99 lines
3.1 KiB
Python
99 lines
3.1 KiB
Python
"""Tools for creating Raw objects from numpy arrays."""
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# Authors: The MNE-Python contributors.
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# License: BSD-3-Clause
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# Copyright the MNE-Python contributors.
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import numpy as np
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from ...utils import _check_option, _validate_type, fill_doc, logger, verbose
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from ..base import BaseRaw
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@fill_doc
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class RawArray(BaseRaw):
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"""Raw object from numpy array.
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Parameters
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----------
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data : array, shape (n_channels, n_times)
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The channels' time series. See notes for proper units of measure.
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%(info_not_none)s Consider using :func:`mne.create_info` to populate
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this structure. This may be modified in place by the class.
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first_samp : int
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First sample offset used during recording (default 0).
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.. versionadded:: 0.12
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copy : {'data', 'info', 'both', 'auto', None}
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Determines what gets copied on instantiation. "auto" (default)
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will copy info, and copy "data" only if necessary to get to
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double floating point precision.
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.. versionadded:: 0.18
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%(verbose)s
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See Also
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--------
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mne.EpochsArray
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mne.EvokedArray
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mne.create_info
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Notes
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-----
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Proper units of measure:
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* V: eeg, eog, seeg, dbs, emg, ecg, bio, ecog
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* T: mag
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* T/m: grad
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* M: hbo, hbr
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* Am: dipole
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* AU: misc
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"""
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@verbose
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def __init__(self, data, info, first_samp=0, copy="auto", verbose=None):
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_validate_type(info, "info", "info")
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_check_option("copy", copy, ("data", "info", "both", "auto", None))
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dtype = np.complex128 if np.any(np.iscomplex(data)) else np.float64
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orig_data = data
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data = np.asanyarray(orig_data, dtype=dtype)
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if data.ndim != 2:
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raise ValueError(
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"Data must be a 2D array of shape (n_channels, n_samples), got shape "
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f"{data.shape}"
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)
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if len(data) != len(info["ch_names"]):
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raise ValueError(
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'len(data) ({}) does not match len(info["ch_names"]) ({})'.format(
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len(data), len(info["ch_names"])
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)
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)
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assert len(info["ch_names"]) == info["nchan"]
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if copy in ("auto", "info", "both"):
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info = info.copy()
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if copy in ("data", "both"):
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if data is orig_data:
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data = data.copy()
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elif copy != "auto" and data is not orig_data:
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raise ValueError(
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f"data copying was not requested by copy={copy!r} but it was required "
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"to get to double floating point precision"
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)
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logger.info(
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f"Creating RawArray with {dtype.__name__} data, "
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f"n_channels={data.shape[0]}, n_times={data.shape[1]}"
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)
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super().__init__(
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info, data, first_samps=(int(first_samp),), dtype=dtype, verbose=verbose
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)
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logger.info(
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" Range : %d ... %d = %9.3f ... %9.3f secs"
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% (
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self.first_samp,
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self.last_samp,
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float(self.first_samp) / info["sfreq"],
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float(self.last_samp) / info["sfreq"],
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)
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)
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logger.info("Ready.")
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