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/eximia/eximia.py
+++ b/mne/io/eximia/eximia.py
@@ -0,0 +1,103 @@
+# Authors: The MNE-Python contributors.
+# License: BSD-3-Clause
+# Copyright the MNE-Python contributors.
+
+import os.path as op
+
+from ..._fiff.meas_info import create_info
+from ..._fiff.utils import _file_size, _read_segments_file
+from ...utils import _check_fname, fill_doc, logger, verbose, warn
+from ..base import BaseRaw
+
+
+@fill_doc
+def read_raw_eximia(fname, preload=False, verbose=None) -> "RawEximia":
+    """Reader for an eXimia EEG file.
+
+    Parameters
+    ----------
+    fname : path-like
+        Path to the eXimia ``.nxe`` data file.
+    %(preload)s
+    %(verbose)s
+
+    Returns
+    -------
+    raw : instance of RawEximia
+        A Raw object containing eXimia data.
+        See :class:`mne.io.Raw` for documentation of attributes and methods.
+
+    See Also
+    --------
+    mne.io.Raw : Documentation of attributes and methods of RawEximia.
+    """
+    return RawEximia(fname, preload, verbose)
+
+
+@fill_doc
+class RawEximia(BaseRaw):
+    """Raw object from an Eximia EEG file.
+
+    Parameters
+    ----------
+    fname : path-like
+        Path to the eXimia data file (.nxe).
+    %(preload)s
+    %(verbose)s
+
+    See Also
+    --------
+    mne.io.Raw : Documentation of attributes and methods.
+    """
+
+    @verbose
+    def __init__(self, fname, preload=False, verbose=None):
+        fname = str(_check_fname(fname, "read", True, "fname"))
+        data_name = op.basename(fname)
+        logger.info(f"Loading {data_name}")
+        # Create vhdr and vmrk files so that we can use mne_brain_vision2fiff
+        n_chan = 64
+        sfreq = 1450.0
+        # data are multiplexed int16
+        ch_names = ["GateIn", "Trig1", "Trig2", "EOG"]
+        ch_types = ["stim", "stim", "stim", "eog"]
+        cals = [
+            0.0015259021896696422,
+            0.0015259021896696422,
+            0.0015259021896696422,
+            0.3814755474174106,
+        ]
+        ch_names += (
+            "Fp1 Fpz Fp2 AF1 AFz AF2 "
+            "F7 F3 F1 Fz F2 F4 F8 "
+            "FT9 FT7 FC5 FC3 FC1 FCz FC2 FC4 FC6 FT8 FT10 "
+            "T7 C5 C3 C1 Cz C2 C4 C6 T8 "
+            "TP9 TP7 CP5 CP3 CP1 CPz CP2 CP4 CP6 TP8 TP10 "
+            "P9 P7 P3 P1 Pz P2 P4 P8 "
+            "P10 PO3 POz PO4 O1 Oz O2 Iz".split()
+        )
+        n_eeg = len(ch_names) - len(cals)
+        cals += [0.07629510948348212] * n_eeg
+        ch_types += ["eeg"] * n_eeg
+        assert len(ch_names) == n_chan
+        info = create_info(ch_names, sfreq, ch_types)
+        n_bytes = _file_size(fname)
+        n_samples, extra = divmod(n_bytes, (n_chan * 2))
+        if extra != 0:
+            warn(
+                f"Incorrect number of samples in file ({n_samples}), the file is likely"
+                " truncated"
+            )
+        for ch, cal in zip(info["chs"], cals):
+            ch["cal"] = cal
+        super().__init__(
+            info,
+            preload=preload,
+            last_samps=(n_samples - 1,),
+            filenames=[fname],
+            orig_format="short",
+        )
+
+    def _read_segment_file(self, data, idx, fi, start, stop, cals, mult):
+        """Read a chunk of raw data."""
+        _read_segments_file(self, data, idx, fi, start, stop, cals, mult, dtype="<i2")