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)[source]

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)

  • od_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'}, 'metadata': {'Description': 'Intracellular volume fraction from NODDI'}}, 'isovf_image': {'bids': {'model': 'noddi', 'param': 'isovf'}, 'metadata': {'Description': 'Isotropic volume fraction from NODDI'}}, 'od_image': {'bids': {'model': 'noddi', 'param': 'od'}, 'metadata': {'Description': 'Orientation dispersion index from NODDI'}}}
class qsirecon.interfaces.recon_scalars.BrainSuite3dSHOREReconScalars(from_file=None, resource_monitor=None, **inputs)[source]

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)[source]

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_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_rd (a pathlike object or string representing an existing file)

  • dki_rk (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 AD'}}, 'dki_ak': {'bids': {'model': 'dki', 'param': 'ak'}, 'metadata': {'Description': 'DKI AK'}}, 'dki_fa': {'bids': {'model': 'tensor', 'param': 'fa'}, 'metadata': {'Description': 'DKI FA'}}, 'dki_kfa': {'bids': {'model': 'dki', 'param': 'kfa'}, 'metadata': {'Description': 'DKI KFA'}}, 'dki_md': {'bids': {'model': 'dki', 'param': 'md'}, 'metadata': {'Description': 'DKI MD'}}, 'dki_mk': {'bids': {'model': 'dki', 'param': 'mk'}, 'metadata': {'Description': 'DKI MK'}}, 'dki_mkt': {'bids': {'model': 'dki', 'param': 'mkt'}, 'metadata': {'Description': 'DKI MKT'}}, 'dki_rd': {'bids': {'model': 'dki', 'param': 'rd'}, 'metadata': {'Description': 'DKI RD'}}, 'dki_rk': {'bids': {'model': 'dki', 'param': 'rk'}, 'metadata': {'Description': 'DKI RK'}}}
class qsirecon.interfaces.recon_scalars.DIPYMAPMRIReconScalars(from_file=None, resource_monitor=None, **inputs)[source]

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)[source]

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': 'Apparent Diffusivity from a tensor fit'}}, 'dti_fa_file': {'bids': {'model': 'tensor', 'param': 'fa'}, 'metadata': {'Description': 'Radial Diffusivity 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'}}, 'qa_file': {'bids': {'model': 'gqi', 'param': 'qa'}, 'metadata': {'Description': 'Quantitative Anisotropy from a GQI fit'}}, 'rd1_file': {'bids': {'model': 'rdi', 'param': 'rd1'}, 'metadata': {'Description': 'RD1'}}, 'rd2_file': {'bids': {'model': 'rdi', 'param': 'rd2'}, 'metadata': {'Description': 'RD2'}}, 'rd_file': {'bids': {'model': 'tensor', 'param': 'rd'}, 'metadata': {'Description': 'Radial Diffusivity'}}, '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.OrganizeScalarData(from_file=None, resource_monitor=None, **inputs)[source]

Bases: SimpleInterface

Optional Inputs:

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

Outputs:

  • 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.ReconScalars(from_file=None, resource_monitor=None, **inputs)[source]

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)[source]

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)

  • 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)[source]

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': 'Apparent 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'}}}