visbrain.objects.SourceObj.analyse_sources¶

SourceObj.analyse_sources(roi_obj='talairach', replace_bad=True, bad_patterns=[-1, 'undefined', 'None'], distance=None, replace_with='Not found', keep_only=None)[source][source]¶

Analyse sources using Region of interest (ROI).

This method can be used to identify in which structure is located a source.

Parameters:

Parameters:	roi_obj : string/list \| ‘talairach’ The ROI object to use. Use either ‘talairach’, ‘brodmann’ or ‘aal’ to use a predefined ROI template. Otherwise, use a RoiObj object or a list of RoiObj. replace_bad : bool \| True Replace bad values (True) or not (False). bad_patterns : list \| [-1, ‘undefined’, ‘None’] Bad patterns to replace if replace_bad is True. replace_with : string \| ‘Not found’ Replace bad patterns with this string. keep_only : list \| None List of string patterns to keep only sources that match.
Returns:	df : pandas.DataFrames A Pandas DataFrame or a list of DataFrames if roi_obj is a list.

roi_obj : string/list | ‘talairach’: The ROI object to use. Use either ‘talairach’, ‘brodmann’ or ‘aal’ to use a predefined ROI template. Otherwise, use a RoiObj object or a list of RoiObj.
replace_bad : bool | True: Replace bad values (True) or not (False).
bad_patterns : list | [-1, ‘undefined’, ‘None’]: Bad patterns to replace if replace_bad is True.
replace_with : string | ‘Not found’: Replace bad patterns with this string.
keep_only : list | None: List of string patterns to keep only sources that match.

Returns:

df : pandas.DataFrames: A Pandas DataFrame or a list of DataFrames if roi_obj is a list.