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 (-) – the input fMRI data set (there may be multi parcels)
• output_dir (-) – 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)