[med-svn] [python-mne] 119/376: bug fix due to new Evoked class + pyflakes
Yaroslav Halchenko
debian at onerussian.com
Fri Nov 27 17:22:19 UTC 2015
This is an automated email from the git hooks/post-receive script.
yoh pushed a commit to annotated tag v0.1
in repository python-mne.
commit 5c7c9935e4fefe775b4a4e4adc24fa8b7589a97b
Author: Alexandre Gramfort <alexandre.gramfort at inria.fr>
Date: Tue Mar 8 18:06:47 2011 -0500
bug fix due to new Evoked class + pyflakes
---
examples/plot_compute_mne_inverse.py | 1 -
examples/plot_estimate_covariance_matrix.py | 1 -
examples/plot_read_forward.py | 1 -
examples/plot_read_noise_covariance_matrix.py | 1 -
examples/plot_read_stc.py | 1 -
examples/plot_topography.py | 7 ++--
examples/plot_whiten_forward_solution.py | 1 -
examples/plot_whitened_evoked_data.py | 21 +++++-----
examples/read_events.py | 1 -
examples/read_inverse.py | 1 -
mne/cov.py | 55 +++++++++++++--------------
mne/fiff/tests/test_raw.py | 8 +---
mne/layouts/layout.py | 2 +-
mne/stats/tests/test_permutations.py | 1 -
mne/tests/test_bem_surfaces.py | 2 +-
mne/tests/test_cov.py | 1 -
mne/tests/test_epochs.py | 1 -
mne/tests/test_event.py | 1 -
mne/tests/test_forward.py | 4 +-
mne/tests/test_inverse.py | 3 +-
mne/tests/test_stc.py | 1 -
mne/viz.py | 10 ++---
22 files changed, 51 insertions(+), 74 deletions(-)
diff --git a/examples/plot_compute_mne_inverse.py b/examples/plot_compute_mne_inverse.py
index ab30d7a..7cfb025 100644
--- a/examples/plot_compute_mne_inverse.py
+++ b/examples/plot_compute_mne_inverse.py
@@ -14,7 +14,6 @@ and stores the solution in stc files for visualisation.
print __doc__
-import os
import numpy as np
import pylab as pl
import mne
diff --git a/examples/plot_estimate_covariance_matrix.py b/examples/plot_estimate_covariance_matrix.py
index 66a92d3..65c62bc 100644
--- a/examples/plot_estimate_covariance_matrix.py
+++ b/examples/plot_estimate_covariance_matrix.py
@@ -10,7 +10,6 @@ Estimate covariance matrix from a raw FIF file
print __doc__
-import os
import mne
from mne import fiff
from mne.datasets import sample
diff --git a/examples/plot_read_forward.py b/examples/plot_read_forward.py
index 797f8a9..24c2144 100644
--- a/examples/plot_read_forward.py
+++ b/examples/plot_read_forward.py
@@ -9,7 +9,6 @@ Reading a forward operator a.k.a. lead field matrix
print __doc__
-import os
import mne
from mne.datasets import sample
data_path = sample.data_path('.')
diff --git a/examples/plot_read_noise_covariance_matrix.py b/examples/plot_read_noise_covariance_matrix.py
index 2be0830..8e9b0ab 100644
--- a/examples/plot_read_noise_covariance_matrix.py
+++ b/examples/plot_read_noise_covariance_matrix.py
@@ -9,7 +9,6 @@ Reading/Writing a noise covariance matrix
print __doc__
-import os
import mne
from mne.datasets import sample
diff --git a/examples/plot_read_stc.py b/examples/plot_read_stc.py
index d8b7778..374c614 100644
--- a/examples/plot_read_stc.py
+++ b/examples/plot_read_stc.py
@@ -12,7 +12,6 @@ reconstructions
print __doc__
-import os
import numpy as np
import mne
from mne.datasets import sample
diff --git a/examples/plot_topography.py b/examples/plot_topography.py
index 939ec8e..7df851a 100644
--- a/examples/plot_topography.py
+++ b/examples/plot_topography.py
@@ -11,7 +11,6 @@ Plot topographies for MEG sensors
print __doc__
-import os
import pylab as pl
from mne import fiff
@@ -23,13 +22,13 @@ data_path = sample.data_path('.')
fname = data_path + '/MEG/sample/sample_audvis-ave.fif'
# Reading
-data = fiff.read_evoked(fname, setno=0, baseline=(None, 0))
+evoked = fiff.read_evoked(fname, setno=0, baseline=(None, 0))
layout = Layout('Vectorview-all')
###############################################################################
# Show topography
-plot_topo(data, layout)
-title = 'MNE sample data (condition : %s)' % data['evoked']['comment']
+plot_topo(evoked, layout)
+title = 'MNE sample data (condition : %s)' % evoked.comment
pl.figtext(0.03, 0.93, title, color='w', fontsize=18)
pl.show()
diff --git a/examples/plot_whiten_forward_solution.py b/examples/plot_whiten_forward_solution.py
index 4899da8..828240e 100644
--- a/examples/plot_whiten_forward_solution.py
+++ b/examples/plot_whiten_forward_solution.py
@@ -9,7 +9,6 @@ Whiten a forward operator with a noise covariance matrix
print __doc__
-import os
import mne
from mne import fiff
from mne.datasets import sample
diff --git a/examples/plot_whitened_evoked_data.py b/examples/plot_whitened_evoked_data.py
index 1228f77..af01bbc 100644
--- a/examples/plot_whitened_evoked_data.py
+++ b/examples/plot_whitened_evoked_data.py
@@ -10,7 +10,6 @@ Whiten evoked data using a noise covariance matrix
print __doc__
-import os
import mne
from mne import fiff
from mne.datasets import sample
@@ -20,35 +19,33 @@ fname = data_path + '/MEG/sample/sample_audvis-ave.fif'
cov_fname = data_path + '/MEG/sample/sample_audvis-cov.fif'
# Reading
-ave = fiff.read_evoked(fname, setno=0, baseline=(None, 0))
+evoked = fiff.read_evoked(fname, setno=0, baseline=(None, 0))
cov = mne.Covariance()
cov.load(cov_fname)
-ave_whiten, W = cov.whiten_evoked(ave)
+evoked_whiten, W = cov.whiten_evoked(evoked)
-bads = ave_whiten['info']['bads']
-ind_meg_grad = fiff.pick_types(ave['info'], meg='grad', exclude=bads)
-ind_meg_mag = fiff.pick_types(ave['info'], meg='mag', exclude=bads)
-ind_eeg = fiff.pick_types(ave['info'], meg=False, eeg=True, exclude=bads)
+bads = evoked_whiten.info['bads']
+ind_meg_grad = fiff.pick_types(evoked.info, meg='grad', exclude=bads)
+ind_meg_mag = fiff.pick_types(evoked.info, meg='mag', exclude=bads)
+ind_eeg = fiff.pick_types(evoked.info, meg=False, eeg=True, exclude=bads)
###############################################################################
# Show result
import pylab as pl
pl.clf()
pl.subplot(3, 1, 1)
-pl.plot(ave['evoked']['times'],
- ave_whiten['evoked']['epochs'][ind_meg_grad,:].T)
+pl.plot(evoked.times, evoked_whiten.data[ind_meg_grad,:].T)
pl.title('MEG Planar Gradiometers')
pl.xlabel('time (s)')
pl.ylabel('MEG data')
pl.subplot(3, 1, 2)
-pl.plot(ave['evoked']['times'],
- ave_whiten['evoked']['epochs'][ind_meg_mag,:].T)
+pl.plot(evoked.times, evoked_whiten.data[ind_meg_mag,:].T)
pl.title('MEG Magnetometers')
pl.xlabel('time (s)')
pl.ylabel('MEG data')
pl.subplot(3, 1, 3)
-pl.plot(ave['evoked']['times'], ave_whiten['evoked']['epochs'][ind_eeg,:].T)
+pl.plot(evoked.times, evoked_whiten.data[ind_eeg,:].T)
pl.title('EEG')
pl.xlabel('time (s)')
pl.ylabel('EEG data')
diff --git a/examples/read_events.py b/examples/read_events.py
index cc3fc1f..2e3fbb3 100644
--- a/examples/read_events.py
+++ b/examples/read_events.py
@@ -9,7 +9,6 @@ Reading an event file
print __doc__
-import os
import mne
from mne.datasets import sample
diff --git a/examples/read_inverse.py b/examples/read_inverse.py
index 025832a..6e5bcbd 100644
--- a/examples/read_inverse.py
+++ b/examples/read_inverse.py
@@ -27,7 +27,6 @@ print "Number of channels: %s" % inv['nchan']
# Show result
# 3D source space
-import numpy as np
lh_points = inv['src'][0]['rr']
lh_faces = inv['src'][0]['use_tris']
rh_points = inv['src'][1]['rr']
diff --git a/mne/cov.py b/mne/cov.py
index 5fc4826..7c9ca10 100644
--- a/mne/cov.py
+++ b/mne/cov.py
@@ -91,7 +91,7 @@ class Covariance(object):
for ii in ind:
data[ind,ind] += reg
- def whiten_evoked(self, ave, eps=0.2):
+ def whiten_evoked(self, evoked, eps=0.2):
"""Whiten an evoked data file
The whitening matrix is estimated and then multiplied to data.
@@ -100,14 +100,14 @@ class Covariance(object):
Parameters
----------
- ave : evoked data
- A evoked data set read with fiff.read_evoked
+ evoked : Evoked object
+ A evoked data set
eps : float
The regularization factor used.
Returns
-------
- ave : evoked data
+ evoked_whiten : Evoked object
Evoked data set after whitening.
W : array of shape [n_channels, n_channels]
The whitening matrix
@@ -118,18 +118,18 @@ class Covariance(object):
# Add (eps x identity matrix) to magnetometers only.
# This is based on the mean magnetometer variance like MNE C-code does it.
- mag_ind = pick_types(ave['info'], meg='mag', eeg=False, stim=False)
- mag_names = [ave['info']['chs'][k]['ch_name'] for k in mag_ind]
+ mag_ind = pick_types(evoked.info, meg='mag', eeg=False, stim=False)
+ mag_names = [evoked.info['chs'][k]['ch_name'] for k in mag_ind]
self._regularize(data, variances, mag_names, eps)
# Add (eps x identity matrix) to gradiometers only.
- grad_ind = pick_types(ave['info'], meg='grad', eeg=False, stim=False)
- grad_names = [ave['info']['chs'][k]['ch_name'] for k in grad_ind]
+ grad_ind = pick_types(evoked.info, meg='grad', eeg=False, stim=False)
+ grad_names = [evoked.info['chs'][k]['ch_name'] for k in grad_ind]
self._regularize(data, variances, grad_names, eps)
# Add (eps x identity matrix) to eeg only.
- eeg_ind = pick_types(ave['info'], meg=False, eeg=True, stim=False)
- eeg_names = [ave['info']['chs'][k]['ch_name'] for k in eeg_ind]
+ eeg_ind = pick_types(evoked.info, meg=False, eeg=True, stim=False)
+ eeg_names = [evoked.info['chs'][k]['ch_name'] for k in eeg_ind]
self._regularize(data, variances, eeg_names, eps)
d, V = linalg.eigh(data) # Compute eigen value decomposition.
@@ -141,18 +141,17 @@ class Covariance(object):
W = d[:,None] * V.T
# Get all channel indices
- n_channels = len(ave['info']['chs'])
- ave_ch_names = [ave['info']['chs'][k]['ch_name']
+ n_channels = len(evoked.info['chs'])
+ ave_ch_names = [evoked.info['chs'][k]['ch_name']
for k in range(n_channels)]
ind = [ave_ch_names.index(name) for name in self._cov['names']]
- ave_whiten = copy.copy(ave)
- ave_whiten['evoked']['epochs'][ind] = np.dot(W,
- ave['evoked']['epochs'][ind])
+ evoked_whiten = copy.copy(evoked)
+ evoked_whiten.data[ind] = np.dot(W, evoked.data[ind])
- return ave_whiten, W
+ return evoked_whiten, W
- def whiten_evoked_and_forward(self, ave, fwd, eps=0.2):
+ def whiten_evoked_and_forward(self, evoked, fwd, eps=0.2):
"""Whiten an evoked data set and a forward solution
The whitening matrix is estimated and then multiplied to
@@ -162,8 +161,8 @@ class Covariance(object):
Parameters
----------
- ave : evoked data
- A evoked data set read with fiff.read_evoked
+ evoked : Evoked object
+ A evoked data set
fwd : forward data
A forward solution read with mne.read_forward
eps : float
@@ -171,17 +170,17 @@ class Covariance(object):
Returns
-------
- ave : evoked data
- A evoked data set read with fiff.read_evoked
- fwd : evoked data
- Forward solution after whitening.
+ ave : Evoked object
+ The whitened evoked data set
+ fwd : dict
+ The whitened forward solution.
W : array of shape [n_channels, n_channels]
The whitening matrix
"""
# handle evoked
- ave_whiten, W = self.whiten_evoked(ave, eps=eps)
+ evoked_whiten, W = self.whiten_evoked(evoked, eps=eps)
- ave_ch_names = [ch['ch_name'] for ch in ave_whiten['info']['chs']]
+ evoked_ch_names = [ch['ch_name'] for ch in evoked_whiten.info['chs']]
# handle forward (keep channels in covariance matrix)
fwd_whiten = copy.copy(fwd)
@@ -194,10 +193,10 @@ class Covariance(object):
fwd_whiten['chs'] = [fwd_whiten['chs'][k] for k in ind]
# keep in forward the channels in the evoked dataset
- fwd_whiten = pick_channels_forward(fwd, include=ave_ch_names,
- exclude=ave['info']['bads'])
+ fwd_whiten = pick_channels_forward(fwd, include=evoked_ch_names,
+ exclude=evoked.info['bads'])
- return ave_whiten, fwd_whiten, W
+ return evoked_whiten, fwd_whiten, W
def __repr__(self):
s = "kind : %s" % self.kind
diff --git a/mne/fiff/tests/test_raw.py b/mne/fiff/tests/test_raw.py
index 9f5851c..9cf74b3 100644
--- a/mne/fiff/tests/test_raw.py
+++ b/mne/fiff/tests/test_raw.py
@@ -1,12 +1,8 @@
-import os
import os.path as op
-from numpy.testing import assert_array_almost_equal, assert_equal
-
-from math import ceil
-from .. import Raw, read_raw_segment_times, pick_types, \
- start_writing_raw, write_raw_buffer, finish_writing_raw
+# from numpy.testing import assert_array_almost_equal, assert_equal
+from .. import Raw, pick_types
fname = op.join(op.dirname(__file__), 'data', 'test_raw.fif')
diff --git a/mne/layouts/layout.py b/mne/layouts/layout.py
index d205e38..c9b33ca 100644
--- a/mne/layouts/layout.py
+++ b/mne/layouts/layout.py
@@ -1,11 +1,11 @@
import os.path as op
import numpy as np
-import pylab as pl
class Layout(object):
"""Sensor layouts"""
+
def __init__(self, kind='Vectorview-all', path=None):
"""
Parameters
diff --git a/mne/stats/tests/test_permutations.py b/mne/stats/tests/test_permutations.py
index 768dbf8..805b9dd 100644
--- a/mne/stats/tests/test_permutations.py
+++ b/mne/stats/tests/test_permutations.py
@@ -2,7 +2,6 @@ import numpy as np
from numpy.testing import assert_array_equal, assert_almost_equal
from scipy import stats
-import mne
from ..permutations import permutation_t_test
diff --git a/mne/tests/test_bem_surfaces.py b/mne/tests/test_bem_surfaces.py
index 59e3c26..7400776 100644
--- a/mne/tests/test_bem_surfaces.py
+++ b/mne/tests/test_bem_surfaces.py
@@ -1,6 +1,6 @@
import os.path as op
-from numpy.testing import assert_array_almost_equal
+# from numpy.testing import assert_array_almost_equal
import mne
from mne.datasets import sample
diff --git a/mne/tests/test_cov.py b/mne/tests/test_cov.py
index ac86811..3613fa3 100644
--- a/mne/tests/test_cov.py
+++ b/mne/tests/test_cov.py
@@ -1,4 +1,3 @@
-import os
import os.path as op
from numpy.testing import assert_array_almost_equal
diff --git a/mne/tests/test_epochs.py b/mne/tests/test_epochs.py
index a335fe6..3760b3f 100644
--- a/mne/tests/test_epochs.py
+++ b/mne/tests/test_epochs.py
@@ -2,7 +2,6 @@
#
# License: BSD (3-clause)
-import os
import os.path as op
import mne
diff --git a/mne/tests/test_event.py b/mne/tests/test_event.py
index d51496a..3e9680b 100644
--- a/mne/tests/test_event.py
+++ b/mne/tests/test_event.py
@@ -1,4 +1,3 @@
-import os
import os.path as op
from numpy.testing import assert_array_almost_equal
diff --git a/mne/tests/test_forward.py b/mne/tests/test_forward.py
index 5bf55ba..15e3006 100644
--- a/mne/tests/test_forward.py
+++ b/mne/tests/test_forward.py
@@ -1,7 +1,6 @@
-import os
import os.path as op
-from numpy.testing import assert_array_almost_equal, assert_equal
+# from numpy.testing import assert_array_almost_equal, assert_equal
import mne
from mne.datasets import sample
@@ -16,3 +15,4 @@ def test_io_forward():
fwd = mne.read_forward_solution(fname)
fwd = mne.read_forward_solution(fname, force_fixed=True)
leadfield = fwd['sol']['data']
+ # XXX : test something
diff --git a/mne/tests/test_inverse.py b/mne/tests/test_inverse.py
index 840e02c..09ce352 100644
--- a/mne/tests/test_inverse.py
+++ b/mne/tests/test_inverse.py
@@ -1,8 +1,7 @@
-import os
import os.path as op
import numpy as np
-from numpy.testing import assert_array_almost_equal, assert_equal
+# from numpy.testing import assert_array_almost_equal, assert_equal
import mne
from mne.datasets import sample
diff --git a/mne/tests/test_stc.py b/mne/tests/test_stc.py
index 8eece25..611abee 100644
--- a/mne/tests/test_stc.py
+++ b/mne/tests/test_stc.py
@@ -1,4 +1,3 @@
-import os
import os.path as op
from numpy.testing import assert_array_almost_equal
diff --git a/mne/viz.py b/mne/viz.py
index 1763c46..4265a00 100644
--- a/mne/viz.py
+++ b/mne/viz.py
@@ -8,12 +8,12 @@
import pylab as pl
-def plot_topo(data, layout):
+def plot_topo(evoked, layout):
"""Plot 2D topographies
"""
- ch_names = data['info']['ch_names']
- times = data['evoked']['times']
- epochs = data['evoked']['epochs']
+ ch_names = evoked.info['ch_names']
+ times = evoked.times
+ data = evoked.data
pl.rcParams['axes.edgecolor'] = 'w'
pl.figure(facecolor='k')
@@ -21,7 +21,7 @@ def plot_topo(data, layout):
if name in ch_names:
idx = ch_names.index(name)
ax = pl.axes(layout.pos[idx], axisbg='k')
- ax.plot(times, epochs[idx,:], 'w')
+ ax.plot(times, data[idx,:], 'w')
pl.xticks([], ())
pl.yticks([], ())
--
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