def test_zmap(self):
# This is not in R, so tested by using:
# (testcase[i]-mean(testcase,axis=0)) / sqrt(var(testcase)*3/4)
y = mstats.zmap(self.testcase, self.testcase)
desired_unmaskedvals = ([-1.3416407864999, -0.44721359549996,
0.44721359549996, 1.3416407864999])
assert_array_almost_equal(desired_unmaskedvals,
y.data[y.mask == False], decimal=12)
def test_zmap(self):
# This is not in R, so tested by using:
# (testcase[i]-mean(testcase,axis=0)) / sqrt(var(testcase)*3/4)
y = mstats.zmap(self.testcase, self.testcase)
desired_unmaskedvals = ([-1.3416407864999, -0.44721359549996,
0.44721359549996, 1.3416407864999])
assert_array_almost_equal(desired_unmaskedvals,
y.data[y.mask == False], decimal=12)
def standardize_pow_mat(stripped_pow_mat, events, sessions, outsample_session=None, outsample_list=None):
zpow_mat = np.array(stripped_pow_mat)
outsample_mask = None
for session in sessions:
sess_event_mask = (events.session == session)
if session == outsample_session:
outsample_mask = (events.list == outsample_list) & sess_event_mask
insample_mask = ~outsample_mask & sess_event_mask
zpow_mat[outsample_mask] = zmap(zpow_mat[outsample_mask], zpow_mat[insample_mask], axis=0, ddof=1)
zpow_mat[insample_mask] = zscore(zpow_mat[insample_mask], axis=0, ddof=1)
else:
zpow_mat[sess_event_mask] = zscore(zpow_mat[sess_event_mask], axis=0, ddof=1)
return zpow_mat, outsample_mask
def standardize_pow_mat(stripped_pow_mat,
events,
sessions,
outsample_session=None,
outsample_list=None):
zpow_mat = np.array(stripped_pow_mat)
outsample_mask = None
for session in sessions:
sess_event_mask = (events.session == session)
if session == outsample_session:
outsample_mask = (events.list == outsample_list) & sess_event_mask
insample_mask = ~outsample_mask & sess_event_mask
zpow_mat[outsample_mask] = zmap(zpow_mat[outsample_mask],
zpow_mat[insample_mask],
axis=0,
ddof=1)
zpow_mat[insample_mask] = zscore(zpow_mat[insample_mask],
axis=0,
ddof=1)
else:
zpow_mat[sess_event_mask] = zscore(zpow_mat[sess_event_mask],
axis=0,
ddof=1)
return zpow_mat, outsample_mask