exp_pips_rme_min.py

import io
import json
import numpy as np
from expyfun.io import read_hdf5
from expyfun.analyze import decimals_to_binary

# make the blank trigger pulses
fs = 44100.
trig_on_dur = 10e-3
trig_pause_dur = 10e-3
trig_on_len = int(fs * trig_on_dur)
trig_pause_len = int(fs * trig_pause_dur)
tube_len_meters = 11. * 25.4 * 1e-3
tube_delay = tube_len_meters / 343.
tube_delay_len = int(np.round(tube_delay * fs))
run_file = 'CALIBRATION'
with io.open('CALIBRATION', 'r', encoding='utf-8-sig') as fid:
    runs = json.load(fid)
n_run_bits = np.maximum(1, int(np.ceil(np.log2(len(runs)))))
data = dict()
data_fn = [r['fn_stim'] for r in runs]
print('Loading data for %i runs...' % len(runs)),
for r in runs:
    if r['fn_stim'] not in data.keys():
        data[r['fn_stim']] = read_hdf5(r['fn_stim'])
print('%i unique data files loaded.' % len(data))
fs = data[data_fn[0]]['fs']
n_tok_bits = int(np.ceil(np.log2(np.max([d['x'].shape[0]
                                         for d in data.values()]))))


trig_blanks = np.tile(np.atleast_2d(
    np.concatenate((np.ones(trig_on_len), np.zeros(trig_pause_len)))),
    [1 + n_run_bits + n_tok_bits, 1])

# write the stamp INCLUDING THE 1 TRIGGER
ri, tok = 1, 2  # XXX arbitrary values here, in practice span some range and depend on the trial
stamp = [1]
stamp += [1 << (b + 2) for b in
          decimals_to_binary([ri, tok], [n_run_bits, n_tok_bits])]
stamp = [b << 8 for b in stamp]
trig = np.ravel(np.atleast_2d(stamp).T * trig_blanks)