The pyAFQ API methods

After defining your pyAFQ API object, you can ask for the output of any step of the pipeline. It is common for users to just call export_all (for example, myafq.export_all()). However, if the user only wants the tractography, the user can instead call myafq.export(“streamlines”). Here is a list of all of pyAFQ’s possible outputs:

data:

DWI data as an ndarray for selected b values

gtab:

A DIPY GradientTable with all the gradient information

dwi:

DWI data in a Nifti1Image

dwi_affine:

the affine transformation of the DWI data.

b0:

full path to a nifti file containing the mean b0

masked_b0:

full path to a nifti file containing the mean b0 after applying the brain mask

dti_tf:

DTI TensorFit object

dti_params:

full path to a nifti file containing parameters for the DTI fit

fwdti_tf:

Free-water DTI TensorFit object

fwdti_params:

Full path to a nifti file containing parameters for the free-water DTI fit.

dki_tf:

DKI DiffusionKurtosisFit object

dki_params:

full path to a nifti file containing parameters for the DKI fit

msdki_tf:

Mean Signal DKI DiffusionKurtosisFit object

msdki_params:

full path to a nifti file containing parameters for the Mean Signal DKI fit

msdki_msd:

full path to a nifti file containing the MSDKI mean signal diffusivity

msdki_msk:

full path to a nifti file containing the MSDKI mean signal kurtosis

csd_params:

full path to a nifti file containing parameters for the CSD fit

csd_pmap:

full path to a nifti file containing the anisotropic power map

csd_ai:

full path to a nifti file containing the anisotropic index

gq_params:

full path to a nifti file containing parameters for the Generalized Q-Sampling shm_coeff

gq_iso:

full path to a nifti file containing isotropic diffusion component

gq_aso:

full path to a nifti file containing anisotropic diffusion component

gq_pmap:

full path to a nifti file containing the anisotropic power map from GQ

gq_ai:

full path to a nifti file containing the anisotropic index from GQ

rumba_model:

fit for RUMBA-SD model as documented on dipy reconstruction options

rumba_params:

Takes the fitted RUMBA-SD model as input and returns the spherical harmonics coefficients (SHM).

rumba_fit:

RUMBA FIT

rumba_f_csf:

full path to a nifti file containing the CSF volume fraction for each voxel.

rumba_f_gm:

full path to a nifti file containing the GM volume fraction for each voxel.

rumba_f_wm:

full path to a nifti file containing the white matter volume fraction for each voxel.

opdt_params:

full path to a nifti file containing parameters for the Orientation Probability Density Transform shm_coeff

opdt_gfa:

full path to a nifti file containing GFA

opdt_pmap:

full path to a nifti file containing the anisotropic power map from OPDT

opdt_ai:

full path to a nifti file containing the anisotropic index from OPDT

csa_params:

full path to a nifti file containing parameters for the Constant Solid Angle shm_coeff

csa_gfa:

full path to a nifti file containing GFA

csa_pmap:

full path to a nifti file containing the anisotropic power map from CSA

csa_ai:

full path to a nifti file containing the anisotropic index from CSA

fwdti_fa:

full path to a nifti file containing the Free-water DTI fractional anisotropy

fwdti_md:

full path to a nifti file containing the Free-water DTI mean diffusivity

fwdti_fwf:

full path to a nifti file containing the Free-water DTI free water fraction

dti_fa:

full path to a nifti file containing the DTI fractional anisotropy

dti_lt0:

Image of first element in the DTI tensor according to DIPY convention i.e. Dxx (rate of diffusion from the left to right side of the brain)

dti_lt1:

Image of second element in the DTI tensor according to DIPY convention i.e. Dyy (rate of diffusion from the posterior to anterior part of the brain)

dti_lt2:

Image of third element in the DTI tensor according to DIPY convention i.e. Dzz (rate of diffusion from the inferior to superior part of the brain)

dti_lt3:

Image of fourth element in the DTI tensor according to DIPY convention i.e. Dxy (rate of diffusion in the xy plane indicating the relationship between the x and y directions)

dti_lt4:

Image of fifth element in the DTI tensor according to DIPY convention i.e. Dxz (rate of diffusion in the xz plane indicating the relationship between the x and z directions)

dti_lt5:

Image of sixth element in the DTI tensor according to DIPY convention i.e. Dyz (rate of diffusion in the yz plane indicating the relationship between the y and z directions)

dti_cfa:

full path to a nifti file containing the DTI color fractional anisotropy

dti_pdd:

full path to a nifti file containing the DTI principal diffusion direction

dti_md:

full path to a nifti file containing the DTI mean diffusivity

dti_ga:

full path to a nifti file containing the DTI geodesic anisotropy

dti_rd:

full path to a nifti file containing the DTI radial diffusivity

dti_ad:

full path to a nifti file containing the DTI axial diffusivity

dki_kt0:

Image of first element in the DKI kurtosis model

dki_kt1:

Image of second element in the DKI kurtosis model

dki_kt2:

Image of third element in the DKI kurtosis model

dki_kt3:

Image of fourth element in the DKI kurtosis model

dki_kt4:

Image of fifth element in the DKI kurtosis model

dki_kt5:

Image of sixth element in the DKI kurtosis model

dki_kt6:

Image of seventh element in the DKI kurtosis model

dki_kt7:

Image of eighth element in the DKI kurtosis model

dki_kt8:

Image of ninth element in the DKI kurtosis model

dki_kt9:

Image of tenth element in the DKI kurtosis model

dki_kt10:

Image of eleventh element in the DKI kurtosis model

dki_kt11:

Image of twelfth element in the DKI kurtosis model

dki_kt12:

Image of thirteenth element in the DKI kurtosis model

dki_kt13:

Image of fourteenth element in the DKI kurtosis model

dki_kt14:

Image of fifteenth element in the DKI kurtosis model

dki_lt0:

Image of first element in the DTI tensor from DKI

dki_lt1:

Image of second element in the DTI tensor from DKI

dki_lt2:

Image of third element in the DTI tensor from DKI

dki_lt3:

Image of fourth element in the DTI tensor from DKI

dki_lt4:

Image of fifth element in the DTI tensor from DKI

dki_lt5:

Image of sixth element in the DTI tensor from DKI

dki_fa:

full path to a nifti file containing the DKI fractional anisotropy

dki_md:

full path to a nifti file containing the DKI mean diffusivity

dki_awf:

full path to a nifti file containing the DKI axonal water fraction

dki_mk:

full path to a nifti file containing the DKI mean kurtosis file

dki_kfa:

full path to a nifti file containing the DKI kurtosis FA file

dki_ga:

full path to a nifti file containing the DKI geodesic anisotropy

dki_rd:

full path to a nifti file containing the DKI radial diffusivity

dki_ad:

full path to a nifti file containing the DKI axial diffusivity

dki_rk:

full path to a nifti file containing the DKI radial kurtosis

dki_ak:

full path to a nifti file containing the DKI axial kurtosis file

brain_mask:

full path to a nifti file containing the brain mask

bundle_dict:

Dictionary defining the different bundles to be segmented

reg_template:

a Nifti1Image containing the template for registration

b0_warped:

full path to a nifti file containing b0 transformed to template space

template_xform:

full path to a nifti file containing registration template transformed to subject space

rois:

dictionary of full paths to Nifti1Image files of ROIs transformed to subject space

mapping:

mapping from subject to template space.

reg_subject:

Nifti1Image which represents this subject when registering the subject to the template

bundles:

full path to a trk/trx file containing containing segmented streamlines, labeled by bundle

indiv_bundles:

dictionary of paths, where each path is a full path to a trk file containing the streamlines of a given bundle.

sl_counts:

full path to a JSON file containing streamline counts

median_bundle_lengths:

full path to a JSON file containing median bundle lengths

density_maps:

full path to 4d nifti file containing streamline counts per voxel per bundle, where the 4th dimension encodes the bundle

profiles:

full path to a CSV file containing tract profiles

scalar_dict:

dicionary mapping scalar names to their respective file paths

seed:

full path to a nifti file containing the tractography seed mask

stop:

full path to a nifti file containing the tractography stop mask

streamlines:

full path to the complete, unsegmented tractography file

all_bundles_figure:

figure for the visualizaion of the recognized bundles in the subject’s brain.

indiv_bundles_figures:

list of full paths to html or gif files containing visualizaions of individual bundles

tract_profile_plots:

list of full paths to png files, where files contain plots of the tract profiles

viz_backend:

An instance of the AFQ.viz.utils.viz_backend class.