API Documentation

Python SOFA API for reading, writing and creating .sofa files.

class sofa.Database[source]

Read and write NETCDF4 files following the SOFA specifications and conventions

static create(path, convention, dimensions=None)[source]

Create a new .sofa file following a SOFA convention

Parameters:
  • path (str) – Relative or absolute path to .sofa file
  • convention (str) – Name of the SOFA convention to create, see sofa.conventions.implemented()
  • dimensions (dict or int, optional) – Number of measurements or dict of dimensions to define (standard dimensions: “M”: measurements, “R”: receivers, “E”: emitters, “N”: data length)
Returns:

database (sofa.Database)
static open(path, mode='r', parallel=False)[source]
Parameters:
  • path (str) – Relative or absolute path to .sofa file
  • mode (str, optional) – File access mode (‘r’: readonly, ‘r+’: read/write)
  • parallel (bool, optional) – Whether to open the file with parallel access enabled (requires parallel-enabled netCDF4)
Returns:

database (sofa.Database)
close()[source]
save()[source]
convention
Data

DataType specific access for the measurement data, see sofa.datatypes

Dimensions

sofa.access.Dimensions for the database dimensions

Listener

sofa.spatial.SpatialObject for the Listener

Source

sofa.spatial.SpatialObject for the Source

Receiver

sofa.spatial.SpatialObject for the Receiver(s)

Emitter

sofa.spatial.SpatialObject for the Emitter(s)

Room

RoomType specific access for the room data, see sofa.roomtypes

Metadata

sofa.access.Metadata for the database metadata

Variables

sofa.access.DatasetVariables for direct access to database variables

sofa.access

class sofa.access.DatasetVariables(database)[source]
get_variable(name)[source]
Parameters:name (str) – Name of the variable
Returns:value (sofa.access.Variable) – Access object for the variable
get_string_array(name)[source]
Parameters:name (str) – Name of the string array
Returns:value (sofa.access.StringArray) – Access object for the string array
create_variable(name, dims, data_type='d', fill_value=0)[source]
Parameters:
  • name (str) – Name of the variable
  • dims (tuple(str)) – Dimensions of the variable
Returns:

value (sofa.access.Variable) – Access object for the variable
create_string_array(name, dims)[source]
Parameters:
  • name (str) – Name of the variable
  • dims (tuple(str)) – Dimensions of the variable
Returns:

value (sofa.access.StringArray) – Access object for the string array
list_variables()[source]
Returns:attrs (list) – List of the existing dataset variable and string array names
dump()[source]

Prints all variables and their dimensions

class sofa.access.Dimensions(dataset)[source]

Dimensions specified by SOFA as int

C

Coordinate dimension size

I

Scalar dimension size

M

Number of measurements

R

Number of receivers

E

Number of emitters

N

Number of data samples per measurement

S

Largest data string size

get_dimension(dim)[source]
create_dimension(dim, size)[source]
list_dimensions()[source]
dump()[source]

Prints all dimension sizes

class sofa.access.Metadata(dataset)[source]
get_attribute(name)[source]
Parameters:name (str) – Name of the attribute
Returns:value (str) – Value of the attribute
set_attribute(name, value)[source]
Parameters:
  • name (str) – Name of the attribute
  • value (str) – New value of the attribute
create_attribute(name, value='')[source]
Parameters:
  • name (str) – Name of the attribute
  • value (str, optional) – New value of the attribute
list_attributes()[source]
Returns:attrs (list) – List of the existing dataset attribute names
dump()[source]

Prints all metadata attributes

class sofa.access.ProxyObject(database, name)[source]

Proxy object that provides access to variables and attributes of a name group in the netCDF4 dataset

database
name
dataset
create_attribute(name, value='')[source]

Creates the attribute in the netCDF4 dataset with its full name self.name+name

Parameters:
  • name (str) – Name of the variable
  • value (str, optional) – Initial value of the attribute
create_variable(name, dims, data_type='d', fill_value=0)[source]

Creates the variable in the netCDF4 dataset with its full name self.name+name

Parameters:
  • name (str) – Name of the variable
  • dims (tuple(str)) – Dimensions of the variable
Returns:

value (sofa.access.Variable) – Access object for the variable
create_string_array(name, dims)[source]

Creates the string array in the netCDF4 dataset with its full name self.name+name

Parameters:
  • name (str) – Name of the variable
  • dims (tuple(str)) – Dimensions of the variable
Returns:

value (sofa.access.StringArray) – Access object for the string array
class sofa.access.StringArray(database, name)[source]
initialize(dims, data_type='c', fill_value='\x00')[source]

Create the zero-padded character array in the underlying netCDF4 dataset. Dimension ‘S’ must be the last dimension, and is appended if not included in dims.

get_values(indices=None, dim_order=None)[source]
Parameters:
  • indices (dict(key:str, value:int or slice), optional) – Key: dimension name, value: indices to be returned, complete axis assumed if not provided
  • dim_order (tuple of str, optional) – Desired order of dimensions in the output array
Returns:

values (np.ndarray) – Requested array range in regular or desired dimension order, if provided
axis(dim)
Parameters:dim (str) – Name of the dimension
Returns:axis (int) – Index of the dimension axis or None if unused
database
dimensions()
Returns:dimensions (tuple of str) – Variable dimension names in order
exists()
Returns:exists (bool) – True if variable exists, False otherwise
name
set_values(values, indices=None, dim_order=None, repeat_dim=None)[source]
Parameters:
  • values (np.ndarray) – New values for the array range
  • indices (dict(key:str, value:int or slice), optional) – Key: dimension name, value: indices to be set, complete axis assumed if not provided
  • dim_order (tuple of str, optional) – Dimension names in provided order, regular order assumed
  • repeat_dim (tuple of str, optional) – Tuple of dimension names along which to repeat the values
class sofa.access.Variable(database, name)[source]
Units

Units of the values

axis(dim)
Parameters:dim (str) – Name of the dimension
Returns:axis (int) – Index of the dimension axis or None if unused
database
dimensions()
Returns:dimensions (tuple of str) – Variable dimension names in order
exists()
Returns:exists (bool) – True if variable exists, False otherwise
get_values(indices=None, dim_order=None)
Parameters:
  • indices (dict(key:str, value:int or slice), optional) – Key: dimension name, value: indices to be returned, complete axis assumed if not provided
  • dim_order (tuple of str, optional) – Desired order of dimensions in the output array
Returns:

values (np.ndarray) – Requested array range in regular or desired dimension order, if provided
initialize(dims, data_type='d', fill_value=0)

Create the variable in the underlying netCDF4 dataset

name
set_values(values, indices=None, dim_order=None, repeat_dim=None)
Parameters:
  • values (np.ndarray) – New values for the array range
  • indices (dict(key:str, value:int or slice), optional) – Key: dimension name, value: indices to be set, complete axis assumed if not provided
  • dim_order (tuple of str, optional) – Dimension names in provided order, regular order assumed
  • repeat_dim (tuple of str, optional) – Tuple of dimension names along which to repeat the values

sofa.conventions

sofa.conventions.implemented()[source]
Returns:list – Names of implemented SOFA conventions

sofa.datatypes

Classes for accessing DataType-specific measurement data.

sofa.datatypes.implemented()[source]
Returns:list – Names of implemented SOFA data types
class sofa.datatypes.FIR(database)[source]

Finite Impulse Response data type

IR : sofa.access.Variable
Discrete time impulse responses, dimensions (‘M’, ‘R’, ‘N’)
Delay : sofa.access.Variable
Broadband delay in units of dimension ‘N’, dimensions (‘I’, ‘R’) or (‘M’, ‘R’)
SamplingRate : sofa.access.Variable
Sampling rate, dimensions (‘I’) or (‘M’), with attribute “Units”
Type

SOFA data type

create_attribute(name, value='')

Creates the attribute in the netCDF4 dataset with its full name self.name+name

Parameters:
  • name (str) – Name of the variable
  • value (str, optional) – Initial value of the attribute
create_string_array(name, dims)

Creates the string array in the netCDF4 dataset with its full name self.name+name

Parameters:
  • name (str) – Name of the variable
  • dims (tuple(str)) – Dimensions of the variable
Returns:

value (sofa.access.StringArray) – Access object for the string array
create_variable(name, dims, data_type='d', fill_value=0)

Creates the variable in the netCDF4 dataset with its full name self.name+name

Parameters:
  • name (str) – Name of the variable
  • dims (tuple(str)) – Dimensions of the variable
Returns:

value (sofa.access.Variable) – Access object for the variable
database
dataset
initialize(sample_count=None, variances=[], string_length=None)

Create the necessary variables and attributes

Parameters:
  • sample_count (int, optional) – Number of samples per measurement, mandatory if dimension N has not been defined
  • variances (list) – Names of the variables that vary along dimension M
  • string_length (int, optional) – Size of the longest data string
name
optional_variance_names()

Returns a list of standardized data elements that may vary between measurements

class sofa.datatypes.FIRE(database)[source]

Finite Impulse Response per Emitter data type

IR : sofa.access.Variable
Discrete time impulse responses, dimensions (‘M’, ‘R’, ‘E’, ‘N’)
Delay : sofa.access.Variable
Broadband delay in units of dimension ‘N’, dimensions (‘I’, ‘R’, ‘E’) or (‘M’, ‘R’, ‘E’)
SamplingRate : sofa.access.Variable
Sampling rate, dimensions (‘I’) or (‘M’), with attribute “Units”
Type

SOFA data type

create_attribute(name, value='')

Creates the attribute in the netCDF4 dataset with its full name self.name+name

Parameters:
  • name (str) – Name of the variable
  • value (str, optional) – Initial value of the attribute
create_string_array(name, dims)

Creates the string array in the netCDF4 dataset with its full name self.name+name

Parameters:
  • name (str) – Name of the variable
  • dims (tuple(str)) – Dimensions of the variable
Returns:

value (sofa.access.StringArray) – Access object for the string array
create_variable(name, dims, data_type='d', fill_value=0)

Creates the variable in the netCDF4 dataset with its full name self.name+name

Parameters:
  • name (str) – Name of the variable
  • dims (tuple(str)) – Dimensions of the variable
Returns:

value (sofa.access.Variable) – Access object for the variable
database
dataset
initialize(sample_count=None, variances=[], string_length=None)

Create the necessary variables and attributes

Parameters:
  • sample_count (int, optional) – Number of samples per measurement, mandatory if dimension N has not been defined
  • variances (list) – Names of the variables that vary along dimension M
  • string_length (int, optional) – Size of the longest data string
name
optional_variance_names()

Returns a list of standardized data elements that may vary between measurements

class sofa.datatypes.SOS(database)[source]

Second Order Sections data type

SOS : sofa.access.Variable
Second order sections, dimensions (‘M’, ‘R’, ‘N’)
Delay : sofa.access.Variable
Broadband delay in samples resulting from SamplingRate, dimensions (‘M’, ‘R’)
SamplingRate : sofa.access.Variable
Sampling rate, dimensions (‘I’) or (‘M’), with attribute “Units”
initialize(sample_count=None, variances=[], string_length=None)[source]

Create the necessary variables and attributes

Parameters:
  • sample_count (int, optional) – Number of samples per measurement, mandatory if dimension N has not been defined
  • variances (list) – Names of the variables that vary along dimension M
  • string_length (int, optional) – Size of the longest data string
Type

SOFA data type

create_attribute(name, value='')

Creates the attribute in the netCDF4 dataset with its full name self.name+name

Parameters:
  • name (str) – Name of the variable
  • value (str, optional) – Initial value of the attribute
create_string_array(name, dims)

Creates the string array in the netCDF4 dataset with its full name self.name+name

Parameters:
  • name (str) – Name of the variable
  • dims (tuple(str)) – Dimensions of the variable
Returns:

value (sofa.access.StringArray) – Access object for the string array
create_variable(name, dims, data_type='d', fill_value=0)

Creates the variable in the netCDF4 dataset with its full name self.name+name

Parameters:
  • name (str) – Name of the variable
  • dims (tuple(str)) – Dimensions of the variable
Returns:

value (sofa.access.Variable) – Access object for the variable
database
dataset
name
optional_variance_names()

Returns a list of standardized data elements that may vary between measurements

class sofa.datatypes.TF(database)[source]

Transfer Function data type

Real : sofa.access.Variable
Real part of the complex spectrum, dimensions (‘M’, ‘R’, ‘N’)
Imag : sofa.access.Variable
Imaginary part of the complex spectrum, dimensions (‘M’, ‘R’, ‘N’)
N : sofa.access.Variable
Frequency values, dimension (‘N’,), with attributes “LongName” and “Units”
N

Frequency values

Type

SOFA data type

create_attribute(name, value='')

Creates the attribute in the netCDF4 dataset with its full name self.name+name

Parameters:
  • name (str) – Name of the variable
  • value (str, optional) – Initial value of the attribute
create_string_array(name, dims)

Creates the string array in the netCDF4 dataset with its full name self.name+name

Parameters:
  • name (str) – Name of the variable
  • dims (tuple(str)) – Dimensions of the variable
Returns:

value (sofa.access.StringArray) – Access object for the string array
create_variable(name, dims, data_type='d', fill_value=0)

Creates the variable in the netCDF4 dataset with its full name self.name+name

Parameters:
  • name (str) – Name of the variable
  • dims (tuple(str)) – Dimensions of the variable
Returns:

value (sofa.access.Variable) – Access object for the variable
database
dataset
initialize(sample_count=None, variances=[], string_length=None)[source]

Create the necessary variables and attributes

Parameters:
  • sample_count (int, optional) – Number of samples per measurement, mandatory if dimension N has not been defined
  • variances (list) – Names of the variables that vary along dimension M
  • string_length (int, optional) – Size of the longest data string
name
optional_variance_names()

Returns a list of standardized data elements that may vary between measurements

sofa.roomtypes

Classes for accessing RoomType-specific data.

sofa.roomtypes.implemented()[source]
Returns:list – Names of implemented SOFA room types
class sofa.roomtypes.FreeField(database)[source]
Type

SOFA data type

create_attribute(name, value='')

Creates the attribute in the netCDF4 dataset with its full name self.name+name

Parameters:
  • name (str) – Name of the variable
  • value (str, optional) – Initial value of the attribute
create_string_array(name, dims)

Creates the string array in the netCDF4 dataset with its full name self.name+name

Parameters:
  • name (str) – Name of the variable
  • dims (tuple(str)) – Dimensions of the variable
Returns:

value (sofa.access.StringArray) – Access object for the string array
create_variable(name, dims, data_type='d', fill_value=0)

Creates the variable in the netCDF4 dataset with its full name self.name+name

Parameters:
  • name (str) – Name of the variable
  • dims (tuple(str)) – Dimensions of the variable
Returns:

value (sofa.access.Variable) – Access object for the variable
database
dataset
initialize(variances=[], string_length=None)

Create the necessary variables and attributes

Parameters:
  • measurement_count (int) – Number of measurements
  • sample_count (int) – Number of samples per measurement
  • variances (list) – Names of the variables that vary along dimension M
  • string_length (int, optional) – Size of the longest data string
name
optional_variance_names()

Returns a list of standardized data elements that may vary between measurements

class sofa.roomtypes.Reverberant(database)[source]
initialize(variances=[], string_length=None)[source]

Create the necessary variables and attributes

Parameters:
  • measurement_count (int) – Number of measurements
  • sample_count (int) – Number of samples per measurement
  • variances (list) – Names of the variables that vary along dimension M
  • string_length (int, optional) – Size of the longest data string
Type

SOFA data type

create_attribute(name, value='')

Creates the attribute in the netCDF4 dataset with its full name self.name+name

Parameters:
  • name (str) – Name of the variable
  • value (str, optional) – Initial value of the attribute
create_string_array(name, dims)

Creates the string array in the netCDF4 dataset with its full name self.name+name

Parameters:
  • name (str) – Name of the variable
  • dims (tuple(str)) – Dimensions of the variable
Returns:

value (sofa.access.StringArray) – Access object for the string array
create_variable(name, dims, data_type='d', fill_value=0)

Creates the variable in the netCDF4 dataset with its full name self.name+name

Parameters:
  • name (str) – Name of the variable
  • dims (tuple(str)) – Dimensions of the variable
Returns:

value (sofa.access.Variable) – Access object for the variable
database
dataset
name
optional_variance_names()

Returns a list of standardized data elements that may vary between measurements

class sofa.roomtypes.Shoebox(database)[source]

Shoebox room type

CornerA : sofa.spatial.Coordinates
First corner of room cuboid, dimensions (‘I’, ‘C’) or (‘M’, ‘C’)
CornerB : sofa.spatial.Coordinates
Opposite corner of room cuboid, dimensions (‘I’, ‘C’) or (‘M’, ‘C’)
CornerA

First corner of room cuboid

CornerB

Opposite corner of room cuboid

initialize(variances=[], string_length=None)[source]

Create the necessary variables and attributes

Parameters:
  • measurement_count (int) – Number of measurements
  • sample_count (int) – Number of samples per measurement
  • variances (list) – Names of the variables that vary along dimension M
  • string_length (int, optional) – Size of the longest data string
Type

SOFA data type

create_attribute(name, value='')

Creates the attribute in the netCDF4 dataset with its full name self.name+name

Parameters:
  • name (str) – Name of the variable
  • value (str, optional) – Initial value of the attribute
create_string_array(name, dims)

Creates the string array in the netCDF4 dataset with its full name self.name+name

Parameters:
  • name (str) – Name of the variable
  • dims (tuple(str)) – Dimensions of the variable
Returns:

value (sofa.access.StringArray) – Access object for the string array
create_variable(name, dims, data_type='d', fill_value=0)

Creates the variable in the netCDF4 dataset with its full name self.name+name

Parameters:
  • name (str) – Name of the variable
  • dims (tuple(str)) – Dimensions of the variable
Returns:

value (sofa.access.Variable) – Access object for the variable
database
dataset
name
optional_variance_names()

Returns a list of standardized data elements that may vary between measurements

sofa.spatial

sofa.spatial.sph2cart(alpha, beta, r)[source]

Spherical to cartesian coordinate transform.

\[\begin{split}x = r \cos \alpha \sin \beta \\ y = r \sin \alpha \sin \beta \\ z = r \cos \beta\end{split}\]

with \(\alpha \in [0, 2\pi), \beta \in [-\frac{\pi}{2}, \frac{\pi}{2}], r \geq 0\)

Parameters:
  • alpha (float or array_like) – Azimuth angle in radians
  • beta (float or array_like) – Elevation angle in radians (with 0 denoting azimuthal plane)
  • r (float or array_like) – Radius
Returns:

  • x (float or numpy.ndarray) – x-component of Cartesian coordinates
  • y (float or numpy.ndarray) – y-component of Cartesian coordinates
  • z (float or numpy.ndarray) – z-component of Cartesian coordinates
sofa.spatial.cart2sph(x, y, z)[source]

Cartesian to spherical coordinate transform.

\[\begin{split}\alpha = \arctan \left( \frac{y}{x} \right) \\ \beta = \arccos \left( \frac{z}{r} \right) \\ r = \sqrt{x^2 + y^2 + z^2}\end{split}\]

with \(\alpha \in [-pi, pi], \beta \in [-\frac{\pi}{2}, \frac{\pi}{2}], r \geq 0\)

Parameters:
  • x (float or array_like) – x-component of Cartesian coordinates
  • y (float or array_like) – y-component of Cartesian coordinates
  • z (float or array_like) – z-component of Cartesian coordinates
Returns:
class sofa.spatial.Units[source]
static first_unit(unit_string)[source]
static last_unit(unit_string)[source]
Metre = 'metre'
Meter = 'meter'
static is_Metre(value)[source]
static is_Meter(value)[source]
Degree = 'degree'
static is_Degree(value)[source]
Radians = 'radians'
static is_Radians(value)[source]
static convert_angle_units(coords, dimensions, old_units, new_units)[source]
Parameters:
  • coords (array_like) – Array of spherical coordinate values
  • dimensions (tuple of str) – Names of the array dimensions in order, must contain “C”
  • old_units (str) – Units of the angle values in the array
  • new_units (str) – Target angle units
Returns:

new_coords (np.ndarray) – Array of converted spherical coordinate values in identical dimension order
class sofa.spatial.System[source]

Enum of valid coordinate systems

Cartesian = 'cartesian'
Spherical = 'spherical'
static convert(coords, dimensions, old_system, new_system, old_angle_unit=None, new_angle_unit=None)[source]
Parameters:
  • coords (array_like) – Array of coordinate values
  • dimensions (tuple of str) – Names of the array dimensions in order, must contain “C”
  • old_system (str) – Coordinate system of the values in the array
  • new_system (str) – Target coordinate system
  • old_angle_unit (str, optional) – Unit of the angular spherical coordinates
  • new_angle_unit (str, optional) – Target unit of the angular spherical coordinates
Returns:

new_coords (np.ndarray) – Array of converted coordinate values in identical dimension order
class sofa.spatial.Coordinates(obj, descriptor)[source]

Specialized sofa.access.Variable for spatial coordinates

default_values = {'Position': (array([0, 0, 0]), 'cartesian'), 'Up': (array([0, 0, 1]), 'cartesian'), 'View': (array([1, 0, 0]), 'cartesian')}
initialize(varies, defaults=None)[source]

Create the variable in the underlying netCDF4 dataset

Type

Coordinate system of the values

get_global_reference_object()[source]
get_local_dimension()[source]
get_values(indices=None, dim_order=None, system=None, angle_unit=None)[source]

Gets the coordinates in their original reference system

Parameters:
  • indices (dict(key:str, value:int or slice), optional) – Key: dimension name, value: indices to be returned, complete axis assumed if not provided
  • dim_order (tuple of str, optional) – Desired order of dimensions in the output array
  • system (str, optional) – Target coordinate system
  • angle_unit (str, optional) – Unit for spherical angles in the output array
Returns:

values (np.ndarray) – Coordinates in the original reference system
get_global_values(indices=None, dim_order=None, system=None, angle_unit=None)[source]

Transform local coordinates (such as Receiver or Emitter) into the global reference system

Parameters:
  • indices (dict(key:str, value:int or slice), optional) – Key: dimension name, value: indices to be returned, complete axis assumed if not provided
  • dim_order (tuple of str, optional) – Desired order of dimensions in the output array
  • system (str, optional) – Target coordinate system
  • angle_unit (str, optional) – Unit for spherical angles in the output array
Returns:

global_values (np.ndarray) – Transformed coordinates in global reference system
get_relative_values(ref_object, indices=None, dim_order=None, system=None, angle_unit=None)[source]

Transform coordinates (such as Receiver or Emitter) into the reference system of a given sofa.spatial.SpatialObject, aligning the x-axis with View and the z-axis with Up

Parameters:
  • ref_object (sofa.spatial.Object) – Spatial object providing the reference system, None for
  • indices (dict(key:str, value:int or slice), optional) – Key: dimension name, value: indices to be returned, complete axis assumed if not provided
  • dim_order (tuple of str, optional) – Desired order of dimensions in the output array
  • system (str, optional) – Target coordinate system
  • angle_unit (str, optional) – Unit for spherical angles in the output array
Returns:

relative_values (np.ndarray) – Transformed coordinates in original or provided reference system
set_system(ctype=None, cunits=None)[source]

Set the coordinate Type and Units

set_values(values, indices=None, dim_order=None, repeat_dim=None, system=None, angle_unit=None)[source]

Sets the coordinate values after converting them to the system and units given by the dataset variable

Parameters:
  • values (np.ndarray) – New values for the array range
  • indices (dict(key:str, value:int or slice), optional) – Key: dimension name, value: indices to be set, complete axis assumed if not provided
  • dim_order (tuple of str, optional) – Dimension names in provided order, regular order assumed
  • repeat_dim (tuple of str, optional) – Tuple of dimension names along which to repeat the values
  • system (str, optional) – Coordinate system of the provided values
  • angle_unit (str, optional) – Angle units of the provided values
class sofa.spatial.SpatialObject(database, name)[source]

Spatial object such as Listener, Receiver, Source, Emitter

Position

Position of the spatial object relative to its reference system

View

View (x-axis) of the spatial object relative to its reference system

Up

Up (z-axis) of the spatial object relative to its reference system

Type

Coordinate syste, of the values

initialize(fixed=[], variances=[], count=None)[source]

Create the necessary variables and attributes

Parameters:
  • fixed (list(str), optional) – List of spatial coordinates that are fixed for all measurements [“Position”, “View”, “Up”]
  • variances (list(str), optional) – List of spatial coordinates that vary between measurements [“Position”, “View”, “Up”], overrides mentions in fixed
  • count (int, optional) – Number of objects (such as Emitters or Receivers), ignored for Listener and Source
initialize_coordinates(fixed=[], variances=[])[source]
Parameters:
  • fixed (list(str), optional) – List of spatial coordinates that are fixed for all measurements [“Position”, “View”, “Up”]
  • variances (list(str), optional) – List of spatial coordinates that vary between measurements [“Position”, “View”, “Up”], overrides mentions in fixed
get_pose(indices=None, dim_order=None, system=None, angle_unit=None)[source]

Gets the spatial object coordinates or their defaults if they have not been defined. Relative spatial objects return their global pose, or their reference object’s pose values if theirs are undefined.

Parameters:
  • indices (dict(key:str, value:int or slice), optional) – Key: dimension name, value: indices to be returned, complete axis assumed if not provided
  • dim_order (tuple of str, optional) – Desired order of dimensions in the output arrays
  • system (str, optional) – Target coordinate system
  • angle_unit (str, optional) – Unit for spherical angles in the output arrays
Returns:

position, view, up (np.ndarray, np.ndarray, np.ndarray) – Spatial object reference system