pyhrf.ui.analyser_ui module¶

class pyhrf.ui.analyser_ui.FMRIAnalyser(outputPrefix='', roiAverage=False, pass_error=True, gzip_outputs=False)¶

Bases: pyhrf.xmlio.Initable

P_OUTPUT_PREFIX = 'outputPrefix'¶

P_ROI_AVERAGE = 'averageRoiBold'¶

analyse(data, output_dir=None)¶

Launch the wrapped analyser onto the given data

Parameters:	data (FmriData) – the input fMRI data set (there may be multi parcels) output_dir (str) – the path where to store parcel-specific fMRI data sets (after splitting according to the parcellation mask)
Returns:	a list of analysis results -> (list of tuple(FmriData, None|output of analyse_roi, str)) = (list of tuple(parcel data, analysis results, analysis report)) See method analyse_roi_wrap

analyse_roi(roiData)¶

analyse_roi_wrap(roiData)¶

Wrap the analyse_roi method to catch potential exception

analyse_roi_wrap_bak(roiData)¶

clean_output_files(output_dir)¶

enable_draft_testing()¶

filter_crashed_results(results)¶

get_label()¶

joinOutputs(cuboids, roiIds, mappers)¶

make_outputs_multi_subjects(data_rois, irois, all_outputs, targetAxes, ext, meta_data, output_dir)¶

make_outputs_single_subject(data_rois, irois, all_outputs, targetAxes, ext, meta_data, output_dir)¶

outputResults(results, output_dir, filter='.\\A')¶

Return: a tuple (dictionary of outputs, output file names)

outputResults_back_compat(results, output_dir, filter='.\\A')¶

parametersComments = {'averageRoiBold': 'Average BOLD signals within each ROI before analysis.', 'outputPrefix': 'Tag to prefix every output name'}¶

parametersToShow = ['averageRoiBold', 'outputPrefix']¶

set_gzip_outputs(gzip_outputs)¶

set_pass_errors(pass_error)¶

split_data(fdata, output_dir=None)¶