API

ddmra.workflows: Common workflows

Perform distance-dependent motion-related artifact analyses.

ddmra.workflows.run_analyses(files, qc[, ...])	Run scrubbing, high-low motion, and QCRSFC analyses.
ddmra.workflows.run_pipeline_comparison(...)	Run DDMRA analyses for multiple processing pipelines.

ddmra.analysis: Analysis functions

Perform distance-dependent motion-related artifact analyses.

ddmra.analysis.scrubbing_analysis(qc_values, ...)	Perform Power scrubbing analysis.
ddmra.analysis.highlow_analysis(mean_qcs, ...)	Perform high-low QC analysis.
ddmra.analysis.qcrsfc_analysis(mean_qcs, ...)	Perform quality-control resting-state functional connectivity analysis.
ddmra.analysis.qcrsfc_summary(mean_qcs, ...)	Compute descriptive QC-FC benchmark summaries.

ddmra.plotting: Figure generation functions

Generate distance-dependent motion-related artifact plots.

The annotated p-values compare the observed smoothing-curve intercept at 35 mm and the 35-to-100 mm slope against permutation-derived null smoothing curves. Edgewise ranks, when written by the workflow, are diagnostics and are not used as inferential p-values.

ddmra.plotting.plot_analysis(data_points, ...)	Generate plot for a DDMRA analysis.
ddmra.plotting.plot_results(in_dir)	Plot the available analyses from a workflow run and save to a file.

ddmra.filter: Filtering functions

Functions for the Earl filter.

ddmra.filter.filter_earl(motpars, t_r[, ...])	Apply Earl filter to motion parameters.
ddmra.filter.respiration_iirnotch(TR_in_sec)	Calculate filter parameters for respiration filter.

ddmra.utils: Miscellaneous utility functions

Miscellaneous utility functions for the DDMRA package.

ddmra.utils.get_val(x_arr, y_arr, x_val)	Perform interpolation to get value from y_arr at index of x_val based on x_arr.
ddmra.utils.null_to_p(test_value, null_array)	Return p-value for test value(s) against null array.
ddmra.utils.fast_pearson(X, y)	Fast correlations between y and each row of X, for QC-RSFC.
ddmra.utils.get_fd_power(motion[, order, ...])	Calculate Framewise Displacement (Power version).
ddmra.utils.moving_average(values, window)	Calculate running average along values array.
ddmra.utils.average_across_distances(values, ...)
ddmra.utils.assess_significance(curve, ...)	Measure significance of smoothing curve against null curves.