[med-svn] [python-mne] 261/353: TST : better tests in stim artifact

Yaroslav Halchenko debian at onerussian.com
Fri Nov 27 17:25:11 UTC 2015


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yoh pushed a commit to tag 0.4
in repository python-mne.

commit a3d41d41ee1907ec51cc0da2fe054c45b25f2c3a
Author: Daniel Strohmeier <daniel.strohmeier at googlemail.com>
Date:   Thu Jul 12 19:00:41 2012 +0200

    TST : better tests in stim artifact
---
 mne/artifacts/stim.py            |  2 +-
 mne/artifacts/tests/test_stim.py | 13 ++++++++++++-
 2 files changed, 13 insertions(+), 2 deletions(-)

diff --git a/mne/artifacts/stim.py b/mne/artifacts/stim.py
index 01af320..0bdabcb 100644
--- a/mne/artifacts/stim.py
+++ b/mne/artifacts/stim.py
@@ -5,7 +5,7 @@ from scipy import signal, interpolate
 def eliminate_stim_artifact(raw, events, event_id, tmin=-0.005,
                                 tmax=0.01, mode='linear'):
     """Eliminates stimulations artifacts from raw data
-     
+
     The raw object will be modified in place (no copy)
 
     Parameters
diff --git a/mne/artifacts/tests/test_stim.py b/mne/artifacts/tests/test_stim.py
index 8cbdc85..3a6827d 100644
--- a/mne/artifacts/tests/test_stim.py
+++ b/mne/artifacts/tests/test_stim.py
@@ -1,4 +1,5 @@
 import os.path as op
+import numpy as np
 
 from nose.tools import assert_true
 from numpy.testing import assert_array_almost_equal
@@ -16,6 +17,16 @@ def test_find_ecg():
     """Test eliminate stim artifact"""
     raw = Raw(raw_fname, preload=True)
     events = read_events(event_fname)
-    n_events = len(events)
+    event_idx = np.where(events[:, 2] == 1)[0][0]
+    tidx = events[event_idx, 0] - raw.first_samp
+
     raw = eliminate_stim_artifact(raw, events, event_id=1, tmin=-0.005,
                                   tmax=0.01, mode='linear')
+    data, times = raw[:, tidx - 3:tidx + 5]
+    diff_data0 = np.diff(data[0])
+    diff_data0 -= np.mean(diff_data0)
+    assert_array_almost_equal(diff_data0, np.zeros(len(diff_data0)))
+    raw = eliminate_stim_artifact(raw, events, event_id=1, tmin=-0.005,
+                                  tmax=0.01, mode='window')
+    data, times = raw[:, tidx:tidx + 1]
+    assert_true(np.all(data) == 0.)

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