def search_clusters(self, data):
"""This function performs the search for significant clusters.
Uses a class from eegpy.stats.cluster
"""
plotid = 0
for i_ch in range(data[0].shape[2]):
for i_b in range(data[0].shape[3]):
#print i_ch,i_b
cs_data = [d[:, :, i_ch, i_b].T for d in data]
#print len(cs_data), [csd.shape for csd in cs_data]
fs, sct, scp, ct, cp = ClusterSearch1d(
cs_data, num_surrogates=self._num_surrogates).search()
#print "CPM: fs.shape=",fs.shape
#print ct, cp
for i_c in range(len(sct)):
self._clusters.append((i_ch, i_b, sct[i_c], scp[i_c]))
#Do plot if significant cluster found
if len(sct) > 0:
#print "CPM: fs.shape=",fs.shape, fs.dtype
#print "CPM: fs[499:510]", fs[498:510]
p.plot(np.array(fs))
p.title("Channel %i, band %i" % (i_ch, i_b))
for cluster in sct:
p.axvspan(cluster[0], cluster[1], color="y", alpha=0.2)
p.savefig("/tmp/fbpm%03d.png" % plotid)
plotid += 1
p.clf()
def test_DataWithNoClusterFindNoCluster(self):
#arange
cl1d = ClusterSearch1d(self.data_without_cluster, num_surrogates=100)
#act
results = cl1d.search()
#assert
assert len(results[1]) == 0
assert results[4].min() > 0.01
def test_DataWithOneClusterFindOneCluster(self):
#arange
cl1d = ClusterSearch1d(self.data_with_one_cluster, num_surrogates=100)
#act
results = cl1d.search()
cluster = results[1][0]
#assert
assert len(results[1]) == 1
assert cluster[0] > 40
assert cluster[1] < 60
def search_clusters(self, data):
"""This function performs the search for significant clusters.
Uses a class from eegpy.stats.cluster
"""
plotid = 0
print data[0].shape
for i_ch in range(data[0].shape[2]):
for i_b in range(data[0].shape[3]):
#print i_ch,i_b
cs_data = [d[:, :, i_ch, i_b].T for d in data]
#print len(cs_data), [csd.shape for csd in cs_data]
fs, sct, scp, ct, cp = ClusterSearch1d(
cs_data, num_surrogates=self._num_surrogates).search()
#print "CPM: fs.shape=",fs.shape
#print ct, cp
for i_c in range(len(sct)):
self._clusters.append((i_ch, i_b, sct[i_c], scp[i_c]))
def test_Cluster1dForNegativeNumberOfSurrogates(self):
cl1d = ClusterSearch1d(self.data_with_one_cluster[0],
num_surrogates=-10)
def test_Cluster1dForZeroSurrogates(self):
cl1d = ClusterSearch1d(self.data_with_one_cluster[0], num_surrogates=0)
def test_Cluster1dFor1dArrays(self):
data = [d[:, 0] for d in self.data_with_one_cluster]
cl1d = ClusterSearch1d(data)
def test_Cluster1dForArrayListNotAList(self):
data = self.data_with_one_cluster[0]
cl1d = ClusterSearch1d(data)