nireports.interfaces.nuisance module

Screening nuisance signals.

class nireports.interfaces.nuisance.CompCorVariancePlot(from_file=None, resource_monitor=None, **inputs)[source]

Bases: SimpleInterface

Plot the number of components necessary to explain the specified levels of variance.

Mandatory Inputs:

metadata_files (a list of items which are a pathlike object or string representing an existing file) – List of files containing component metadata.

Optional Inputs:

  • metadata_sources (a list of items which are a string) – List of names of decompositions (e.g., aCompCor, tCompCor) yielding the arguments in metadata_files.

  • out_file (a pathlike object or string representing a file or None) – Path to save plot. (Nipype default value: None)

  • variance_thresholds (a tuple of the form: (a float, a float, a float)) – Levels of explained variance to include in plot. (Nipype default value: (0.5, 0.7, 0.9))

Outputs:

out_file (a pathlike object or string representing an existing file) – Path to saved plot.

class nireports.interfaces.nuisance.ConfoundsCorrelationPlot(from_file=None, resource_monitor=None, **inputs)[source]

Bases: SimpleInterface

Plot the correlation among confound regressors.

Mandatory Inputs:

confounds_file (a pathlike object or string representing an existing file) – File containing confound regressors.

Optional Inputs:

  • columns (a list of items which are a string) – Filter out all regressors not found in this list.

  • ignore_initial_volumes (an integer) – Number of non-steady-state volumes at the beginning of the scan to ignore. (Nipype default value: 0)

  • max_dim (an integer) – Maximum number of regressors to include in plot. Regressors with highest magnitude of correlation with reference_column will be selected. (Nipype default value: 20)

  • out_file (a pathlike object or string representing a file or None) – Path to save plot. (Nipype default value: None)

  • reference_column (a string) – Column in the confound file for which all correlation magnitudes should be ranked and plotted. (Nipype default value: global_signal)

Outputs:

out_file (a pathlike object or string representing an existing file) – Path to saved plot.

class nireports.interfaces.nuisance.RaincloudPlot(from_file=None, resource_monitor=None, **inputs)[source]

Bases: SimpleInterface

Plot a raincloud of values.

Mandatory Inputs:

  • data_file (a pathlike object or string representing an existing file) – File containing the data.

  • feature (a string) – Feature of interest.

  • group_name (a string) – Group name of interest.

Optional Inputs:

  • density (a boolean) – True to plot the density. (Nipype default value: True)

  • limit_offset (a float) – Offset to plot the values over/under the upper/lower limit values. (Nipype default value: None)

  • lower_limit_color (a string) – Color name to represent values under lower_limit_value. (Nipype default value: gray)

  • lower_limit_value (a float) – (Nipype default value: None)

  • mark_nans (a boolean) – True to plot NaNs as dots. nans_values must be provided if True. (Nipype default value: True)

  • nans_color (a string) – Color name to represent NaN values. (Nipype default value: black)

  • nans_value (a float) – Value to use for NaN values`. (Nipype default value: None)

  • orient (a string) – Orientation. (Nipype default value: v)

  • out_file (a pathlike object or string representing a file or None) – Path to save plot. (Nipype default value: None)

  • palette (a string) – Color palette name. (Nipype default value: Set2)

  • upper_limit_color (a string) – Lower limit value under which any value in the data will be styled with a different style. (Nipype default value: gray)

  • upper_limit_value (a float) – Upper limit value over which any value in the data will be styled with a different style. (Nipype default value: None)

Outputs:

out_file (a pathlike object or string representing an existing file) – Path to saved plot.