def __init__(self, vox_stat, vox_map, vox_stat_ranking,
max_stat_dist, min_stat_dist,
snpm_ptail_clusters, snpm_ptail_nulls,
snpm_ntail_clusters, snpm_ntail_nulls):
"""
Parameters
----------
All TimeFreqSnPMResults arguments, plus
snpm_ptail_clusters: list
List of ScoredStatClusters, for each (t,f) point
snpm_ptail_nulls: ndarray
Array of positive-tail null distributions for each (t,f) point
snpm_ntail_clusters: list
List of ScoredStatClusters, for each (t,f) point
snpm_ntail_nulls: ndarray
Array of negative-tail null distributions for each (t,f) point
"""
super(TimeFreqSnPMClusters, self).__init__(
vox_stat, vox_map, vox_stat_ranking,
max_stat_dist, min_stat_dist
)
t, f = self.t.shape[1:]
assert t*f==len(snpm_ptail_clusters) or \
(t==len(snpm_ptail_clusters) and \
f==len(snpm_ptail_clusters[0])), \
'Not enough pos-tail clusters for every time-freq point'
assert t*f==len(snpm_ntail_clusters) or \
(t==len(snpm_ntail_clusters) and \
f==len(snpm_ntail_clusters[0])), \
'Not enough neg-tail clusters for every time-freq point'
self.ptail_clusters = tablify_list(snpm_ptail_clusters, t, f)
self.ptail_nulls = snpm_ptail_nulls
self.ntail_clusters = tablify_list(snpm_ntail_clusters, t, f)
self.ntail_nulls = snpm_ntail_nulls
def pscore_clusters(self, tail, corrected_dims=(), pooled_dims=()):
"""
Returns
-------
scores
A list of p values for each list of clusters (at each (t,f) point)
scored against the null
"""
if len(corrected_dims) or len(pooled_dims):
raise NotImplementedError(
'Not yet combining time-freq dimensions for correction/pooling'
)
pvalues = []
if tail.lower()=='pos':
clusters = self.ptail_clusters
nulls = np.sort(self.ptail_nulls, axis=0)
else:
clusters = self.ntail_clusters
nulls = np.sort(self.ntail_nulls, axis=0)
n_perm = float(nulls.shape[0])
nt, nf = nulls.shape[1:]
for t in xrange(nt):
for f in xrange(nf):
if not clusters[t][f]:
pvalues.append([])
continue
ntf = nulls[:,t,f]
wscores = [ci.wscore for ci in clusters[t][f]]
pvalues.append(
1.0 - ntf.searchsorted(wscores, side='left')/n_perm
)
return tablify_list(pvalues, nt, nf)
