSourceInfo

Bases: wrapper

get(*args, **kwargs)

get() is ambiguous: rc_ptr / Object has the get() method, providing access to the underlying object. GenericObject has the method get(key, default=None) as a dictionary-like object. This proxy calls the right one depending on arguments.

isNull()

release()

reset()

class soma.aims.rc_ptr_Edge

Bases: wrapper

get(*args, **kwargs)

get() is ambiguous: rc_ptr / Object has the get() method, providing access to the underlying object. GenericObject has the method get(key, default=None) as a dictionary-like object. This proxy calls the right one depending on arguments.

isNull()

release()

reset()

class soma.aims.rc_ptr_GenericObject

Bases: wrapper

get(*args, **kwargs)

get() is ambiguous: rc_ptr / Object has the get() method, providing access to the underlying object. GenericObject has the method get(key, default=None) as a dictionary-like object. This proxy calls the right one depending on arguments.

isNull()

release()

reset()

class soma.aims.rc_ptr_Graph

Bases: wrapper

get(*args, **kwargs)

get() is ambiguous: rc_ptr / Object has the get() method, providing access to the underlying object. GenericObject has the method get(key, default=None) as a dictionary-like object. This proxy calls the right one depending on arguments.

isNull()

release()

reset()

class soma.aims.rc_ptr_Interpolator

Bases: wrapper

get(*args, **kwargs)

get() is ambiguous: rc_ptr / Object has the get() method, providing access to the underlying object. GenericObject has the method get(key, default=None) as a dictionary-like object. This proxy calls the right one depending on arguments.

isNull()

release()

reset()

class soma.aims.rc_ptr_Site

Bases: wrapper

get(*args, **kwargs)

get() is ambiguous: rc_ptr / Object has the get() method, providing access to the underlying object. GenericObject has the method get(key, default=None) as a dictionary-like object. This proxy calls the right one depending on arguments.

isNull()

release()

reset()

class soma.aims.rc_ptr_SiteIterator

Bases: wrapper

get(*args, **kwargs)

get() is ambiguous: rc_ptr / Object has the get() method, providing access to the underlying object. GenericObject has the method get(key, default=None) as a dictionary-like object. This proxy calls the right one depending on arguments.

isNull()

release()

reset()

class soma.aims.rc_ptr_SparseMatrix

Bases: wrapper

get(*args, **kwargs)

get() is ambiguous: rc_ptr / Object has the get() method, providing access to the underlying object. GenericObject has the method get(key, default=None) as a dictionary-like object. This proxy calls the right one depending on arguments.

isNull()

release()

reset()

class soma.aims.rc_ptr_SparseOrDenseMatrix

Bases: wrapper

get(*args, **kwargs)

get() is ambiguous: rc_ptr / Object has the get() method, providing access to the underlying object. GenericObject has the method get(key, default=None) as a dictionary-like object. This proxy calls the right one depending on arguments.

isNull()

release()

reset()

class soma.aims.rc_ptr_TimeTexture_DOUBLE

Bases: wrapper

get(*args, **kwargs)

get() is ambiguous: rc_ptr / Object has the get() method, providing access to the underlying object. GenericObject has the method get(key, default=None) as a dictionary-like object. This proxy calls the right one depending on arguments.

isNull()

release()

reset()

class soma.aims.rc_ptr_TimeTexture_FLOAT

Bases: wrapper

get(*args, **kwargs)

get() is ambiguous: rc_ptr / Object has the get() method, providing access to the underlying object. GenericObject has the method get(key, default=None) as a dictionary-like object. This proxy calls the right one depending on arguments.

isNull()

release()

reset()

class soma.aims.rc_ptr_TimeTexture_POINT2DF

Bases: wrapper

get(*args, **kwargs)

get() is ambiguous: rc_ptr / Object has the get() method, providing access to the underlying object. GenericObject has the method get(key, default=None) as a dictionary-like object. This proxy calls the right one depending on arguments.

isNull()

release()

reset()

class soma.aims.rc_ptr_TimeTexture_S16

Bases: wrapper

get(*args, **kwargs)

get() is ambiguous: rc_ptr / Object has the get() method, providing access to the underlying object. GenericObject has the method get(key, default=None) as a dictionary-like object. This proxy calls the right one depending on arguments.

isNull()

release()

reset()

class soma.aims.rc_ptr_TimeTexture_S32

Bases: wrapper

get(*args, **kwargs)

get() is ambiguous: rc_ptr / Object has the get() method, providing access to the underlying object. GenericObject has the method get(key, default=None) as a dictionary-like object. This proxy calls the right one depending on arguments.

isNull()

release()

reset()

class soma.aims.rc_ptr_TimeTexture_U16

Bases: wrapper

get(*args, **kwargs)

get() is ambiguous: rc_ptr / Object has the get() method, providing access to the underlying object. GenericObject has the method get(key, default=None) as a dictionary-like object. This proxy calls the right one depending on arguments.

isNull()

release()

reset()

class soma.aims.rc_ptr_TimeTexture_U32

Bases: wrapper

get(*args, **kwargs)

get() is ambiguous: rc_ptr / Object has the get() method, providing access to the underlying object. GenericObject has the method get(key, default=None) as a dictionary-like object. This proxy calls the right one depending on arguments.

isNull()

release()

reset()

class soma.aims.rc_ptr_TimeTexture_U8

Bases: wrapper

get(*args, **kwargs)

get() is ambiguous: rc_ptr / Object has the get() method, providing access to the underlying object. GenericObject has the method get(key, default=None) as a dictionary-like object. This proxy calls the right one depending on arguments.

isNull()

release()

reset()

class soma.aims.rc_ptr_Transformation3d

Bases: wrapper

get(*args, **kwargs)

get() is ambiguous: rc_ptr / Object has the get() method, providing access to the underlying object. GenericObject has the method get(key, default=None) as a dictionary-like object. This proxy calls the right one depending on arguments.

isNull()

release()

reset()

class soma.aims.rc_ptr_Tree

Bases: wrapper

get(*args, **kwargs)

get() is ambiguous: rc_ptr / Object has the get() method, providing access to the underlying object. GenericObject has the method get(key, default=None) as a dictionary-like object. This proxy calls the right one depending on arguments.

isNull()

release()

reset()

class soma.aims.rc_ptr_Vertex

Bases: wrapper

get(*args, **kwargs)

get() is ambiguous: rc_ptr / Object has the get() method, providing access to the underlying object. GenericObject has the method get(key, default=None) as a dictionary-like object. This proxy calls the right one depending on arguments.

isNull()

release()

reset()

class soma.aims.rc_ptr_Volume_BOOL

Bases: wrapper

get(*args, **kwargs)

get() is ambiguous: rc_ptr / Object has the get() method, providing access to the underlying object. GenericObject has the method get(key, default=None) as a dictionary-like object. This proxy calls the right one depending on arguments.

isNull()

release()

reset()

class soma.aims.rc_ptr_Volume_CDOUBLE

Bases: wrapper

get(*args, **kwargs)

get() is ambiguous: rc_ptr / Object has the get() method, providing access to the underlying object. GenericObject has the method get(key, default=None) as a dictionary-like object. This proxy calls the right one depending on arguments.

isNull()

release()

reset()

class soma.aims.rc_ptr_Volume_CFLOAT

Bases: wrapper

get(*args, **kwargs)

get() is ambiguous: rc_ptr / Object has the get() method, providing access to the underlying object. GenericObject has the method get(key, default=None) as a dictionary-like object. This proxy calls the right one depending on arguments.

isNull()

release()

reset()

class soma.aims.rc_ptr_Volume_DOUBLE

Bases: wrapper

get(*args, **kwargs)

get() is ambiguous: rc_ptr / Object has the get() method, providing access to the underlying object. GenericObject has the method get(key, default=None) as a dictionary-like object. This proxy calls the right one depending on arguments.

isNull()

release()

reset()

class soma.aims.rc_ptr_Volume_FLOAT

Bases: wrapper

get(*args, **kwargs)

get() is ambiguous: rc_ptr / Object has the get() method, providing access to the underlying object. GenericObject has the method get(key, default=None) as a dictionary-like object. This proxy calls the right one depending on arguments.

isNull()

release()

reset()

class soma.aims.rc_ptr_Volume_HSV

Bases: wrapper

get(*args, **kwargs)

get() is ambiguous: rc_ptr / Object has the get() method, providing access to the underlying object. GenericObject has the method get(key, default=None) as a dictionary-like object. This proxy calls the right one depending on arguments.

isNull()

release()

reset()

class soma.aims.rc_ptr_Volume_POINT3DF

Bases: wrapper

get(*args, **kwargs)

get() is ambiguous: rc_ptr / Object has the get() method, providing access to the underlying object. GenericObject has the method get(key, default=None) as a dictionary-like object. This proxy calls the right one depending on arguments.

isNull()

release()

reset()

class soma.aims.rc_ptr_Volume_RGB

Bases: wrapper

get(*args, **kwargs)

get() is ambiguous: rc_ptr / Object has the get() method, providing access to the underlying object. GenericObject has the method get(key, default=None) as a dictionary-like object. This proxy calls the right one depending on arguments.

isNull()

release()

reset()

class soma.aims.rc_ptr_Volume_RGBA

Bases: wrapper

get(*args, **kwargs)

get() is ambiguous: rc_ptr / Object has the get() method, providing access to the underlying object. GenericObject has the method get(key, default=None) as a dictionary-like object. This proxy calls the right one depending on arguments.

isNull()

release()

reset()

class soma.aims.rc_ptr_Volume_S16

Bases: wrapper

get(*args, **kwargs)

get() is ambiguous: rc_ptr / Object has the get() method, providing access to the underlying object. GenericObject has the method get(key, default=None) as a dictionary-like object. This proxy calls the right one depending on arguments.

isNull()

release()

reset()

class soma.aims.rc_ptr_Volume_S32

Bases: wrapper

get(*args, **kwargs)

get() is ambiguous: rc_ptr / Object has the get() method, providing access to the underlying object. GenericObject has the method get(key, default=None) as a dictionary-like object. This proxy calls the right one depending on arguments.

isNull()

release()

reset()

class soma.aims.rc_ptr_Volume_U16

Bases: wrapper

get(*args, **kwargs)

get() is ambiguous: rc_ptr / Object has the get() method, providing access to the underlying object. GenericObject has the method get(key, default=None) as a dictionary-like object. This proxy calls the right one depending on arguments.

isNull()

release()

reset()

class soma.aims.rc_ptr_Volume_U32

Bases: wrapper

get(*args, **kwargs)

get() is ambiguous: rc_ptr / Object has the get() method, providing access to the underlying object. GenericObject has the method get(key, default=None) as a dictionary-like object. This proxy calls the right one depending on arguments.

isNull()

release()

reset()

class soma.aims.rc_ptr_Volume_U8

Bases: wrapper

get(*args, **kwargs)

get() is ambiguous: rc_ptr / Object has the get() method, providing access to the underlying object. GenericObject has the method get(key, default=None) as a dictionary-like object. This proxy calls the right one depending on arguments.

isNull()

release()

reset()

soma.aims.read(filename, border=0, frame=-1, dtype=None, allocmode=None, options=None, object=None)

Equivalent to:

r = Reader(allocmode=allocmode, options=options)
return r.read(filename, border=border, frame=frame, dtype=dtype,
              object=object)

Ex:

• read a volume:

  vol = aims.read('file.nii')
  

• read a mesh:

  mesh = aims.read('file.gii')
  

• read part of a volume, with borders (warning, all formats do not allow it):

  vol = aims.read(
      'file.nii', options={'border': 2, 'ox': 100, 'sx': 100,
                           'oy': 50, 'sy': 150, 'oz': 20, 'sz': 60})
  

  or (equivalent):

  vol = aims.read(
    'file.nii?border=2&ox=100&sx=100&oy=50&sy=150&oz=20&sz=60')
  

• read a view inside a larger volume (warning, all formats do not allow it, and they may produce inpredictible results, and probably crashes):

  border = aims.Volume_S16(500, 500, 200)
  view = aims.VolumeView(border, [50, 50, 50], [256, 256, 124])
  aims.read('file.nii', object=view, options={'keep_allocation': True})
  

soma.aims.readSpmNormalization(matfilename, source=None, destref=None, srcref=None)

Read a SPM *_sn.mat normalization file and converts it to an Aims AffineTransformation3d. The converted transformation has for source the AIMS referential of the source image, and for destination the template referential of the SPM .mat file. All coordinates are in millimeters.

The source image information may be provided either as its filename, its header object, or the image itself. It should carry the needed information: source volume storage_to_memory transformation matrix, voxel_size, etc. If None is passed as source (the default), then the source image name will be built from the .mat filename and will be read if found.

• matfilename: string

  file name of the *_sn.mat normalization file to reading

• source: filename (string), or Volume Volume, or volume header (MappingType)

  file name of the *_sn.mat normalization file to reading

• destref: string or UUID (Uuid)

  destination referential for the transformation. If not specified, none will be set. If provided as a symbolic name (‘Talairach-MNI template-SPM’), it will be converted to an UUID string.

• srcref: string or UUID

  source referential for the transformation. If not specified, an attempt will be made to take it from the source image, otherwise it will not be set. If provided as a symbolic name (‘Talairach-MNI template-SPM’), it will be converted to an UUID string.

• returns: AffineTransformation3d object

  the converted transformation

class soma.aims.set_DOUBLE

Bases: wrapper

add()

insert()

list()

remove()

size()

class soma.aims.set_DOUBLE_iterator

Bases: wrapper

class soma.aims.set_EdgePtr

Bases: wrapper

add()

insert()

list()

remove()

size()

class soma.aims.set_EdgePtr_iterator

Bases: wrapper

class soma.aims.set_FLOAT

Bases: wrapper

add()

insert()

list()

remove()

size()

class soma.aims.set_FLOAT_iterator

Bases: wrapper

class soma.aims.set_S16

Bases: wrapper

add()

insert()

list()

remove()

size()

class soma.aims.set_S16_iterator

Bases: wrapper

class soma.aims.set_S32

Bases: wrapper

add()

insert()

list()

remove()

size()

class soma.aims.set_S32_iterator

Bases: wrapper

class soma.aims.set_STRING

Bases: wrapper

add()

insert()

list()

remove()

size()

class soma.aims.set_STRING_iterator

Bases: wrapper

class soma.aims.set_U32

Bases: wrapper

add()

insert()

list()

remove()

size()

class soma.aims.set_U32_iterator

Bases: wrapper

class soma.aims.set_VertexPtr

Bases: wrapper

add()

insert()

list()

remove()

size()

class soma.aims.set_VertexPtr_iterator

Bases: wrapper

class soma.aims.soma

Bases: simplewrapper

class DataSource(*args)

Bases: RCObject

Abstraction layer for various data sources (file, buffer, socket…).

It can be seen as a stream, and is inspired by the QIODevice of Qt library.

Abstract class.

DirectAccess = 1

class IterateMode

Bases: int

class Mode

Bases: int

Read = 1

ReadWrite = 3

SequentialAccess = 2

Write = 2

allowsMemoryMapping()

returns True if memory mapping is allowed on this kind of stream

at()

offset = at()

returns the current position in the stream

bool at(pos)

Sets the current position in the stream (when supported). Returns True if successful.

atEnd()

True if the current position is at the end of the stream

clone()

duplicate the DataSource object

close()

Close the stream

eof()

when the end of stream is reached

flush()

flush the stream for buffered output

getch()

read one char and returns it

isOpen()

tells if the stream is open / ok.

iterateMode()

bitwise combination of possible access: direct (1) or sequential (2) access

mode()

access mode(s) (read/write): bitwise OR of Mode values

none()

An empty ref-counter that is more convenient than calling a constructor of rc_ptr_DataSource (useful when calling functions)

open(mode)

Opens the stream (when supported) in the specified Mode

Parameters:

mode (int) – access Mode: Read (1), Write (2) or ReadWrite (3)

Returns:

ok – if the operation was successful

Return type:

bool

putch(ch)

write one char, and returns it

Parameters:

ch (int) – char to write

readBlock(data, maxlen)

Parameters:

• data (char*) – read buffer (C++)

• maxlen (unsigned long int) – number of bytes to read

Returns:

num – number of bytes actually read

Return type:

long int

reset()

reset the stream and get to the start

size()

size (or len) of the data inn stream, in bytes

ungetch(ch)

un-read one char: put it back in the read buffer, and rewind one char

url()

URL of filename for the stream, when available

writeBlock(data, len)

Parameters:

• data (const char * (C++)) – buffer to be written

• len (unsigned long int) – size of the buffer to be written

Returns:

num – number of bytes actually written

Return type:

long int

class DataSourceInfo

Bases: wrapper

DataSourceInfo(ds, dim=[]):

Build a DataSourceInfo from a DataSource, and dimensions

DSList is set as containing only ds pointed by “default” key. Capabilities are set uninitialized. If dim is given, a header is built with keys size[X,Y,Z,T]. Else the header is none().

DataSourceInfo(ds, header):

Build a DataSourceInfo from a DataSource and an existing header

DataSourceInfo(fname):

Builds a DataSourceInfo from a filename

Parameters:

• ds (rc_ptr_DataSource) –

• dim (vector_S32) – dimensions (for a volume), up to 4 dimensions

• header (Object) –

• fname (string) –

Informative object used by IO system

This object is used by FormatChecker, FormatReader or FormatWriter to describe a DataSource. It contains a DataSourceList which contains at first a single default DataSource, a Object header and a DataSourceCapabilities.

• The list is built by a FormatChecker and contains all the files involved in the reading/writing process (header, data, …)

• The header is built by a FormatChecker and contains meta information.

• The DSC contains properties dependant of the format, the specific file, the reading process (partial reading), etc.

It is possible to fix some or all of these three objects so that they are not recomputed by the FormatChecker.

see DataSourceInfoLoader DataSourceList DataSourceCapabilities

header()

get the header dict of the underlying data

identifiedFormat()

file format name

list()

get the DataSourceList of the underlying data

setIdentifiedFormat(format)

force the identified format name

url()

main filename or URL

class DataSourceInfoLoader

Bases: wrapper

Generic information retreiver / checker for all data sources and file formats

It replaces aims.Finder.

DataSourceInfoLoader provides a plug-in system for new formats and data types. Formats are hidden in the plugins and should never be accessed directly.

Usage: check() the DataSourceInfo and then process according to the object type (“Volume of S16”, “Mesh”, “Texture”, “Bucket”, …).

Use the generic Reader once the data type is known, the right format will be selected automatically.

Avoiding manually switching on objects and data types is possible using the ReaderAlgorithm interface and presumably, template functions.

Here is an example of how to use the DataSourceInfoLoader class:

from soma import aims
from soma.aims import soma

f = soma.DataSourceInfoLoader()
info = f.check("toto.nii")
if not info.header():
    print "could not load", info.url()
else:
  object_type = info.header()["object_type"]
  if object_type == aims.typeCode(aims.Volume_S16):
      vr = soma.Reader_Volume_S16(info)
      try:
          vol = vr.read()
          print "volume read"
      except:
          print "Error loading", info.url()
  elif object_type == aims.typeCode(aims.Object):
      # do your thing
      print "Object"
  else:
      print info.url(), "is of type", object_type, \
          "which is not handled"

see DataSourceInfo, Reader, ReaderAlgorithm

Error = 2

Ok = 1

class State

Bases: int

Unchecked = 0

check(dsi, options=aims.carto.none(), passbegin=1, passend=3)

Finds the right format checker

It is possible to specify wich passes to process through passbegin and passend. * pass 1: extension * pass 2: empty extension * pass 3: all writers see DataSourceInfo DataSourceList DataSourceCapabilities

Parameters:

• dsi (DataSourceInfo containing header, DSlist and .) – capabilities. It allows us to have none, some or all information already computed. It is for the DSIloader to deal with the all case, and for the FormatCheckers to deal with some and none cases.

• options (A dictionary containing options. They may not be of) – any use to the checker, but soma are (resolution_level).

Returns:

• A DataSourceInfo object containing a header, a list of

• DataSource and a list of Capabilities.

errorMessage()

error message from the last check

extensions(format)

Query supported file extensions for a format

Parameters:

format (string) – format to query

Returns:

exts – set of extensions names

Return type:

set_STRING

launchException()

raise the read exception which was most probably the cause of a check() failure

readMinf(ds, base=aims.none(), options=aims.none())

read a .minf file dictionary

Parameters:

• ds (DataSource) – minf file DataSource

• base (Object) – base dict to be completed by .minf information

• options (Object) – options dict

Returns:

minf – the minf file contents as a dictionary

Return type:

Object

state()

state of the DataSourceInfoLoader reading trial

class DataSourceList

Bases: wrapper

DataSourceList():

Builds a map containing only (“default”, empty pointer)

DataSourceList(ds, type=”default”):

Builds a 1-element map This allows to construct easily a 1 element list, useful when declaring a Reader which creator takes a source as parameter.

Parameters:

• ds (rc_ptr_DataSource) – Element to insert

• type (string) – Category of the source. default key is “default”: used at Reader construction

This class allows to manipulate “lists” of pointers to DataSource.

It has the design of a dictionary in order to sort sources by content (header, minf, data, …). Since those contents depend on the format, the keywords used are defined by specific checkers and readers.

see FormatChecker FormatReader

The only global keyword is “default” which is used to store the DataSource defining (at construction) a reader.

see Reader

Note

The “default” keyword always contains at least one entry, which may be empty. I haven’t for now found any use to several “default” entries.

Access to a source is done using dataSource(…) methods. Sources are ordered by increasing order of insertion and numbering starts at 0.

addDataSource(key, ds)

Adds an element to the dictionary If new keyword, creates it.

Parameters:

• key (string) – keyword

• ds (rc_ptr_DataSource) – DataSource to be added

dataSource()

datasource(key=”default”, i=0)

Accessing an element of the list If keyword doesn’t exist, or is empty, or coordinate is undefined, launches exception.

Parameters:

• key (string (optional)) – keyword

• i (int (optional)) – number of the element in list. Numbering starts at 0

empty()

Returns true only if no keyword inserted.

Warning

May return false while no DataSource present

True if there is no key in the dictionary

exists(key)

True if the key exists in the dictionary

reset()

clear the dictionary: all keys and contents are removed.

size(key)

number of elements with the key key

typecount()

number of keys in the types dictionary

types()

Returns existing keywords.

Warning

There may be existing keywords with no DataSource

class FDDataSource(*args)

Bases: DataSource

DataSource specialization for file descriptor stream

allowsMemoryMapping()

returns True if memory mapping is allowed on this kind of stream

at()

offset = at()

returns the current position in the stream

bool at(pos)

Sets the current position in the stream (when supported). Returns True if successful.

clone()

duplicate the DataSource object

close()

Close the stream

descriptor()

get the file descriptor

getch()

read one char and returns it

isFile()

True if the DataSource is a file

isOpen()

tells if the stream is open / ok.

iterateMode()

bitwise combination of possible access: direct (1) or sequential (2) access

open(mode)

Opens the stream (when supported) in the specified Mode

Parameters:

mode (int) – access Mode: Read (1), Write (2) or ReadWrite (3)

Returns:

ok – if the operation was successful

Return type:

bool

putch(ch)

write one char, and returns it

Parameters:

ch (int) – char to write

readBlock(data, maxlen)

Parameters:

• data (char*) – read buffer (C++)

• maxlen (unsigned long int) – number of bytes to read

Returns:

num – number of bytes actually read

Return type:

long int

setDescriptor(fd)

Set the file descriptor fd (int)

size()

size (or len) of the data inn stream, in bytes

ungetch(ch)

un-read one char: put it back in the read buffer, and rewind one char

writeBlock(data, len)

Parameters:

• data (const char * (C++)) – buffer to be written

• len (unsigned long int) – size of the buffer to be written

Returns:

num – number of bytes actually written

Return type:

long int

class FileDataSource(filename, offset=0, mode=aims.soma.DataSource.Read)

Bases: DataSource

Parameters:

• filename (string) – file name on the filesystem

• offset (soma.offset_t (optional)) – offset to start reading in the file

• mode (aims.soma.DataSource.Mode (optional)) – read / write mode

DataSource specialization for a file.

allowsMemoryMapping()

returns True if memory mapping is allowed on this kind of stream

at()

offset = at()

returns the current position in the stream

bool at(pos)

Sets the current position in the stream (when supported). Returns True if successful.

clone()

duplicate the DataSource object

close()

Close the stream

getch()

read one char and returns it

initialOffset()

initial offset in the input file to start reading

isOpen()

tells if the stream is open / ok.

iterateMode()

bitwise combination of possible access: direct (1) or sequential (2) access

open(mode)

Opens the stream (when supported) in the specified Mode

Parameters:

mode (int) – access Mode: Read (1), Write (2) or ReadWrite (3)

Returns:

ok – if the operation was successful

Return type:

bool

putch(ch)

write one char, and returns it

Parameters:

ch (int) – char to write

readBlock(data, maxlen)

Parameters:

• data (char*) – read buffer (C++)

• maxlen (unsigned long int) – number of bytes to read

Returns:

num – number of bytes actually read

Return type:

long int

size()

size (or len) of the data inn stream, in bytes

ungetch(ch)

un-read one char: put it back in the read buffer, and rewind one char

url()

file name or URL of the file

writeBlock(data, len)

Parameters:

• data (const char * (C++)) – buffer to be written

• len (unsigned long int) – size of the buffer to be written

Returns:

num – number of bytes actually written

Return type:

long int

class Reader_Object

Bases: wrapper

Soma-IO Reader class. This is a C++ template class, which can read a specific type of data. All supported formats can be read.

Constructor parameters may be:

• string: filename

• rc_ptr_DataSource: generic DataSource

• rc_ptr_DataSourceInfo: DataSource with info (more optimal when the data source has been identified and the header loaded)

allocatorContext()

Get the allocation context

attach(ds)

Attach a DataSource to read from (rc_ptr_DataSource)

attach(filename, offset=0)

Attach a new filename + offset for reading

close()

Close the data source stream

dataSource()

Get the data source (rc_ptr_DataSource)

dataSourceInfo()

Get the dataSourceInfo, providing information on the read data

flush()

Flush the read buffer

options()

Get reading options (Object dictionary)

read()

Read an object from source. Two main modes exist:

• full: read a full new object and return it

• in-place: read an existing object, in-place

A multi-pass procedure is used to identify and read the data from the data source:

• pass 1: format hint

• pass 2: extension

• pass 3: empty extension

• pass 4: all readers

Parameters:

• header (Object (optional)) – in-place mode: carto::Object, object to be read. OR: full mode: header (Object), optional

• header –

• passbegin (int (optional)) – begin at given step of the multi-pass identification/read procedure

• passend (int (optional)) – end at given step of the multi-pass identification/read procedure

Returns:

• in-place mode – True upon success False upon failure (but readers will more likely throw an exception)

• full mode – the read object

setAllocatorContext(context)

Set allocation context for reading

setOptions(options)

set reading options (Object dictionary)

class Reader_Volume_CDOUBLE

Bases: wrapper

Soma-IO Reader class. This is a C++ template class, which can read a specific type of data. All supported formats can be read.

Constructor parameters may be:

• string: filename

• rc_ptr_DataSource: generic DataSource

• rc_ptr_DataSourceInfo: DataSource with info (more optimal when the data source has been identified and the header loaded)

allocatorContext()

Get the allocation context

attach(ds)

Attach a DataSource to read from (rc_ptr_DataSource)

attach(filename, offset=0)

Attach a new filename + offset for reading

close()

Close the data source stream

dataSource()

Get the data source (rc_ptr_DataSource)

dataSourceInfo()

Get the dataSourceInfo, providing information on the read data

flush()

Flush the read buffer

options()

Get reading options (Object dictionary)

read()

Read an object from source. Two main modes exist:

• full: read a full new object and return it

• in-place: read an existing object, in-place

A multi-pass procedure is used to identify and read the data from the data source:

• pass 1: format hint

• pass 2: extension

• pass 3: empty extension

• pass 4: all readers

Parameters:

• header (Object (optional)) – in-place mode: Volume_CDOUBLE, object to be read. OR: full mode: header (Object), optional

• header –

• passbegin (int (optional)) – begin at given step of the multi-pass identification/read procedure

• passend (int (optional)) – end at given step of the multi-pass identification/read procedure

Returns:

• in-place mode – True upon success False upon failure (but readers will more likely throw an exception)

• full mode – the read object

setAllocatorContext(context)

Set allocation context for reading

setOptions(options)

set reading options (Object dictionary)

class Reader_Volume_CFLOAT

Bases: wrapper

Soma-IO Reader class. This is a C++ template class, which can read a specific type of data. All supported formats can be read.

Constructor parameters may be:

• string: filename

• rc_ptr_DataSource: generic DataSource

• rc_ptr_DataSourceInfo: DataSource with info (more optimal when the data source has been identified and the header loaded)

allocatorContext()

Get the allocation context

attach(ds)

Attach a DataSource to read from (rc_ptr_DataSource)

attach(filename, offset=0)

Attach a new filename + offset for reading

close()

Close the data source stream

dataSource()

Get the data source (rc_ptr_DataSource)

dataSourceInfo()

Get the dataSourceInfo, providing information on the read data

flush()

Flush the read buffer

options()

Get reading options (Object dictionary)

read()

Read an object from source. Two main modes exist:

• full: read a full new object and return it

• in-place: read an existing object, in-place

A multi-pass procedure is used to identify and read the data from the data source:

• pass 1: format hint

• pass 2: extension

• pass 3: empty extension

• pass 4: all readers

Parameters:

• header (Object (optional)) – in-place mode: Volume_CFLOAT, object to be read. OR: full mode: header (Object), optional

• header –

• passbegin (int (optional)) – begin at given step of the multi-pass identification/read procedure

• passend (int (optional)) – end at given step of the multi-pass identification/read procedure

Returns:

• in-place mode – True upon success False upon failure (but readers will more likely throw an exception)

• full mode – the read object

setAllocatorContext(context)

Set allocation context for reading

setOptions(options)

set reading options (Object dictionary)

class Reader_Volume_DOUBLE

Bases: wrapper

Soma-IO Reader class. This is a C++ template class, which can read a specific type of data. All supported formats can be read.

Constructor parameters may be:

• string: filename

• rc_ptr_DataSource: generic DataSource

• rc_ptr_DataSourceInfo: DataSource with info (more optimal when the data source has been identified and the header loaded)

allocatorContext()

Get the allocation context

attach(ds)

Attach a DataSource to read from (rc_ptr_DataSource)

attach(filename, offset=0)

Attach a new filename + offset for reading

close()

Close the data source stream

dataSource()

Get the data source (rc_ptr_DataSource)

dataSourceInfo()

Get the dataSourceInfo, providing information on the read data

flush()

Flush the read buffer

options()

Get reading options (Object dictionary)

read()

Read an object from source. Two main modes exist:

• full: read a full new object and return it

• in-place: read an existing object, in-place

A multi-pass procedure is used to identify and read the data from the data source:

• pass 1: format hint

• pass 2: extension

• pass 3: empty extension

• pass 4: all readers

Parameters:

• header (Object (optional)) – in-place mode: Volume_DOUBLE, object to be read. OR: full mode: header (Object), optional

• header –

• passbegin (int (optional)) – begin at given step of the multi-pass identification/read procedure

• passend (int (optional)) – end at given step of the multi-pass identification/read procedure

Returns:

• in-place mode – True upon success False upon failure (but readers will more likely throw an exception)

• full mode – the read object

setAllocatorContext(context)

Set allocation context for reading

setOptions(options)

set reading options (Object dictionary)

class Reader_Volume_FLOAT

Bases: wrapper

Soma-IO Reader class. This is a C++ template class, which can read a specific type of data. All supported formats can be read.

Constructor parameters may be:

• string: filename

• rc_ptr_DataSource: generic DataSource

• rc_ptr_DataSourceInfo: DataSource with info (more optimal when the data source has been identified and the header loaded)

allocatorContext()

Get the allocation context

attach(ds)

Attach a DataSource to read from (rc_ptr_DataSource)

attach(filename, offset=0)

Attach a new filename + offset for reading

close()

Close the data source stream

dataSource()

Get the data source (rc_ptr_DataSource)

dataSourceInfo()

Get the dataSourceInfo, providing information on the read data

flush()

Flush the read buffer

options()

Get reading options (Object dictionary)

read()

Read an object from source. Two main modes exist:

• full: read a full new object and return it

• in-place: read an existing object, in-place

A multi-pass procedure is used to identify and read the data from the data source:

• pass 1: format hint

• pass 2: extension

• pass 3: empty extension

• pass 4: all readers

Parameters:

• header (Object (optional)) – in-place mode: Volume_FLOAT, object to be read. OR: full mode: header (Object), optional

• header –

• passbegin (int (optional)) – begin at given step of the multi-pass identification/read procedure

• passend (int (optional)) – end at given step of the multi-pass identification/read procedure

Returns:

• in-place mode – True upon success False upon failure (but readers will more likely throw an exception)

• full mode – the read object

setAllocatorContext(context)

Set allocation context for reading

setOptions(options)

set reading options (Object dictionary)

class Reader_Volume_HSV

Bases: wrapper

Soma-IO Reader class. This is a C++ template class, which can read a specific type of data. All supported formats can be read.

Constructor parameters may be:

• string: filename

• rc_ptr_DataSource: generic DataSource

• rc_ptr_DataSourceInfo: DataSource with info (more optimal when the data source has been identified and the header loaded)

allocatorContext()

Get the allocation context

attach(ds)

Attach a DataSource to read from (rc_ptr_DataSource)

attach(filename, offset=0)

Attach a new filename + offset for reading

close()

Close the data source stream

dataSource()

Get the data source (rc_ptr_DataSource)

dataSourceInfo()

Get the dataSourceInfo, providing information on the read data

flush()

Flush the read buffer

options()

Get reading options (Object dictionary)

read()

Read an object from source. Two main modes exist:

• full: read a full new object and return it

• in-place: read an existing object, in-place

A multi-pass procedure is used to identify and read the data from the data source:

• pass 1: format hint

• pass 2: extension

• pass 3: empty extension

• pass 4: all readers

Parameters:

• header (Object (optional)) – in-place mode: Volume_HSV, object to be read. OR: full mode: header (Object), optional

• header –

• passbegin (int (optional)) – begin at given step of the multi-pass identification/read procedure

• passend (int (optional)) – end at given step of the multi-pass identification/read procedure

Returns:

• in-place mode – True upon success False upon failure (but readers will more likely throw an exception)

• full mode – the read object

setAllocatorContext(context)

Set allocation context for reading

setOptions(options)

set reading options (Object dictionary)

class Reader_Volume_POINT3DF

Bases: wrapper

Soma-IO Reader class. This is a C++ template class, which can read a specific type of data. All supported formats can be read.

Constructor parameters may be:

• string: filename

• rc_ptr_DataSource: generic DataSource

• rc_ptr_DataSourceInfo: DataSource with info (more optimal when the data source has been identified and the header loaded)

allocatorContext()

Get the allocation context

attach(ds)

Attach a DataSource to read from (rc_ptr_DataSource)

attach(filename, offset=0)

Attach a new filename + offset for reading

close()

Close the data source stream

dataSource()

Get the data source (rc_ptr_DataSource)

dataSourceInfo()

Get the dataSourceInfo, providing information on the read data

flush()

Flush the read buffer

options()

Get reading options (Object dictionary)

read()

Read an object from source. Two main modes exist:

• full: read a full new object and return it

• in-place: read an existing object, in-place

A multi-pass procedure is used to identify and read the data from the data source:

• pass 1: format hint

• pass 2: extension

• pass 3: empty extension

• pass 4: all readers

Parameters:

• header (Object (optional)) – in-place mode: Volume_POINT3DF, object to be read. OR: full mode: header (Object), optional

• header –

• passbegin (int (optional)) – begin at given step of the multi-pass identification/read procedure

• passend (int (optional)) – end at given step of the multi-pass identification/read procedure

Returns:

• in-place mode – True upon success False upon failure (but readers will more likely throw an exception)

• full mode – the read object

setAllocatorContext(context)

Set allocation context for reading

setOptions(options)

set reading options (Object dictionary)

class Reader_Volume_RGB

Bases: wrapper

Soma-IO Reader class. This is a C++ template class, which can read a specific type of data. All supported formats can be read.

Constructor parameters may be:

• string: filename

• rc_ptr_DataSource: generic DataSource

• rc_ptr_DataSourceInfo: DataSource with info (more optimal when the data source has been identified and the header loaded)

allocatorContext()

Get the allocation context

attach(ds)

Attach a DataSource to read from (rc_ptr_DataSource)

attach(filename, offset=0)

Attach a new filename + offset for reading

close()

Close the data source stream

dataSource()

Get the data source (rc_ptr_DataSource)

dataSourceInfo()

Get the dataSourceInfo, providing information on the read data

flush()

Flush the read buffer

options()

Get reading options (Object dictionary)

read()

Read an object from source. Two main modes exist:

• full: read a full new object and return it

• in-place: read an existing object, in-place

A multi-pass procedure is used to identify and read the data from the data source:

• pass 1: format hint

• pass 2: extension

• pass 3: empty extension

• pass 4: all readers

Parameters:

• header (Object (optional)) – in-place mode: Volume_RGB, object to be read. OR: full mode: header (Object), optional

• header –

• passbegin (int (optional)) – begin at given step of the multi-pass identification/read procedure

• passend (int (optional)) – end at given step of the multi-pass identification/read procedure

Returns:

• in-place mode – True upon success False upon failure (but readers will more likely throw an exception)

• full mode – the read object

setAllocatorContext(context)

Set allocation context for reading

setOptions(options)

set reading options (Object dictionary)

class Reader_Volume_RGBA

Bases: wrapper

Soma-IO Reader class. This is a C++ template class, which can read a specific type of data. All supported formats can be read.

Constructor parameters may be:

• string: filename

• rc_ptr_DataSource: generic DataSource

• rc_ptr_DataSourceInfo: DataSource with info (more optimal when the data source has been identified and the header loaded)

allocatorContext()

Get the allocation context

attach(ds)

Attach a DataSource to read from (rc_ptr_DataSource)

attach(filename, offset=0)

Attach a new filename + offset for reading

close()

Close the data source stream

dataSource()

Get the data source (rc_ptr_DataSource)

dataSourceInfo()

Get the dataSourceInfo, providing information on the read data

flush()

Flush the read buffer

options()

Get reading options (Object dictionary)

read()

Read an object from source. Two main modes exist:

• full: read a full new object and return it

• in-place: read an existing object, in-place

A multi-pass procedure is used to identify and read the data from the data source:

• pass 1: format hint

• pass 2: extension

• pass 3: empty extension

• pass 4: all readers

Parameters:

• header (Object (optional)) – in-place mode: Volume_RGBA, object to be read. OR: full mode: header (Object), optional

• header –

• passbegin (int (optional)) – begin at given step of the multi-pass identification/read procedure

• passend (int (optional)) – end at given step of the multi-pass identification/read procedure

Returns:

• in-place mode – True upon success False upon failure (but readers will more likely throw an exception)

• full mode – the read object

setAllocatorContext(context)

Set allocation context for reading

setOptions(options)

set reading options (Object dictionary)

class Reader_Volume_S16

Bases: wrapper

Soma-IO Reader class. This is a C++ template class, which can read a specific type of data. All supported formats can be read.

Constructor parameters may be:

• string: filename

• rc_ptr_DataSource: generic DataSource

• rc_ptr_DataSourceInfo: DataSource with info (more optimal when the data source has been identified and the header loaded)

allocatorContext()

Get the allocation context

attach(ds)

Attach a DataSource to read from (rc_ptr_DataSource)

attach(filename, offset=0)

Attach a new filename + offset for reading

close()

Close the data source stream

dataSource()

Get the data source (rc_ptr_DataSource)

dataSourceInfo()

Get the dataSourceInfo, providing information on the read data

flush()

Flush the read buffer

options()

Get reading options (Object dictionary)

read()

Read an object from source. Two main modes exist:

• full: read a full new object and return it

• in-place: read an existing object, in-place

A multi-pass procedure is used to identify and read the data from the data source:

• pass 1: format hint

• pass 2: extension

• pass 3: empty extension

• pass 4: all readers

Parameters:

• header (Object (optional)) – in-place mode: Volume_S16, object to be read. OR: full mode: header (Object), optional

• header –

• passbegin (int (optional)) – begin at given step of the multi-pass identification/read procedure

• passend (int (optional)) – end at given step of the multi-pass identification/read procedure

Returns:

• in-place mode – True upon success False upon failure (but readers will more likely throw an exception)

• full mode – the read object

setAllocatorContext(context)

Set allocation context for reading

setOptions(options)

set reading options (Object dictionary)

class Reader_Volume_S32

Bases: wrapper

Soma-IO Reader class. This is a C++ template class, which can read a specific type of data. All supported formats can be read.

Constructor parameters may be:

• string: filename

• rc_ptr_DataSource: generic DataSource

• rc_ptr_DataSourceInfo: DataSource with info (more optimal when the data source has been identified and the header loaded)

allocatorContext()

Get the allocation context

attach(ds)

Attach a DataSource to read from (rc_ptr_DataSource)

attach(filename, offset=0)

Attach a new filename + offset for reading

close()

Close the data source stream

dataSource()

Get the data source (rc_ptr_DataSource)

dataSourceInfo()

Get the dataSourceInfo, providing information on the read data

flush()

Flush the read buffer

options()

Get reading options (Object dictionary)

read()

Read an object from source. Two main modes exist:

• full: read a full new object and return it

• in-place: read an existing object, in-place

A multi-pass procedure is used to identify and read the data from the data source:

• pass 1: format hint

• pass 2: extension

• pass 3: empty extension

• pass 4: all readers

Parameters:

• header (Object (optional)) – in-place mode: Volume_S32, object to be read. OR: full mode: header (Object), optional

• header –

• passbegin (int (optional)) – begin at given step of the multi-pass identification/read procedure

• passend (int (optional)) – end at given step of the multi-pass identification/read procedure

Returns:

• in-place mode – True upon success False upon failure (but readers will more likely throw an exception)

• full mode – the read object

setAllocatorContext(context)

Set allocation context for reading

setOptions(options)

set reading options (Object dictionary)

class Reader_Volume_U16

Bases: wrapper

Soma-IO Reader class. This is a C++ template class, which can read a specific type of data. All supported formats can be read.

Constructor parameters may be:

• string: filename

• rc_ptr_DataSource: generic DataSource

• rc_ptr_DataSourceInfo: DataSource with info (more optimal when the data source has been identified and the header loaded)

allocatorContext()

Get the allocation context

attach(ds)

Attach a DataSource to read from (rc_ptr_DataSource)

attach(filename, offset=0)

Attach a new filename + offset for reading

close()

Close the data source stream

dataSource()

Get the data source (rc_ptr_DataSource)

dataSourceInfo()

Get the dataSourceInfo, providing information on the read data

flush()

Flush the read buffer

options()

Get reading options (Object dictionary)

read()

Read an object from source. Two main modes exist:

• full: read a full new object and return it

• in-place: read an existing object, in-place

A multi-pass procedure is used to identify and read the data from the data source:

• pass 1: format hint

• pass 2: extension

• pass 3: empty extension

• pass 4: all readers

Parameters:

• header (Object (optional)) – in-place mode: Volume_U16, object to be read. OR: full mode: header (Object), optional

• header –

• passbegin (int (optional)) – begin at given step of the multi-pass identification/read procedure

• passend (int (optional)) – end at given step of the multi-pass identification/read procedure

Returns:

• in-place mode – True upon success False upon failure (but readers will more likely throw an exception)

• full mode – the read object

setAllocatorContext(context)

Set allocation context for reading

setOptions(options)

set reading options (Object dictionary)

class Reader_Volume_U32

Bases: wrapper

Soma-IO Reader class. This is a C++ template class, which can read a specific type of data. All supported formats can be read.

Constructor parameters may be:

• string: filename

• rc_ptr_DataSource: generic DataSource

• rc_ptr_DataSourceInfo: DataSource with info (more optimal when the data source has been identified and the header loaded)

allocatorContext()

Get the allocation context

attach(ds)

Attach a DataSource to read from (rc_ptr_DataSource)

attach(filename, offset=0)

Attach a new filename + offset for reading

close()

Close the data source stream

dataSource()

Get the data source (rc_ptr_DataSource)

dataSourceInfo()

Get the dataSourceInfo, providing information on the read data

flush()

Flush the read buffer

options()

Get reading options (Object dictionary)

read()

Read an object from source. Two main modes exist:

• full: read a full new object and return it

• in-place: read an existing object, in-place

A multi-pass procedure is used to identify and read the data from the data source:

• pass 1: format hint

• pass 2: extension

• pass 3: empty extension

• pass 4: all readers

Parameters:

• header (Object (optional)) – in-place mode: Volume_U32, object to be read. OR: full mode: header (Object), optional

• header –

• passbegin (int (optional)) – begin at given step of the multi-pass identification/read procedure

• passend (int (optional)) – end at given step of the multi-pass identification/read procedure

Returns:

• in-place mode – True upon success False upon failure (but readers will more likely throw an exception)

• full mode – the read object

setAllocatorContext(context)

Set allocation context for reading

setOptions(options)

set reading options (Object dictionary)

class Reader_Volume_U8

Bases: wrapper

Soma-IO Reader class. This is a C++ template class, which can read a specific type of data. All supported formats can be read.

Constructor parameters may be:

• string: filename

• rc_ptr_DataSource: generic DataSource

• rc_ptr_DataSourceInfo: DataSource with info (more optimal when the data source has been identified and the header loaded)

allocatorContext()

Get the allocation context

attach(ds)

Attach a DataSource to read from (rc_ptr_DataSource)

attach(filename, offset=0)

Attach a new filename + offset for reading

close()

Close the data source stream

dataSource()

Get the data source (rc_ptr_DataSource)

dataSourceInfo()

Get the dataSourceInfo, providing information on the read data

flush()

Flush the read buffer

options()

Get reading options (Object dictionary)

read()

Read an object from source. Two main modes exist:

• full: read a full new object and return it

• in-place: read an existing object, in-place

A multi-pass procedure is used to identify and read the data from the data source:

• pass 1: format hint

• pass 2: extension

• pass 3: empty extension

• pass 4: all readers

Parameters:

• header (Object (optional)) – in-place mode: Volume_U8, object to be read. OR: full mode: header (Object), optional

• header –

• passbegin (int (optional)) – begin at given step of the multi-pass identification/read procedure

• passend (int (optional)) – end at given step of the multi-pass identification/read procedure

Returns:

• in-place mode – True upon success False upon failure (but readers will more likely throw an exception)

• full mode – the read object

setAllocatorContext(context)

Set allocation context for reading

setOptions(options)

set reading options (Object dictionary)

class Transformation(*args)

Bases: RCObject

Base class for spatial transformations.

header()

isIdentity()

Test if the transformation can safely be omitted

This method must only return true if the transformation behaves exactly like an identity transformation (notably, the transform methods will always return the input coordinates unchanged).

NOTE: Implementors of derived classes may choose to always return false if a test would be difficult to implement or expensive to run.

setHeader()

class Transformation3d(*args)

Bases: Transformation

Base class for spatial transformations in 3D.

fromObject()

toObject()

transform()

transformDouble()

transformFloat()

transformPoint3d()

transformPoint3dd()

transformPoint3df()

transformPoints()

class Writer_Object

Bases: wrapper

Soma-IO Writer class. This is a C++ template class, which can write a specific type of data. All supported formats can be written.

Constructor parameters may be:

• string: filename

• rc_ptr_DataSource: generic DataSource

attach(ds)

Attach a new data source (rc_ptr_DataSource) to write into

attach(filename)

Attach a new output file name to write into

close()

Close the data source stream

dataSource()

Get the data source (rc_ptr_DataSource)

flush()

flush the write buffer

write()

Write the given object to the data source (generally files)

A multi-pass procedure is used to identify and write the data to the data source:

• pass 1: format hint

• pass 2: extension

• pass 3: empty extension

• pass 4: all writes

Parameters:

• obj (carto::Object) – object to write

• options (Object (optional)) – Options can be passed to specify some writing parameters. The most important is the format (“format” property): if it is specified, this format is tried first, so you can use it to force the format, otherwise it will be determined from the filename extension (if available). If no extension and no format are given, the first working format will be used.

• passbegin (int (optional)) –

• passend (int (optional)) –

Return type:

True upon success, False upon failure, but an exception is more likely thrown in such case

writtenObjectType()

After writing, get the object type code (string) of the data

class Writer_Volume_CDOUBLE

Bases: wrapper

Soma-IO Writer class. This is a C++ template class, which can write a specific type of data. All supported formats can be written.

Constructor parameters may be:

• string: filename

• rc_ptr_DataSource: generic DataSource

attach(ds)

Attach a new data source (rc_ptr_DataSource) to write into

attach(filename)

Attach a new output file name to write into

close()

Close the data source stream

dataSource()

Get the data source (rc_ptr_DataSource)

flush()

flush the write buffer

write()

Write the given object to the data source (generally files)

A multi-pass procedure is used to identify and write the data to the data source:

• pass 1: format hint

• pass 2: extension

• pass 3: empty extension

• pass 4: all writes

Parameters:

• obj (Volume_CDOUBLE) – object to write

• options (Object (optional)) – Options can be passed to specify some writing parameters. The most important is the format (“format” property): if it is specified, this format is tried first, so you can use it to force the format, otherwise it will be determined from the filename extension (if available). If no extension and no format are given, the first working format will be used.

• passbegin (int (optional)) –

• passend (int (optional)) –

Return type:

True upon success, False upon failure, but an exception is more likely thrown in such case

writtenObjectType()

After writing, get the object type code (string) of the data

class Writer_Volume_CFLOAT

Bases: wrapper

Soma-IO Writer class. This is a C++ template class, which can write a specific type of data. All supported formats can be written.

Constructor parameters may be:

• string: filename

• rc_ptr_DataSource: generic DataSource

attach(ds)

Attach a new data source (rc_ptr_DataSource) to write into

attach(filename)

Attach a new output file name to write into

close()

Close the data source stream

dataSource()

Get the data source (rc_ptr_DataSource)

flush()

flush the write buffer

write()

Write the given object to the data source (generally files)

A multi-pass procedure is used to identify and write the data to the data source:

• pass 1: format hint

• pass 2: extension

• pass 3: empty extension

• pass 4: all writes

Parameters:

• obj (Volume_CFLOAT) – object to write

• options (Object (optional)) – Options can be passed to specify some writing parameters. The most important is the format (“format” property): if it is specified, this format is tried first, so you can use it to force the format, otherwise it will be determined from the filename extension (if available). If no extension and no format are given, the first working format will be used.

• passbegin (int (optional)) –

• passend (int (optional)) –

Return type:

True upon success, False upon failure, but an exception is more likely thrown in such case

writtenObjectType()

After writing, get the object type code (string) of the data

class Writer_Volume_DOUBLE

Bases: wrapper

Soma-IO Writer class. This is a C++ template class, which can write a specific type of data. All supported formats can be written.

Constructor parameters may be:

• string: filename

• rc_ptr_DataSource: generic DataSource

attach(ds)

Attach a new data source (rc_ptr_DataSource) to write into

attach(filename)

Attach a new output file name to write into

close()

Close the data source stream

dataSource()

Get the data source (rc_ptr_DataSource)

flush()

flush the write buffer

write()

Write the given object to the data source (generally files)

A multi-pass procedure is used to identify and write the data to the data source:

• pass 1: format hint

• pass 2: extension

• pass 3: empty extension

• pass 4: all writes

Parameters:

• obj (Volume_DOUBLE) – object to write

• options (Object (optional)) – Options can be passed to specify some writing parameters. The most important is the format (“format” property): if it is specified, this format is tried first, so you can use it to force the format, otherwise it will be determined from the filename extension (if available). If no extension and no format are given, the first working format will be used.

• passbegin (int (optional)) –

• passend (int (optional)) –

Return type:

True upon success, False upon failure, but an exception is more likely thrown in such case

writtenObjectType()

After writing, get the object type code (string) of the data

class Writer_Volume_FLOAT

Bases: wrapper

Soma-IO Writer class. This is a C++ template class, which can write a specific type of data. All supported formats can be written.

Constructor parameters may be:

• string: filename

• rc_ptr_DataSource: generic DataSource

attach(ds)

Attach a new data source (rc_ptr_DataSource) to write into

attach(filename)

Attach a new output file name to write into

close()

Close the data source stream

dataSource()

Get the data source (rc_ptr_DataSource)

flush()

flush the write buffer

write()

Write the given object to the data source (generally files)

A multi-pass procedure is used to identify and write the data to the data source:

• pass 1: format hint

• pass 2: extension

• pass 3: empty extension

• pass 4: all writes

Parameters:

• obj (Volume_FLOAT) – object to write

• options (Object (optional)) – Options can be passed to specify some writing parameters. The most important is the format (“format” property): if it is specified, this format is tried first, so you can use it to force the format, otherwise it will be determined from the filename extension (if available). If no extension and no format are given, the first working format will be used.

• passbegin (int (optional)) –

• passend (int (optional)) –

Return type:

True upon success, False upon failure, but an exception is more likely thrown in such case

writtenObjectType()

After writing, get the object type code (string) of the data

class Writer_Volume_HSV

Bases: wrapper

Soma-IO Writer class. This is a C++ template class, which can write a specific type of data. All supported formats can be written.

Constructor parameters may be:

• string: filename

• rc_ptr_DataSource: generic DataSource

attach(ds)

Attach a new data source (rc_ptr_DataSource) to write into

attach(filename)

Attach a new output file name to write into

close()

Close the data source stream

dataSource()

Get the data source (rc_ptr_DataSource)

flush()

flush the write buffer

write()

Write the given object to the data source (generally files)

A multi-pass procedure is used to identify and write the data to the data source:

• pass 1: format hint

• pass 2: extension

• pass 3: empty extension

• pass 4: all writes

Parameters:

• obj (Volume_HSV) – object to write

• options (Object (optional)) – Options can be passed to specify some writing parameters. The most important is the format (“format” property): if it is specified, this format is tried first, so you can use it to force the format, otherwise it will be determined from the filename extension (if available). If no extension and no format are given, the first working format will be used.

• passbegin (int (optional)) –

• passend (int (optional)) –

Return type:

True upon success, False upon failure, but an exception is more likely thrown in such case

writtenObjectType()

After writing, get the object type code (string) of the data

class Writer_Volume_POINT3DF

Bases: wrapper

Soma-IO Writer class. This is a C++ template class, which can write a specific type of data. All supported formats can be written.

Constructor parameters may be:

• string: filename

• rc_ptr_DataSource: generic DataSource

attach(ds)

Attach a new data source (rc_ptr_DataSource) to write into

attach(filename)

Attach a new output file name to write into

close()

Close the data source stream

dataSource()

Get the data source (rc_ptr_DataSource)

flush()

flush the write buffer

write()

Write the given object to the data source (generally files)

A multi-pass procedure is used to identify and write the data to the data source:

• pass 1: format hint

• pass 2: extension

• pass 3: empty extension

• pass 4: all writes

Parameters:

• obj (Volume_POINT3DF) – object to write

• options (Object (optional)) – Options can be passed to specify some writing parameters. The most important is the format (“format” property): if it is specified, this format is tried first, so you can use it to force the format, otherwise it will be determined from the filename extension (if available). If no extension and no format are given, the first working format will be used.

• passbegin (int (optional)) –

• passend (int (optional)) –

Return type:

True upon success, False upon failure, but an exception is more likely thrown in such case

writtenObjectType()

After writing, get the object type code (string) of the data

class Writer_Volume_RGB

Bases: wrapper

Soma-IO Writer class. This is a C++ template class, which can write a specific type of data. All supported formats can be written.

Constructor parameters may be:

• string: filename

• rc_ptr_DataSource: generic DataSource

attach(ds)

Attach a new data source (rc_ptr_DataSource) to write into

attach(filename)

Attach a new output file name to write into

close()

Close the data source stream

dataSource()

Get the data source (rc_ptr_DataSource)

flush()

flush the write buffer

write()

Write the given object to the data source (generally files)

A multi-pass procedure is used to identify and write the data to the data source:

• pass 1: format hint

• pass 2: extension

• pass 3: empty extension

• pass 4: all writes

Parameters:

• obj (Volume_RGB) – object to write

• options (Object (optional)) – Options can be passed to specify some writing parameters. The most important is the format (“format” property): if it is specified, this format is tried first, so you can use it to force the format, otherwise it will be determined from the filename extension (if available). If no extension and no format are given, the first working format will be used.

• passbegin (int (optional)) –

• passend (int (optional)) –

Return type:

True upon success, False upon failure, but an exception is more likely thrown in such case

writtenObjectType()

After writing, get the object type code (string) of the data

class Writer_Volume_RGBA

Bases: wrapper

Soma-IO Writer class. This is a C++ template class, which can write a specific type of data. All supported formats can be written.

Constructor parameters may be:

• string: filename

• rc_ptr_DataSource: generic DataSource

attach(ds)

Attach a new data source (rc_ptr_DataSource) to write into

attach(filename)

Attach a new output file name to write into

close()

Close the data source stream

dataSource()

Get the data source (rc_ptr_DataSource)

flush()

flush the write buffer

write()

Write the given object to the data source (generally files)

A multi-pass procedure is used to identify and write the data to the data source:

• pass 1: format hint

• pass 2: extension

• pass 3: empty extension

• pass 4: all writes

Parameters:

• obj (Volume_RGBA) – object to write

• options (Object (optional)) – Options can be passed to specify some writing parameters. The most important is the format (“format” property): if it is specified, this format is tried first, so you can use it to force the format, otherwise it will be determined from the filename extension (if available). If no extension and no format are given, the first working format will be used.

• passbegin (int (optional)) –

• passend (int (optional)) –

Return type:

True upon success, False upon failure, but an exception is more likely thrown in such case

writtenObjectType()

After writing, get the object type code (string) of the data

class Writer_Volume_S16

Bases: wrapper

Soma-IO Writer class. This is a C++ template class, which can write a specific type of data. All supported formats can be written.

Constructor parameters may be:

• string: filename

• rc_ptr_DataSource: generic DataSource

attach(ds)

Attach a new data source (rc_ptr_DataSource) to write into

attach(filename)

Attach a new output file name to write into

close()

Close the data source stream

dataSource()

Get the data source (rc_ptr_DataSource)

flush()

flush the write buffer

write()

Write the given object to the data source (generally files)

A multi-pass procedure is used to identify and write the data to the data source:

• pass 1: format hint

• pass 2: extension

• pass 3: empty extension

• pass 4: all writes

Parameters:

• obj (Volume_S16) – object to write

• options (Object (optional)) – Options can be passed to specify some writing parameters. The most important is the format (“format” property): if it is specified, this format is tried first, so you can use it to force the format, otherwise it will be determined from the filename extension (if available). If no extension and no format are given, the first working format will be used.

• passbegin (int (optional)) –

• passend (int (optional)) –

Return type:

True upon success, False upon failure, but an exception is more likely thrown in such case

writtenObjectType()

After writing, get the object type code (string) of the data

class Writer_Volume_S32

Bases: wrapper

Soma-IO Writer class. This is a C++ template class, which can write a specific type of data. All supported formats can be written.

Constructor parameters may be:

• string: filename

• rc_ptr_DataSource: generic DataSource

attach(ds)

Attach a new data source (rc_ptr_DataSource) to write into

attach(filename)

Attach a new output file name to write into

close()

Close the data source stream

dataSource()

Get the data source (rc_ptr_DataSource)

flush()

flush the write buffer

write()

Write the given object to the data source (generally files)

A multi-pass procedure is used to identify and write the data to the data source:

• pass 1: format hint

• pass 2: extension

• pass 3: empty extension

• pass 4: all writes

Parameters:

• obj (Volume_S32) – object to write

• options (Object (optional)) – Options can be passed to specify some writing parameters. The most important is the format (“format” property): if it is specified, this format is tried first, so you can use it to force the format, otherwise it will be determined from the filename extension (if available). If no extension and no format are given, the first working format will be used.

• passbegin (int (optional)) –

• passend (int (optional)) –

Return type:

True upon success, False upon failure, but an exception is more likely thrown in such case

writtenObjectType()

After writing, get the object type code (string) of the data

class Writer_Volume_U16

Bases: wrapper

Soma-IO Writer class. This is a C++ template class, which can write a specific type of data. All supported formats can be written.

Constructor parameters may be:

• string: filename

• rc_ptr_DataSource: generic DataSource

attach(ds)

Attach a new data source (rc_ptr_DataSource) to write into

attach(filename)

Attach a new output file name to write into

close()

Close the data source stream

dataSource()

Get the data source (rc_ptr_DataSource)

flush()

flush the write buffer

write()

Write the given object to the data source (generally files)

A multi-pass procedure is used to identify and write the data to the data source:

• pass 1: format hint

• pass 2: extension

• pass 3: empty extension

• pass 4: all writes

Parameters:

• obj (Volume_U16) – object to write

• options (Object (optional)) – Options can be passed to specify some writing parameters. The most important is the format (“format” property): if it is specified, this format is tried first, so you can use it to force the format, otherwise it will be determined from the filename extension (if available). If no extension and no format are given, the first working format will be used.

• passbegin (int (optional)) –

• passend (int (optional)) –

Return type:

True upon success, False upon failure, but an exception is more likely thrown in such case

writtenObjectType()

After writing, get the object type code (string) of the data

class Writer_Volume_U32

Bases: wrapper

Soma-IO Writer class. This is a C++ template class, which can write a specific type of data. All supported formats can be written.

Constructor parameters may be:

• string: filename

• rc_ptr_DataSource: generic DataSource

attach(ds)

Attach a new data source (rc_ptr_DataSource) to write into

attach(filename)

Attach a new output file name to write into

close()

Close the data source stream

dataSource()

Get the data source (rc_ptr_DataSource)

flush()

flush the write buffer

write()

Write the given object to the data source (generally files)

A multi-pass procedure is used to identify and write the data to the data source:

• pass 1: format hint

• pass 2: extension

• pass 3: empty extension

• pass 4: all writes

Parameters:

• obj (Volume_U32) – object to write

• options (Object (optional)) – Options can be passed to specify some writing parameters. The most important is the format (“format” property): if it is specified, this format is tried first, so you can use it to force the format, otherwise it will be determined from the filename extension (if available). If no extension and no format are given, the first working format will be used.

• passbegin (int (optional)) –

• passend (int (optional)) –

Return type:

True upon success, False upon failure, but an exception is more likely thrown in such case

writtenObjectType()

After writing, get the object type code (string) of the data

class Writer_Volume_U8

Bases: wrapper

Soma-IO Writer class. This is a C++ template class, which can write a specific type of data. All supported formats can be written.

Constructor parameters may be:

• string: filename

• rc_ptr_DataSource: generic DataSource

attach(ds)

Attach a new data source (rc_ptr_DataSource) to write into

attach(filename)

Attach a new output file name to write into

close()

Close the data source stream

dataSource()

Get the data source (rc_ptr_DataSource)

flush()

flush the write buffer

write()

Write the given object to the data source (generally files)

A multi-pass procedure is used to identify and write the data to the data source:

• pass 1: format hint

• pass 2: extension

• pass 3: empty extension

• pass 4: all writes

Parameters:

• obj (Volume_U8) – object to write

• options (Object (optional)) – Options can be passed to specify some writing parameters. The most important is the format (“format” property): if it is specified, this format is tried first, so you can use it to force the format, otherwise it will be determined from the filename extension (if available). If no extension and no format are given, the first working format will be used.

• passbegin (int (optional)) –

• passend (int (optional)) –

Return type:

True upon success, False upon failure, but an exception is more likely thrown in such case

writtenObjectType()

After writing, get the object type code (string) of the data

soma.aims.somaio_typeCode(data)

returns the Soma-IO type code (as in soma.carto.IOObjectTypesDictionary.readTypes() dict keys) for the given input type.

Parameters:

data (string or type or instance, or 2-tuple) – If type or instance, get the type code for the given object. If string, try to translate AIMS IO to soma-IO codes. If 2-tuple, translate AIMS object type / data type couple

soma.aims.stdList(*args, **kwargs)

Create an instance of STL C++ list (list_<type>) from a type parameter, which may be specified as the dtype keyword argument, or as one of the arguments if one is identitied as a type.

Type definitions should match those accepted by typeCode().

soma.aims.stdSet(*args, **kwargs)

Create an instance of STL C++ set (set_<type>) from a type parameter, which may be specified as the dtype keyword argument, or as one of the arguments if one is identitied as a type.

Type definitions should match those accepted by typeCode().

soma.aims.stdVector(*args, **kwargs)

Create an instance of STL C++ vector (vector_<type>) from a type parameter, which may be specified as the dtype keyword argument, or as one of the arguments if one is identitied as a type.

Type definitions should match those accepted by typeCode().

soma.aims.supported_io_formats(otypes=None, access='')

Returns a list of formats supported to read or write the given object types. Both AIMS and Soma-IO support are queried.

Parameters:

• otypes (dict, list, str, or None) – object types. May be given in several shapes: 1. None: will query all possible object types. 2. str: will get all data types (voxel, texture) for the given container object type (Volume, Mesh etc.). 3. list of str: a list of container object types, as in the str case. 4. dict: allows to specify precisely object type / data types mapping: for each object type, a list of data types will be used. When a data type is None, then all possible ones will be used.

• access (str) – read / write capabilities: restricts soma-io IO queries to the specified access modes. aims IO will not be affected by this parameter since it does not separate reading and writing capabilities. Possible values are: ‘’: any, ‘r’: read, ‘w’: write, ‘rw’: both needed.

Returns:

formats – set of formats names

Return type:

set of str

soma.aims.textureMax()

class soma.aims.threshold_t

Bases: int

soma.aims.transformBoundingBox()

soma.aims.typeCode(data)

returns the AIMS type code for the given input data. data may be a string code, a python/numpy numeric type, an AIMS type, or an instance of such a type.

soma.aims.vectProduct()

class soma.aims.vector_AimsVector_U32_2

Bases: wrapper

append()

array_struct()

Return a numpy array of elements. For vectors of scalar types, this is the same as the other functions __array__() and arraydata(). But for vectors where the elements are “sub-arrays”, ie objects that can be mapped to arrays, the returned array elements will be structures: for instance a Point3df will be mapped to numpy.dtype([(‘v’, ‘3f4’)])

arraydata()

assign()

checkResize()

fromObject()

index()

list()

property np

The np property is a shortcut to the __array__ method. Thus:

something.np

is a handier equivalent to:

numpy.asarray(something)

remove()

resize()

size()

toObject()

class soma.aims.vector_AimsVector_U32_2_iterator

Bases: wrapper

class soma.aims.vector_AimsVector_U32_3

Bases: wrapper

append()

array_struct()

Return a numpy array of elements. For vectors of scalar types, this is the same as the other functions __array__() and arraydata(). But for vectors where the elements are “sub-arrays”, ie objects that can be mapped to arrays, the returned array elements will be structures: for instance a Point3df will be mapped to numpy.dtype([(‘v’, ‘3f4’)])

arraydata()

assign()

checkResize()

fromObject()

index()

list()

property np

The np property is a shortcut to the __array__ method. Thus:

something.np

is a handier equivalent to:

numpy.asarray(something)

remove()

resize()

size()

toObject()

class soma.aims.vector_AimsVector_U32_3_iterator

Bases: wrapper

class soma.aims.vector_AimsVector_U32_4

Bases: wrapper

append()

array_struct()

Return a numpy array of elements. For vectors of scalar types, this is the same as the other functions __array__() and arraydata(). But for vectors where the elements are “sub-arrays”, ie objects that can be mapped to arrays, the returned array elements will be structures: for instance a Point3df will be mapped to numpy.dtype([(‘v’, ‘3f4’)])

arraydata()

assign()

checkResize()

fromObject()

index()

list()

property np

The np property is a shortcut to the __array__ method. Thus:

something.np

is a handier equivalent to:

numpy.asarray(something)

remove()

resize()

size()

toObject()

class soma.aims.vector_AimsVector_U32_4_iterator

Bases: wrapper

class soma.aims.vector_DOUBLE

Bases: wrapper

append()

array_struct()

Return a numpy array of elements. For vectors of scalar types, this is the same as the other functions __array__() and arraydata(). But for vectors where the elements are “sub-arrays”, ie objects that can be mapped to arrays, the returned array elements will be structures: for instance a Point3df will be mapped to numpy.dtype([(‘v’, ‘3f4’)])

arraydata()

assign()

checkResize()

fromObject()

index()

list()

property np

The np property is a shortcut to the __array__ method. Thus:

something.np

is a handier equivalent to:

numpy.asarray(something)

remove()

resize()

size()

toObject()

class soma.aims.vector_DOUBLE_iterator

Bases: wrapper

class soma.aims.vector_FLOAT

Bases: wrapper

append()

array_struct()

Return a numpy array of elements. For vectors of scalar types, this is the same as the other functions __array__() and arraydata(). But for vectors where the elements are “sub-arrays”, ie objects that can be mapped to arrays, the returned array elements will be structures: for instance a Point3df will be mapped to numpy.dtype([(‘v’, ‘3f4’)])

arraydata()

assign()

checkResize()

fromObject()

index()

list()

property np

The np property is a shortcut to the __array__ method. Thus:

something.np

is a handier equivalent to:

numpy.asarray(something)

remove()

resize()

size()

toObject()

class soma.aims.vector_FLOAT_iterator

Bases: wrapper

class soma.aims.vector_POINT2DF

Bases: wrapper

append()

array_struct()

Return a numpy array of elements. For vectors of scalar types, this is the same as the other functions __array__() and arraydata(). But for vectors where the elements are “sub-arrays”, ie objects that can be mapped to arrays, the returned array elements will be structures: for instance a Point3df will be mapped to numpy.dtype([(‘v’, ‘3f4’)])

arraydata()

assign()

checkResize()

fromObject()

index()

list()

property np

The np property is a shortcut to the __array__ method. Thus:

something.np

is a handier equivalent to:

numpy.asarray(something)

remove()

resize()

size()

toObject()

class soma.aims.vector_POINT2DF_iterator

Bases: wrapper

class soma.aims.vector_POINT3D

Bases: wrapper

append()

array_struct()

Return a numpy array of elements. For vectors of scalar types, this is the same as the other functions __array__() and arraydata(). But for vectors where the elements are “sub-arrays”, ie objects that can be mapped to arrays, the returned array elements will be structures: for instance a Point3df will be mapped to numpy.dtype([(‘v’, ‘3f4’)])

arraydata()

assign()

checkResize()

fromObject()

index()

list()

property np

The np property is a shortcut to the __array__ method. Thus:

something.np

is a handier equivalent to:

numpy.asarray(something)

remove()

resize()

size()

toObject()

class soma.aims.vector_POINT3DD

Bases: wrapper

append()

array_struct()

Return a numpy array of elements. For vectors of scalar types, this is the same as the other functions __array__() and arraydata(). But for vectors where the elements are “sub-arrays”, ie objects that can be mapped to arrays, the returned array elements will be structures: for instance a Point3df will be mapped to numpy.dtype([(‘v’, ‘3f4’)])

arraydata()

assign()

checkResize()

fromObject()

index()

list()

property np

The np property is a shortcut to the __array__ method. Thus:

something.np

is a handier equivalent to:

numpy.asarray(something)

remove()

resize()

size()

toObject()

class soma.aims.vector_POINT3DD_iterator

Bases: wrapper

class soma.aims.vector_POINT3DF

Bases: wrapper

append()

array_struct()

Return a numpy array of elements. For vectors of scalar types, this is the same as the other functions __array__() and arraydata(). But for vectors where the elements are “sub-arrays”, ie objects that can be mapped to arrays, the returned array elements will be structures: for instance a Point3df will be mapped to numpy.dtype([(‘v’, ‘3f4’)])

arraydata()

assign()

checkResize()

fromObject()

index()

list()

property np

The np property is a shortcut to the __array__ method. Thus:

something.np

is a handier equivalent to:

numpy.asarray(something)

remove()

resize()

size()

toObject()

class soma.aims.vector_POINT3DF_iterator

Bases: wrapper

class soma.aims.vector_POINT3D_iterator

Bases: wrapper

class soma.aims.vector_S16

Bases: wrapper

append()

array_struct()

Return a numpy array of elements. For vectors of scalar types, this is the same as the other functions __array__() and arraydata(). But for vectors where the elements are “sub-arrays”, ie objects that can be mapped to arrays, the returned array elements will be structures: for instance a Point3df will be mapped to numpy.dtype([(‘v’, ‘3f4’)])

arraydata()

assign()

checkResize()

fromObject()

index()

list()

property np

The np property is a shortcut to the __array__ method. Thus:

something.np

is a handier equivalent to:

numpy.asarray(something)

remove()

resize()

size()

toObject()

class soma.aims.vector_S16_iterator

Bases: wrapper

class soma.aims.vector_S32

Bases: wrapper

append()

array_struct()

Return a numpy array of elements. For vectors of scalar types, this is the same as the other functions __array__() and arraydata(). But for vectors where the elements are “sub-arrays”, ie objects that can be mapped to arrays, the returned array elements will be structures: for instance a Point3df will be mapped to numpy.dtype([(‘v’, ‘3f4’)])

arraydata()

assign()

checkResize()

fromObject()

index()

list()

property np

The np property is a shortcut to the __array__ method. Thus:

something.np

is a handier equivalent to:

numpy.asarray(something)

remove()

resize()

size()

toObject()

class soma.aims.vector_S32_iterator

Bases: wrapper

class soma.aims.vector_STRING

Bases: wrapper

append()

assign()

fromObject()

index()

list()

remove()

resize()

size()

toObject()

class soma.aims.vector_STRING_iterator

Bases: wrapper

class soma.aims.vector_U16

Bases: wrapper

append()

array_struct()

Return a numpy array of elements. For vectors of scalar types, this is the same as the other functions __array__() and arraydata(). But for vectors where the elements are “sub-arrays”, ie objects that can be mapped to arrays, the returned array elements will be structures: for instance a Point3df will be mapped to numpy.dtype([(‘v’, ‘3f4’)])

arraydata()

assign()

checkResize()

fromObject()

index()

list()

property np

The np property is a shortcut to the __array__ method. Thus:

something.np

is a handier equivalent to:

numpy.asarray(something)

remove()

resize()

size()

toObject()

class soma.aims.vector_U16_iterator

Bases: wrapper

class soma.aims.vector_U32

Bases: wrapper

append()

array_struct()

Return a numpy array of elements. For vectors of scalar types, this is the same as the other functions __array__() and arraydata(). But for vectors where the elements are “sub-arrays”, ie objects that can be mapped to arrays, the returned array elements will be structures: for instance a Point3df will be mapped to numpy.dtype([(‘v’, ‘3f4’)])

arraydata()

assign()

checkResize()

fromObject()

index()

list()

property np

The np property is a shortcut to the __array__ method. Thus:

something.np

is a handier equivalent to:

numpy.asarray(something)

remove()

resize()

size()

toObject()

class soma.aims.vector_U32_iterator

Bases: wrapper

class soma.aims.vector_U8

Bases: wrapper

append()

array_struct()

Return a numpy array of elements. For vectors of scalar types, this is the same as the other functions __array__() and arraydata(). But for vectors where the elements are “sub-arrays”, ie objects that can be mapped to arrays, the returned array elements will be structures: for instance a Point3df will be mapped to numpy.dtype([(‘v’, ‘3f4’)])

arraydata()

assign()

checkResize()

fromObject()

index()

list()

property np

The np property is a shortcut to the __array__ method. Thus:

something.np

is a handier equivalent to:

numpy.asarray(something)

remove()

resize()

size()

toObject()

class soma.aims.vector_U8_iterator

Bases: wrapper

class soma.aims.vector_ULONG

Bases: wrapper

append()

array_struct()

Return a numpy array of elements. For vectors of scalar types, this is the same as the other functions __array__() and arraydata(). But for vectors where the elements are “sub-arrays”, ie objects that can be mapped to arrays, the returned array elements will be structures: for instance a Point3df will be mapped to numpy.dtype([(‘v’, ‘3f4’)])

arraydata()

assign()

checkResize()

fromObject()

index()

list()

property np

The np property is a shortcut to the __array__ method. Thus:

something.np

is a handier equivalent to:

numpy.asarray(something)

remove()

resize()

size()

toObject()

class soma.aims.vector_ULONGLONG

Bases: wrapper

append()

array_struct()

Return a numpy array of elements. For vectors of scalar types, this is the same as the other functions __array__() and arraydata(). But for vectors where the elements are “sub-arrays”, ie objects that can be mapped to arrays, the returned array elements will be structures: for instance a Point3df will be mapped to numpy.dtype([(‘v’, ‘3f4’)])

arraydata()

assign()

checkResize()

fromObject()

index()

list()

property np

The np property is a shortcut to the __array__ method. Thus:

something.np

is a handier equivalent to:

numpy.asarray(something)

remove()

resize()

size()

toObject()

class soma.aims.vector_ULONGLONG_iterator

Bases: wrapper

class soma.aims.vector_ULONG_iterator

Bases: wrapper

class soma.aims.vector_VOID

Bases: wrapper

append()

assign()

fromObject()

index()

list()

remove()

resize()

size()

toObject()

class soma.aims.vector_VOID_iterator

Bases: wrapper

class soma.aims.vector_list_U32

Bases: wrapper

append()

assign()

fromObject()

index()

list()

remove()

resize()

size()

toObject()

class soma.aims.vector_list_U32_iterator

Bases: wrapper

class soma.aims.vector_rc_ptr_AimsTimeSurface_3_VOID

Bases: wrapper

append()

assign()

fromObject()

index()

list()

remove()

resize()

size()

toObject()

class soma.aims.vector_rc_ptr_AimsTimeSurface_3_VOID_iterator

Bases: wrapper

class soma.aims.vector_set_U32

Bases: wrapper

append()

assign()

fromObject()

index()

list()

remove()

resize()

size()

toObject()

class soma.aims.vector_set_U32_iterator

Bases: wrapper

class soma.aims.vector_vector_FLOAT

Bases: wrapper

append()

assign()

fromObject()

index()

list()

remove()

resize()

size()

toObject()

class soma.aims.vector_vector_FLOAT_iterator

Bases: wrapper

class soma.aims.vector_vector_POINT3DF

Bases: wrapper

append()

assign()

fromObject()

index()

list()

remove()

resize()

size()

toObject()

class soma.aims.vector_vector_POINT3DF_iterator

Bases: wrapper

class soma.aims.vector_vector_S32

Bases: wrapper

append()

assign()

fromObject()

index()

list()

remove()

resize()

size()

toObject()

class soma.aims.vector_vector_S32_iterator

Bases: wrapper

class soma.aims.vector_vector_STRING

Bases: wrapper

append()

assign()

fromObject()

index()

list()

remove()

resize()

size()

toObject()

class soma.aims.vector_vector_STRING_iterator

Bases: wrapper

soma.aims.version()

AIMS / Cartobase version, as a 2-digit tuple

soma.aims.versionString()

AIMS / Cartobase full version, as a string

soma.aims.voxelTypeCode(data)

returns the AIMS type code for the given input data voxel type. For instance, for a volume of 16 bit ints, it will be ‘S16’, whereas typeCode() would return ‘Volume_S16’.

Input data may be a type or an instance of a container type.

soma.aims.write(obj, filename, format=None, options={})

Equivalent to:

w = Writer() w.write(obj, filename, format=format, options=options)

soma.aims.xmlInitParser()