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
|
"""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 ..meas_info import Info
from ...utils import verbose, logger
class RawArray(_BaseRaw):
"""Raw object from numpy array
Parameters
----------
data : array, shape (n_channels, n_times)
The channels' time series.
info : instance of Info
Info dictionary. Consider using `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
verbose : bool, str, int, or None
If not None, override default verbose level (see mne.verbose).
See Also
--------
EpochsArray, EvokedArray, create_info
"""
@verbose
def __init__(self, data, info, first_samp=0, verbose=None):
if not isinstance(info, Info):
raise TypeError('info must be an instance of Info, got %s'
% type(info))
dtype = np.complex128 if np.any(np.iscomplex(data)) else np.float64
data = np.asanyarray(data, dtype=dtype)
if data.ndim != 2:
raise ValueError('Data must be a 2D array of shape (n_channels, '
'n_samples')
logger.info('Creating RawArray with %s data, n_channels=%s, n_times=%s'
% (dtype.__name__, data.shape[0], data.shape[1]))
if len(data) != len(info['ch_names']):
raise ValueError('len(data) does not match len(info["ch_names"])')
assert len(info['ch_names']) == info['nchan']
if info.get('buffer_size_sec', None) is None:
info['buffer_size_sec'] = 1. # reasonable default
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.')
|
