[med-svn] [python-mne] 136/376: fix one more bug and make function _pval_from_histogram more readable
Yaroslav Halchenko
debian at onerussian.com
Fri Nov 27 17:22:21 UTC 2015
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yoh pushed a commit to annotated tag v0.1
in repository python-mne.
commit 59b801f0c2de8f3f1d515923917aedf1d34b3c0e
Author: Alexandre Gramfort <alexandre.gramfort at inria.fr>
Date: Tue Mar 15 13:51:53 2011 -0400
fix one more bug and make function _pval_from_histogram more readable
---
examples/stats/plot_cluster_1samp_test_time_frequency.py | 6 +++---
mne/stats/cluster_level.py | 13 +++++--------
2 files changed, 8 insertions(+), 11 deletions(-)
diff --git a/examples/stats/plot_cluster_1samp_test_time_frequency.py b/examples/stats/plot_cluster_1samp_test_time_frequency.py
index 711c187..39fc9c8 100644
--- a/examples/stats/plot_cluster_1samp_test_time_frequency.py
+++ b/examples/stats/plot_cluster_1samp_test_time_frequency.py
@@ -75,10 +75,10 @@ epochs_power /= np.mean(epochs_power[:,:,times < 0], axis=2)[:,:,None]
epochs_power -= 1.0
###############################################################################
# Compute statistic
-threshold = 6.0
+threshold = 5.0
T_obs, clusters, cluster_p_values, H0 = \
permutation_cluster_t_test(epochs_power,
- n_permutations=100, threshold=threshold, tail=0)
+ n_permutations=100, threshold=threshold, tail=1)
###############################################################################
# View time-frequency plots
@@ -92,7 +92,7 @@ pl.title('Evoked response (%s)' % ch_name)
pl.xlabel('time (ms)')
pl.ylabel('Magnetic Field (fT/cm)')
pl.xlim(times[0], times[-1])
-pl.ylim(-100, 200)
+pl.ylim(-100, 250)
pl.subplot(2, 1, 2)
diff --git a/mne/stats/cluster_level.py b/mne/stats/cluster_level.py
index 452c85c..599da57 100644
--- a/mne/stats/cluster_level.py
+++ b/mne/stats/cluster_level.py
@@ -8,7 +8,7 @@
import numpy as np
from scipy import ndimage
-from scipy.stats import percentileofscore, ttest_1samp
+from scipy.stats import ttest_1samp
from .parametric import f_oneway
@@ -72,17 +72,14 @@ def _pval_from_histogram(T, H0, tail):
if not tail in [-1, 0, 1]:
raise ValueError('invalid tail parameter')
- pval = np.array([percentileofscore(H0, t) for t in T])
-
# from pct to fraction
if tail == -1: # up tail
- pval = pval / 100.0
+ pval = np.array([np.mean(H0 <= t) for t in T])
elif tail == 1: # low tail
- pval = (100.0 - pval) / 100.0
+ pval = np.array([np.mean(H0 >= t) for t in T])
elif tail == 0: # both tails
- pval = 100.0 - pval
- pval += np.array([percentileofscore(H0, -t) for t in T])
- pval /= 100.0
+ pval = np.array([np.mean(H0 >= abs(t)) for t in T])
+ pval += np.array([np.mean(H0 <= -abs(t)) for t in T])
return pval
--
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