[med-svn] [python-mne] 260/353: ENH : new stim artifact rejection function

[Yaroslav Halchenko]

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

commit 8f985c10224a13fa767772b23beb6c6094a2d9a0
Author: Daniel Strohmeier <daniel.strohmeier at googlemail.com>
Date:   Thu Jul 12 18:48:51 2012 +0200

    ENH : new stim artifact rejection function
---
 mne/artifacts/stim.py            | 56 ++++++++++++++++++++++++++++++++++++++++
 mne/artifacts/tests/test_stim.py | 21 +++++++++++++++
 2 files changed, 77 insertions(+)

diff --git a/mne/artifacts/stim.py b/mne/artifacts/stim.py
new file mode 100644
index 0000000..01af320
--- /dev/null
+++ b/mne/artifacts/stim.py
@@ -0,0 +1,56 @@
+import numpy as np
+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
+    ----------
+    raw: Raw object
+        raw data object
+    events: array, shape (n_events, 3)
+        The list of events
+    event_id: int
+        The id of the events generating the stimulation artifacts.
+    tmin : float
+        Start time before event in seconds
+    tmax : float
+        End time after event in seconds
+    mode : 'linear' | 'window'
+        way to fill the artifacted time interval
+        'linear' does linear interpolation
+        'window' applies a (1 - hanning) window
+
+    Returns
+    -------
+    raw: Raw object
+        raw data object
+    """
+    events_sel = (events[:, 2] == event_id)
+    event_start = events[events_sel, 0]
+    s_start = np.ceil(raw.info['sfreq'] * np.abs(tmin))[0]
+    s_end = np.ceil(raw.info['sfreq'] * tmax)[0]
+    if mode == 'linear':
+        for k in range(len(event_start)):
+            x = np.array([event_start[k] - raw.first_samp - s_start, \
+                            event_start[k] - raw.first_samp + s_end])
+            data = raw._data[:, [event_start[k] - raw.first_samp - s_start, \
+                                event_start[k] - raw.first_samp + s_end]]
+            f = interpolate.interp1d(x, data)
+            xnew = np.arange(event_start[k] - raw.first_samp - s_start, \
+                             event_start[k] - raw.first_samp + s_end)
+            interp_data = f(xnew)
+            raw._data[:, event_start[k] - raw.first_samp - s_start:\
+                         event_start[k] - raw.first_samp + s_end] = interp_data
+    if mode == 'window':
+        window = 1 - np.r_[signal.hann(4)[:2], np.ones(s_end + s_start - 4), \
+                            signal.hann(4)[-2:]].T
+        for k in range(len(event_start)):
+            raw._data[:, event_start[k] - raw.first_samp - s_start:\
+                         event_start[k] - raw.first_samp + s_end] *= \
+                                                    window[np.newaxis, :]
+    return raw
diff --git a/mne/artifacts/tests/test_stim.py b/mne/artifacts/tests/test_stim.py
new file mode 100644
index 0000000..8cbdc85
--- /dev/null
+++ b/mne/artifacts/tests/test_stim.py
@@ -0,0 +1,21 @@
+import os.path as op
+
+from nose.tools import assert_true
+from numpy.testing import assert_array_almost_equal
+
+from ...fiff import Raw
+from ...event import read_events
+from ..stim import eliminate_stim_artifact
+
+data_path = op.join(op.dirname(__file__), '..', '..', 'fiff', 'tests', 'data')
+raw_fname = op.join(data_path, 'test_raw.fif')
+event_fname = op.join(data_path, 'test-eve.fif')
+
+
+def test_find_ecg():
+    """Test eliminate stim artifact"""
+    raw = Raw(raw_fname, preload=True)
+    events = read_events(event_fname)
+    n_events = len(events)
+    raw = eliminate_stim_artifact(raw, events, event_id=1, tmin=-0.005,
+                                  tmax=0.01, mode='linear')

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