qsirecon.interfaces.recon_scalars module

Classes that collect scalar images and metadata from Recon Workflows

class qsirecon.interfaces.recon_scalars.AMICOReconScalars(from_file=None, resource_monitor=None, **inputs)

Bases: ReconScalars

Mandatory Inputs:

• qsirecon_suffix (a string)

• source_file (a pathlike object or string representing an existing file)

Optional Inputs:

• directions_image (a pathlike object or string representing an existing file)

• dismiss_entities (a list of items which are any value) – (Nipype default value: [])

• icvf_image (a pathlike object or string representing an existing file)

• isovf_image (a pathlike object or string representing an existing file)

• model_info (a dictionary with keys which are any value and with values which are any value)

• model_name (a string)

• modulated_icvf_image (a pathlike object or string representing an existing file)

• modulated_od_image (a pathlike object or string representing an existing file)

• nrmse_image (a pathlike object or string representing an existing file)

• od_image (a pathlike object or string representing an existing file)

• rmse_image (a pathlike object or string representing an existing file)

• tf_image (a pathlike object or string representing an existing file)

Outputs:

scalar_info (a list of items which are any value)

scalar_metadata = {'directions_image': {'bids': {'model': 'noddi', 'param': 'direction'}, 'metadata': {'Description': 'Peak directions from NODDI'}, 'reorient_on_resample': True}, 'icvf_image': {'bids': {'model': 'noddi', 'param': 'icvf'}, 'figure': {'vmax': 1, 'vmin': 0}, 'metadata': {'Description': 'Intracellular volume fraction from NODDI'}}, 'isovf_image': {'bids': {'model': 'noddi', 'param': 'isovf'}, 'figure': {'vmax': 1, 'vmin': 0}, 'metadata': {'Description': 'Isotropic volume fraction from NODDI'}}, 'modulated_icvf_image': {'bids': {'desc': 'modulated', 'model': 'noddi', 'param': 'icvf'}, 'figure': {'vmax': 1, 'vmin': 0}, 'metadata': {'Description': 'Tissue fraction modulated intracellular volume fraction from NODDI'}}, 'modulated_od_image': {'bids': {'desc': 'modulated', 'model': 'noddi', 'param': 'od'}, 'figure': {'vmax': 1, 'vmin': 0}, 'metadata': {'Description': 'Tissue fraction modulated intracellular volume fraction from NODDI'}}, 'nrmse_image': {'bids': {'model': 'noddi', 'param': 'nrmse'}, 'figure': {'vmin': 0}, 'metadata': {'Description': 'NRMSE between predicted and measured signal from NODDI'}}, 'od_image': {'bids': {'model': 'noddi', 'param': 'od'}, 'metadata': {'Description': 'Orientation dispersion index from NODDI'}}, 'rmse_image': {'bids': {'model': 'noddi', 'param': 'rmse'}, 'figure': {'vmin': 0}, 'metadata': {'Description': 'RMSE between predicted and measured signal from NODDI'}}, 'tf_image': {'bids': {'model': 'noddi', 'param': 'tf'}, 'figure': {'vmax': 1, 'vmin': 0}, 'metadata': {'Description': 'Tissue fraction from NODDI'}}}

class qsirecon.interfaces.recon_scalars.BrainSuite3dSHOREReconScalars(from_file=None, resource_monitor=None, **inputs)

Bases: ReconScalars

Mandatory Inputs:

• qsirecon_suffix (a string)

• source_file (a pathlike object or string representing an existing file)

Optional Inputs:

• alpha_image (a pathlike object or string representing an existing file)

• cnr_image (a pathlike object or string representing an existing file)

• dismiss_entities (a list of items which are any value) – (Nipype default value: [])

• lapnorm_file (a pathlike object or string representing an existing file)

• mapcoeffs_file (a pathlike object or string representing an existing file)

• model_info (a dictionary with keys which are any value and with values which are any value)

• model_name (a string)

• msd_file (a pathlike object or string representing an existing file)

• ng_file (a pathlike object or string representing an existing file)

• ngpar_file (a pathlike object or string representing an existing file)

• ngperp_file (a pathlike object or string representing an existing file)

• qiv_file (a pathlike object or string representing an existing file)

• r2_image (a pathlike object or string representing an existing file)

• regularization_image (a pathlike object or string representing an existing file)

• rtap_file (a pathlike object or string representing an existing file)

• rtop_file (a pathlike object or string representing an existing file)

• rtpp_file (a pathlike object or string representing an existing file)

Outputs:

scalar_info (a list of items which are any value)

scalar_metadata = {'alpha_image': {'bids': {'model': '3dshore', 'param': 'alpha'}, 'metadata': {'Description': 'alpha used when fitting in each voxel'}}, 'cnr_image': {'bids': {'model': '3dshore', 'param': 'CNR'}, 'metadata': {'Description': 'Contrast to noise ratio for 3dshore fit'}}, 'lapnorm_file': {'bids': {'model': '3dshore', 'param': 'lapnorm'}, 'metadata': {'Description': 'Laplacian norm from regularized MAPMRI (MAPL)'}}, 'mapcoeffs_file': {'bids': {'model': '3dshore', 'param': 'mapcoeffs'}, 'metadata': {'Description': 'MAPMRI coefficients'}}, 'msd_file': {'bids': {'model': '3dshore', 'param': 'msd'}, 'metadata': {'Description': 'mean square displacement from MAPMRI'}}, 'ng_file': {'bids': {'model': '3dshore', 'param': 'ng'}, 'metadata': {'Description': 'Non-Gaussianity from MAPMRI'}}, 'ngpar_file': {'bids': {'model': '3dshore', 'param': 'ngpar'}, 'metadata': {'Description': 'Non-Gaussianity parallel from MAPMRI'}}, 'ngperp_file': {'bids': {'model': '3dshore', 'param': 'ngperp'}, 'metadata': {'Description': 'Non-Gaussianity perpendicular from MAPMRI'}}, 'qiv_file': {'bids': {'model': '3dshore', 'param': 'qiv'}, 'metadata': {'Description': 'q-space inverse variance from MAPMRI'}}, 'r2_image': {'bids': {'model': '3dshore', 'param': 'r2'}, 'metadata': {'Description': 'r^2 of the 3dshore fit'}}, 'regularization_image': {'bids': {'model': '3dshore', 'param': 'regularization'}, 'metadata': {'Description': 'regularization of the 3dshore fit'}}, 'rtap_file': {'bids': {'model': '3dshore', 'param': 'rtap'}, 'metadata': {'Description': 'Return to axis probability from MAPMRI'}}, 'rtop_file': {'bids': {'model': '3dshore', 'param': 'rtop'}, 'metadata': {'Description': 'Return to origin probability from MAPMRI'}}, 'rtpp_file': {'bids': {'model': '3dshore', 'param': 'rtpp'}, 'metadata': {'Description': 'Return to plane probability from MAPMRI'}}}

class qsirecon.interfaces.recon_scalars.DIPYDKIReconScalars(from_file=None, resource_monitor=None, **inputs)

Bases: ReconScalars

Mandatory Inputs:

• qsirecon_suffix (a string)

• source_file (a pathlike object or string representing an existing file)

Optional Inputs:

• dismiss_entities (a list of items which are any value) – (Nipype default value: [])

• dki_ad (a pathlike object or string representing an existing file)

• dki_ak (a pathlike object or string representing an existing file)

• dki_fa (a pathlike object or string representing an existing file)

• dki_kfa (a pathlike object or string representing an existing file)

• dki_linearity (a pathlike object or string representing an existing file)

• dki_md (a pathlike object or string representing an existing file)

• dki_mk (a pathlike object or string representing an existing file)

• dki_mkt (a pathlike object or string representing an existing file)

• dki_planarity (a pathlike object or string representing an existing file)

• dki_rd (a pathlike object or string representing an existing file)

• dki_rk (a pathlike object or string representing an existing file)

• dki_sphericity (a pathlike object or string representing an existing file)

• dkimicro_ad (a pathlike object or string representing an existing file)

• dkimicro_ade (a pathlike object or string representing an existing file)

• dkimicro_ak (a pathlike object or string representing an existing file)

• dkimicro_awf (a pathlike object or string representing an existing file)

• dkimicro_axonald (a pathlike object or string representing an existing file)

• dkimicro_kfa (a pathlike object or string representing an existing file)

• dkimicro_md (a pathlike object or string representing an existing file)

• dkimicro_rd (a pathlike object or string representing an existing file)

• dkimicro_rde (a pathlike object or string representing an existing file)

• dkimicro_tortuosity (a pathlike object or string representing an existing file)

• dkimicro_trace (a pathlike object or string representing an existing file)

• model_info (a dictionary with keys which are any value and with values which are any value)

• model_name (a string)

Outputs:

scalar_info (a list of items which are any value)

scalar_metadata = {'dki_ad': {'bids': {'model': 'dki', 'param': 'ad'}, 'metadata': {'Description': 'DKI axial diffusivity'}}, 'dki_ak': {'bids': {'model': 'dki', 'param': 'ak'}, 'metadata': {'Description': 'DKI axial kurtosis'}}, 'dki_fa': {'bids': {'model': 'tensor', 'param': 'fa'}, 'metadata': {'Description': 'DKI fractional anisotropy'}}, 'dki_kfa': {'bids': {'model': 'dki', 'param': 'kfa'}, 'metadata': {'Description': 'DKI kurtosis fractional anisotropy'}}, 'dki_linearity': {'bids': {'model': 'dki', 'param': 'linearity'}, 'metadata': {'Description': 'DKI linearity'}}, 'dki_md': {'bids': {'model': 'dki', 'param': 'md'}, 'metadata': {'Description': 'DKI mean diffusivity'}}, 'dki_mk': {'bids': {'model': 'dki', 'param': 'mk'}, 'metadata': {'Description': 'DKI mean kurtosis'}}, 'dki_mkt': {'bids': {'model': 'dki', 'param': 'mkt'}, 'metadata': {'Description': 'DKI mean of the kurtosis tensor'}}, 'dki_planarity': {'bids': {'model': 'dki', 'param': 'planarity'}, 'metadata': {'Description': 'DKI planarity'}}, 'dki_rd': {'bids': {'model': 'dki', 'param': 'rd'}, 'metadata': {'Description': 'DKI radial diffusivity'}}, 'dki_rk': {'bids': {'model': 'dki', 'param': 'rk'}, 'metadata': {'Description': 'DKI radial kurtosis'}}, 'dki_sphericity': {'bids': {'model': 'dki', 'param': 'sphericity'}, 'metadata': {'Description': 'DKI sphericity'}}, 'dkimicro_ad': {'bids': {'model': 'dkimicro', 'param': 'ad'}, 'metadata': {'Description': 'DKI Microstructural Axial Diffusivity'}}, 'dkimicro_ade': {'bids': {'model': 'dkimicro', 'param': 'ade'}, 'metadata': {'Description': 'DKI Microstructural Axial Diffusivity of the Extra-Cellular Compartment'}}, 'dkimicro_ak': {'bids': {'model': 'dkimicro', 'param': 'ak'}, 'metadata': {'Description': 'DKI Microstructural Axial Kurtosis'}}, 'dkimicro_awf': {'bids': {'model': 'dkimicro', 'param': 'awf'}, 'metadata': {'Description': 'DKI axonal water fraction'}}, 'dkimicro_axonald': {'bids': {'model': 'dkimicro', 'param': 'axonald'}, 'metadata': {'Description': 'DKI Microstructural Axonal Diffusivity'}}, 'dkimicro_kfa': {'bids': {'model': 'dkimicro', 'param': 'kfa'}, 'metadata': {'Description': 'DKI Microstructural Kurtosis Fractional Anisotropy'}}, 'dkimicro_md': {'bids': {'model': 'dkimicro', 'param': 'md'}, 'metadata': {'Description': 'DKI Microstructural Mean Diffusivity'}}, 'dkimicro_rd': {'bids': {'model': 'dkimicro', 'param': 'rd'}, 'metadata': {'Description': 'DKI Microstructural Radial Diffusivity'}}, 'dkimicro_rde': {'bids': {'model': 'dkimicro', 'param': 'rde'}, 'metadata': {'Description': 'DKI radial diffusivity of the extra-cellular compartment'}}, 'dkimicro_tortuosity': {'bids': {'model': 'dkimicro', 'param': 'tortuosity'}, 'metadata': {'Description': 'DKI Microstructural Tortuosity'}}, 'dkimicro_trace': {'bids': {'model': 'dkimicro', 'param': 'trace'}, 'metadata': {'Description': 'DKI Microstructural Trace'}}}

class qsirecon.interfaces.recon_scalars.DIPYMAPMRIReconScalars(from_file=None, resource_monitor=None, **inputs)

Bases: ReconScalars

Mandatory Inputs:

• qsirecon_suffix (a string)

• source_file (a pathlike object or string representing an existing file)

Optional Inputs:

• dismiss_entities (a list of items which are any value) – (Nipype default value: [])

• lapnorm_file (a pathlike object or string representing an existing file)

• mapcoeffs_file (a pathlike object or string representing an existing file)

• model_info (a dictionary with keys which are any value and with values which are any value)

• model_name (a string)

• msd_file (a pathlike object or string representing an existing file)

• ng_file (a pathlike object or string representing an existing file)

• ngpar_file (a pathlike object or string representing an existing file)

• ngperp_file (a pathlike object or string representing an existing file)

• qiv_file (a pathlike object or string representing an existing file)

• rtap_file (a pathlike object or string representing an existing file)

• rtop_file (a pathlike object or string representing an existing file)

• rtpp_file (a pathlike object or string representing an existing file)

Outputs:

scalar_info (a list of items which are any value)

scalar_metadata = {'lapnorm_file': {'bids': {'model': 'mapmri', 'param': 'lapnorm'}, 'metadata': {'Description': 'Laplacian norm from regularized MAPMRI (MAPL)'}}, 'mapcoeffs_file': {'bids': {'model': 'mapmri', 'param': 'mapcoeffs'}, 'metadata': {'Description': 'MAPMRI coefficients'}}, 'msd_file': {'bids': {'model': 'mapmri', 'param': 'msd'}, 'metadata': {'Description': 'mean square displacement from MAPMRI'}}, 'ng_file': {'bids': {'model': 'mapmri', 'param': 'ng'}, 'metadata': {'Description': 'Non-Gaussianity from MAPMRI'}}, 'ngpar_file': {'bids': {'model': 'mapmri', 'param': 'ngpar'}, 'metadata': {'Description': 'Non-Gaussianity parallel from MAPMRI'}}, 'ngperp_file': {'bids': {'model': 'mapmri', 'param': 'ngperp'}, 'metadata': {'Description': 'Non-Gaussianity perpendicular from MAPMRI'}}, 'qiv_file': {'bids': {'model': 'mapmri', 'param': 'qiv'}, 'metadata': {'Description': 'q-space inverse variance from MAPMRI'}}, 'rtap_file': {'bids': {'model': 'mapmri', 'param': 'rtap'}, 'metadata': {'Description': 'Return to axis probability from MAPMRI'}}, 'rtop_file': {'bids': {'model': 'mapmri', 'param': 'rtop'}, 'metadata': {'Description': 'Return to origin probability from MAPMRI'}}, 'rtpp_file': {'bids': {'model': 'mapmri', 'param': 'rtpp'}, 'metadata': {'Description': 'Return to plane probability from MAPMRI'}}}

class qsirecon.interfaces.recon_scalars.DSIStudioReconScalars(from_file=None, resource_monitor=None, **inputs)

Bases: ReconScalars

Mandatory Inputs:

• qsirecon_suffix (a string)

• source_file (a pathlike object or string representing an existing file)

Optional Inputs:

• ad_file (a pathlike object or string representing an existing file)

• dismiss_entities (a list of items which are any value) – (Nipype default value: [])

• dti_fa_file (a pathlike object or string representing an existing file)

• gfa_file (a pathlike object or string representing an existing file)

• ha_file (a pathlike object or string representing an existing file)

• iso_file (a pathlike object or string representing an existing file)

• md_file (a pathlike object or string representing an existing file)

• model_info (a dictionary with keys which are any value and with values which are any value)

• model_name (a string)

• qa_file (a pathlike object or string representing an existing file)

• rd1_file (a pathlike object or string representing an existing file)

• rd2_file (a pathlike object or string representing an existing file)

• rd_file (a pathlike object or string representing an existing file)

• txx_file (a pathlike object or string representing an existing file)

• txy_file (a pathlike object or string representing an existing file)

• txz_file (a pathlike object or string representing an existing file)

• tyy_file (a pathlike object or string representing an existing file)

• tyz_file (a pathlike object or string representing an existing file)

• tzz_file (a pathlike object or string representing an existing file)

Outputs:

scalar_info (a list of items which are any value)

scalar_metadata = {'ad_file': {'bids': {'model': 'tensor', 'param': 'ad'}, 'metadata': {'Description': 'Axial Diffusivity from a tensor fit. The first eigenvalue of the tensor.'}}, 'dti_fa_file': {'bids': {'model': 'tensor', 'param': 'fa'}, 'metadata': {'Description': 'Fractional Anisotropy from a tensor fit'}}, 'gfa_file': {'bids': {'model': 'gqi', 'param': 'gfa'}, 'metadata': {'Description': 'Generalized Fractional Anisotropy'}}, 'ha_file': {'bids': {'model': 'tensor', 'param': 'ha'}, 'metadata': {'Description': 'Helix Angle from tensor fit'}}, 'iso_file': {'bids': {'model': 'gqi', 'param': 'iso'}, 'metadata': {'Description': 'Isotropic Diffusion from GQI'}}, 'md_file': {'bids': {'model': 'tensor', 'param': 'md'}, 'metadata': {'Description': 'Mean Diffusivity from a tensor fit. The mean of the three eigenvalues.'}}, 'qa_file': {'bids': {'model': 'gqi', 'param': 'qa'}, 'metadata': {'Description': 'Quantitative Anisotropy from a GQI fit'}}, 'rd1_file': {'bids': {'model': 'tensor', 'param': 'rd1'}, 'metadata': {'Description': 'Lambda 2 (second eigenvalue) from a tensor fit.'}}, 'rd2_file': {'bids': {'model': 'tensor', 'param': 'rd2'}, 'metadata': {'Description': 'Lambda 3 (third eigenvalue) from a tensor fit.'}}, 'rd_file': {'bids': {'model': 'tensor', 'param': 'rd'}, 'metadata': {'Description': 'Radial Diffusivity from a tensor fit. The mean of the second and third eigenvalues (rd1 and rd2).'}}, 'txx_file': {'bids': {'model': 'tensor', 'param': 'txx'}, 'metadata': {'Description': 'Tensor fit txx'}}, 'txy_file': {'bids': {'model': 'tensor', 'param': 'txy'}, 'metadata': {'Description': 'Tensor fit txy'}}, 'txz_file': {'bids': {'model': 'tensor', 'param': 'txz'}, 'metadata': {'Description': 'Tensor fit txz'}}, 'tyy_file': {'bids': {'model': 'tensor', 'param': 'tyy'}, 'metadata': {'Description': 'Tensor fit tyy'}}, 'tyz_file': {'bids': {'model': 'tensor', 'param': 'tyz'}, 'metadata': {'Description': 'Tensor fit tyz'}}, 'tzz_file': {'bids': {'model': 'tensor', 'param': 'tzz'}, 'metadata': {'Description': 'Tensor fit tzz'}}}

class qsirecon.interfaces.recon_scalars.DisorganizeScalarData(from_file=None, resource_monitor=None, **inputs)

Bases: SimpleInterface

Optional Inputs:

• scalar_config (a dictionary with keys which are any value and with values which are any value)

• scalar_file (a pathlike object or string representing an existing file)

Outputs:

scalar_config (a dictionary with keys which are any value and with values which are any value)

class qsirecon.interfaces.recon_scalars.OrganizeScalarData(from_file=None, resource_monitor=None, **inputs)

Bases: SimpleInterface

Optional Inputs:

scalar_config (a dictionary with keys which are any value and with values which are any value)

Outputs:

• desc (a string or a _Undefined or None or None)

• metadata (a dictionary with keys which are any value and with values which are any value)

• model (a string or a _Undefined or None)

• param (a string or a _Undefined or None)

• scalar_file (a pathlike object or string representing an existing file)

class qsirecon.interfaces.recon_scalars.ParcellateScalars(from_file=None, resource_monitor=None, **inputs)

Bases: SimpleInterface

Optional Inputs:

• atlas_config (a dictionary with keys which are any value and with values which are any value)

• brain_mask (a pathlike object or string representing an existing file)

• mapping_metadata (a dictionary with keys which are any value and with values which are any value) – Info about the upstream workflow that created the anatomical mapping units.

• scalars_config (a list of items which are a dictionary with keys which are any value and with values which are any value)

• scalars_from (a list of items which are a string)

Outputs:

• metadata (a dictionary with keys which are any value and with values which are any value)

• parcellated_scalar_tsv (a pathlike object or string representing an existing file)

• seg (a string)

class qsirecon.interfaces.recon_scalars.ParcellationTableSplitterDataSink(from_file=None, resource_monitor=None, **inputs)

Bases: SimpleInterface

Mandatory Inputs:

• in_file (a pathlike object or string representing an existing file) – Tsv of combined scalar summaries.

• seg (a string) – The name of the segmentation.

• source_file (a pathlike object or string representing a file) – The source file(s) to extract entities from.

Optional Inputs:

• base_directory (a string or os.PathLike object) – Path to the base directory for storing data.

• compress (a boolean) – (Nipype default value: False)

• dataset_links (a dictionary with keys which are any value and with values which are any value) – Dataset links.

• dismiss_entities (a list of items which are any value) – (Nipype default value: [])

• meta_dict (a dictionary with keys which are any value and with values which are any value) – Metadata dictionary.

• suffix (a string) – The suffix of the parcellated data. (Nipype default value: dwimap)

Outputs:

• out_file (a list of items which are a pathlike object or string representing an existing file)

• out_meta (a list of items which are a pathlike object or string representing an existing file)

class qsirecon.interfaces.recon_scalars.ReconScalars(from_file=None, resource_monitor=None, **inputs)

Bases: SimpleInterface

Mandatory Inputs:

• qsirecon_suffix (a string)

• source_file (a pathlike object or string representing an existing file)

Optional Inputs:

• dismiss_entities (a list of items which are any value) – (Nipype default value: [])

• model_info (a dictionary with keys which are any value and with values which are any value)

• model_name (a string)

Outputs:

scalar_info (a list of items which are any value)

scalar_metadata = {}

class qsirecon.interfaces.recon_scalars.ReconScalarsTableSplitterDataSink(from_file=None, resource_monitor=None, **inputs)

Bases: SimpleInterface

Mandatory Inputs:

• suffix (a string)

• summary_tsv (a pathlike object or string representing an existing file) – Tsv of combined scalar summaries.

Optional Inputs:

• base_directory (a pathlike object or string representing a file)

• compress (a boolean) – (Nipype default value: True)

• dismiss_entities (a list of items which are any value) – (Nipype default value: [])

• infer_suffix (a boolean) – (Nipype default value: False)

• metadata (a dictionary with keys which are any value and with values which are any value) – List of metadata dictionaries.

• recon_scalars (a list of items which are any value)

• resampled_files (a list of items which are a pathlike object or string representing an existing file) – Resampled scalar files. This field is not used, but we keep it so that the files won’t be automatically deleted by Nipype.

• source_file (a pathlike object or string representing a file)

class qsirecon.interfaces.recon_scalars.TORTOISEReconScalars(from_file=None, resource_monitor=None, **inputs)

Bases: ReconScalars

Mandatory Inputs:

• qsirecon_suffix (a string)

• source_file (a pathlike object or string representing an existing file)

Optional Inputs:

• ad_file (a pathlike object or string representing an existing file)

• am_file (a pathlike object or string representing an existing file)

• dismiss_entities (a list of items which are any value) – (Nipype default value: [])

• fa_file (a pathlike object or string representing an existing file)

• li_file (a pathlike object or string representing an existing file)

• model_info (a dictionary with keys which are any value and with values which are any value)

• model_name (a string)

• ng_file (a pathlike object or string representing an existing file)

• ngpar_file (a pathlike object or string representing an existing file)

• ngperp_file (a pathlike object or string representing an existing file)

• pa_file (a pathlike object or string representing an existing file)

• path_file (a pathlike object or string representing an existing file)

• rd_file (a pathlike object or string representing an existing file)

• rtap_file (a pathlike object or string representing an existing file)

• rtop_file (a pathlike object or string representing an existing file)

• rtpp_file (a pathlike object or string representing an existing file)

Outputs:

scalar_info (a list of items which are any value)

scalar_metadata = {'ad_file': {'bids': {'model': 'tensor', 'param': 'ad'}, 'metadata': {'Description': 'Axial Diffusivity from a tensor fit'}}, 'am_file': {'bids': {'model': 'tensor', 'param': 'am'}, 'metadata': {'Description': 'A0 from a tensor fit'}}, 'fa_file': {'bids': {'model': 'tensor', 'param': 'fa'}, 'metadata': {'Description': 'Fractional Anisotropy from a tensor fit'}}, 'li_file': {'bids': {'model': 'tensor', 'param': 'li'}, 'metadata': {'Description': 'LI from a tensor fit'}}, 'ng_file': {'bids': {'model': 'mapmri', 'param': 'ng'}, 'metadata': {'Description': 'Non-Gaussianity from MAPMRI'}}, 'ngpar_file': {'bids': {'model': 'mapmri', 'param': 'ngpar'}, 'metadata': {'Description': 'Non-Gaussianity parallel from MAPMRI'}}, 'ngperp_file': {'bids': {'model': 'mapmri', 'param': 'ngperp'}, 'metadata': {'Description': 'Non-Gaussianity perpendicular from MAPMRI'}}, 'pa_file': {'bids': {'model': 'mapmri', 'param': 'pa'}, 'metadata': {'Description': 'PA from MAPMRI'}}, 'path_file': {'bids': {'model': 'mapmri', 'param': 'path'}, 'metadata': {'Description': 'PAth from MAPMRI'}}, 'rd_file': {'bids': {'model': 'tensor', 'param': 'rd'}, 'metadata': {'Description': 'Radial Diffusivity from a tensor fit'}}, 'rtap_file': {'bids': {'model': 'mapmri', 'param': 'rtap'}, 'metadata': {'Description': 'Return to axis probability from MAPMRI'}}, 'rtop_file': {'bids': {'model': 'mapmri', 'param': 'rtop'}, 'metadata': {'Description': 'Return to origin probability from MAPMRI'}}, 'rtpp_file': {'bids': {'model': 'mapmri', 'param': 'rtpp'}, 'metadata': {'Description': 'Return to plane probability from MAPMRI'}}}