surface_plot.cluster_plot

Functions

boxplot(data1, data2, slm, outdir, g1_name, ...)

Generates and saves boxplots for significant clusters in brain surface data.

correlation_plot(slm, dep_data, indep_data, ...)

Parameters slm dict['left', 'right'] Dictionary with keys "left" and "right", containing results from brainstat SLM dep_data pd.DataFrame or dict{'left', 'right'} If the independent variable is a "regular" variable (e.g. age, MMSE etc.) dep_data should be a 1D pd.Dataframe with dep_name as column name and ids as indices. If the independent variable is another surface, it should be similar to indep_data, i.e.: Dictionary with keys "left" and "right", containing surface data of the dependent variable for left and right hemisphere indep_data dict{'left': pd.DataFrame, 'right': pd.DataFrame} Dataframe of surface data Dictionary with keys "left" and "right", containing surface data of the independent variable for left and right hemisphere indep_name str Name of independent surface data outdir str Location of ouputs hue dataframe | None Dataframe with subject ids as index and group as column alpha float | 0.05 Corrected p-value threshold on cluster-level (family wise error rate) clobber Boolean | False If true, existing files will be overwritten