Merge pull request mne-tools#3335 from gamazeps/fix-issue-3268

[WIP][FIX] Adds apply_baseline to Evoked

mne/epochs.py

@@ -392,7 +392,7 @@ def decimate(self, decim, offset=0):
         return self
 
     @verbose
-    def apply_baseline(self, baseline, verbose=None):
+    def apply_baseline(self, baseline=(None, 0), verbose=None):
         """Baseline correct epochs
 
         Parameters

mne/evoked.py

@@ -56,12 +56,14 @@ class Evoked(ProjMixin, ContainsMixin, UpdateChannelsMixin,
         Dataset ID number (int) or comment/name (str). Optional if there is
         only one data set in file.
     baseline : tuple or list of length 2, or None
+        This parameter has been deprecated and will be removed in 0.14
+        Use inst.apply_baseline(baseline) instead.
         The time interval to apply rescaling / baseline correction.
         If None do not apply it. If baseline is (a, b)
         the interval is between "a (s)" and "b (s)".
         If a is None the beginning of the data is used
         and if b is None then b is set to the end of the interval.
-        If baseline is equal ot (None, None) all the time
+        If baseline is equal to (None, None) all the time
         interval is used. If None, no correction is applied.
     proj : bool, optional
         Apply SSP projection vectors
@@ -113,7 +115,38 @@ def __init__(self, fname, condition=None, baseline=None, proj=True,
         # project and baseline correct
         if proj:
             self.apply_proj()
+        self.apply_baseline(baseline, self.verbose)
+
+    @verbose
+    def apply_baseline(self, baseline=(None, 0), verbose=None):
+        """Baseline correct evoked data
+
+        Parameters
+        ----------
+        baseline : tuple of length 2
+            The time interval to apply rescaling / baseline correction.
+            If None do not apply it. If baseline is (a, b)
+            the interval is between "a (s)" and "b (s)".
+            If a is None the beginning of the data is used
+            and if b is None then b is set to the end of the interval.
+            If baseline is equal to (None, None) all the time
+            interval is used. If None, no correction is applied.
+        verbose : bool, str, int, or None
+            If not None, override default verbose level (see mne.verbose).
+
+        Returns
+        -------
+        evoked : instance of Evoked
+            The baseline-corrected Evoked object.
+
+        Notes
+        -----
+        Baseline correction can be done multiple times.
+
+        .. versionadded:: 0.13.0
+        """
         self.data = rescale(self.data, self.times, baseline, copy=False)
+        return self
 
     def save(self, fname):
         """Save dataset to file.
@@ -1258,8 +1291,8 @@ def read_evokeds(fname, condition=None, baseline=None, kind='average',
         condition = [condition]
         return_list = False
 
-    out = [Evoked(fname, c, baseline=baseline, kind=kind, proj=proj,
-           verbose=verbose) for c in condition]
+    out = [Evoked(fname, c, kind=kind, proj=proj, verbose=verbose)
+            .apply_baseline(baseline) for c in condition]
 
     return out if return_list else out[0]
 

mne/io/tests/data/test-ave-2.log

@@ -12,6 +12,7 @@ Created an SSP operator (subspace dimension = 4)
 4 projection items activated
 SSP projectors applied...
 No baseline correction applied...
+No baseline correction applied...
 Reading mne/fiff/tests/data/test-ave.fif ...
     Read a total of 4 projection items:
         PCA-v1 (1 x 102)  idle
@@ -26,3 +27,4 @@ Created an SSP operator (subspace dimension = 4)
 4 projection items activated
 SSP projectors applied...
 No baseline correction applied...
+No baseline correction applied...

mne/io/tests/data/test-ave.log

@@ -12,3 +12,4 @@ Created an SSP operator (subspace dimension = 4)
 4 projection items activated
 SSP projectors applied...
 No baseline correction applied...
+No baseline correction applied...

mne/tests/test_evoked.py

@@ -543,4 +543,17 @@ def test_add_channels():
     assert_raises(AssertionError, evoked_meg.add_channels, evoked_badsf)
 
 
+def test_evoked_baseline():
+    """Test evoked baseline"""
+    evoked = read_evokeds(fname, condition=0, baseline=None)
+
+    # Here we create a data_set with constant data.
+    evoked = EvokedArray(np.ones_like(evoked.data), evoked.info, evoked.times[0])
+
+    # Mean baseline correction is applied, since the data is equal to its mean
+    # the resulting data should be a matrix of zeroes.
+    evoked.apply_baseline((None, None))
+
+    assert_allclose(evoked.data, np.zeros_like(evoked.data))
+
 run_tests_if_main()