initial commit

2025-08-19 09:13:22 -07:00
parent 28464811d6
commit 0977a3e14d
820 changed files with 1003358 additions and 2 deletions
--- a/mne/io/array/array.py
+++ b/mne/io/array/array.py
@@ -0,0 +1,96 @@
+"""Tools for creating Raw objects from numpy arrays."""
+
+# Authors: The MNE-Python contributors.
+# License: BSD-3-Clause
+# Copyright the MNE-Python contributors.
+
+import numpy as np
+
+from ...utils import _check_option, _validate_type, fill_doc, logger, verbose
+from ..base import BaseRaw
+
+
+@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_not_none)s 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
+
+    See Also
+    --------
+    mne.EpochsArray
+    mne.EvokedArray
+    mne.create_info
+
+    Notes
+    -----
+    Proper units of measure:
+
+    * V: eeg, eog, seeg, dbs, emg, ecg, bio, ecog
+    * T: mag
+    * T/m: grad
+    * M: hbo, hbr
+    * Am: dipole
+    * AU: misc
+    """
+
+    @verbose
+    def __init__(self, data, info, first_samp=0, copy="auto", verbose=None):
+        _validate_type(info, "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 "
+                f"{data.shape}"
+            )
+        if len(data) != len(info["ch_names"]):
+            raise ValueError(
+                'len(data) ({}) does not match len(info["ch_names"]) ({})'.format(
+                    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(
+                f"data copying was not requested by copy={copy!r} but it was required "
+                "to get to double floating point precision"
+            )
+        logger.info(
+            f"Creating RawArray with {dtype.__name__} data, "
+            f"n_channels={data.shape[0]}, n_times={data.shape[1]}"
+        )
+        super().__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.")