74dae883a6f0bb31f55b8c1bd426a832b429ff4a,brainiak/utils/fmrisim.py,,generate_stimfunction,#Any#Any#Any#Any#Any#Any#,378

Before Change

            onset_counter])) * temporal_resolution)

        // For the appropriate number of indexes and duration, make this value 1
        idx_n = round(event_durations[onset_counter] * temporal_resolution)
        stimfunction[onset_idx:offset_idx] = [weights[onset_counter]] * idx_n

    // Shorten the data if it"s too long
    if len(stimfunction) > total_time * temporal_resolution:
        stimfunction = stimfunction[0:int(total_time * temporal_resolution)]

After Change

    // Generate the time course as empty, each element is a millisecond by
    // default
    stimfunction = np.zeros((int(round(total_time * temporal_resolution)), 1))

    // Cycle through the onsets
    for onset_counter in list(range(len(onsets))):
        // Adjust for the resolution

Instances