strfspeed.py

from time import time
import numpy as np
import mne

mne.cuda.init_cuda(ignore_config=True, verbose=True)
rng = np.random.RandomState(0)

# Stimulus -> Neural model
sfreq = 10e3
tmin, tmax = -150e-3, 250e-3
n_in = 2
n_samp = int(round(60 * sfreq))
n_epochs = 60


def run():
    print('Running %2s in, %d - %d ms; %0.1f min epochs; %6.1f Hz; %2d epochs'
          % (n_in, tmin * 1000, tmax * 1000, n_samp / (60 * sfreq),
             sfreq, n_epochs))

    X = rng.randn(n_samp, n_epochs, n_in)
    for n_out in (2, 60):
        y = rng.randn(n_samp, n_epochs, n_out)
        for n_jobs in (1, 'cuda'):
            print('  n_out=%2d n_jobs=%4s: ' % (n_out, n_jobs), end='')
            rf = mne.decoding.ReceptiveField(tmin, tmax, sfreq, n_jobs=n_jobs,
                                             edge_correction=False,
                                             verbose=True)
            t0 = time()
            rf.fit(X, y)
            print('%0.2f min' % ((time() - t0) / 60.,))