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# nipype.interfaces.fsl.model module

The fsl module provides classes for interfacing with the FSL command line tools. This was written to work with FSL version 4.1.4.

## Cluster

Link to code

> Bases: FSLCommand

> Wrapped executable: `cluster`.

> Uses FSL cluster to perform clustering on statistical output

> Examples

>     >>> cl = Cluster()
>     >>> cl.inputs.threshold = 2.3
>     >>> cl.inputs.in_file = 'zstat1.nii.gz'
>     >>> cl.inputs.out_localmax_txt_file = 'stats.txt'
>     >>> cl.inputs.use_mm = True
>     >>> cl.cmdline
>     'cluster --in=zstat1.nii.gz --olmax=stats.txt --thresh=2.3000000000 --mm'

> in_filea pathlike object or string representing an existing file

>   Input volume. Maps to a command-line argument: `--in=%s`.

> thresholda float

>   Threshold for input volume. Maps to a command-line argument: `--thresh=%.10f`.

> argsa unicode string

>   Additional parameters to the command. Maps to a command-line argument: `%s`.

> connectivityan integer (int or long)

>   The connectivity of voxels (default 26). Maps to a command-line argument: `--connectivity=%d`.

> cope_filea pathlike object or string representing a file

>   Cope volume. Maps to a command-line argument: `--cope=%s`.

> dlha float

>   Smoothness estimate = sqrt(det(Lambda)). Maps to a command-line argument: `--dlh=%.10f`.

> environa dictionary with keys which are a bytes or None or a value of class ‘str’ and with values which are a bytes or None or a value of class ‘str’

>   Environment variables. (Nipype default value: `{}`)

> find_mina boolean

>   Find minima instead of maxima. Maps to a command-line argument: `--min`. (Nipype default value: `False`)

> fractionala boolean

>   Interprets the threshold as a fraction of the robust range. Maps to a command-line argument: `--fractional`. (Nipype default value: `False`)

> minclustersizea boolean

>   Prints out minimum significant cluster size. Maps to a command-line argument: `--minclustersize`. (Nipype default value: `False`)

> no_tablea boolean

>   Suppresses printing of the table info. Maps to a command-line argument: `--no_table`. (Nipype default value: `False`)

> num_maximaan integer (int or long)

>   No of local maxima to report. Maps to a command-line argument: `--num=%d`.

> out_index_filea boolean or a pathlike object or string representing a file

>   Output of cluster index (in size order). Maps to a command-line argument: `--oindex=%s`.

> out_localmax_txt_filea boolean or a pathlike object or string representing a file

>   Local maxima text file. Maps to a command-line argument: `--olmax=%s`.

> out_localmax_vol_filea boolean or a pathlike object or string representing a file

>   Output of local maxima volume. Maps to a command-line argument: `--olmaxim=%s`.

> out_max_filea boolean or a pathlike object or string representing a file

>   Filename for output of max image. Maps to a command-line argument: `--omax=%s`.

> out_mean_filea boolean or a pathlike object or string representing a file

>   Filename for output of mean image. Maps to a command-line argument: `--omean=%s`.

> out_pval_filea boolean or a pathlike object or string representing a file

>   Filename for image output of log pvals. Maps to a command-line argument: `--opvals=%s`.

> out_size_filea boolean or a pathlike object or string representing a file

>   Filename for output of size image. Maps to a command-line argument: `--osize=%s`.

> out_threshold_filea boolean or a pathlike object or string representing a file

>   Thresholded image. Maps to a command-line argument: `--othresh=%s`.

> output_type‘NIFTI’ or ‘NIFTI_PAIR’ or ‘NIFTI_GZ’ or ‘NIFTI_PAIR_GZ’

>   FSL output type.

> peak_distancea float

>   Minimum distance between local maxima/minima, in mm (default 0). Maps to a command-line argument: `--peakdist=%.10f`.

> pthresholda float

>   P-threshold for clusters. Maps to a command-line argument: `--pthresh=%.10f`. Requires inputs: `dlh`, `volume`.

> std_space_filea pathlike object or string representing a file

>   Filename for standard-space volume. Maps to a command-line argument: `--stdvol=%s`.

> use_mma boolean

>   Use mm, not voxel, coordinates. Maps to a command-line argument: `--mm`. (Nipype default value: `False`)

> volumean integer (int or long)

>   Number of voxels in the mask. Maps to a command-line argument: `--volume=%d`.

> warpfield_filea pathlike object or string representing a file

>   File contining warpfield. Maps to a command-line argument: `--warpvol=%s`.

> xfm_filea pathlike object or string representing a file

>   Filename for Linear: input->standard-space transform. Non-linear: input->highres transform. Maps to a command-line argument: `--xfm=%s`.

> index_filea pathlike object or string representing a file

>   Output of cluster index (in size order).

> localmax_txt_filea pathlike object or string representing a file

>   Local maxima text file.

> localmax_vol_filea pathlike object or string representing a file

>   Output of local maxima volume.

> max_filea pathlike object or string representing a file

>   Filename for output of max image.

> mean_filea pathlike object or string representing a file

>   Filename for output of mean image.

> pval_filea pathlike object or string representing a file

>   Filename for image output of log pvals.

> size_filea pathlike object or string representing a file

>   Filename for output of size image.

> threshold_filea pathlike object or string representing a file

>   Thresholded image.

> Cluster.filemap = {'out_index_file': 'index', 'out_localmax_txt_file': 'localmax.txt', 'out_localmax_vol_file': 'localmax', 'out_max_file': 'max', 'out_mean_file': 'mean', 'out_pval_file': 'pval', 'out_size_file': 'size', 'out_threshold_file': 'threshold'}

## ContrastMgr

Link to code

> Bases: FSLCommand

> Wrapped executable: `contrast_mgr`.

> Use FSL contrast_mgr command to evaluate contrasts

> In interface mode this file assumes that all the required inputs are in the same location. This has deprecated for FSL versions 5.0.7+ as the necessary corrections file is no longer generated by FILMGLS.

> correctionsa pathlike object or string representing an existing file

>   Statistical corrections used within FILM modelling.

> dof_filea pathlike object or string representing an existing file

>   Degrees of freedom.

> param_estimatesa list of items which are a pathlike object or string representing an existing file

>   Parameter estimates for each column of the design matrix.

> sigmasquaredsa pathlike object or string representing an existing file

>   Summary of residuals, See Woolrich, et. al., 2001.

> tcon_filea pathlike object or string representing an existing file

>   Contrast file containing T-contrasts. Maps to a command-line argument: `%s` (position: -1).

> argsa unicode string

>   Additional parameters to the command. Maps to a command-line argument: `%s`.

> contrast_numa long integer >= 1

>   Contrast number to start labeling copes from. Maps to a command-line argument: `-cope`.

> environa dictionary with keys which are a bytes or None or a value of class ‘str’ and with values which are a bytes or None or a value of class ‘str’

>   Environment variables. (Nipype default value: `{}`)

> fcon_filea pathlike object or string representing an existing file

>   Contrast file containing F-contrasts. Maps to a command-line argument: `-f %s`.

> output_type‘NIFTI’ or ‘NIFTI_PAIR’ or ‘NIFTI_GZ’ or ‘NIFTI_PAIR_GZ’

>   FSL output type.

> suffixa unicode string

>   Suffix to put on the end of the cope filename before the contrast number, default is nothing. Maps to a command-line argument: `-suffix %s`.

> copesa list of items which are a pathlike object or string representing an existing file

>   Contrast estimates for each contrast.

> fstatsa list of items which are a pathlike object or string representing an existing file

>   F-stat file for each contrast.

> neffsa list of items which are a pathlike object or string representing an existing file

>   Neff file ?? for each contrast.

> tstatsa list of items which are a pathlike object or string representing an existing file

>   T-stat file for each contrast.

> varcopesa list of items which are a pathlike object or string representing an existing file

>   Variance estimates for each contrast.

> zfstatsa list of items which are a pathlike object or string representing an existing file

>   Z-stat file for each F contrast.

> zstatsa list of items which are a pathlike object or string representing an existing file

>   Z-stat file for each contrast.

## DualRegression

Link to code

> Bases: FSLCommand

> Wrapped executable: `dual_regression`.

> Wrapper Script for Dual Regression Workflow

> Examples

>     >>> dual_regression = DualRegression()
>     >>> dual_regression.inputs.in_files = ["functional.nii", "functional2.nii", "functional3.nii"]
>     >>> dual_regression.inputs.group_IC_maps_4D = "allFA.nii"
>     >>> dual_regression.inputs.des_norm = False
>     >>> dual_regression.inputs.one_sample_group_mean = True
>     >>> dual_regression.inputs.n_perm = 10
>     >>> dual_regression.inputs.out_dir = "my_output_directory"
>     >>> dual_regression.cmdline
>     'dual_regression allFA.nii 0 -1 10 my_output_directory functional.nii functional2.nii functional3.nii'
>     >>> dual_regression.run()

> group_IC_maps_4Da pathlike object or string representing an existing file

>   4D image containing spatial IC maps (melodic_IC) from the whole-group ICA analysis. Maps to a command-line argument: `%s` (position: 1).

> in_filesa list of items which are a pathlike object or string representing an existing file

>   List all subjects’ preprocessed, standard-space 4D datasets. Maps to a command-line argument: `%s` (position: -1).

> n_perman integer (int or long)

>   Number of permutations for randomise; set to 1 for just raw tstat output, set to 0 to not run randomise at all. Maps to a command-line argument: `%i` (position: 5).

> argsa unicode string

>   Additional parameters to the command. Maps to a command-line argument: `%s`.

> con_filea pathlike object or string representing an existing file

>   Design contrasts for final cross-subject modelling with randomise. Maps to a command-line argument: `%s` (position: 4).

> des_norma boolean

>   Whether to variance-normalise the timecourses used as the stage-2 regressors; True is default and recommended. Maps to a command-line argument: `%i` (position: 2). (Nipype default value: `True`)

> design_filea pathlike object or string representing an existing file

>   Design matrix for final cross-subject modelling with randomise. Maps to a command-line argument: `%s` (position: 3).

> environa dictionary with keys which are a bytes or None or a value of class ‘str’ and with values which are a bytes or None or a value of class ‘str’

>   Environment variables. (Nipype default value: `{}`)

> one_sample_group_meana boolean

>   Perform 1-sample group-mean test instead of generic permutation test. Maps to a command-line argument: `-1` (position: 3).

> out_dira pathlike object or string representing a directory

>   This directory will be created to hold all output and logfiles. Maps to a command-line argument: `%s` (position: 6). (Nipype default value: `output`)

> output_type‘NIFTI’ or ‘NIFTI_PAIR’ or ‘NIFTI_GZ’ or ‘NIFTI_PAIR_GZ’

>   FSL output type.

> out_dir : a pathlike object or string representing an existing directory

## FEAT

Link to code

> Bases: FSLCommand

> Wrapped executable: `feat`.

> Uses FSL feat to calculate first level stats

> fsf_filea pathlike object or string representing an existing file

>   File specifying the feat design spec file. Maps to a command-line argument: `%s` (position: 0).

> argsa unicode string

>   Additional parameters to the command. Maps to a command-line argument: `%s`.

> environa dictionary with keys which are a bytes or None or a value of class ‘str’ and with values which are a bytes or None or a value of class ‘str’

>   Environment variables. (Nipype default value: `{}`)

> output_type‘NIFTI’ or ‘NIFTI_PAIR’ or ‘NIFTI_GZ’ or ‘NIFTI_PAIR_GZ’

>   FSL output type.

> feat_dir : a pathlike object or string representing an existing directory

## FEATModel

Link to code

> Bases: FSLCommand

> Wrapped executable: `feat_model`.

> Uses FSL feat_model to generate design.mat files

> ev_filesa list of items which are a pathlike object or string representing an existing file

>   Event spec files generated by level1design. Maps to a command-line argument: `%s` (position: 1).

> fsf_filea pathlike object or string representing an existing file

>   File specifying the feat design spec file. Maps to a command-line argument: `%s` (position: 0).

> argsa unicode string

>   Additional parameters to the command. Maps to a command-line argument: `%s`.

> environa dictionary with keys which are a bytes or None or a value of class ‘str’ and with values which are a bytes or None or a value of class ‘str’

>   Environment variables. (Nipype default value: `{}`)

> output_type‘NIFTI’ or ‘NIFTI_PAIR’ or ‘NIFTI_GZ’ or ‘NIFTI_PAIR_GZ’

>   FSL output type.

> con_filea pathlike object or string representing an existing file

>   Contrast file containing contrast vectors.

> design_cova pathlike object or string representing an existing file

>   Graphical representation of design covariance.

> design_filea pathlike object or string representing an existing file

>   Mat file containing ascii matrix for design.

> design_imagea pathlike object or string representing an existing file

>   Graphical representation of design matrix.

> fcon_filea pathlike object or string representing a file

>   Contrast file containing contrast vectors.

## FEATRegister

Link to code

> Bases: BaseInterface

> Register feat directories to a specific standard

> feat_dirsa list of items which are a pathlike object or string representing an existing directory

>   Lower level feat dirs.

> reg_imagea pathlike object or string representing an existing file

>   Image to register to (will be treated as standard).

> reg_dofan integer (int or long)

>   Registration degrees of freedom. (Nipype default value: `12`)

> fsf_filea pathlike object or string representing an existing file

>   FSL feat specification file.

## FILMGLS

Link to code

> Bases: FSLCommand

> Wrapped executable: `film_gls`.

> Use FSL film_gls command to fit a design matrix to voxel timeseries

> Examples

> Initialize with no options, assigning them when calling run:

>     >>> from nipype.interfaces import fsl
>     >>> fgls = fsl.FILMGLS()
>     >>> res = fgls.run('in_file', 'design_file', 'thresh', rn='stats')

> Assign options through the `inputs` attribute:

>     >>> fgls = fsl.FILMGLS()
>     >>> fgls.inputs.in_file = 'functional.nii'
>     >>> fgls.inputs.design_file = 'design.mat'
>     >>> fgls.inputs.threshold = 10
>     >>> fgls.inputs.results_dir = 'stats'
>     >>> res = fgls.run()

> Specify options when creating an instance:

>     >>> fgls = fsl.FILMGLS(in_file='functional.nii', design_file='design.mat', threshold=10, results_dir='stats')
>     >>> res = fgls.run()

> in_filea pathlike object or string representing an existing file

>   Input data file. Maps to a command-line argument: `%s` (position: -3).

> argsa unicode string

>   Additional parameters to the command. Maps to a command-line argument: `%s`.

> autocorr_estimate_onlya boolean

>   Perform autocorrelation estimatation only. Maps to a command-line argument: `-ac`. Mutually exclusive with inputs: `autocorr_estimate_only`, `fit_armodel`, `tukey_window`, `multitaper_product`, `use_pava`, `autocorr_noestimate`.

> autocorr_noestimatea boolean

>   Do not estimate autocorrs. Maps to a command-line argument: `-noest`. Mutually exclusive with inputs: `autocorr_estimate_only`, `fit_armodel`, `tukey_window`, `multitaper_product`, `use_pava`, `autocorr_noestimate`.

> brightness_thresholda long integer >= 0

>   Susan brightness threshold, otherwise it is estimated. Maps to a command-line argument: `-epith %d`.

> design_filea pathlike object or string representing an existing file

>   Design matrix file. Maps to a command-line argument: `%s` (position: -2).

> environa dictionary with keys which are a bytes or None or a value of class ‘str’ and with values which are a bytes or None or a value of class ‘str’

>   Environment variables. (Nipype default value: `{}`)

> fit_armodela boolean

>   Fits autoregressive model - default is to use tukey with M=sqrt(numvols). Maps to a command-line argument: `-ar`. Mutually exclusive with inputs: `autocorr_estimate_only`, `fit_armodel`, `tukey_window`, `multitaper_product`, `use_pava`, `autocorr_noestimate`.

> full_dataa boolean

>   Output full data. Maps to a command-line argument: `-v`.

> mask_sizean integer (int or long)

>   Susan mask size. Maps to a command-line argument: `-ms %d`.

> multitaper_productan integer (int or long)

>   Multitapering with slepian tapers and num is the time-bandwidth product. Maps to a command-line argument: `-mt %d`. Mutually exclusive with inputs: `autocorr_estimate_only`, `fit_armodel`, `tukey_window`, `multitaper_product`, `use_pava`, `autocorr_noestimate`.

> output_pwdataa boolean

>   Output prewhitened data and average design matrix. Maps to a command-line argument: `-output_pwdata`.

> output_type‘NIFTI’ or ‘NIFTI_PAIR’ or ‘NIFTI_GZ’ or ‘NIFTI_PAIR_GZ’

>   FSL output type.

> results_dira pathlike object or string representing a directory

>   Directory to store results in. Maps to a command-line argument: `-rn %s`. (Nipype default value: `results`)

> smooth_autocorra boolean

>   Smooth auto corr estimates. Maps to a command-line argument: `-sa`.

> thresholda floating point number >= 0.0

>   Threshold. Maps to a command-line argument: `%f` (position: -1). (Nipype default value: `1000.0`)

> tukey_windowan integer (int or long)

>   Tukey window size to estimate autocorr. Maps to a command-line argument: `-tukey %d`. Mutually exclusive with inputs: `autocorr_estimate_only`, `fit_armodel`, `tukey_window`, `multitaper_product`, `use_pava`, `autocorr_noestimate`.

> use_pavaa boolean

>   Estimates autocorr using PAVA. Maps to a command-line argument: `-pava`.

> correctionsa pathlike object or string representing an existing file

>   Statistical corrections used within FILM modeling.

> dof_filea pathlike object or string representing an existing file

>   Degrees of freedom.

> logfilea pathlike object or string representing an existing file

>   FILM run logfile.

> param_estimatesa list of items which are a pathlike object or string representing an existing file

>   Parameter estimates for each column of the design matrix.

> residual4da pathlike object or string representing an existing file

>   Model fit residual mean-squared error for each time point.

> results_dira pathlike object or string representing an existing directory

>   Directory storing model estimation output.

> sigmasquaredsa pathlike object or string representing an existing file

>   Summary of residuals, See Woolrich, et. al., 2001.

> thresholdaca pathlike object or string representing an existing file

>   The FILM autocorrelation parameters.

## FLAMEO

Link to code

> Bases: FSLCommand

> Wrapped executable: `flameo`.

> Use FSL flameo command to perform higher level model fits

> Examples

> Initialize FLAMEO with no options, assigning them when calling run:

>     >>> from nipype.interfaces import fsl
>     >>> flameo = fsl.FLAMEO()
>     >>> flameo.inputs.cope_file = 'cope.nii.gz'
>     >>> flameo.inputs.var_cope_file = 'varcope.nii.gz'
>     >>> flameo.inputs.cov_split_file = 'cov_split.mat'
>     >>> flameo.inputs.design_file = 'design.mat'
>     >>> flameo.inputs.t_con_file = 'design.con'
>     >>> flameo.inputs.mask_file = 'mask.nii'
>     >>> flameo.inputs.run_mode = 'fe'
>     >>> flameo.cmdline
>     'flameo --copefile=cope.nii.gz --covsplitfile=cov_split.mat --designfile=design.mat --ld=stats --maskfile=mask.nii --runmode=fe --tcontrastsfile=design.con --varcopefile=varcope.nii.gz'

> cope_filea pathlike object or string representing an existing file

>   Cope regressor data file. Maps to a command-line argument: `--copefile=%s`.

> cov_split_filea pathlike object or string representing an existing file

>   Ascii matrix specifying the groups the covariance is split into. Maps to a command-line argument: `--covsplitfile=%s`.

> design_filea pathlike object or string representing an existing file

>   Design matrix file. Maps to a command-line argument: `--designfile=%s`.

> mask_filea pathlike object or string representing an existing file

>   Mask file. Maps to a command-line argument: `--maskfile=%s`.

> run_mode‘fe’ or ‘ols’ or ‘flame1’ or ‘flame12’

>   Inference to perform. Maps to a command-line argument: `--runmode=%s`.

> t_con_filea pathlike object or string representing an existing file

>   Ascii matrix specifying t-contrasts. Maps to a command-line argument: `--tcontrastsfile=%s`.

> argsa unicode string

>   Additional parameters to the command. Maps to a command-line argument: `%s`.

> burninan integer (int or long)

>   Number of jumps at start of mcmc to be discarded. Maps to a command-line argument: `--burnin=%d`.

> dof_var_cope_filea pathlike object or string representing an existing file

>   Dof data file for varcope data. Maps to a command-line argument: `--dofvarcopefile=%s`.

> environa dictionary with keys which are a bytes or None or a value of class ‘str’ and with values which are a bytes or None or a value of class ‘str’

>   Environment variables. (Nipype default value: `{}`)

> f_con_filea pathlike object or string representing an existing file

>   Ascii matrix specifying f-contrasts. Maps to a command-line argument: `--fcontrastsfile=%s`.

> fix_meana boolean

>   Fix mean for tfit. Maps to a command-line argument: `--fixmean`.

> infer_outliersa boolean

>   Infer outliers - not for fe. Maps to a command-line argument: `--inferoutliers`.

> log_dira pathlike object or string representing a directory

>   Maps to a command-line argument: `--ld=%s`. (Nipype default value: `stats`)

> n_jumpsan integer (int or long)

>   Number of jumps made by mcmc. Maps to a command-line argument: `--njumps=%d`.

> no_pe_outputsa boolean

>   Do not output pe files. Maps to a command-line argument: `--nopeoutput`.

> outlier_iteran integer (int or long)

>   Number of max iterations to use when inferring outliers. Default is 12. Maps to a command-line argument: `--ioni=%d`.

> output_type‘NIFTI’ or ‘NIFTI_PAIR’ or ‘NIFTI_GZ’ or ‘NIFTI_PAIR_GZ’

>   FSL output type.

> sample_everyan integer (int or long)

>   Number of jumps for each sample. Maps to a command-line argument: `--sampleevery=%d`.

> sigma_dofsan integer (int or long)

>   Sigma (in mm) to use for Gaussian smoothing the DOFs in FLAME 2. Default is 1mm, -1 indicates no smoothing. Maps to a command-line argument: `--sigma_dofs=%d`.

> var_cope_filea pathlike object or string representing an existing file

>   Varcope weightings data file. Maps to a command-line argument: `--varcopefile=%s`.

> copesa list of items which are a pathlike object or string representing an existing file

>   Contrast estimates for each contrast.

> fstatsa list of items which are a pathlike object or string representing an existing file

>   F-stat file for each contrast.

> mrefvarsa list of items which are a pathlike object or string representing an existing file

>   Mean random effect variances for each contrast.

> pesa list of items which are a pathlike object or string representing an existing file

>   Parameter estimates for each column of the design matrix for each voxel.

> res4da list of items which are a pathlike object or string representing an existing file

>   Model fit residual mean-squared error for each time point.

> stats_dira pathlike object or string representing a directory

>   Directory storing model estimation output.

> tdofa list of items which are a pathlike object or string representing an existing file

>   Temporal dof file for each contrast.

> tstatsa list of items which are a pathlike object or string representing an existing file

>   T-stat file for each contrast.

> var_copesa list of items which are a pathlike object or string representing an existing file

>   Variance estimates for each contrast.

> weightsa list of items which are a pathlike object or string representing an existing file

>   Weights file for each contrast.

> zfstatsa list of items which are a pathlike object or string representing an existing file

>   Z stat file for each f contrast.

> zstatsa list of items which are a pathlike object or string representing an existing file

>   Z-stat file for each contrast.

## GLM

Link to code

> Bases: FSLCommand

> Wrapped executable: `fsl_glm`.

> FSL GLM:

> Example

>     >>> import nipype.interfaces.fsl as fsl
>     >>> glm = fsl.GLM(in_file='functional.nii', design='maps.nii', output_type='NIFTI')
>     >>> glm.cmdline
>     'fsl_glm -i functional.nii -d maps.nii -o functional_glm.nii'

> designa pathlike object or string representing an existing file

>   File name of the GLM design matrix (text time courses for temporal regression or an image file for spatial regression). Maps to a command-line argument: `-d %s` (position: 2).

> in_filea pathlike object or string representing an existing file

>   Input file name (text matrix or 3D/4D image file). Maps to a command-line argument: `-i %s` (position: 1).

> argsa unicode string

>   Additional parameters to the command. Maps to a command-line argument: `%s`.

> contrastsa pathlike object or string representing an existing file

>   Matrix of t-statics contrasts. Maps to a command-line argument: `-c %s`.

> dat_norma boolean

>   Switch on normalization of the data time series to unit std deviation. Maps to a command-line argument: `--dat_norm`.

> demeana boolean

>   Switch on demeaining of design and data. Maps to a command-line argument: `--demean`.

> des_norma boolean

>   Switch on normalization of the design matrix columns to unit std deviation. Maps to a command-line argument: `--des_norm`.

> dofan integer (int or long)

>   Set degrees of freedom explicitly. Maps to a command-line argument: `--dof=%d`.

> environa dictionary with keys which are a bytes or None or a value of class ‘str’ and with values which are a bytes or None or a value of class ‘str’

>   Environment variables. (Nipype default value: `{}`)

> maska pathlike object or string representing an existing file

>   Mask image file name if input is image. Maps to a command-line argument: `-m %s`.

> out_copea pathlike object or string representing a file

>   Output file name for COPE (either as txt or image. Maps to a command-line argument: `--out_cope=%s`.

> out_data_namea pathlike object or string representing a file

>   Output file name for pre-processed data. Maps to a command-line argument: `--out_data=%s`.

> out_f_namea pathlike object or string representing a file

>   Output file name for F-value of full model fit. Maps to a command-line argument: `--out_f=%s`.

> out_filea pathlike object or string representing a file

>   Filename for GLM parameter estimates (GLM betas). Maps to a command-line argument: `-o %s` (position: 3).

> out_p_namea pathlike object or string representing a file

>   Output file name for p-values of Z-stats (either as text file or image). Maps to a command-line argument: `--out_p=%s`.

> out_pf_namea pathlike object or string representing a file

>   Output file name for p-value for full model fit. Maps to a command-line argument: `--out_pf=%s`.

> out_res_namea pathlike object or string representing a file

>   Output file name for residuals. Maps to a command-line argument: `--out_res=%s`.

> out_sigsq_namea pathlike object or string representing a file

>   Output file name for residual noise variance sigma-square. Maps to a command-line argument: `--out_sigsq=%s`.

> out_t_namea pathlike object or string representing a file

>   Output file name for t-stats (either as txt or image. Maps to a command-line argument: `--out_t=%s`.

> out_varcb_namea pathlike object or string representing a file

>   Output file name for variance of COPEs. Maps to a command-line argument: `--out_varcb=%s`.

> out_vnscales_namea pathlike object or string representing a file

>   Output file name for scaling factors for variance normalisation. Maps to a command-line argument: `--out_vnscales=%s`.

> out_z_namea pathlike object or string representing a file

>   Output file name for Z-stats (either as txt or image. Maps to a command-line argument: `--out_z=%s`.

> output_type‘NIFTI’ or ‘NIFTI_PAIR’ or ‘NIFTI_GZ’ or ‘NIFTI_PAIR_GZ’

>   FSL output type.

> var_norma boolean

>   Perform MELODIC variance-normalisation on data. Maps to a command-line argument: `--vn`.

> out_copea list of items which are a pathlike object or string representing an existing file

>   Output file name for COPEs (either as text file or image).

> out_dataa list of items which are a pathlike object or string representing an existing file

>   Output file for preprocessed data.

> out_fa list of items which are a pathlike object or string representing an existing file

>   Output file name for F-value of full model fit.

> out_filea pathlike object or string representing an existing file

>   File name of GLM parameters (if generated).

> out_pa list of items which are a pathlike object or string representing an existing file

>   Output file name for p-values of Z-stats (either as text file or image).

> out_pfa list of items which are a pathlike object or string representing an existing file

>   Output file name for p-value for full model fit.

> out_resa list of items which are a pathlike object or string representing an existing file

>   Output file name for residuals.

> out_sigsqa list of items which are a pathlike object or string representing an existing file

>   Output file name for residual noise variance sigma-square.

> out_ta list of items which are a pathlike object or string representing an existing file

>   Output file name for t-stats (either as text file or image).

> out_varcba list of items which are a pathlike object or string representing an existing file

>   Output file name for variance of COPEs.

> out_vnscalesa list of items which are a pathlike object or string representing an existing file

>   Output file name for scaling factors for variance normalisation.

> out_za list of items which are a pathlike object or string representing an existing file

>   Output file name for COPEs (either as text file or image).

## L2Model

Link to code

> Bases: BaseInterface

> Generate subject specific second level model

> Examples

>     >>> from nipype.interfaces.fsl import L2Model
>     >>> model = L2Model(num_copes=3) # 3 sessions

> num_copesa long integer >= 1

>   Number of copes to be combined.

> design_cona pathlike object or string representing an existing file

>   Design contrast file.

> design_grpa pathlike object or string representing an existing file

>   Design group file.

> design_mata pathlike object or string representing an existing file

>   Design matrix file.

## Level1Design

Link to code

> Bases: BaseInterface

> Generate FEAT specific files

> Examples

>     >>> level1design = Level1Design()
>     >>> level1design.inputs.interscan_interval = 2.5
>     >>> level1design.inputs.bases = {'dgamma':{'derivs': False}}
>     >>> level1design.inputs.session_info = 'session_info.npz'
>     >>> level1design.run()

> basesa dictionary with keys which are ‘dgamma’ and with values which are a dictionary with keys which are ‘derivs’ and with values which are a boolean or a dictionary with keys which are ‘gamma’ and with values which are a dictionary with keys which are ‘derivs’ or ‘gammasigma’ or ‘gammadelay’ and with values which are any value or a dictionary with keys which are ‘custom’ and with values which are a dictionary with keys which are ‘bfcustompath’ and with values which are a unicode string or a dictionary with keys which are ‘none’ and with values which are a dictionary with keys which are any value and with values which are any value or a dictionary with keys which are ‘none’ and with values which are None

>   Name of basis function and options e.g., {‘dgamma’: {‘derivs’: True}}.

> interscan_intervala float

>   Interscan interval (in secs).

> model_serial_correlationsa boolean

>   Option to model serial correlations using an autoregressive estimator (order 1). Setting this option is only useful in the context of the fsf file. If you set this to False, you need to repeat this option for FILMGLS by setting autocorr_noestimate to True.

> session_infoany value

>   Session specific information generated by `modelgen.SpecifyModel`.

> contrastsa list of items which are a tuple of the form: (a unicode string, ‘T’, a list of items which are a unicode string, a list of items which are a float) or a tuple of the form: (a unicode string, ‘T’, a list of items which are a unicode string, a list of items which are a float, a list of items which are a float) or a tuple of the form: (a unicode string, ‘F’, a list of items which are a tuple of the form: (a unicode string, ‘T’, a list of items which are a unicode string, a list of items which are a float) or a tuple of the form: (a unicode string, ‘T’, a list of items which are a unicode string, a list of items which are a float, a list of items which are a float))

>   List of contrasts with each contrast being a list of the form - [(‘name’, ‘stat’, [condition list], [weight list], [session list])]. if session list is None or not provided, all sessions are used. For F contrasts, the condition list should contain previously defined T-contrasts.

> orthogonalizationa dictionary with keys which are an integer (int or long) and with values which are a dictionary with keys which are an integer (int or long) and with values which are a boolean or an integer (int or long)

>   Which regressors to make orthogonal e.g., {1: {0:0,1:0,2:0}, 2: {0:1,1:1,2:0}} to make the second regressor in a 2-regressor model orthogonal to the first. (Nipype default value: `{}`)

> ev_filesa list of items which are a list of items which are a pathlike object or string representing an existing file

>   Condition information files.

> fsf_filesa list of items which are a pathlike object or string representing an existing file

>   FSL feat specification files.

## MELODIC

Link to code

> Bases: FSLCommand

> Wrapped executable: `melodic`.

> Multivariate Exploratory Linear Optimised Decomposition into Independent Components

> Examples

>     >>> melodic_setup = MELODIC()
>     >>> melodic_setup.inputs.approach = 'tica'
>     >>> melodic_setup.inputs.in_files = ['functional.nii', 'functional2.nii', 'functional3.nii']
>     >>> melodic_setup.inputs.no_bet = True
>     >>> melodic_setup.inputs.bg_threshold = 10
>     >>> melodic_setup.inputs.tr_sec = 1.5
>     >>> melodic_setup.inputs.mm_thresh = 0.5
>     >>> melodic_setup.inputs.out_stats = True
>     >>> melodic_setup.inputs.t_des = 'timeDesign.mat'
>     >>> melodic_setup.inputs.t_con = 'timeDesign.con'
>     >>> melodic_setup.inputs.s_des = 'subjectDesign.mat'
>     >>> melodic_setup.inputs.s_con = 'subjectDesign.con'
>     >>> melodic_setup.inputs.out_dir = 'groupICA.out'
>     >>> melodic_setup.cmdline
>     'melodic -i functional.nii,functional2.nii,functional3.nii -a tica --bgthreshold=10.000000 --mmthresh=0.500000 --nobet -o groupICA.out --Ostats --Scon=subjectDesign.con --Sdes=subjectDesign.mat --Tcon=timeDesign.con --Tdes=timeDesign.mat --tr=1.500000'
>     >>> melodic_setup.run()

> in_filesa list of items which are a pathlike object or string representing an existing file

>   Input file names (either single file name or a list). Maps to a command-line argument: `-i %s` (position: 0).

> ICsa pathlike object or string representing an existing file

>   Filename of the IC components file for mixture modelling. Maps to a command-line argument: `--ICs=%s`.

> approacha unicode string

>   Approach for decomposition, 2D: defl, symm (default), 3D: tica (default), concat. Maps to a command-line argument: `-a %s`.

> argsa unicode string

>   Additional parameters to the command. Maps to a command-line argument: `%s`.

> bg_imagea pathlike object or string representing an existing file

>   Specify background image for report (default: mean image). Maps to a command-line argument: `--bgimage=%s`.

> bg_thresholda float

>   Brain/non-brain threshold used to mask non-brain voxels, as a percentage (only if –nobet selected). Maps to a command-line argument: `--bgthreshold=%f`.

> cov_weighta float

>   Voxel-wise weights for the covariance matrix (e.g. segmentation information). Maps to a command-line argument: `--covarweight=%f`.

> diman integer (int or long)

>   Dimensionality reduction into #num dimensions (default: automatic estimation). Maps to a command-line argument: `-d %d`.

> dim_esta unicode string

>   Use specific dim. estimation technique: lap, bic, mdl, aic, mean (default: lap). Maps to a command-line argument: `--dimest=%s`.

> environa dictionary with keys which are a bytes or None or a value of class ‘str’ and with values which are a bytes or None or a value of class ‘str’

>   Environment variables. (Nipype default value: `{}`)

> epsilona float

>   Minimum error change. Maps to a command-line argument: `--eps=%f`.

> epsilonSa float

>   Minimum error change for rank-1 approximation in TICA. Maps to a command-line argument: `--epsS=%f`.

> log_powera boolean

>   Calculate log of power for frequency spectrum. Maps to a command-line argument: `--logPower`.

> maska pathlike object or string representing an existing file

>   File name of mask for thresholding. Maps to a command-line argument: `-m %s`.

> max_restartan integer (int or long)

>   Maximum number of restarts. Maps to a command-line argument: `--maxrestart=%d`.

> maxitan integer (int or long)

>   Maximum number of iterations before restart. Maps to a command-line argument: `--maxit=%d`.

> migpa boolean

>   Switch on MIGP data reduction. Maps to a command-line argument: `--migp`.

> migpNan integer (int or long)

>   Number of internal Eigenmaps. Maps to a command-line argument: `--migpN %d`.

> migp_factoran integer (int or long)

>   Internal Factor of mem-threshold relative to number of Eigenmaps (default: 2). Maps to a command-line argument: `--migp_factor %d`.

> migp_shufflea boolean

>   Randomise MIGP file order (default: TRUE). Maps to a command-line argument: `--migp_shuffle`.

> mixa pathlike object or string representing an existing file

>   Mixing matrix for mixture modelling / filtering. Maps to a command-line argument: `--mix=%s`.

> mm_thresha float

>   Threshold for Mixture Model based inference. Maps to a command-line argument: `--mmthresh=%f`.

> no_beta boolean

>   Switch off BET. Maps to a command-line argument: `--nobet`.

> no_maska boolean

>   Switch off masking. Maps to a command-line argument: `--nomask`.

> no_mma boolean

>   Switch off mixture modelling on IC maps. Maps to a command-line argument: `--no_mm`.

> non_linearitya unicode string

>   Nonlinearity: gauss, tanh, pow3, pow4. Maps to a command-line argument: `--nl=%s`.

> num_ICsan integer (int or long)

>   Number of IC’s to extract (for deflation approach). Maps to a command-line argument: `-n %d`.

> out_alla boolean

>   Output everything. Maps to a command-line argument: `--Oall`.

> out_dira pathlike object or string representing a directory

>   Output directory name. Maps to a command-line argument: `-o %s`.

> out_meana boolean

>   Output mean volume. Maps to a command-line argument: `--Omean`.

> out_origa boolean

>   Output the original ICs. Maps to a command-line argument: `--Oorig`.

> out_pcaa boolean

>   Output PCA results. Maps to a command-line argument: `--Opca`.

> out_statsa boolean

>   Output thresholded maps and probability maps. Maps to a command-line argument: `--Ostats`.

> out_unmixa boolean

>   Output unmixing matrix. Maps to a command-line argument: `--Ounmix`.

> out_whitea boolean

>   Output whitening/dewhitening matrices. Maps to a command-line argument: `--Owhite`.

> output_type‘NIFTI’ or ‘NIFTI_PAIR’ or ‘NIFTI_GZ’ or ‘NIFTI_PAIR_GZ’

>   FSL output type.

> pbsca boolean

>   Switch off conversion to percent BOLD signal change. Maps to a command-line argument: `--pbsc`.

> rem_cmpa list of items which are an integer (int or long)

>   Component numbers to remove. Maps to a command-line argument: `-f %d`.

> remove_deriva boolean

>   Removes every second entry in paradigm file (EV derivatives). Maps to a command-line argument: `--remove_deriv`.

> reporta boolean

>   Generate Melodic web report. Maps to a command-line argument: `--report`.

> report_mapsa unicode string

>   Control string for spatial map images (see slicer). Maps to a command-line argument: `--report_maps=%s`.

> s_cona pathlike object or string representing an existing file

>   T-contrast matrix across subject-domain. Maps to a command-line argument: `--Scon=%s`.

> s_desa pathlike object or string representing an existing file

>   Design matrix across subject-domain. Maps to a command-line argument: `--Sdes=%s`.

> sep_vna boolean

>   Switch off joined variance normalization. Maps to a command-line argument: `--sep_vn`.

> sep_whitena boolean

>   Switch on separate whitening. Maps to a command-line argument: `--sep_whiten`.

> smodea pathlike object or string representing an existing file

>   Matrix of session modes for report generation. Maps to a command-line argument: `--smode=%s`.

> t_cona pathlike object or string representing an existing file

>   T-contrast matrix across time-domain. Maps to a command-line argument: `--Tcon=%s`.

> t_desa pathlike object or string representing an existing file

>   Design matrix across time-domain. Maps to a command-line argument: `--Tdes=%s`.

> tr_seca float

>   TR in seconds. Maps to a command-line argument: `--tr=%f`.

> update_maska boolean

>   Switch off mask updating. Maps to a command-line argument: `--update_mask`.

> var_norma boolean

>   Switch off variance normalization. Maps to a command-line argument: `--vn`.

> out_dir : a pathlike object or string representing an existing directory report_dir : a pathlike object or string representing an existing directory

## MultipleRegressDesign

Link to code

> Bases: BaseInterface

> Generate multiple regression design

> Note

> FSL does not demean columns for higher level analysis.

> Please see FSL documentation for more details on model specification for higher level analysis.

> Examples

>     >>> from nipype.interfaces.fsl import MultipleRegressDesign
>     >>> model = MultipleRegressDesign()
>     >>> model.inputs.contrasts = [['group mean', 'T',['reg1'],[1]]]
>     >>> model.inputs.regressors = dict(reg1=[1, 1, 1], reg2=[2.,-4, 3])
>     >>> model.run()

> contrastsa list of items which are a tuple of the form: (a unicode string, ‘T’, a list of items which are a unicode string, a list of items which are a float) or a tuple of the form: (a unicode string, ‘F’, a list of items which are a tuple of the form: (a unicode string, ‘T’, a list of items which are a unicode string, a list of items which are a float))

>   List of contrasts with each contrast being a list of the form - [(‘name’, ‘stat’, [condition list], [weight list])]. if session list is None or not provided, all sessions are used. For F contrasts, the condition list should contain previously defined T-contrasts without any weight list.

> regressorsa dictionary with keys which are a unicode string and with values which are a list of items which are a float

>   Dictionary containing named lists of regressors.

> groupsa list of items which are an integer (int or long)

>   List of group identifiers (defaults to single group).

> design_cona pathlike object or string representing an existing file

>   Design t-contrast file.

> design_ftsa pathlike object or string representing an existing file

>   Design f-contrast file.

> design_grpa pathlike object or string representing an existing file

>   Design group file.

> design_mata pathlike object or string representing an existing file

>   Design matrix file.

## Randomise

Link to code

> Bases: FSLCommand

> Wrapped executable: `randomise`.

> FSL Randomise: feeds the 4D projected FA data into GLM modelling and thresholding in order to find voxels which correlate with your model

> Example

>     >>> import nipype.interfaces.fsl as fsl
>     >>> rand = fsl.Randomise(in_file='allFA.nii', mask = 'mask.nii', tcon='design.con', design_mat='design.mat')
>     >>> rand.cmdline
>     'randomise -i allFA.nii -o "randomise" -d design.mat -t design.con -m mask.nii'

> in_filea pathlike object or string representing an existing file

>   4D input file. Maps to a command-line argument: `-i %s` (position: 0).

> argsa unicode string

>   Additional parameters to the command. Maps to a command-line argument: `%s`.

> base_namea unicode string

>   The rootname that all generated files will have. Maps to a command-line argument: `-o "%s"` (position: 1). (Nipype default value: `randomise`)

> c_thresha float

>   Carry out cluster-based thresholding. Maps to a command-line argument: `-c %.1f`.

> cm_thresha float

>   Carry out cluster-mass-based thresholding. Maps to a command-line argument: `-C %.1f`.

> demeana boolean

>   Demean data temporally before model fitting. Maps to a command-line argument: `-D`.

> design_mata pathlike object or string representing an existing file

>   Design matrix file. Maps to a command-line argument: `-d %s` (position: 2).

> environa dictionary with keys which are a bytes or None or a value of class ‘str’ and with values which are a bytes or None or a value of class ‘str’

>   Environment variables. (Nipype default value: `{}`)

> f_c_thresha float

>   Carry out f cluster thresholding. Maps to a command-line argument: `-F %.2f`.

> f_cm_thresha float

>   Carry out f cluster-mass thresholding. Maps to a command-line argument: `-S %.2f`.

> f_onlya boolean

>   Calculate f-statistics only. Maps to a command-line argument: `--fonly`.

> fcona pathlike object or string representing an existing file

>   F contrasts file. Maps to a command-line argument: `-f %s`.

> maska pathlike object or string representing an existing file

>   Mask image. Maps to a command-line argument: `-m %s`.

> num_perman integer (int or long)

>   Number of permutations (default 5000, set to 0 for exhaustive). Maps to a command-line argument: `-n %d`.

> one_sample_group_meana boolean

>   Perform 1-sample group-mean test instead of generic permutation test. Maps to a command-line argument: `-1`.

> output_type‘NIFTI’ or ‘NIFTI_PAIR’ or ‘NIFTI_GZ’ or ‘NIFTI_PAIR_GZ’

>   FSL output type.

> p_vec_n_dist_filesa boolean

>   Output permutation vector and null distribution text files. Maps to a command-line argument: `-P`.

> raw_stats_imgsa boolean

>   Output raw ( unpermuted ) statistic images. Maps to a command-line argument: `-R`.

> seedan integer (int or long)

>   Specific integer seed for random number generator. Maps to a command-line argument: `--seed=%d`.

> show_info_parallel_modea boolean

>   Print out information required for parallel mode and exit. Maps to a command-line argument: `-Q`.

> show_total_permsa boolean

>   Print out how many unique permutations would be generated and exit. Maps to a command-line argument: `-q`.

> tcona pathlike object or string representing an existing file

>   T contrasts file. Maps to a command-line argument: `-t %s` (position: 3).

> tfcea boolean

>   Carry out Threshold-Free Cluster Enhancement. Maps to a command-line argument: `-T`.

> tfce2Da boolean

>   Carry out Threshold-Free Cluster Enhancement with 2D optimisation. Maps to a command-line argument: `--T2`.

> tfce_Ca float

>   TFCE connectivity (6 or 26; default=6). Maps to a command-line argument: `--tfce_C=%.2f`.

> tfce_Ea float

>   TFCE extent parameter (default=0.5). Maps to a command-line argument: `--tfce_E=%.2f`.

> tfce_Ha float

>   TFCE height parameter (default=2). Maps to a command-line argument: `--tfce_H=%.2f`.

> var_smoothan integer (int or long)

>   Use variance smoothing (std is in mm). Maps to a command-line argument: `-v %d`.

> vox_p_valuesa boolean

>   Output voxelwise (corrected and uncorrected) p-value images. Maps to a command-line argument: `-x`.

> x_block_labelsa pathlike object or string representing an existing file

>   Exchangeability block labels file. Maps to a command-line argument: `-e %s`.

> f_corrected_p_filesa list of items which are a pathlike object or string representing an existing file

>   F contrast FWE (Family-wise error) corrected p values files.

> f_p_filesa list of items which are a pathlike object or string representing an existing file

>   F contrast uncorrected p values files.

> fstat_filesa list of items which are a pathlike object or string representing an existing file

>   F contrast raw statistic.

> t_corrected_p_filesa list of items which are a pathlike object or string representing an existing file

>   T contrast FWE (Family-wise error) corrected p values files.

> t_p_filesa list of items which are a pathlike object or string representing an existing file

>   F contrast uncorrected p values files.

> tstat_filesa list of items which are a pathlike object or string representing an existing file

>   T contrast raw statistic.

## SMM

Link to code

> Bases: FSLCommand

> Wrapped executable: `mm --ld=logdir`.

> Spatial Mixture Modelling. For more detail on the spatial mixture modelling see Mixture Models with Adaptive Spatial Regularisation for Segmentation with an Application to FMRI Data; Woolrich, M., Behrens, T., Beckmann, C., and Smith, S.; IEEE Trans. Medical Imaging, 24(1):1-11, 2005.

> maska pathlike object or string representing an existing file

>   Mask file. Maps to a command-line argument: `--mask="%s"` (position: 1).

> spatial_data_filea pathlike object or string representing an existing file

>   Statistics spatial map. Maps to a command-line argument: `--sdf="%s"` (position: 0).

> argsa unicode string

>   Additional parameters to the command. Maps to a command-line argument: `%s`.

> environa dictionary with keys which are a bytes or None or a value of class ‘str’ and with values which are a bytes or None or a value of class ‘str’

>   Environment variables. (Nipype default value: `{}`)

> no_deactivation_classa boolean

>   Enforces no deactivation class. Maps to a command-line argument: `--zfstatmode` (position: 2).

> output_type‘NIFTI’ or ‘NIFTI_PAIR’ or ‘NIFTI_GZ’ or ‘NIFTI_PAIR_GZ’

>   FSL output type.

> activation_p_map : a pathlike object or string representing an existing file deactivation_p_map : a pathlike object or string representing an existing file null_p_map : a pathlike object or string representing an existing file

## SmoothEstimate

Link to code

> Bases: FSLCommand

> Wrapped executable: `smoothest`.

> Estimates the smoothness of an image

> Examples

>     >>> est = SmoothEstimate()
>     >>> est.inputs.zstat_file = 'zstat1.nii.gz'
>     >>> est.inputs.mask_file = 'mask.nii'
>     >>> est.cmdline
>     'smoothest --mask=mask.nii --zstat=zstat1.nii.gz'

> dofan integer (int or long)

>   Number of degrees of freedom. Maps to a command-line argument: `--dof=%d`. Mutually exclusive with inputs: `zstat_file`.

> mask_filea pathlike object or string representing an existing file

>   Brain mask volume. Maps to a command-line argument: `--mask=%s`.

> argsa unicode string

>   Additional parameters to the command. Maps to a command-line argument: `%s`.

> environa dictionary with keys which are a bytes or None or a value of class ‘str’ and with values which are a bytes or None or a value of class ‘str’

>   Environment variables. (Nipype default value: `{}`)

> output_type‘NIFTI’ or ‘NIFTI_PAIR’ or ‘NIFTI_GZ’ or ‘NIFTI_PAIR_GZ’

>   FSL output type.

> residual_fit_filea pathlike object or string representing an existing file

>   Residual-fit image file. Maps to a command-line argument: `--res=%s`. Requires inputs: `dof`.

> zstat_filea pathlike object or string representing an existing file

>   Zstat image file. Maps to a command-line argument: `--zstat=%s`. Mutually exclusive with inputs: `dof`.

> dlha float

>   Smoothness estimate sqrt(det(Lambda)).

> reselsa float

>   Volume of resel, in voxels, defined as FWHM_x * FWHM_y * FWHM_z.

> volumean integer (int or long)

>   Number of voxels in mask.

> SmoothEstimate.aggregate_outputs(runtime=None, needed_outputs=None)

>   Collate expected outputs and apply output traits validation.

nipype.interfaces.fsl.model.load_template(name)

  Load a template from the model_templates directory

  Parameters

    name (str) – The name of the file to load

  Returns

    template

  Return type

    string.Template