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"""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
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
verbose : bool, str, int, or None
If not None, override default verbose level (see :func:`mne.verbose`
and :ref:`Logging documentation <tut_logging>` for more).
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, verbose=None): # noqa: D102
_validate_type(info, "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) (%s) does not match '
'len(info["ch_names"]) (%s)'
% (len(data), len(info['ch_names'])))
assert len(info['ch_names']) == info['nchan']
info = info.copy() # do not modify original info
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.')
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