feat: create cropped mne from trc

micromed_io/to_mne.py

@@ -1,57 +1,71 @@
 """Micromed module to load and transform data from Micromed recordings to mne format"""
-from datetime import timezone
+from datetime import timedelta, timezone
 from pathlib import Path
 from typing import List, Union
 
 import mne
 import numpy as np
+
 from micromed_io.trc import MicromedTRC
 
 
 def create_mne_from_micromed_recording(
     recording_file: Union[str, Path],
     sub_channels: List[str] = None,
+    start_time: float = 0.0,
+    stop_time: float = None,
     ch_types: Union[List[str], str] = "eeg",
 ) -> mne.io.RawArray:
-    """Create a mne Raw instance from a Micromed recording
+    """Create a mne Raw instance from a Micromed recording.
 
     Parameters
     ----------
     recording_file : Union[str, Path]
-        The micromed recording file
+        The micromed recording file.
     sub_channels : List[str], optional
         The channels to pick from the recording. If None, all channels are picked.
-    ch_types: Union[List[str], str], optional
-        The list of channel types. Types must be in ``['grad', 'mag', 'ref_meg', 'eeg',
+    start_time : float, optional
+        The start time (in seconds) of the recording data to include in the mne Raw instance.
+        Defaults to 0.0.
+    stop_time : float, optional
+        The stop time (in seconds) of the recording data to include in the mne Raw instance.
+        If None, all data until the end of the recording is included. Defaults to None.
+    ch_types : Union[List[str], str], optional
+        The list of channel types. Types must be in ['grad', 'mag', 'ref_meg', 'eeg',
         'seeg', 'dbs', 'ecog', 'eog', 'emg', 'ecg', 'resp', 'bio', 'misc', 'stim', 'exci',
         'syst', 'ias', 'gof', 'dipole', 'chpi', 'fnirs_cw_amplitude', 'fnirs_fd_ac_amplitude',
-        'fnirs_fd_phase', 'fnirs_od', 'hbo', 'hbr', 'csd']``
+        'fnirs_fd_phase', 'fnirs_od', 'hbo', 'hbr', 'csd'].
 
     Returns
     -------
     mne.io.RawArray
-        A mne Raw instance containing the requested channels
+        A mne Raw instance containing the requested channels.
 
     Notes
     -----
     Some info are hardcoded, such as:
 
-    - ``device_info`` type: Micromed
-    - ``device_info`` site: Unknown
+    - `device_info` type: Micromed
+    - `device_info` site: Unknown
 
-    Update the code if needed
+    Update the code if needed.
 
     Examples
     --------
     >>> from micromed_io.to_mne import create_mne_from_micromed_recording
-    >>> mne_raw = create_mne_from_micromed_recording("path/to/file.TRC")
+    >>> mne_raw = create_mne_from_micromed_recording("path/to/file.TRC", start_time=10.0, stop_time=20.0)
 
     """
     micromed_trc = MicromedTRC(recording_file)
 
     if sub_channels is None:
         sub_channels = micromed_trc.micromed_header.ch_names
-    sub_eegs = micromed_trc.get_data(picks=sub_channels)
+    sfreq = micromed_trc.get_sfreq()
+    start_sample = int(start_time * sfreq)
+    stop_sample = int(stop_time * sfreq) if stop_time is not None else None
+    sub_eegs = micromed_trc.get_data(
+        picks=sub_channels, start=start_sample, stop=stop_sample
+    )
 
     info = mne.create_info(
         ch_names=sub_channels,
@@ -72,20 +86,32 @@ def create_mne_from_micromed_recording(
         sub_eegs,
         info,
     )
-    raw.set_meas_date(
-        micromed_trc.micromed_header.recording_date.replace(tzinfo=timezone.utc)
-    )
-
+    # set measurement date
+    meas_date = micromed_trc.micromed_header.recording_date.replace(
+        tzinfo=timezone.utc
+    ) + timedelta(seconds=start_time)
+    raw.set_meas_date(meas_date)
+
+    # markers and notes should be added only if not in
+    # start_time-stop_time interval
+    if stop_sample is None:
+        stop_sample = np.inf
     # Add annotations from notes
     for note_sample, note_val in micromed_trc.get_notes().items():
-        raw.annotations.append(
-            onset=note_sample / info["sfreq"], duration=0, description=note_val
-        )
+        if stop_sample > note_sample >= start_sample:
+            raw.annotations.append(
+                onset=(note_sample - start_sample) / info["sfreq"],
+                duration=0,
+                description=note_val,
+            )
 
     # Add annotations from markers
     for marker_sample, marker_val in micromed_trc.get_markers().items():
-        raw.annotations.append(
-            onset=marker_sample / info["sfreq"], duration=0, description=marker_val
-        )
+        if stop_sample > marker_sample >= start_sample:
+            raw.annotations.append(
+                onset=(marker_sample - start_sample) / info["sfreq"],
+                duration=0,
+                description=marker_val,
+            )
 
     return raw