io

References

read_bvec_file

dipy.io.bvectxt.read_bvec_file(filename, atol=0.001)

dipy.io.bvectxt module is deprecated, Please use dipy.core.gradients module instead

• deprecated from version: 1.4

• Raises <class ‘dipy.utils.deprecator.ExpiredDeprecationError’> as of version: 1.5

Read gradient table information from a pair of files with extensions .bvec and .bval. The bval file should have one row of values representing the bvalues of each volume in the dwi data set. The bvec file should have three rows, where the rows are the x, y, and z components of the normalized gradient direction for each of the volumes.

Parameters

filename :

The path to the either the bvec or bval file

atolfloat, optional

The tolerance used to check all the gradient directions are normalized. Default is .001

ornt_mapping

dipy.io.bvectxt.ornt_mapping(ornt1, ornt2)

Calculate the mapping needing to get from orn1 to orn2.

dipy.io.bvectxt module is deprecated, Please use dipy.core.gradients module instead

• deprecated from version: 1.4

• Raises <class ‘dipy.utils.deprecator.ExpiredDeprecationError’> as of version: 1.5

reorient_vectors

dipy.io.bvectxt.reorient_vectors(bvecs, current_ornt, new_ornt, axis=0)

Change the orientation of gradients or other vectors.

dipy.io.bvectxt module is deprecated, Please use dipy.core.gradients module instead

• deprecated from version: 1.4

• Raises <class ‘dipy.utils.deprecator.ExpiredDeprecationError’> as of version: 1.5

Moves vectors, storted along axis, from current_ornt to new_ornt. For example the vector [x, y, z] in “RAS” will be [-x, -y, z] in “LPS”.

R: Right A: Anterior S: Superior L: Left P: Posterior I: Inferior

reorient_on_axis

dipy.io.bvectxt.reorient_on_axis(bvecs, current_ornt, new_ornt, axis=0)

dipy.io.bvectxt module is deprecated, Please use dipy.core.gradients module instead

• deprecated from version: 1.4

• Raises <class ‘dipy.utils.deprecator.ExpiredDeprecationError’> as of version: 1.5

orientation_from_string

dipy.io.bvectxt.orientation_from_string(string_ornt)

Return an array representation of an ornt string.

dipy.io.bvectxt module is deprecated, Please use dipy.core.gradients module instead

• deprecated from version: 1.4

• Raises <class ‘dipy.utils.deprecator.ExpiredDeprecationError’> as of version: 1.5

orientation_to_string

dipy.io.bvectxt.orientation_to_string(ornt)

Return a string representation of a 3d ornt.

dipy.io.bvectxt module is deprecated, Please use dipy.core.gradients module instead

• deprecated from version: 1.4

• Raises <class ‘dipy.utils.deprecator.ExpiredDeprecationError’> as of version: 1.5

Dpy

class dipy.io.dpy.Dpy(fname, mode='r', compression=0)

Bases: object

__init__(fname, mode='r', compression=0)

Advanced storage system for tractography based on HDF5

Parameters

fname : str, full filename mode : ‘r’ read

‘w’ write ‘r+’ read and write only if file already exists

compression : 0 no compression to 9 maximum compression

Examples

>>> import os
>>> from tempfile import mkstemp #temp file
>>> from dipy.io.dpy import Dpy
>>> def dpy_example():
...     fd,fname = mkstemp()
...     fname += '.dpy'#add correct extension
...     dpw = Dpy(fname,'w')
...     A=np.ones((5,3))
...     B=2*A.copy()
...     C=3*A.copy()
...     dpw.write_track(A)
...     dpw.write_track(B)
...     dpw.write_track(C)
...     dpw.close()
...     dpr = Dpy(fname,'r')
...     dpr.read_track()
...     dpr.read_track()
...     dpr.read_tracksi([0, 1, 2, 0, 0, 2])
...     dpr.close()
...     os.remove(fname) #delete file from disk
>>> dpy_example()

close()

read_track()

read one track each time

read_tracks()

read the entire tractography

read_tracksi(indices)

read tracks with specific indices

version()

write_track(track)

write on track each time

write_tracks(tracks)

write many tracks together

read_bvals_bvecs

dipy.io.gradients.read_bvals_bvecs(fbvals, fbvecs)

Read b-values and b-vectors from disk.

Parameters

fbvalsstr

Full path to file with b-values. None to not read bvals.

fbvecsstr

Full path of file with b-vectors. None to not read bvecs.

Returns

bvals : array, (N,) or None bvecs : array, (N, 3) or None

Notes

Files can be either ‘.bvals’/’.bvecs’ or ‘.txt’ or ‘.npy’ (containing arrays stored with the appropriate values).

load_nifti_data

dipy.io.image.load_nifti_data(fname, as_ndarray=True)

Load only the data array from a nifti file.

Parameters

fnamestr

Full path to the file.

as_ndarray: bool, optional

convert nibabel ArrayProxy to a numpy.ndarray. If you want to save memory and delay this casting, just turn this option to False (default: True)

Returns

data: np.ndarray or nib.ArrayProxy

See Also

load_nifti

load_nifti

dipy.io.image.load_nifti(fname, return_img=False, return_voxsize=False, return_coords=False, as_ndarray=True)

Load data and other information from a nifti file.

Parameters

fnamestr

Full path to a nifti file.

return_imgbool, optional

Whether to return the nibabel nifti img object. Default: False

return_voxsize: bool, optional

Whether to return the nifti header zooms. Default: False

return_coordsbool, optional

Whether to return the nifti header aff2axcodes. Default: False

as_ndarray: bool, optional

convert nibabel ArrayProxy to a numpy.ndarray. If you want to save memory and delay this casting, just turn this option to False (default: True)

Returns

A tuple, with (at the most, if all keyword args are set to True): (data, img.affine, img, vox_size, nib.aff2axcodes(img.affine))

See Also

load_nifti_data

save_nifti

dipy.io.image.save_nifti(fname, data, affine, hdr=None, dtype=None)

Save a data array into a nifti file.

Parameters

fnamestr

The full path to the file to be saved.

datandarray

The array with the data to save.

affine4x4 array

The affine transform associated with the file.

hdrnifti header, optional

May contain additional information to store in the file header.

Returns

None

save_qa_metric

dipy.io.image.save_qa_metric(fname, xopt, fopt)

Save Quality Assurance metrics.

Parameters

fname: string

File name to save the metric values.

xopt: numpy array

The metric containing the optimal parameters for image registration.

fopt: int

The distance between the registered images.

load_peaks

dipy.io.peaks.load_peaks(fname, verbose=False)

Load a PeaksAndMetrics HDF5 file (PAM5)

Parameters

fnamestring

Filename of PAM5 file.

verbosebool

Print summary information about the loaded file.

Returns

pam : PeaksAndMetrics object

save_peaks

dipy.io.peaks.save_peaks(fname, pam, affine=None, verbose=False)

Save all important attributes of object PeaksAndMetrics in a PAM5 file (HDF5).

Parameters

fnamestring

Filename of PAM5 file

pamPeaksAndMetrics

Object holding peak_dirs, shm_coeffs and other attributes

affinearray

The 4x4 matrix transforming the date from native to world coordinates. PeaksAndMetrics should have that attribute but if not it can be provided here. Default None.

verbosebool

Print summary information about the saved file.

peaks_to_niftis

dipy.io.peaks.peaks_to_niftis(pam, fname_shm, fname_dirs, fname_values, fname_indices, fname_gfa, reshape_dirs=False)

Save SH, directions, indices and values of peaks to Nifti.

save_pickle

dipy.io.pickles.save_pickle(fname, dix)

Save dix to fname as pickle.

Parameters

fnamestr

filename to save object e.g. a dictionary

dixstr

dictionary or other object

Examples

>>> import os
>>> from tempfile import mkstemp
>>> fd, fname = mkstemp() # make temporary file (opened, attached to fh)
>>> d={0:{'d':1}}
>>> save_pickle(fname, d)
>>> d2=load_pickle(fname)

We remove the temporary file we created for neatness

>>> os.close(fd) # the file is still open, we need to close the fh
>>> os.remove(fname)

See Also

dipy.io.pickles.load_pickle

load_pickle

dipy.io.pickles.load_pickle(fname)

Load object from pickle file fname.

Parameters

fnamestr

filename to load dict or other python object

Returns

dixobject

dictionary or other object

Examples

dipy.io.pickles.save_pickle

Space

class dipy.io.stateful_tractogram.Space(value)

Bases: Enum

Enum to simplify future change to convention

__init__()

RASMM = 'rasmm'

VOX = 'vox'

VOXMM = 'voxmm'

Origin

class dipy.io.stateful_tractogram.Origin(value)

Bases: Enum

Enum to simplify future change to convention

__init__()

NIFTI = 'center'

TRACKVIS = 'corner'

StatefulTractogram

class dipy.io.stateful_tractogram.StatefulTractogram(streamlines, reference, space, origin=Origin.NIFTI, data_per_point=None, data_per_streamline=None)

Bases: object

Class for stateful representation of collections of streamlines Object designed to be identical no matter the file format (trk, tck, vtk, fib, dpy). Facilitate transformation between space and data manipulation for each streamline / point.

__init__(streamlines, reference, space, origin=Origin.NIFTI, data_per_point=None, data_per_streamline=None)

Create a strict, state-aware, robust tractogram

Parameters

streamlineslist or ArraySequence

Streamlines of the tractogram

referenceNifti or Trk filename, Nifti1Image or TrkFile,

Nifti1Header, trk.header (dict) or another Stateful Tractogram Reference that provides the spatial attributes. Typically a nifti-related object from the native diffusion used for streamlines generation

spaceEnum (dipy.io.stateful_tractogram.Space)

Current space in which the streamlines are (vox, voxmm or rasmm) After tracking the space is VOX, after loading with nibabel the space is RASMM

originEnum (dipy.io.stateful_tractogram.Origin), optional

Current origin in which the streamlines are (center or corner) After loading with nibabel the origin is CENTER

data_per_pointdict, optional

Dictionary in which each key has X items, each items has Y_i items X being the number of streamlines Y_i being the number of points on streamlines #i

data_per_streamlinedict, optional

Dictionary in which each key has X items X being the number of streamlines

Notes

Very important to respect the convention, verify that streamlines match the reference and are effectively in the right space.

Any change to the number of streamlines, data_per_point or data_per_streamline requires particular verification.

In a case of manipulation not allowed by this object, use Nibabel directly and be careful.

property affine

Getter for the reference affine

static are_compatible(sft_1, sft_2)

Compatibility verification of two StatefulTractogram to ensure space, origin, data_per_point and data_per_streamline consistency

compute_bounding_box()

Compute the bounding box of the streamlines in their current state

Returns

outputndarray

8 corners of the XYZ aligned box, all zeros if no streamlines

property data_per_point

Getter for data_per_point

property data_per_streamline

Getter for data_per_streamline

property dimensions

Getter for the reference dimensions

property dtype_dict

Getter for dtype_dict

static from_sft(streamlines, sft, data_per_point=None, data_per_streamline=None)

Create an instance of StatefulTractogram from another instance of StatefulTractogram.

Parameters

streamlineslist or ArraySequence

Streamlines of the tractogram

sftStatefulTractogram,

The other StatefulTractogram to copy the space_attribute AND state from.

data_per_pointdict, optional

Dictionary in which each key has X items, each items has Y_i items X being the number of streamlines Y_i being the number of points on streamlines #i

data_per_streamlinedict, optional

Dictionary in which each key has X items X being the number of streamlines

---

get_data_per_point_keys()

Return a list of the data_per_point attribute names

get_data_per_streamline_keys()

Return a list of the data_per_streamline attribute names

get_streamlines_copy()

Safe getter for streamlines (for slicing)

is_bbox_in_vox_valid()

Verify that the bounding box is valid in voxel space. Negative coordinates or coordinates above the volume dimensions are considered invalid in voxel space.

Returns

outputbool

Are the streamlines within the volume of the associated reference

property origin

Getter for origin standard

remove_invalid_streamlines(epsilon=0.001)

Remove streamlines with invalid coordinates from the object. Will also remove the data_per_point and data_per_streamline. Invalid coordinates are any X,Y,Z values above the reference dimensions or below zero

Parameters

epsilonfloat (optional)

Epsilon value for the bounding box verification. Default is 1e-6.

Returns

outputtuple

Tuple of two list, indices_to_remove, indices_to_keep

property space

Getter for the current space

property space_attributes

Getter for spatial attribute

property streamlines

Partially safe getter for streamlines

to_center()

Safe function to shift streamlines so the center of voxel is the origin

to_corner()

Safe function to shift streamlines so the corner of voxel is the origin

to_origin(target_origin)

Safe function to change streamlines to a particular origin standard False means NIFTI (center) and True means TrackVis (corner)

to_rasmm()

Safe function to transform streamlines and update state

to_space(target_space)

Safe function to transform streamlines to a particular space using an enum and update state

to_vox()

Safe function to transform streamlines and update state

to_voxmm()

Safe function to transform streamlines and update state

property voxel_order

Getter for the reference voxel order

property voxel_sizes

Getter for the reference voxel sizes

logger

dipy.io.stateful_tractogram.logger()

Instances of the Logger class represent a single logging channel. A “logging channel” indicates an area of an application. Exactly how an “area” is defined is up to the application developer. Since an application can have any number of areas, logging channels are identified by a unique string. Application areas can be nested (e.g. an area of “input processing” might include sub-areas “read CSV files”, “read XLS files” and “read Gnumeric files”). To cater for this natural nesting, channel names are organized into a namespace hierarchy where levels are separated by periods, much like the Java or Python package namespace. So in the instance given above, channel names might be “input” for the upper level, and “input.csv”, “input.xls” and “input.gnu” for the sub-levels. There is no arbitrary limit to the depth of nesting.

set_sft_logger_level

dipy.io.stateful_tractogram.set_sft_logger_level(log_level)

Change the logger of the StatefulTractogram to one on the following: DEBUG, INFO, WARNING, CRITICAL, ERROR

Parameters

log_levelstr

Log level for the StatefulTractogram only

save_tractogram

dipy.io.streamline.save_tractogram(sft, filename, bbox_valid_check=True)

Save the stateful tractogram in any format (trk/tck/vtk/vtp/fib/dpy)

Parameters

sftStatefulTractogram

The stateful tractogram to save

filenamestring

Filename with valid extension

bbox_valid_checkbool

Verification for negative voxel coordinates or values above the volume dimensions. Default is True, to enforce valid file.

Returns

outputbool

True if the saving operation was successful

load_tractogram

dipy.io.streamline.load_tractogram(filename, reference, to_space=Space.RASMM, to_origin=Origin.NIFTI, bbox_valid_check=True, trk_header_check=True)

Load the stateful tractogram from any format (trk/tck/vtk/vtp/fib/dpy)

Parameters

filenamestring

Filename with valid extension

referenceNifti or Trk filename, Nifti1Image or TrkFile, Nifti1Header or

trk.header (dict), or ‘same’ if the input is a trk file. Reference that provides the spatial attribute. Typically a nifti-related object from the native diffusion used for streamlines generation

to_spaceEnum (dipy.io.stateful_tractogram.Space)

Space to which the streamlines will be transformed after loading

to_originEnum (dipy.io.stateful_tractogram.Origin)

Origin to which the streamlines will be transformed after loading

NIFTI standard, default (center of the voxel) TRACKVIS standard (corner of the voxel)

bbox_valid_checkbool

Verification for negative voxel coordinates or values above the volume dimensions. Default is True, to enforce valid file.

trk_header_checkbool

Verification that the reference has the same header as the spatial attributes as the input tractogram when a Trk is loaded

Returns

outputStatefulTractogram

The tractogram to load (must have been saved properly)

load_generator

dipy.io.streamline.load_generator(ttype)

Generate a loading function that performs a file extension check to restrict the user to a single file format.

Parameters

ttypestring

Extension of the file format that requires a loader

Returns

outputfunction

Function (load_tractogram) that handle only one file format

save_generator

dipy.io.streamline.save_generator(ttype)

Generate a saving function that performs a file extension check to restrict the user to a single file format.

Parameters

ttypestring

Extension of the file format that requires a saver

Returns

outputfunction

Function (save_tractogram) that handle only one file format

load_trk

dipy.io.streamline.load_trk(filename, reference, to_space=Space.RASMM, to_origin=Origin.NIFTI, bbox_valid_check=True, trk_header_check=True)

Load the stateful tractogram of the .trk format

Parameters

filenamestring

Filename with valid extension

referenceNifti or Trk filename, Nifti1Image or TrkFile, Nifti1Header or

trk.header (dict), or ‘same’ if the input is a trk file. Reference that provides the spatial attribute. Typically a nifti-related object from the native diffusion used for streamlines generation

to_spaceEnum (dipy.io.stateful_tractogram.Space)

Space to which the streamlines will be transformed after loading

to_originEnum (dipy.io.stateful_tractogram.Origin)

Origin to which the streamlines will be transformed after loading

NIFTI standard, default (center of the voxel) TRACKVIS standard (corner of the voxel)

bbox_valid_checkbool

Verification for negative voxel coordinates or values above the volume dimensions. Default is True, to enforce valid file.

trk_header_checkbool

Verification that the reference has the same header as the spatial attributes as the input tractogram when a Trk is loaded

Returns

outputStatefulTractogram

The tractogram to load (must have been saved properly)

load_tck

dipy.io.streamline.load_tck(filename, reference, to_space=Space.RASMM, to_origin=Origin.NIFTI, bbox_valid_check=True, trk_header_check=True)

Load the stateful tractogram of the .tck format

Parameters

filenamestring

Filename with valid extension

referenceNifti or Trk filename, Nifti1Image or TrkFile, Nifti1Header or

trk.header (dict), or ‘same’ if the input is a trk file. Reference that provides the spatial attribute. Typically a nifti-related object from the native diffusion used for streamlines generation

to_spaceEnum (dipy.io.stateful_tractogram.Space)

Space to which the streamlines will be transformed after loading

to_originEnum (dipy.io.stateful_tractogram.Origin)

Origin to which the streamlines will be transformed after loading

NIFTI standard, default (center of the voxel) TRACKVIS standard (corner of the voxel)

bbox_valid_checkbool

Verification for negative voxel coordinates or values above the volume dimensions. Default is True, to enforce valid file.

trk_header_checkbool

Verification that the reference has the same header as the spatial attributes as the input tractogram when a Trk is loaded

Returns

outputStatefulTractogram

The tractogram to load (must have been saved properly)

load_vtk

dipy.io.streamline.load_vtk(filename, reference, to_space=Space.RASMM, to_origin=Origin.NIFTI, bbox_valid_check=True, trk_header_check=True)

Load the stateful tractogram of the .vtk format

Parameters

filenamestring

Filename with valid extension

referenceNifti or Trk filename, Nifti1Image or TrkFile, Nifti1Header or

trk.header (dict), or ‘same’ if the input is a trk file. Reference that provides the spatial attribute. Typically a nifti-related object from the native diffusion used for streamlines generation

to_spaceEnum (dipy.io.stateful_tractogram.Space)

Space to which the streamlines will be transformed after loading

to_originEnum (dipy.io.stateful_tractogram.Origin)

Origin to which the streamlines will be transformed after loading

NIFTI standard, default (center of the voxel) TRACKVIS standard (corner of the voxel)

bbox_valid_checkbool

Verification for negative voxel coordinates or values above the volume dimensions. Default is True, to enforce valid file.

trk_header_checkbool

Verification that the reference has the same header as the spatial attributes as the input tractogram when a Trk is loaded

Returns

outputStatefulTractogram

The tractogram to load (must have been saved properly)

load_vtp

dipy.io.streamline.load_vtp(filename, reference, to_space=Space.RASMM, to_origin=Origin.NIFTI, bbox_valid_check=True, trk_header_check=True)

Load the stateful tractogram of the .vtp format

Parameters

filenamestring

Filename with valid extension

referenceNifti or Trk filename, Nifti1Image or TrkFile, Nifti1Header or

trk.header (dict), or ‘same’ if the input is a trk file. Reference that provides the spatial attribute. Typically a nifti-related object from the native diffusion used for streamlines generation

to_spaceEnum (dipy.io.stateful_tractogram.Space)

Space to which the streamlines will be transformed after loading

to_originEnum (dipy.io.stateful_tractogram.Origin)

Origin to which the streamlines will be transformed after loading

NIFTI standard, default (center of the voxel) TRACKVIS standard (corner of the voxel)

bbox_valid_checkbool

Verification for negative voxel coordinates or values above the volume dimensions. Default is True, to enforce valid file.

trk_header_checkbool

Verification that the reference has the same header as the spatial attributes as the input tractogram when a Trk is loaded

Returns

outputStatefulTractogram

The tractogram to load (must have been saved properly)

load_fib

dipy.io.streamline.load_fib(filename, reference, to_space=Space.RASMM, to_origin=Origin.NIFTI, bbox_valid_check=True, trk_header_check=True)

Load the stateful tractogram of the .fib format

Parameters

filenamestring

Filename with valid extension

referenceNifti or Trk filename, Nifti1Image or TrkFile, Nifti1Header or

trk.header (dict), or ‘same’ if the input is a trk file. Reference that provides the spatial attribute. Typically a nifti-related object from the native diffusion used for streamlines generation

to_spaceEnum (dipy.io.stateful_tractogram.Space)

Space to which the streamlines will be transformed after loading

to_originEnum (dipy.io.stateful_tractogram.Origin)

Origin to which the streamlines will be transformed after loading

NIFTI standard, default (center of the voxel) TRACKVIS standard (corner of the voxel)

bbox_valid_checkbool

Verification for negative voxel coordinates or values above the volume dimensions. Default is True, to enforce valid file.

trk_header_checkbool

Verification that the reference has the same header as the spatial attributes as the input tractogram when a Trk is loaded

Returns

outputStatefulTractogram

The tractogram to load (must have been saved properly)

load_dpy

dipy.io.streamline.load_dpy(filename, reference, to_space=Space.RASMM, to_origin=Origin.NIFTI, bbox_valid_check=True, trk_header_check=True)

Load the stateful tractogram of the .dpy format

Parameters

filenamestring

Filename with valid extension

referenceNifti or Trk filename, Nifti1Image or TrkFile, Nifti1Header or

trk.header (dict), or ‘same’ if the input is a trk file. Reference that provides the spatial attribute. Typically a nifti-related object from the native diffusion used for streamlines generation

to_spaceEnum (dipy.io.stateful_tractogram.Space)

Space to which the streamlines will be transformed after loading

to_originEnum (dipy.io.stateful_tractogram.Origin)

Origin to which the streamlines will be transformed after loading

NIFTI standard, default (center of the voxel) TRACKVIS standard (corner of the voxel)

bbox_valid_checkbool

Verification for negative voxel coordinates or values above the volume dimensions. Default is True, to enforce valid file.

trk_header_checkbool

Verification that the reference has the same header as the spatial attributes as the input tractogram when a Trk is loaded

Returns

outputStatefulTractogram

The tractogram to load (must have been saved properly)

save_trk

dipy.io.streamline.save_trk(sft, filename, bbox_valid_check=True)

Save the stateful tractogram of the .trk format

Parameters

sftStatefulTractogram

The stateful tractogram to save

filenamestring

Filename with valid extension

bbox_valid_checkbool

Verification for negative voxel coordinates or values above the volume dimensions. Default is True, to enforce valid file.

Returns

outputbool

True if the saving operation was successful

save_tck

dipy.io.streamline.save_tck(sft, filename, bbox_valid_check=True)

Save the stateful tractogram of the .tck format

Parameters

sftStatefulTractogram

The stateful tractogram to save

filenamestring

Filename with valid extension

bbox_valid_checkbool

Verification for negative voxel coordinates or values above the volume dimensions. Default is True, to enforce valid file.

Returns

outputbool

True if the saving operation was successful

save_vtk

dipy.io.streamline.save_vtk(sft, filename, bbox_valid_check=True)

Save the stateful tractogram of the .vtk format

Parameters

sftStatefulTractogram

The stateful tractogram to save

filenamestring

Filename with valid extension

bbox_valid_checkbool

Verification for negative voxel coordinates or values above the volume dimensions. Default is True, to enforce valid file.

Returns

outputbool

True if the saving operation was successful

save_vtp

dipy.io.streamline.save_vtp(sft, filename, bbox_valid_check=True)

Save the stateful tractogram of the .vtp format

Parameters

sftStatefulTractogram

The stateful tractogram to save

filenamestring

Filename with valid extension

bbox_valid_checkbool

Verification for negative voxel coordinates or values above the volume dimensions. Default is True, to enforce valid file.

Returns

outputbool

True if the saving operation was successful

save_fib

dipy.io.streamline.save_fib(sft, filename, bbox_valid_check=True)

Save the stateful tractogram of the .fib format

Parameters

sftStatefulTractogram

The stateful tractogram to save

filenamestring

Filename with valid extension

bbox_valid_checkbool

Verification for negative voxel coordinates or values above the volume dimensions. Default is True, to enforce valid file.

Returns

outputbool

True if the saving operation was successful

save_dpy

dipy.io.streamline.save_dpy(sft, filename, bbox_valid_check=True)

Save the stateful tractogram of the .dpy format

Parameters

sftStatefulTractogram

The stateful tractogram to save

filenamestring

Filename with valid extension

bbox_valid_checkbool

Verification for negative voxel coordinates or values above the volume dimensions. Default is True, to enforce valid file.

Returns

outputbool

True if the saving operation was successful

nifti1_symmat

dipy.io.utils.nifti1_symmat(image_data, *args, **kwargs)

Returns a Nifti1Image with a symmetric matrix intent

Parameters

image_dataarray-like

should have lower triangular elements of a symmetric matrix along the last dimension

all other arguments and keywords are passed to Nifti1Image

Returns

imageNifti1Image

5d, extra dimensions added before the last. Has symmetric matrix intent code

make5d

dipy.io.utils.make5d(data)

reshapes the input to have 5 dimensions, adds extra dimensions just before the last dimension

decfa

dipy.io.utils.decfa(img_orig, scale=False)

Create a nifti-compliant directional-encoded color FA image.

Parameters

img_origNifti1Image class instance.

Contains encoding of the DEC FA image with a 4D volume of data, where the elements on the last dimension represent R, G and B components.

scale: bool.

Whether to scale the incoming data from the 0-1 to the 0-255 range expected in the output.

Returns

imgNifti1Image class instance with dtype set to store tuples of

uint8 in (R, G, B) order.

Notes

For a description of this format, see:

https://nifti.nimh.nih.gov/nifti-1/documentation/nifti1fields/nifti1fields_pages/datatype.html

decfa_to_float

dipy.io.utils.decfa_to_float(img_orig)

Convert a nifti-compliant directional-encoded color FA image into a nifti image with RGB encoded in floating point resolution.

Parameters

img_origNifti1Image class instance.

Contains encoding of the DEC FA image with a 3D volume of data, where each element is a (R, G, B) tuple in uint8.

Returns

img : Nifti1Image class instance with float dtype.

Notes

For a description of this format, see:

https://nifti.nimh.nih.gov/nifti-1/documentation/nifti1fields/nifti1fields_pages/datatype.html

is_reference_info_valid

dipy.io.utils.is_reference_info_valid(affine, dimensions, voxel_sizes, voxel_order)

Validate basic data type and value of spatial attribute.

Does not ensure that voxel_sizes and voxel_order are self-coherent with the affine. Only verify the following:

• affine is of the right type (float) and dimension (4,4)

• affine contain values in the rotation part

• dimensions is of right type (int) and length (3)

• voxel_sizes is of right type (float) and length (3)

• voxel_order is of right type (str) and length (3)

The listed parameters are what is expected, provide something else and this function should fail (cover common mistakes).

Parameters

affine: ndarray (4,4)

Transformation of VOX to RASMM

dimensions: ndarray (3,), int16

Volume shape for each axis

voxel_sizes: ndarray (3,), float32

Size of voxel for each axis

voxel_order: string

Typically ‘RAS’ or ‘LPS’

Returns

outputbool

Does the input represent a valid ‘state’ of spatial attribute

get_reference_info

dipy.io.utils.get_reference_info(reference)

Will compare the spatial attribute of 2 references

Parameters

referenceNifti or Trk filename, Nifti1Image or TrkFile, Nifti1Header or

trk.header (dict) Reference that provides the spatial attribute.

Returns

outputtuple

• affine ndarray (4,4), np.float32, transformation of VOX to RASMM

• dimensions ndarray (3,), int16, volume shape for each axis

• voxel_sizes ndarray (3,), float32, size of voxel for each axis

• voxel_order, string, Typically ‘RAS’ or ‘LPS’

is_header_compatible

dipy.io.utils.is_header_compatible(reference_1, reference_2)

Will compare the spatial attribute of 2 references

Parameters

reference_1Nifti or Trk filename, Nifti1Image or TrkFile,

Nifti1Header or trk.header (dict) Reference that provides the spatial attribute.

reference_2Nifti or Trk filename, Nifti1Image or TrkFile,

Nifti1Header or trk.header (dict) Reference that provides the spatial attribute.

Returns

outputbool

Does all the spatial attribute match

create_tractogram_header

dipy.io.utils.create_tractogram_header(tractogram_type, affine, dimensions, voxel_sizes, voxel_order)

Write a standard trk/tck header from spatial attribute

create_nifti_header

dipy.io.utils.create_nifti_header(affine, dimensions, voxel_sizes)

Write a standard nifti header from spatial attribute

save_buan_profiles_hdf5

dipy.io.utils.save_buan_profiles_hdf5(fname, dt)

Saves the given input dataframe to .h5 file

Parameters

fnamestring

file name for saving the hdf5 file

dtPandas DataFrame

DataFrame to be saved as .h5 file

read_img_arr_or_path

dipy.io.utils.read_img_arr_or_path(data, affine=None)

Helper function that handles inputs that can be paths, nifti img or arrays

Parameters

dataarray or nib.Nifti1Image or str.

Either as a 3D/4D array or as a nifti image object, or as a string containing the full path to a nifti file.

affine4x4 array, optional.

Must be provided for data provided as an array. If provided together with Nifti1Image or str data, this input will over-ride the affine that is stored in the data input. Default: use the affine stored in data.

Returns

data, affine : ndarray and 4x4 array

load_polydata

dipy.io.vtk.load_polydata(file_name)

Load a vtk polydata to a supported format file.

Supported file formats are OBJ, VTK, VTP, FIB, PLY, STL and XML

Parameters

file_name : string

Returns

output : vtkPolyData

save_polydata

dipy.io.vtk.save_polydata(polydata, file_name, binary=False, color_array_name=None)

Save a vtk polydata to a supported format file.

Save formats can be VTK, VTP, FIB, PLY, STL and XML.

Parameters

polydata : vtkPolyData file_name : string

save_vtk_streamlines

dipy.io.vtk.save_vtk_streamlines(streamlines, filename, to_lps=True, binary=False)

Save streamlines as vtk polydata to a supported format file.

File formats can be OBJ, VTK, VTP, FIB, PLY, STL and XML

Parameters

streamlineslist

list of 2D arrays or ArraySequence

filenamestring

output filename (.obj, .vtk, .fib, .ply, .stl and .xml)

to_lpsbool

Default to True, will follow the vtk file convention for streamlines Will be supported by MITKDiffusion and MI-Brain

binarybool

save the file as binary

load_vtk_streamlines

dipy.io.vtk.load_vtk_streamlines(filename, to_lps=True)

Load streamlines from vtk polydata.

Load formats can be VTK, FIB

Parameters

filenamestring

input filename (.vtk or .fib)

to_lpsbool

Default to True, will follow the vtk file convention for streamlines Will be supported by MITKDiffusion and MI-Brain

Returns

outputlist

list of 2D arrays