def save_distribs(lendistribname=ld_name):
errorfield = 'TrialError'
tnumfield = 'trial_type'
eyefield = 'eyepos'
os.chdir('data')
d = u.load_separate(['.'], 'bootsy-bhvit-run[0-9]*.mat')
ed = d[d[errorfield] == 0]
os.chdir('..')
fn, ff, nn, nf = 7, 8, 9, 10
lens, looks, s_bs, s_es = es.get_fixtimes(ed, [fn, ff, nn, nf],
postthr='fixation_off')
observed_lendistrib = np.concatenate(lens[nf] + lens[fn], axis=0)
cp.dump(observed_lendistrib, open(lendistribname, 'wb'))
return observed_lendistrib
def produce_eyes_plot_nums(resorted=True, save=False, fname=None):
if resorted:
pattern = 'bootsy-bhvit-rs-run[0-9]*.mat'
else:
pattern = 'bootsy-bhvit-run[0-9]*.mat'
data = load_separate(['./data/'], pattern)
data = data[data[error_field] == 0]
datavplt = get_only_vplt(data)
lc, xs = get_bias_tc(datavplt, winsize=1, winstep=1)
lens, looks, s_bs, s_es = es.get_fixtimes(datavplt, [7, 8, 9, 10])
for i, tt in enumerate(lens.keys()):
cond_lens = np.concatenate(lens[tt], axis=1)
if i == 0:
all_lens = cond_lens
else:
all_lens = np.concatenate((all_lens, cond_lens), axis=0)
plot_looks(lc, xs)
if save and fname is not None:
np.savez(open(fname, 'wb'), xs=xs, look_course=lc, fix_lens=all_lens)
return lc, xs, all_lens