1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
|
"""Tools for creating Raw objects from numpy arrays."""
# Authors: Eric Larson <larson.eric.d@gmail.com>
#
# License: BSD (3-clause)
import numpy as np
from ..base import BaseRaw
from ...utils import verbose, logger, _validate_type, fill_doc, _check_option
@fill_doc
class RawArray(BaseRaw):
"""Raw object from numpy array.
Parameters
----------
data : array, shape (n_channels, n_times)
The channels' time series. See notes for proper units of measure.
info : instance of Info
Info dictionary. Consider using :func:`mne.create_info` to populate
this structure. This may be modified in place by the class.
first_samp : int
First sample offset used during recording (default 0).
.. versionadded:: 0.12
copy : {'data', 'info', 'both', 'auto', None}
Determines what gets copied on instantiation. "auto" (default)
will copy info, and copy "data" only if necessary to get to
double floating point precision.
.. versionadded:: 0.18
%(verbose)s
Notes
-----
Proper units of measure:
* V: eeg, eog, seeg, emg, ecg, bio, ecog
* T: mag
* T/m: grad
* M: hbo, hbr
* Am: dipole
* AU: misc
See Also
--------
mne.EpochsArray
mne.EvokedArray
mne.create_info
"""
@verbose
def __init__(self, data, info, first_samp=0, copy='auto',
verbose=None): # noqa: D102
_validate_type(info, "info")
_check_option('copy', copy, ('data', 'info', 'both', 'auto', None))
dtype = np.complex128 if np.any(np.iscomplex(data)) else np.float64
orig_data = data
data = np.asanyarray(orig_data, dtype=dtype)
if data.ndim != 2:
raise ValueError('Data must be a 2D array of shape (n_channels, '
'n_samples), got shape %s' % (data.shape,))
if len(data) != len(info['ch_names']):
raise ValueError('len(data) (%s) does not match '
'len(info["ch_names"]) (%s)'
% (len(data), len(info['ch_names'])))
assert len(info['ch_names']) == info['nchan']
if copy in ('auto', 'info', 'both'):
info = info.copy()
if copy in ('data', 'both'):
if data is orig_data:
data = data.copy()
elif copy != 'auto' and data is not orig_data:
raise ValueError('data copying was not requested by copy=%r but '
'it was required to get to double floating point '
'precision' % (copy,))
logger.info('Creating RawArray with %s data, n_channels=%s, n_times=%s'
% (dtype.__name__, data.shape[0], data.shape[1]))
super(RawArray, self).__init__(info, data,
first_samps=(int(first_samp),),
dtype=dtype, verbose=verbose)
logger.info(' Range : %d ... %d = %9.3f ... %9.3f secs' % (
self.first_samp, self.last_samp,
float(self.first_samp) / info['sfreq'],
float(self.last_samp) / info['sfreq']))
logger.info('Ready.')
|
