Skip to content

Clip small negative values in van_rossum_distance before np.sqrt #680

New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

Sign up for GitHub

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Open
wants to merge 1 commit into
base: master
Choose a base branch
from
+22 −4
Open

Clip small negative values in van_rossum_distance before np.sqrt #680

Show file tree
Hide file tree
Changes from all commits
Commits
Show all changes
1 commit
Select commit
File filter

Filter by extension

Filter by extension
Conversations
Failed to load comments.
Loading
Jump to
Jump to file
Failed to load files.
Loading
Diff view
Diff view
11 changes: 10 additions & 1 deletion elephant/spike_train_dissimilarity.py
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -21,7 +21,7 @@
"""

from __future__ import division, print_function, unicode_literals

import warnings
import numpy as np
import quantities as pq
from neo.core import SpikeTrain
Expand Down Expand Up @@ -363,6 +363,15 @@ def van_rossum_distance(spiketrains, time_constant=1.0 * pq.s, sort=True):
for i, j in np.ndindex(k_dist.shape):
vr_dist[i, j] = (
k_dist[i, i] + k_dist[j, j] - k_dist[i, j] - k_dist[j, i])

# Clip small negative values
if np.any(vr_dist < 0):
warnings.warn(
"van_rossum_distance: very small negative values encountered "
"(likely due to floating point error); "
"setting them to 0", RuntimeWarning)
vr_dist = np.maximum(vr_dist, 0.0)

return np.sqrt(vr_dist)


Expand Down
15 changes: 12 additions & 3 deletions elephant/test/test_spike_train_dissimilarity.py
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -14,7 +14,7 @@
import elephant.kernels as kernels
from elephant.spike_train_generation import StationaryPoissonProcess
import elephant.spike_train_dissimilarity as stds

import warnings
from elephant.datasets import download_datasets


Expand Down Expand Up @@ -47,6 +47,7 @@ def setUp(self):
self.st23 = StationaryPoissonProcess(rate=30 * Hz, t_start=0 * ms,
t_stop=1000 * ms
).generate_spiketrain()
self.st24 = SpikeTrain([0.1782, 0.2286, 0.2804, 0.4972, 0.5504], units='s',t_stop=4.0)
self.rd_st_list = [self.st21, self.st22, self.st23]
self.st31 = SpikeTrain([12.0], units='ms', t_stop=1000.0)
self.st32 = SpikeTrain([12.0, 12.0], units='ms', t_stop=1000.0)
Expand All @@ -73,7 +74,7 @@ def setUp(self):
self.tau7 = 0.01 * s
self.q7 = 1.0 / self.tau7
self.t = np.linspace(0, 200, 20000001) * ms

self.tau8 = 0.1 * s
def test_wrong_input(self):
self.assertRaises(TypeError, stds.victor_purpura_distance,
[self.array1, self.array2], self.q3)
Expand Down Expand Up @@ -599,7 +600,15 @@ def test_van_rossum_distance(self):
self.assertEqual(stds.van_rossum_distance(
[self.st21], self.tau3)[0, 0], 0)
self.assertEqual(len(stds.van_rossum_distance([], self.tau3)), 0)


# Check small negative values edge case
with warnings.catch_warnings(record='True') as w:
warnings.simplefilter("always")
result = stds.van_rossum_distance([self.st24, self.st24], self.tau8)
self.assertTrue(any("very small negative values encountered" in str(warn.message)
for warn in w))
self.assertEqual(result[0,1], 0.0)
self.assertFalse(np.any(np.isnan(result)))

if __name__ == '__main__':
unittest.main()
Loading