[med-svn] [python-mne] 360/376: prettify example + adding test for source_induced_power

[Yaroslav Halchenko]

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yoh pushed a commit to annotated tag v0.1
in repository python-mne.

commit 87c0dffa0521a91ed400829f017779bc79657280
Author: Alexandre Gramfort <alexandre.gramfort at inria.fr>
Date:   Fri Sep 16 17:22:57 2011 -0400

    prettify example + adding test for source_induced_power
---
 .../plot_source_label_time_frequency.py              |  4 ++--
 mne/baseline.py                                      |  7 +++++--
 mne/minimum_norm/tests/test_time_frequency.py        | 20 +++++++++++++++++---
 3 files changed, 24 insertions(+), 7 deletions(-)

diff --git a/examples/time_frequency/plot_source_label_time_frequency.py b/examples/time_frequency/plot_source_label_time_frequency.py
index 5c53aef..17621d4 100644
--- a/examples/time_frequency/plot_source_label_time_frequency.py
+++ b/examples/time_frequency/plot_source_label_time_frequency.py
@@ -49,10 +49,10 @@ epochs = mne.Epochs(raw, events, event_id, tmin, tmax, picks=picks,
                     preload=True)
 
 # Compute a source estimate per frequency band
-frequencies = np.arange(7, 30, 3)  # define frequencies of interest
+frequencies = np.arange(7, 30, 2)  # define frequencies of interest
 label = mne.read_label(fname_label)
 power, phase_lock = source_induced_power(epochs, inverse_operator, frequencies,
-                            label, baseline=(None, 0), baseline_mode='logratio',
+                            label, baseline=(-0.1, 0), baseline_mode='percent',
                             n_cycles=2, n_jobs=1)
 
 power = np.mean(power, axis=0)  # average over sources
diff --git a/mne/baseline.py b/mne/baseline.py
index 6cb7c11..16435d4 100644
--- a/mne/baseline.py
+++ b/mne/baseline.py
@@ -29,7 +29,7 @@ def rescale(data, times, baseline, mode, verbose=True, copy=True):
         If baseline is equal ot (None, None) all the time
         interval is used.
 
-    mode: 'logratio' | 'ratio' | 'zscore' | 'mean'
+    mode: 'logratio' | 'ratio' | 'zscore' | 'mean' | 'percent'
         Do baseline correction with ratio (power is divided by mean
         power during baseline) or zscore (power is divided by standard
         deviatio of power during baseline after substracting the mean,
@@ -44,7 +44,7 @@ def rescale(data, times, baseline, mode, verbose=True, copy=True):
     if copy:
         data = data.copy()
 
-    valid_modes = ['logratio', 'ratio', 'zscore', 'mean']
+    valid_modes = ['logratio', 'ratio', 'zscore', 'mean', 'percent']
     if mode not in valid_modes:
         raise Exception('mode should be any of : %s' % valid_modes)
 
@@ -73,6 +73,9 @@ def rescale(data, times, baseline, mode, verbose=True, copy=True):
             std = np.std(data[..., imin:imax], axis=-1)[..., None]
             data -= mean
             data /= std
+        elif mode == 'percent':
+            data -= mean
+            data /= mean
 
     elif verbose:
         print "No baseline correction applied..."
diff --git a/mne/minimum_norm/tests/test_time_frequency.py b/mne/minimum_norm/tests/test_time_frequency.py
index 6423e67..c231db0 100644
--- a/mne/minimum_norm/tests/test_time_frequency.py
+++ b/mne/minimum_norm/tests/test_time_frequency.py
@@ -8,7 +8,7 @@ from ...datasets import sample
 from ... import fiff, find_events, Epochs
 from ...label import read_label
 from ..inverse import read_inverse_operator
-from ..time_frequency import source_band_induced_power
+from ..time_frequency import source_band_induced_power, source_induced_power
 
 
 examples_folder = op.join(op.dirname(__file__), '..', '..', '..', 'examples')
@@ -39,8 +39,8 @@ def test_tfr_with_inverse_operator():
 
     # Load condition 1
     event_id = 1
-    events = events[:3]  # take 3 events to keep the computation time low
-    epochs = Epochs(raw, events, event_id, tmin, tmax, picks=picks,
+    events3 = events[:3]  # take 3 events to keep the computation time low
+    epochs = Epochs(raw, events3, event_id, tmin, tmax, picks=picks,
                     baseline=(None, 0), reject=dict(grad=4000e-13, eog=150e-6),
                     preload=True)
 
@@ -60,3 +60,17 @@ def test_tfr_with_inverse_operator():
                             n_cycles=2, use_fft=False, pca=False, label=label)
 
     assert_array_almost_equal(stcs['alpha'].data, stcs_no_pca['alpha'].data)
+
+    # Compute a source estimate per frequency band
+    events = find_events(raw)
+    epochs = Epochs(raw, events[:10], event_id, tmin, tmax, picks=picks,
+                    baseline=(None, 0), reject=dict(grad=4000e-13, eog=150e-6),
+                    preload=True)
+
+    frequencies = np.arange(7, 30, 2)  # define frequencies of interest
+    power, phase_lock = source_induced_power(epochs, inverse_operator,
+                            frequencies, label, baseline=(-0.1, 0),
+                            baseline_mode='percent', n_cycles=2, n_jobs=1)
+    assert_true(np.all(phase_lock > 0))
+    assert_true(np.all(phase_lock < 1))
+    assert_true(np.max(power) > 10)

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