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Fixed bug for dimension of the pattern spectrum and set default parameter pvalue_spectrum to None in concept_output_to_patterns #149

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merged 2 commits into from
Mar 22, 2018
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Fixed bug for dimension of the pattern spectrum and set default parameter pvalue_spectrum to None in concept_output_to_patterns #149

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8d1b67c
Fixed bug for dimension of the pattern spectrum (previously returned …
pietroquaglio Mar 16, 2018
7b8f9f1
Fixed outdated comment
pietroquaglio Mar 22, 2018
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24 changes: 13 additions & 11 deletions elephant/spade.py
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Original file line number Diff line number Diff line change
Expand Up @@ -359,8 +359,9 @@ def spade(data, binsize, winlen, min_spikes=2, min_occ=2, min_neu=1,
if n_surr == 0:
pv_spec = []
# Transfroming concepts to dictionary containing pattern infos
output['patterns'] = concept_output_to_patterns(concepts, pv_spec,
output['patterns'] = concept_output_to_patterns(concepts,
winlen, binsize,
pv_spec,
data[0].t_start)
else:
output['patterns'] = concepts
Expand Down Expand Up @@ -671,13 +672,13 @@ def _fpgrowth(transactions, min_c=2, min_z=2, max_z=None,
np.prod(rel_matrix[:, intent], axis=1) == 1)[0])
concepts.append((intent, extent))
if report == '#':
spec_matrix[len(intent), supp] += 1
spec_matrix[len(intent) - 1, supp - 1] += 1
del fpgrowth_output
# Computing spectrum
if report == '#':
del concepts
for (z, c) in np.transpose(np.where(spec_matrix != 0)):
spectrum.append((z, c, int(spec_matrix[z, c])))
spectrum.append((z + 1, c + 1, int(spec_matrix[z, c])))
del spec_matrix
return spectrum
else:
Expand Down Expand Up @@ -776,13 +777,13 @@ def _fast_fca(context, min_c=2, min_z=2, max_z=None,
concepts.append((intent, extent))
# computing spectrum
if report == '#':
spec_matrix[len(intent), len(extent)] += 1
spec_matrix[len(intent) - 1, len(extent) - 1] += 1
if report != '#':
return concepts
else:
# returning spectrum
for (z, c) in np.transpose(np.where(spec_matrix != 0)):
spectrum.append((z, c, int(spec_matrix[z, c])))
spectrum.append((z + 1, c + 1, int(spec_matrix[z, c])))
return spectrum


Expand Down Expand Up @@ -1556,7 +1557,7 @@ def pattern_set_reduction(concepts, excluded, winlen, h=0, k=0, l=0, min_spikes=
return [p for i, p in enumerate(concepts) if selected[i]]


def concept_output_to_patterns(concepts, pvalue_spectrum, winlen, binsize,
def concept_output_to_patterns(concepts, winlen, binsize, pvalue_spectrum=None,
t_start=0 * pq.ms):
'''
Construction of dictionaries containing all the information about a pattern
Expand All @@ -1568,12 +1569,13 @@ def concept_output_to_patterns(concepts, pvalue_spectrum, winlen, binsize,
Each element of the tuple correspond to a pattern and it is itself a
tuple consisting of:
((spikes in the pattern), (occurrences of the patterns))
pvalue_spectrum: tuple
Contains a tuple of signatures and the corresponding p-value
winlen: int
Length (in bins) of the sliding window used for the analysis
t_start: int
t_start (in bins) of the analyzed spike trains
pvalue_spectrum: None or tuple
Contains a tuple of signatures and the corresponding p-value. If equal
to None all the pvalues are set to -1
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In the comment below you write:

If an empty list is given in input to the pval spectrum the pvalue is set to -1 (pvalue spectrum not available)

but here you mention that all pvalues are set to -1. It doesn't match with the documentation here. I also see that the dictionary will have afterwards only one entry, -1

output_dict['pvalue'] = -1

t_start: Quantity
t_start of the analyzed spike trains

Returns
--------
Expand Down Expand Up @@ -1617,7 +1619,7 @@ def concept_output_to_patterns(concepts, pvalue_spectrum, winlen, binsize,
output_dict['signature'] = (len(conc[0]), len(conc[1]))
# If an empty list is given in input to the pval spectrum the pvalue
# is set to -1 (pvalue spectrum not available)
if len(pvalue_spectrum) == 0:
if len(pvalue_spectrum) == None:
output_dict['pvalue'] = -1
# p-value assigned to the pattern from the pvalue spectrum
else:
Expand Down
8 changes: 8 additions & 0 deletions elephant/test/test_spade.py
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Original file line number Diff line number Diff line change
Expand Up @@ -116,6 +116,14 @@ def test_spade_cpp(self):
# check the lags
assert_array_equal(lags_cpp, [np.array([0]*(self.n_neu - 1))])

# Testing spectrum cpp
def test_spade_cpp(self):
# Computing Spectrum
spectrum_cpp = spade.concepts_mining(self.cpp, self.binsize,
1,report='#')[0]
# Check spectrum
assert_array_equal(spectrum_cpp, [(len(self.cpp), len(self.cpp[0]), 1)])

# Testing with multiple patterns input
def test_spade_msip(self):
output_msip = spade.spade(self.msip, self.binsize,
Expand Down