bump version to 0.13.1

* FIX:  KIT reference channels (#3721)

* FIX:  KIT (system 52) channel ID 0 are reference channels

* FIX RawKIT:  stim=list with stim_code='channel' (#3737)

Need to coerce list to array

circle.yml

@@ -80,6 +80,10 @@ dependencies:
             if [[ $(cat $FNAME | grep -x ".*brainstorm.*bst_phantom_elekta.*" | wc -l) -gt 0 ]]; then
               python -c "import mne; print(mne.datasets.brainstorm.bst_phantom_elekta.data_path())" --accept-brainstorm-license;
             fi;
+            if [[ $(cat $FNAME | grep -x ".*datasets.*megsim.*" | wc -l) -gt 0 ]]; then
+              python -c "import mne; print(mne.datasets.megsim.load_data(condition='visual', data_format='single-trial', data_type='simulation', update_path=True))";
+              python -c "import mne; print(mne.datasets.megsim.load_data(condition='visual', data_format='raw', data_type='experimental', update_path=True))";
+            fi;
           fi;
         done;
         echo PATTERN="$PATTERN";
@@ -128,7 +132,7 @@ deployment:
       - cd doc/_build/html && cp -rf * ~/mne-tools.github.io/dev
       - cd ../mne-tools.github.io && git add -A && git commit -m 'Automated update of dev docs.' && git push origin master
   stable:
-    branch: maint/0.12
+    branch: maint/0.13
     commands:
       - git config --global user.email "circle@mne.com"
       - git config --global user.name "Circle Ci"

examples/datasets/plot_megsim_data_single_trial.py

@@ -15,7 +15,7 @@ Gilliam K, Donahue CH, Montano R, Bryant JE, Scott A, Stephen JM
 Realistic Simulated and Empirical Data. Neuroinformatics 10:141-158
 """
 
-from mne import read_evokeds
+from mne import read_evokeds, combine_evoked
 from mne.datasets.megsim import load_data
 
 print(__doc__)
@@ -30,7 +30,7 @@ epochs_fnames = load_data(condition=condition, data_format='single-trial',
 epochs_fnames = [f for f in epochs_fnames if 'sim6_trial_' in f][:10]
 
 evokeds = [read_evokeds(f)[0] for f in epochs_fnames]
-mean_evoked = sum(evokeds[1:], evokeds[0])
+mean_evoked = combine_evoked(evokeds, weights='nave')
 
 # Visualize the average
 mean_evoked.plot()

examples/datasets/plot_spm_faces_dataset.py

@@ -25,7 +25,7 @@ import matplotlib.pyplot as plt
 import mne
 from mne.datasets import spm_face
 from mne.preprocessing import ICA, create_eog_epochs
-from mne import io
+from mne import io, combine_evoked
 from mne.minimum_norm import make_inverse_operator, apply_inverse
 
 print(__doc__)
@@ -74,7 +74,7 @@ ica.apply(epochs)  # clean data, default in place
 
 evoked = [epochs[k].average() for k in event_ids]
 
-contrast = evoked[1] - evoked[0]
+contrast = combine_evoked(evoked, weights=[-1, 1])  # Faces - scrambled
 
 evoked.append(contrast)
 
@@ -128,7 +128,6 @@ stc = apply_inverse(contrast, inverse_operator, lambda2, method, pick_ori=None)
 # stc.save('spm_%s_dSPM_inverse' % constrast.comment)
 
 # Plot contrast in 3D with PySurfer if available
-brain = stc.plot(hemi='both', subjects_dir=subjects_dir)
-brain.set_time(170.0)  # milliseconds
-brain.show_view('ventral')
+brain = stc.plot(hemi='both', subjects_dir=subjects_dir, initial_time=0.170,
+                 views=['ven'])
 # brain.save_image('dSPM_map.png')

examples/decoding/plot_decoding_spatio_temporal_source.py

@@ -148,5 +148,5 @@ stc_feat = mne.SourceEstimate(feature_weights, vertices=vertices,
                               tmin=stc.tmin, tstep=stc.tstep,
                               subject='sample')
 
-brain = stc_feat.plot(hemi='split', views=['lat', 'med'], transparent=True,
+brain = stc_feat.plot(views=['lat'], transparent=True,
                       initial_time=0.1, time_unit='s')

examples/inverse/plot_compute_mne_inverse_raw_in_label.py

@@ -35,6 +35,7 @@ raw = mne.io.read_raw_fif(fname_raw)
 inverse_operator = read_inverse_operator(fname_inv)
 label = mne.read_label(fname_label)
 
+raw.set_eeg_reference()  # set average reference.
 start, stop = raw.time_as_index([0, 15])  # read the first 15s of data
 
 # Compute inverse solution

examples/realtime/ftclient_rt_average.py

@@ -74,7 +74,7 @@ with FieldTripClient(host='localhost', port=1972,
         if ii == 0:
             evoked = ev
         else:
-            evoked += ev
+            evoked = mne.combine_evoked([evoked, ev], weights='nave')
 
         ax[0].cla()
         ax[1].cla()  # clear axis

examples/realtime/plot_compute_rt_average.py

@@ -55,7 +55,7 @@ for ii, ev in enumerate(rt_epochs.iter_evoked()):
     if ii == 0:
         evoked = ev
     else:
-        evoked += ev
+        evoked = mne.combine_evoked([evoked, ev], weights='nave')
     plt.clf()  # clear canvas
     evoked.plot(axes=plt.gca())  # plot on current figure
     plt.pause(0.05)

mne/__init__.py

@@ -17,7 +17,7 @@
 # Dev branch marker is: 'X.Y.devN' where N is an integer.
 #
 
-__version__ = '0.13'
+__version__ = '0.13.1'
 
 # have to import verbose first since it's needed by many things
 from .utils import (set_log_level, set_log_file, verbose, set_config,

mne/decoding/tests/test_ems.py

@@ -79,7 +79,7 @@ def test_ems():
     assert_equal(ems.__repr__(), '<EMS: not fitted.>')
     # manual leave-one-out to avoid sklearn version problem
     for test in range(len(y)):
-        train = np.setdiff1d(range(len(y)), test)
+        train = np.setdiff1d(range(len(y)), np.atleast_1d(test))
         ems.fit(X[train], y[train])
         coefs.append(ems.filters_)
         Xt.append(ems.transform(X[[test]]))

mne/decoding/tests/test_time_gen.py

@@ -60,13 +60,13 @@ def test_generalization_across_time():
     y_4classes = np.hstack((epochs.events[:7, 2], epochs.events[7:, 2] + 1))
     if check_version('sklearn', '0.18'):
         from sklearn.model_selection import (KFold, StratifiedKFold,
-                                             ShuffleSplit, LeaveOneLabelOut)
+                                             ShuffleSplit, LeaveOneGroupOut)
         cv_shuffle = ShuffleSplit()
-        cv = LeaveOneLabelOut()
+        cv = LeaveOneGroupOut()
         # XXX we cannot pass any other parameters than X and y to cv.split
         # so we have to build it before hand
         cv_lolo = [(train, test) for train, test in cv.split(
-                   X=y_4classes, y=y_4classes, labels=y_4classes)]
+                   y_4classes, y_4classes, y_4classes)]
 
         # With sklearn >= 0.17, `clf` can be identified as a regressor, and
         # the scoring metrics can therefore be automatically assigned.

mne/externals/tempita/_looper.py

@@ -7,9 +7,9 @@ These can be awkward to manage in a normal Python loop, but using the
 looper you can get a better sense of the context.  Use like::
 
     >>> for loop, item in looper(['a', 'b', 'c']):
-    ...     print("%d %s" % (loop.number, item))
+    ...     print loop.number, item
     ...     if not loop.last:
-    ...         print('---')
+    ...         print '---'
     1 a
     ---
     2 b

mne/externals/tempita/compat3.py

@@ -1,12 +1,11 @@
 import sys
 
-__all__ = ['PY3', 'b', 'basestring_', 'bytes', 'next', 'is_unicode']
+__all__ = ['b', 'basestring_', 'bytes', 'unicode_', 'next', 'is_unicode']
 
-PY3 = True if sys.version_info[0] == 3 else False
-
-if sys.version_info[0] < 3:
+if sys.version < "3":
     b = bytes = str
     basestring_ = basestring
+    unicode_ = unicode
 else:
 
     def b(s):
@@ -15,26 +14,29 @@ else:
         return bytes(s)
     basestring_ = (bytes, str)
     bytes = bytes
+    unicode_ = str
 text = str
 
-if sys.version_info[0] < 3:
+if sys.version < "3":
 
     def next(obj):
         return obj.next()
 else:
     next = next
 
+if sys.version < "3":
 
-def is_unicode(obj):
-    if sys.version_info[0] < 3:
+    def is_unicode(obj):
         return isinstance(obj, unicode)
-    else:
+else:
+
+    def is_unicode(obj):
         return isinstance(obj, str)
 
 
 def coerce_text(v):
     if not isinstance(v, basestring_):
-        if sys.version_info[0] < 3:
+        if sys.version < "3":
             attr = '__unicode__'
         else:
             attr = '__str__'

mne/io/kit/kit.py

@@ -187,11 +187,13 @@ class RawKIT(_BaseRaw):
                 else:
                     raise ValueError("stim needs to be list of int, '>' or "
                                      "'<', not %r" % str(stim))
-            elif np.max(stim) >= self._raw_extras[0]['nchan']:
-                raise ValueError('Tried to set stim channel %i, but sqd file '
-                                 'only has %i channels'
-                                 % (np.max(stim),
-                                    self._raw_extras[0]['nchan']))
+            else:
+                stim = np.asarray(stim, int)
+                if stim.max() >= self._raw_extras[0]['nchan']:
+                    raise ValueError(
+                        'Got stim=%s, but sqd file only has %i channels' %
+                        (stim, self._raw_extras[0]['nchan']))
+
             # modify info
             nchan = self._raw_extras[0]['nchan'] + 1
             ch_name = 'STI 014'
@@ -603,11 +605,15 @@ def get_kit_info(rawfile):
                 # planargradiometer
                 # x,y,z,theta,phi,btheta,bphi,baseline,coilsize
                 sensors.append(np.fromfile(fid, dtype='d', count=9))
-            elif sens_type == 257:
+            elif sens_type in (257, 0):
                 # reference channels
                 sensors.append(np.zeros(7))
                 sqd['i'] = sens_type
+            else:
+                raise IOError("Unknown KIT channel type: %i" % sens_type)
         sqd['sensor_locs'] = np.array(sensors)
+        if len(sqd['sensor_locs']) != KIT_SYS.N_SENS:
+            raise IOError("An error occurred while reading %s" % rawfile)
 
         # amplifier gain
         fid.seek(KIT_SYS.AMPLIFIER_INFO)
@@ -678,27 +684,19 @@ def get_kit_info(rawfile):
 
         # Creates a list of dicts of meg channels for raw.info
         logger.info('Setting channel info structure...')
-        ch_names = {}
-        ch_names['MEG'] = ['MEG %03d' % ch for ch
-                           in range(1, sqd['n_sens'] + 1)]
-        ch_names['MISC'] = ['MISC %03d' % ch for ch
-                            in range(1, sqd['nmiscchan'] + 1)]
         locs = sqd['sensor_locs']
         chan_locs = apply_trans(als_ras_trans, locs[:, :3])
         chan_angles = locs[:, 3:]
-        info['chs'] = []
-        for idx, ch_info in enumerate(zip(ch_names['MEG'], chan_locs,
-                                          chan_angles), 1):
-            ch_name, ch_loc, ch_angles = ch_info
-            chan_info = {}
-            chan_info['cal'] = KIT.CALIB_FACTOR
-            chan_info['logno'] = idx
-            chan_info['scanno'] = idx
-            chan_info['range'] = KIT.RANGE
-            chan_info['unit_mul'] = KIT.UNIT_MUL
-            chan_info['ch_name'] = ch_name
-            chan_info['unit'] = FIFF.FIFF_UNIT_T
-            chan_info['coord_frame'] = FIFF.FIFFV_COORD_DEVICE
+        for idx, (ch_loc, ch_angles) in enumerate(zip(chan_locs, chan_angles),
+                                                  1):
+            chan_info = {'cal': KIT.CALIB_FACTOR,
+                         'logno': idx,
+                         'scanno': idx,
+                         'range': KIT.RANGE,
+                         'unit_mul': KIT.UNIT_MUL,
+                         'ch_name': 'MEG %03d' % idx,
+                         'unit': FIFF.FIFF_UNIT_T,
+                         'coord_frame': FIFF.FIFFV_COORD_DEVICE}
             if idx <= sqd['nmegchan']:
                 chan_info['coil_type'] = FIFF.FIFFV_COIL_KIT_GRAD
                 chan_info['kind'] = FIFF.FIFFV_MEG_CH
@@ -736,19 +734,18 @@ def get_kit_info(rawfile):
             info['chs'].append(chan_info)
 
         # label trigger and misc channels
-        for idy, ch_name in enumerate(ch_names['MISC'],
-                                      sqd['n_sens'] + 1):
-            chan_info = {}
-            chan_info['cal'] = KIT.CALIB_FACTOR
-            chan_info['logno'] = idy
-            chan_info['scanno'] = idy
-            chan_info['range'] = 1.0
-            chan_info['unit'] = FIFF.FIFF_UNIT_V
-            chan_info['unit_mul'] = 0
-            chan_info['ch_name'] = ch_name
-            chan_info['coil_type'] = FIFF.FIFFV_COIL_NONE
-            chan_info['loc'] = np.zeros(12)
-            chan_info['kind'] = FIFF.FIFFV_MISC_CH
+        for idx in range(1, sqd['nmiscchan'] + 1):
+            ch_idx = idx + KIT_SYS.N_SENS
+            chan_info = {'cal': KIT.CALIB_FACTOR,
+                         'logno': ch_idx,
+                         'scanno': ch_idx,
+                         'range': 1.0,
+                         'unit': FIFF.FIFF_UNIT_V,
+                         'unit_mul': 0,
+                         'ch_name': 'MISC %03d' % idx,
+                         'coil_type': FIFF.FIFFV_COIL_NONE,
+                         'loc': np.zeros(12),
+                         'kind': FIFF.FIFFV_MISC_CH}
             info['chs'].append(chan_info)
     info._update_redundant()
     return info, sqd

mne/io/kit/tests/test_kit.py

@@ -131,6 +131,11 @@ def test_raw_events():
     assert_array_equal(find_events(raw, output='step', consecutive=True),
                        evts(0, 160, 0, 160, 0))
 
+    raw = read_raw_kit(sqd_path, stim=range(160, 162), slope='+',
+                       stim_code='channel')
+    assert_array_equal(find_events(raw, output='step', consecutive=True),
+                       evts(0, 160, 0, 160, 0))
+
 
 def test_ch_loc():
     """Test raw kit loc."""

mne/viz/evoked.py

@@ -200,7 +200,8 @@ def _plot_evoked(evoked, picks, exclude, unit, show,
     units = _handle_default('units', units)
     # Valid data types ordered for consistency
     valid_channel_types = ['eeg', 'grad', 'mag', 'seeg', 'eog', 'ecg', 'emg',
-                           'dipole', 'gof', 'bio', 'ecog', 'hbo', 'hbr']
+                           'dipole', 'gof', 'bio', 'ecog', 'hbo', 'hbr',
+                           'misc']
 
     if picks is None:
         picks = list(range(info['nchan']))

setup.cfg

@@ -19,7 +19,7 @@ doc-files = doc
 # cover-html = 1
 # cover-html-dir = coverage
 cover-package = mne
-ignore-files = (?:^\.|^_,|^conf\.py$)
+ignore-files = (?:^\.|^_,|^conf\.py|_tempita\.py|^_looper\.py$)
 
 detailed-errors = 1
 with-doctest = 1
@@ -30,4 +30,4 @@ doctest-fixtures = _fixture
 
 [flake8]
 exclude = __init__.py,*externals*,constants.py,fixes.py
-ignore = E241
+ignore = E241,E305

setup.py

@@ -1,5 +1,4 @@
 #! /usr/bin/env python
-#
 
 # Copyright (C) 2011-2014 Alexandre Gramfort
 # <alexandre.gramfort@telecom-paristech.fr>