WIP add load.cnd()

doc/reference.rst

@@ -86,6 +86,7 @@ Functions and modules for loading specific file formats as Eelbrain object:
    load.eyelink
    load.fiff
    load.txt
+   load.cnd
    load.besa
 
 

eelbrain/_io/cnd.py

@@ -0,0 +1,88 @@
+# Author: Christian Brodbeck <christianbrodbeck@nyu.edu>
+"""Continuous neural data (CND) format used for mTRF-Toolbox"""
+from pathlib import Path
+from typing import Optional
+
+from mne.externals.pymatreader import read_mat
+import numpy
+
+from .._data_obj import Dataset, Factor, NDVar, Sensor, UTS, Var
+from .._types import PathArg
+from .._utils import ui
+
+
+FILETYPES = [("CND files", "*.mat")]
+
+
+def read_cnd(
+        filename: PathArg = None,
+) -> Optional[Dataset]:
+    """Load continuous neural data (CND) file used in the mTRF-Toolbox
+
+    Parameters
+    ----------
+    filename
+        Path to the data file (``*.mat``). If unspecified, open a file dialog.
+
+    Notes
+    -----
+    There are two types of CND files: EEG and stimulus files.
+    EEG files will return the following contents:
+
+    ``eeg``
+        The EEG data.
+    ``stimIdxs``
+        Index of the stimulus on the given trial.
+        Indexes are adjusted for Pyton 0-based indexing.
+    ``condIdxs``
+        Index of the condition on the given trial (when present).
+        Indexes are adjusted for Pyton 0-based indexing.
+    ``condition``
+        Condition label on the given trial (when present).
+    """
+    if filename is None:
+        path = ui.ask_file("Load CND File", "Select CND file to load as NDVar", FILETYPES)
+        if not path:
+            return
+    else:
+        path = Path(filename)
+        if not path.suffix and not path.exists():
+            path = path.with_suffix('.mat')
+    data = read_mat(path)
+    if 'eeg' in data:
+        # EEG data
+        locs = numpy.vstack([data['eeg']['chanlocs'][coord] for coord in 'XYZ']).T
+        sensor = Sensor(locs, data['eeg']['chanlocs']['labels'])
+        eeg = []
+        for trial_data in data['eeg']['data']:
+            uts = UTS(0, 1 / data['eeg']['fs'], trial_data.shape[0])
+            eeg.append(NDVar(trial_data, (uts, sensor), 'eeg'))
+        # Extra channels
+        ds = Dataset({
+            'eeg': eeg,
+            'stimIdxs': Var(data['eeg']['stimIdxs'] - 1),
+        })
+        if 'reRef' in data['eeg']:
+            ds.info['reRef'] = data['eeg']['reRef']
+        if 'condIdxs' in data['eeg']:
+            ds['condIdxs'] = Var(data['eeg']['condIdxs'] - 1)
+            labels = dict(enumerate(data['eeg']['condNames'], 1))
+            ds['condition'] = Factor(data['eeg']['condIdxs'], labels=labels)
+        return ds
+    if 'stim' in data:
+        ds = Dataset()
+        for stim_data in data['stim']:
+            if 'fs' in stim_data:
+                key = Dataset.as_key(stim_data['name'])
+                trials = []
+                for trial_data in stim_data['data']:
+                    uts = UTS(0, 1 / stim_data['fs'], trial_data.shape[0])
+                    trials.append(NDVar(trial_data, uts))
+                ds[key] = trials
+            else:
+                ds.info[stim_data['name']] = stim_data['data']
+        return ds
+    raise IOError("File contains neither 'eeg' or 'stim' entry")
+
+
+

eelbrain/load/__init__.py

@@ -21,6 +21,7 @@
 from . import txt
 
 from .txt import tsv
+from .._io.cnd import read_cnd as cnd
 from .._io.feather import load_feather as feather
 from .._io.pickle import unpickle, update_subjects_dir, convert_pickle_protocol
 from .._io.pyarrow_context import load_arrow as arrow