nipype_lss.py

from nipype.interfaces.base import Bunch
from nipype.algorithms import modelgen
from copy import deepcopy


def lss(bunch_list):
    """Takes input Bunch list and returns list of Bunch lists with LSS regressors.
    """
    all_infos = []
    other_items = ['durations', 'amplitudes',
                   'regressors', 'regressor_names']

    # Take a list of Bunches, loop through runs
    for i_run, run in enumerate(bunch_list):
        # Grab conditions first to get number
        conditions = run.get('conditions')
        for i_cond, cond in enumerate(conditions):
            # Loop through other items, which may be lists or Nones
            onsets = run.get('onsets')
            cond_onsets = onsets[i_cond]
            for trial in range(len(cond_onsets)):
                trial_name = '{0}_{1:04d}'.format(cond, trial)
                trial_dict = {}
                for item in other_items:            
                    item_vals = run.get(item, None)
                    if item_vals is not None:
                        cond_vals = item_vals[i_cond]
                        if len(cond_vals) == len(cond_onsets):
                            val = cond_vals[trial]

                            new_vals = deepcopy(item_vals)
                            new_vals[i_cond].pop(trial)
                            trial_dict[item] = [[item_vals[i_cond][trial]]] + new_vals
                        else:
                            val = cond_vals[0]
                            trial_dict[item] = [[val]] + item_vals
                    else:
                        trial_dict[item] = item_vals
                trial_dict['conditions'] = [trial_name] + conditions
                new_onsets = deepcopy(onsets)
                new_onsets[i_cond].pop(trial)
                trial_dict['onsets'] = [[onsets[i_cond][trial]]] + new_onsets
                trial_info = deepcopy(bunch_list)
                trial_info[i_run] = Bunch(trial_dict)
                all_infos.append(trial_info)
    return all_infos

s = modelgen.SpecifyModel()
s.inputs.input_units = 'secs'
s.inputs.functional_runs = ['functional2.nii', 'functional3.nii']
s.inputs.time_repetition = 6
s.inputs.high_pass_filter_cutoff = 128.
evs_run2 = Bunch(conditions=['cond1', 'cond2'],
                 onsets=[[2, 50, 100, 180], [3, 51, 101, 116]],
                 durations=[[1, 2, 3, 4], [1, 2, 3, 4]])
evs_run3 = Bunch(conditions=['cond1'], onsets=[[30, 40, 100, 150]], durations=[[1]])
s.inputs.subject_info = [evs_run2, evs_run3]
list_of_bunch_lists = lss(s.inputs.subject_info)