MAINT: Backports

mne/io/ctf/info.py

@@ -296,7 +296,7 @@ def _conv_comp(comp, first, last, chs):
     col_names = comp[first]['sensors'][:n_col]
     row_names = [comp[p]['sensor_name'] for p in range(first, last + 1)]
     mask = np.in1d(col_names, ch_names)  # missing channels excluded
-    col_names = np.array(col_names)[mask]
+    col_names = np.array(col_names)[mask].tolist()
     n_col = len(col_names)
     n_row = len(row_names)
     ccomp = dict(ctfkind=np.array([comp[first]['coeff_type']]),

mne/io/egi/egi.py

@@ -63,7 +63,6 @@ def my_fread(*x, **y):
         for event in range(info['n_events']):
             event_codes = ''.join(np.fromfile(fid, 'S1', 4).astype('U1'))
             info['event_codes'].append(event_codes)
-        info['event_codes'] = np.array(info['event_codes'])
     else:
         raise NotImplementedError('Only continuous files are supported')
     info['unsegmented'] = unsegmented

mne/io/egi/events.py

@@ -25,7 +25,7 @@ def _read_events(input_fname, info):
     mff_events, event_codes = _read_mff_events(input_fname, info['sfreq'],
                                                info['n_samples'])
     info['n_events'] = len(event_codes)
-    info['event_codes'] = np.asarray(event_codes).astype('<U4')
+    info['event_codes'] = event_codes
     events = np.zeros([info['n_events'],
                       info['n_segments'] * info['n_samples']])
     for n, event in enumerate(event_codes):

mne/io/meas_info.py

@@ -21,7 +21,8 @@
 from .open import fiff_open
 from .tree import dir_tree_find
 from .tag import read_tag, find_tag, _coord_dict
-from .proj import _read_proj, _write_proj, _uniquify_projs, _normalize_proj
+from .proj import (_read_proj, _write_proj, _uniquify_projs, _normalize_proj,
+                   Projection)
 from .ctf_comp import read_ctf_comp, write_ctf_comp
 from .write import (start_file, end_file, start_block, end_block,
                     write_string, write_dig_points, write_float, write_int,
@@ -31,7 +32,7 @@
 from ..transforms import invert_transform, Transform, _coord_frame_name
 from ..utils import (logger, verbose, warn, object_diff, _validate_type,
                      _stamp_to_dt, _dt_to_stamp, _pl, _is_numeric)
-from ._digitization import (_format_dig_points, _dig_kind_proper,
+from ._digitization import (_format_dig_points, _dig_kind_proper, DigPoint,
                             _dig_kind_rev, _dig_kind_ints, _read_dig_fif)
 from ._digitization import write_dig as _dig_write_dig
 from .compensator import get_current_comp
@@ -190,6 +191,16 @@ def set_montage(self, montage, raise_if_subset=DEPRECATED_PARAM,
         return self
 
 
+def _format_trans(obj, key):
+    try:
+        t = obj[key]
+    except KeyError:
+        pass
+    else:
+        if t is not None:
+            obj[key] = Transform(t['from'], t['to'], t['trans'])
+
+
 # XXX Eventually this should be de-duplicated with the MNE-MATLAB stuff...
 class Info(dict, MontageMixin):
     """Measurement information.
@@ -528,9 +539,24 @@ class Info(dict, MontageMixin):
 
     def __init__(self, *args, **kwargs):
         super(Info, self).__init__(*args, **kwargs)
-        t = self.get('dev_head_t', None)
-        if t is not None and not isinstance(t, Transform):
-            self['dev_head_t'] = Transform(t['from'], t['to'], t['trans'])
+        # Deal with h5io writing things as dict
+        for key in ('dev_head_t', 'ctf_head_t', 'dev_ctf_t'):
+            _format_trans(self, key)
+        for res in self.get('hpi_results', []):
+            _format_trans(res, 'coord_trans')
+        if self.get('dig', None) is not None and len(self['dig']) and \
+                not isinstance(self['dig'][0], DigPoint):
+            self['dig'] = _format_dig_points(self['dig'])
+        for pi, proj in enumerate(self.get('projs', [])):
+            if not isinstance(proj, Projection):
+                self['projs'][pi] = Projection(proj)
+        # Old files could have meas_date as tuple instead of datetime
+        try:
+            meas_date = self['meas_date']
+        except KeyError:
+            pass
+        else:
+            self['meas_date'] = _ensure_meas_date_none_or_dt(meas_date)
 
     def copy(self):
         """Copy the instance.
@@ -1362,11 +1388,7 @@ def read_meas_info(fid, tree, clean_bads=False, verbose=None):
     info['proj_name'] = proj_name
     if meas_date is None:
         meas_date = (info['meas_id']['secs'], info['meas_id']['usecs'])
-    if np.array_equal(meas_date, DATE_NONE):
-        meas_date = None
-    else:
-        meas_date = _stamp_to_dt(meas_date)
-    info['meas_date'] = meas_date
+    info['meas_date'] = _ensure_meas_date_none_or_dt(meas_date)
     info['utc_offset'] = utc_offset
 
     info['sfreq'] = sfreq
@@ -1408,6 +1430,14 @@ def read_meas_info(fid, tree, clean_bads=False, verbose=None):
     return info, meas
 
 
+def _ensure_meas_date_none_or_dt(meas_date):
+    if meas_date is None or np.array_equal(meas_date, DATE_NONE):
+        meas_date = None
+    elif not isinstance(meas_date, datetime.datetime):
+        meas_date = _stamp_to_dt(meas_date)
+    return meas_date
+
+
 def _check_dates(info, prepend_error=''):
     """Check dates before writing as fif files.
 

mne/io/tests/test_raw.py

@@ -16,8 +16,10 @@
 
 from mne import concatenate_raws, create_info, Annotations
 from mne.datasets import testing
-from mne.io import read_raw_fif, RawArray, BaseRaw
-from mne.utils import _TempDir, catch_logging, _raw_annot, _stamp_to_dt
+from mne.externals.h5io import read_hdf5, write_hdf5
+from mne.io import read_raw_fif, RawArray, BaseRaw, Info
+from mne.utils import (_TempDir, catch_logging, _raw_annot, _stamp_to_dt,
+                       object_diff, check_version)
 from mne.io.meas_info import _get_valid_units
 from mne.io._digitization import DigPoint
 
@@ -169,6 +171,13 @@ def _test_raw_reader(reader, test_preloading=True, test_kwargs=True,
         for ch_name, unit in raw._orig_units.items():
             assert unit.lower() in valid_units_lower, ch_name
 
+    # Make sure that writing info to h5 format
+    # (all fields should be compatible)
+    if check_version('h5py'):
+        fname_h5 = op.join(tempdir, 'info.h5')
+        write_hdf5(fname_h5, raw.info)
+        new_info = Info(read_hdf5(fname_h5))
+        assert object_diff(new_info, raw.info) == ''
     return raw
 
 

mne/tests/test_bem.py

@@ -247,28 +247,34 @@ def test_fit_sphere_to_headshape():
         # Top of the head (extra point)
         {'coord_frame': FIFF.FIFFV_COORD_HEAD,
          'kind': FIFF.FIFFV_POINT_EXTRA,
+         'ident': 0,
          'r': np.array([0.0, 0.0, 1.0])},
 
         # EEG points
         # Fz
         {'coord_frame': FIFF.FIFFV_COORD_HEAD,
          'kind': FIFF.FIFFV_POINT_EEG,
+         'ident': 0,
          'r': np.array([0, .72, .69])},
         # F3
         {'coord_frame': FIFF.FIFFV_COORD_HEAD,
          'kind': FIFF.FIFFV_POINT_EEG,
+         'ident': 1,
          'r': np.array([-.55, .67, .50])},
         # F4
         {'coord_frame': FIFF.FIFFV_COORD_HEAD,
          'kind': FIFF.FIFFV_POINT_EEG,
+         'ident': 2,
          'r': np.array([.55, .67, .50])},
         # Cz
         {'coord_frame': FIFF.FIFFV_COORD_HEAD,
          'kind': FIFF.FIFFV_POINT_EEG,
+         'ident': 3,
          'r': np.array([0.0, 0.0, 1.0])},
         # Pz
         {'coord_frame': FIFF.FIFFV_COORD_HEAD,
          'kind': FIFF.FIFFV_POINT_EEG,
+         'ident': 4,
          'r': np.array([0, -.72, .69])},
     ]
     for d in dig:

mne/time_frequency/tests/test_tfr.py

@@ -409,7 +409,9 @@ def test_io():
 
     info = mne.create_info(['MEG 001', 'MEG 002', 'MEG 003'], 1000.,
                            ['mag', 'mag', 'mag'])
-    info['meas_date'] = datetime.datetime(year=2020, month=2, day=5)
+    info['meas_date'] = datetime.datetime(year=2020, month=2, day=5,
+                                          tzinfo=datetime.timezone.utc)
+    info._check_consistency()
     tfr = AverageTFR(info, data=data, times=times, freqs=freqs,
                      nave=20, comment='test', method='crazy-tfr')
     tfr.save(fname)
@@ -426,6 +428,8 @@ def test_io():
     pytest.raises(IOError, tfr.save, fname)
 
     tfr.comment = None
+    # test old meas_date
+    info['meas_date'] = (1, 2)
     tfr.save(fname, overwrite=True)
     assert_equal(read_tfrs(fname, condition=0).comment, tfr.comment)
     tfr.comment = 'test-A'

mne/time_frequency/tfr.py

@@ -2294,6 +2294,7 @@ def read_tfrs(fname, condition=None):
     tfr_data = read_hdf5(fname, title='mnepython', slash='replace')
     for k, tfr in tfr_data:
         tfr['info'] = Info(tfr['info'])
+        tfr['info']._check_consistency()
         if 'metadata' in tfr:
             tfr['metadata'] = _prepare_read_metadata(tfr['metadata'])
     is_average = 'nave' in tfr