diff --git a/cov.ipynb b/cov.ipynb new file mode 100644 index 0000000..b98852f --- /dev/null +++ b/cov.ipynb @@ -0,0 +1,644 @@ +{ + "cells": [ + { + "cell_type": "code", + "execution_count": 1, + "id": "34355f28", + "metadata": {}, + "outputs": [ + { + "ename": "FileNotFoundError", + "evalue": "[Errno 2] Unable to synchronously open file (unable to open file: name = 'c:\\Users\\victor.ferat\\Documents\\Github\\gedai\\gedai\\data\\fsavLEADFIELD_4_GEDAI.mat', errno = 2, error message = 'No such file or directory', flags = 0, o_flags = 0)", + "output_type": "error", + "traceback": [ + "\u001b[31m---------------------------------------------------------------------------\u001b[39m", + "\u001b[31mFileNotFoundError\u001b[39m Traceback (most recent call last)", + "\u001b[36mCell\u001b[39m\u001b[36m \u001b[39m\u001b[32mIn[1]\u001b[39m\u001b[32m, line 25\u001b[39m\n\u001b[32m 20\u001b[39m \u001b[38;5;28;01mreturn\u001b[39;00m (leadfield_gain_matrix, leadfield_ch_names)\n\u001b[32m 23\u001b[39m mat = os.path.abspath(\u001b[33m\"\u001b[39m\u001b[33mgedai/data/fsavLEADFIELD_4_GEDAI.mat\u001b[39m\u001b[33m\"\u001b[39m)\n\u001b[32m---> \u001b[39m\u001b[32m25\u001b[39m leadfield_gain_matrix, leadfield_ch_names = \u001b[43m_compute_refcov\u001b[49m\u001b[43m(\u001b[49m\u001b[43mmat\u001b[49m\u001b[43m)\u001b[49m\n", + "\u001b[36mCell\u001b[39m\u001b[36m \u001b[39m\u001b[32mIn[1]\u001b[39m\u001b[32m, line 8\u001b[39m, in \u001b[36m_compute_refcov\u001b[39m\u001b[34m(mat)\u001b[39m\n\u001b[32m 7\u001b[39m \u001b[38;5;28;01mdef\u001b[39;00m\u001b[38;5;250m \u001b[39m\u001b[34m_compute_refcov\u001b[39m(mat):\n\u001b[32m----> \u001b[39m\u001b[32m8\u001b[39m \u001b[38;5;28;01mwith\u001b[39;00m \u001b[43mh5py\u001b[49m\u001b[43m.\u001b[49m\u001b[43mFile\u001b[49m\u001b[43m(\u001b[49m\u001b[43mmat\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[33;43m\"\u001b[39;49m\u001b[33;43mr\u001b[39;49m\u001b[33;43m\"\u001b[39;49m\u001b[43m)\u001b[49m \u001b[38;5;28;01mas\u001b[39;00m f:\n\u001b[32m 9\u001b[39m leadfield_data = f[\u001b[33m\"\u001b[39m\u001b[33mleadfield4GEDAI\u001b[39m\u001b[33m\"\u001b[39m]\n\u001b[32m 10\u001b[39m \u001b[38;5;66;03m# ch_names\u001b[39;00m\n", + "\u001b[36mFile \u001b[39m\u001b[32mc:\\Users\\victor.ferat\\Documents\\Github\\gedai\\.venv\\Lib\\site-packages\\h5py\\_hl\\files.py:555\u001b[39m, in \u001b[36mFile.__init__\u001b[39m\u001b[34m(self, name, mode, driver, libver, userblock_size, swmr, rdcc_nslots, rdcc_nbytes, rdcc_w0, track_order, fs_strategy, fs_persist, fs_threshold, fs_page_size, page_buf_size, min_meta_keep, min_raw_keep, locking, alignment_threshold, alignment_interval, meta_block_size, track_times, **kwds)\u001b[39m\n\u001b[32m 546\u001b[39m fapl = make_fapl(driver, libver, rdcc_nslots, rdcc_nbytes, rdcc_w0,\n\u001b[32m 547\u001b[39m locking, page_buf_size, min_meta_keep, min_raw_keep,\n\u001b[32m 548\u001b[39m alignment_threshold=alignment_threshold,\n\u001b[32m 549\u001b[39m alignment_interval=alignment_interval,\n\u001b[32m 550\u001b[39m meta_block_size=meta_block_size,\n\u001b[32m 551\u001b[39m **kwds)\n\u001b[32m 552\u001b[39m fcpl = make_fcpl(track_order=track_order, track_times=track_times,\n\u001b[32m 553\u001b[39m fs_strategy=fs_strategy, fs_persist=fs_persist,\n\u001b[32m 554\u001b[39m fs_threshold=fs_threshold, fs_page_size=fs_page_size)\n\u001b[32m--> \u001b[39m\u001b[32m555\u001b[39m fid = \u001b[43mmake_fid\u001b[49m\u001b[43m(\u001b[49m\u001b[43mname\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mmode\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43muserblock_size\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mfapl\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mfcpl\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mswmr\u001b[49m\u001b[43m=\u001b[49m\u001b[43mswmr\u001b[49m\u001b[43m)\u001b[49m\n\u001b[32m 557\u001b[39m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;28misinstance\u001b[39m(libver, \u001b[38;5;28mtuple\u001b[39m):\n\u001b[32m 558\u001b[39m \u001b[38;5;28mself\u001b[39m._libver = libver\n", + "\u001b[36mFile \u001b[39m\u001b[32mc:\\Users\\victor.ferat\\Documents\\Github\\gedai\\.venv\\Lib\\site-packages\\h5py\\_hl\\files.py:232\u001b[39m, in \u001b[36mmake_fid\u001b[39m\u001b[34m(name, mode, userblock_size, fapl, fcpl, swmr)\u001b[39m\n\u001b[32m 230\u001b[39m \u001b[38;5;28;01mif\u001b[39;00m swmr:\n\u001b[32m 231\u001b[39m flags |= h5f.ACC_SWMR_READ\n\u001b[32m--> \u001b[39m\u001b[32m232\u001b[39m fid = \u001b[43mh5f\u001b[49m\u001b[43m.\u001b[49m\u001b[43mopen\u001b[49m\u001b[43m(\u001b[49m\u001b[43mname\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mflags\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mfapl\u001b[49m\u001b[43m=\u001b[49m\u001b[43mfapl\u001b[49m\u001b[43m)\u001b[49m\n\u001b[32m 233\u001b[39m \u001b[38;5;28;01melif\u001b[39;00m mode == \u001b[33m'\u001b[39m\u001b[33mr+\u001b[39m\u001b[33m'\u001b[39m:\n\u001b[32m 234\u001b[39m fid = h5f.open(name, h5f.ACC_RDWR, fapl=fapl)\n", + "\u001b[36mFile \u001b[39m\u001b[32mh5py/_objects.pyx:54\u001b[39m, in \u001b[36mh5py._objects.with_phil.wrapper\u001b[39m\u001b[34m()\u001b[39m\n", + "\u001b[36mFile \u001b[39m\u001b[32mh5py/_objects.pyx:55\u001b[39m, in \u001b[36mh5py._objects.with_phil.wrapper\u001b[39m\u001b[34m()\u001b[39m\n", + "\u001b[36mFile \u001b[39m\u001b[32mh5py/h5f.pyx:106\u001b[39m, in \u001b[36mh5py.h5f.open\u001b[39m\u001b[34m()\u001b[39m\n", + "\u001b[31mFileNotFoundError\u001b[39m: [Errno 2] Unable to synchronously open file (unable to open file: name = 'c:\\Users\\victor.ferat\\Documents\\Github\\gedai\\gedai\\data\\fsavLEADFIELD_4_GEDAI.mat', errno = 2, error message = 'No such file or directory', flags = 0, o_flags = 0)" + ] + } + ], + "source": [ + "import os\n", + "import h5py\n", + "import numpy as np\n", + "import sklearn.metrics\n", + "\n", + "\n", + "def _compute_refcov(mat):\n", + " with h5py.File(mat, \"r\") as f:\n", + " leadfield_data = f[\"leadfield4GEDAI\"]\n", + " # ch_names\n", + " leadfield_channel_data = leadfield_data[\"electrodes\"]\n", + " leadfield_ch_names = [\n", + " f[ref[0]][()].tobytes().decode(\"utf-16le\").lower()\n", + " for ref in leadfield_channel_data[\"Name\"]\n", + " ]\n", + " # leadfield matrix\n", + " leadfield_gain_matrix = leadfield_data[\"gram_matrix_avref\"]\n", + " leadfield_gain_matrix = np.array(leadfield_gain_matrix).T\n", + "\n", + " return (leadfield_gain_matrix, leadfield_ch_names)\n", + "\n", + "\n", + "mat = os.path.abspath(\"gedai/data/fsavLEADFIELD_4_GEDAI.mat\")\n", + "\n", + "leadfield_gain_matrix, leadfield_ch_names = _compute_refcov(mat)\n" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "0e9ab2f0", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Overwriting existing file.\n", + "Overwriting existing file.\n" + ] + } + ], + "source": [ + "import mne\n", + "cov = mne.Covariance(data=leadfield_gain_matrix, names=leadfield_ch_names, bads=[], projs=[], nfree=0)\n", + "cov.save(\"gedai/data/fsavLEADFIELD_4_GEDAI-cov.fif\", overwrite=True)" + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "id": "7b375368", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + " 343 x 343 full covariance (kind = 1) found.\n" + ] + }, + { + "data": { + "text/plain": [ + "array([[211445.51956533, 203627.13517374, 179207.40685434, ...,\n", + " 46161.24641791, 81541.38225979, 62601.30358432],\n", + " [203627.13517374, 217740.51155493, 204890.52680889, ...,\n", + " 44272.33593595, 63394.31624565, 62335.98240826],\n", + " [179207.40685434, 204890.52680889, 212561.69979064, ...,\n", + " 61993.43555224, 63328.37347126, 79972.56331383],\n", + " ...,\n", + " [ 46161.24641791, 44272.33593595, 61993.43555224, ...,\n", + " 186070.80794079, 134148.19067043, 179981.34245703],\n", + " [ 81541.38225979, 63394.31624565, 63328.37347126, ...,\n", + " 134148.19067043, 175405.84685218, 134079.62220867],\n", + " [ 62601.30358432, 62335.98240826, 79972.56331383, ...,\n", + " 179981.34245703, 134079.62220867, 177887.20703003]],\n", + " shape=(343, 343))" + ] + }, + "execution_count": 2, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "import mne\n", + "cov = mne.read_cov(\"gedai/data/fsavLEADFIELD_4_GEDAI-cov.fif\")\n", + "cov.data" + ] + }, + { + "cell_type": "code", + "execution_count": 11, + "id": "5e118897", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Creating RawArray with float64 data, n_channels=343, n_times=1\n", + " Range : 0 ... 0 = 0.000 ... 0.000 secs\n", + "Ready.\n" + ] + }, + { + "data": { + "text/html": [ + "\n", + "\n", + "\n", + "\n", + "\n", + "\n", + "\n", + " \n", + "\n", + "\n", + "\n", + "\n", + "\n", + "\n", + "\n", + "\n", + " \n", + " \n", + 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MNE object typeRawArray
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ExperimenterUnknown
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Duration00:00:01 (HH:MM:SS)
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Head & sensor digitization346 points
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" + ], + "text/plain": [ + "" + ] + }, + "execution_count": 11, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "raw = mne.io.RawArray(np.random.randn(len(cov.ch_names), 1), mne.create_info(cov.ch_names, sfreq=1, ch_types=\"eeg\"))\n", + "raw.set_montage(\"standard_1005\", match_case=False)" + ] + }, + { + "cell_type": "code", + "execution_count": 16, + "id": "b33a951b", + "metadata": {}, + "outputs": [], + "source": [ + "from gedai.gedai.covariances import _compute_distance_cov\n", + "\n", + "distance_cov = _compute_distance_cov(raw)\n", + "\n", + "n_channels = distance_cov.shape[0]\n", + "projection_matrix = np.eye(n_channels) - np.ones((n_channels, n_channels)) / n_channels\n", + "\n", + "# Apply average reference to the distance covariance\n", + "distance_cov_avref = projection_matrix @ distance_cov @ projection_matrix.T" + ] + }, + { + "cell_type": "code", + "execution_count": 18, + "id": "056889eb", + "metadata": {}, + "outputs": [], + "source": [ + "distance_cov = mne.Covariance(data=distance_cov_avref, names=cov.ch_names, bads=[], projs=[], nfree=0)" + ] + }, + { + "cell_type": "code", + "execution_count": 17, + "id": "459869d6", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 17, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "import matplotlib.pyplot as plt\n", + "\n", + "plt.imshow(distance_cov_avref.data, cmap=\"viridis\")" + ] + }, + { + "cell_type": "code", + "execution_count": 21, + "id": "14c1f207", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Extracting EDF parameters from C:\\Users\\victor.ferat\\mne_data\\MNE-eegbci-data\\files\\eegmmidb\\1.0.0\\S001\\S001R04.edf...\n", + "Setting channel info structure...\n", + "Creating raw.info structure...\n", + "Reading 0 ... 19999 = 0.000 ... 124.994 secs...\n", + "Extracting EDF parameters from C:\\Users\\victor.ferat\\mne_data\\MNE-eegbci-data\\files\\eegmmidb\\1.0.0\\S001\\S001R08.edf...\n", + "Setting channel info structure...\n", + "Creating raw.info structure...\n", + "Reading 0 ... 19999 = 0.000 ... 124.994 secs...\n", + "Extracting EDF parameters from C:\\Users\\victor.ferat\\mne_data\\MNE-eegbci-data\\files\\eegmmidb\\1.0.0\\S001\\S001R12.edf...\n", + "Setting channel info structure...\n", + "Creating raw.info structure...\n", + "Reading 0 ... 19999 = 0.000 ... 124.994 secs...\n", + "No projector specified for this dataset. Please consider the method self.add_proj.\n", + "Not setting metadata\n", + "29 matching events found\n", + "No baseline correction applied\n", + "0 projection items activated\n", + "Using data from preloaded Raw for 29 events and 160 original time points ...\n", + "0 bad epochs dropped\n", + "EEG channel type selected for re-referencing\n", + "Applying average reference.\n", + "Applying a custom ('EEG',) reference.\n", + "EEG channel type selected for re-referencing\n", + "Applying average reference.\n", + "Applying a custom ('EEG',) reference.\n" + ] + }, + { + "ename": "TypeError", + "evalue": "Gedai.__init__() got an unexpected keyword argument 'reference_cov'", + "output_type": "error", + "traceback": [ + "\u001b[31m---------------------------------------------------------------------------\u001b[39m", + "\u001b[31mTypeError\u001b[39m Traceback (most recent call last)", + "\u001b[36mCell\u001b[39m\u001b[36m \u001b[39m\u001b[32mIn[21]\u001b[39m\u001b[32m, line 27\u001b[39m\n\u001b[32m 24\u001b[39m gedai_broadband.fit_raw(raw, noise_multiplier=\u001b[32m6.0\u001b[39m, reference_cov=distance_cov)\n\u001b[32m 25\u001b[39m raw_broadband_corrected = gedai_broadband.transform_raw(raw, verbose=\u001b[38;5;28;01mFalse\u001b[39;00m)\n\u001b[32m---> \u001b[39m\u001b[32m27\u001b[39m gedai_spectral = \u001b[43mGedai\u001b[49m\u001b[43m(\u001b[49m\u001b[43mwavelet_type\u001b[49m\u001b[43m=\u001b[49m\u001b[33;43m\"\u001b[39;49m\u001b[33;43mhaar\u001b[39;49m\u001b[33;43m\"\u001b[39;49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mwavelet_level\u001b[49m\u001b[43m=\u001b[49m\u001b[32;43m5\u001b[39;49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mwavelet_low_cutoff\u001b[49m\u001b[43m=\u001b[49m\u001b[32;43m2\u001b[39;49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mreference_cov\u001b[49m\u001b[43m=\u001b[49m\u001b[43mdistance_cov\u001b[49m\u001b[43m)\u001b[49m\n\u001b[32m 28\u001b[39m gedai_spectral.fit_raw(raw_broadband_corrected, noise_multiplier=\u001b[32m3.0\u001b[39m)\n\u001b[32m 29\u001b[39m raw_spectral_corrected = gedai_spectral.transform_raw(\n\u001b[32m 30\u001b[39m raw_broadband_corrected, verbose=\u001b[38;5;28;01mFalse\u001b[39;00m\n\u001b[32m 31\u001b[39m )\n", + "\u001b[31mTypeError\u001b[39m: Gedai.__init__() got an unexpected keyword argument 'reference_cov'" + ] + } + ], + "source": [ + "import matplotlib.pyplot as plt\n", + "from mne.datasets import eegbci\n", + "from mne.io import concatenate_raws, read_raw_edf\n", + "\n", + "from gedai import Gedai\n", + "from gedai.viz import plot_mne_style_overlay_interactive\n", + "\n", + "# %% Load sample EEG data\n", + "subjects = [1]\n", + "runs = [4, 8, 12]\n", + "raw_fnames = eegbci.load_data(subjects, runs, update_path=True)\n", + "raws = [read_raw_edf(f, preload=True) for f in raw_fnames]\n", + "# Concatenate runs from the same subject\n", + "raw = concatenate_raws(raws)\n", + "# Make channel names follow standard conventions\n", + "eegbci.standardize(raw)\n", + "\n", + "# Crop to the first 15 seconds for demonstration purposes\n", + "raw.crop(0, 15)\n", + "raw.pick(\"eeg\").load_data().apply_proj()\n", + "\n", + "\n", + "gedai_broadband = Gedai()\n", + "gedai_broadband.fit_raw(raw, noise_multiplier=6.0, reference_cov=distance_cov)\n", + "raw_broadband_corrected = gedai_broadband.transform_raw(raw, verbose=False)\n", + "\n", + "gedai_spectral = Gedai(wavelet_type=\"haar\", wavelet_level=5, wavelet_low_cutoff=2, reference_cov=distance_cov)\n", + "gedai_spectral.fit_raw(raw_broadband_corrected, noise_multiplier=3.0)\n", + "raw_spectral_corrected = gedai_spectral.transform_raw(\n", + " raw_broadband_corrected, verbose=False\n", + ")\n", + "\n", + "plot_mne_style_overlay_interactive(raw, raw_spectral_corrected)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "e1b04b1f", + "metadata": {}, + "outputs": [], + "source": [] + } + ], + "metadata": { + "kernelspec": { + "display_name": "gedai", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.11.15" + } + }, + "nbformat": 4, + "nbformat_minor": 5 +} diff --git a/gedai/data/OPENMEEG_BEM_leadfield_4_GEDAI_343_electrodes.mat b/gedai/data/OPENMEEG_BEM_leadfield_4_GEDAI_343_electrodes.mat deleted file mode 100644 index f9e5d3d..0000000 Binary files a/gedai/data/OPENMEEG_BEM_leadfield_4_GEDAI_343_electrodes.mat and /dev/null differ diff --git a/gedai/data/fsavLEADFIELD_4_GEDAI-cov.fif b/gedai/data/fsavLEADFIELD_4_GEDAI-cov.fif new file mode 100644 index 0000000..2339aae Binary files /dev/null and b/gedai/data/fsavLEADFIELD_4_GEDAI-cov.fif differ diff --git a/gedai/data/fsavLEADFIELD_4_GEDAI.mat b/gedai/data/fsavLEADFIELD_4_GEDAI.mat deleted file mode 100644 index ccc4b80..0000000 Binary files a/gedai/data/fsavLEADFIELD_4_GEDAI.mat and /dev/null differ diff --git a/gedai/gedai/covariances.py b/gedai/gedai/covariances.py index 7470cb7..84543b9 100644 --- a/gedai/gedai/covariances.py +++ b/gedai/gedai/covariances.py @@ -1,7 +1,9 @@ -import h5py -import numpy as np +import os +import mne import sklearn.metrics +from ..utils._checks import check_type + def _compute_distance_cov(raw): ch_positions = [raw.info["chs"][i]["loc"][:3] for i in range(raw.info["nchan"])] @@ -9,101 +11,45 @@ def _compute_distance_cov(raw): ch_positions, metric="euclidean" ) cov = 1 - ch_distance_matrix + return cov -def _compute_refcov(inst, mat): - inst_ch_names = inst.info["ch_names"] - - with h5py.File(mat, "r") as f: - leadfield_data = f["leadfield4GEDAI"] - # ch_names - leadfield_channel_data = leadfield_data["electrodes"] - leadfield_ch_names = [ - f[ref[0]][()].tobytes().decode("utf-16le").lower() - for ref in leadfield_channel_data["Name"] - ] - # leadfield matrix - leadfield_gain_matrix = leadfield_data["gram_matrix_avref"] - leadfield_gain_matrix = np.array(leadfield_gain_matrix).T - - # Two-pass matching: exact first, then substring - ch_indices = [] - ch_names = [] - matched_inst_indices = set() - match_types = [] # Track match quality for logging - - # Pass 1: Exact matching (case-insensitive) - for inst_idx, inst_ch_name in enumerate(inst_ch_names): - for leadfield_ch_index, leadfield_ch_name in enumerate(leadfield_ch_names): - if inst_ch_name.lower() == leadfield_ch_name.lower(): - ch_indices.append(leadfield_ch_index) - ch_names.append(leadfield_ch_name) - matched_inst_indices.add(inst_idx) - match_types.append("exact") - break # Move to next inst channel after finding exact match - - # Pass 2: Substring matching for unmatched channels - for inst_idx, inst_ch_name in enumerate(inst_ch_names): - if inst_idx in matched_inst_indices: - continue # Already matched exactly - - inst_lower = inst_ch_name.lower() - best_match = None - best_match_length = 0 - - for leadfield_ch_index, leadfield_ch_name in enumerate(leadfield_ch_names): - leadfield_lower = leadfield_ch_name.lower() - - # Check if leadfield name is substring of inst name - # or inst name is substring of leadfield name - if leadfield_lower in inst_lower or inst_lower in leadfield_lower: - # Prefer longer matches to avoid false positives - match_length = min(len(leadfield_lower), len(inst_lower)) - if match_length > best_match_length: - best_match = leadfield_ch_index - best_match_length = match_length - - if best_match is not None: - ch_indices.append(best_match) - ch_names.append(leadfield_ch_names[best_match]) - matched_inst_indices.add(inst_idx) - match_types.append("substring") - - # Validation and warnings - n_inst_channels = len(inst_ch_names) - n_matched = len(ch_indices) - - if n_matched == 0: - raise ValueError( - f"No electrode matches found between data and leadfield " - f"template.\n" - f"Your channels: {inst_ch_names[:10]}\n" - f"Leadfield channels: {leadfield_ch_names[:10]}\n" - f"Please check that your electrode names follow standard " - f"conventions (e.g., Fp1, Fp2, F3, F4)." - ) - - # Always warn if any channels didn't match - if n_matched < n_inst_channels: - import warnings - - unmatched = [ - inst_ch_names[i] - for i in range(n_inst_channels) - if i not in matched_inst_indices - ] - n_exact = match_types.count("exact") - n_substring = match_types.count("substring") - - warnings.warn( - f"Electrode matching: {n_matched}/{n_inst_channels} channels " - f"matched ({n_exact} exact, {n_substring} substring). " - f"Unmatched channels ({len(unmatched)}): " - f"{unmatched}", - UserWarning, - stacklevel=2, - ) - - refCOV = leadfield_gain_matrix[np.ix_(ch_indices, ch_indices)] - return (refCOV, ch_names) +def _ensure_cov(reference_cov): + check_type(reference_cov, (str, mne.Covariance), "reference_cov") + if isinstance(reference_cov, str): + if reference_cov == "leadfield": + reference_cov = mne.read_cov(os.path.join(os.path.dirname(__file__), "../data/fsavLEADFIELD_4_GEDAI-cov.fif")) + else: + raise ValueError( + "Reference covariance must be 'leadfield'" + f"got '{reference_cov}' instead." + ) + return reference_cov + + +def _pick_cov(cov, ch_names): + cov_ch_names = cov.ch_names + + picks_cov = [] + picks_ch_names = [] + for cov_name in cov_ch_names: + for ch_name in ch_names: + if ch_name.lower() == cov_name.lower(): + picks_cov.append(cov_name) + picks_ch_names.append(ch_name) + break + if len(picks_cov) == 0: + raise ValueError("No matching channel names found between inst and cov.\n" + f"Available channels in covariance are {cov_ch_names}.\n" + f"but instance has channels {ch_names}.") + if len(picks_cov) < len(ch_names): + raise ValueError("Only a subset of channels in the instance are present" + " in the covariance.\n" + f"Use inst.pick_channels({picks_ch_names}) to select only the channels" + f" that are in the covariance or provide a covariance that contains" + f" all channels in the instance.") + cov = cov.copy().pick_channels(picks_cov) + # Update the channel names in the covariance to match those in the instance + cov.update(names=ch_names) + return cov diff --git a/gedai/gedai/gedai.py b/gedai/gedai/gedai.py index b748972..5bfd6e2 100644 --- a/gedai/gedai/gedai.py +++ b/gedai/gedai/gedai.py @@ -1,12 +1,12 @@ import os - +import numpy as np +from scipy.linalg import eigh import matplotlib.pyplot as plt import mne -import numpy as np -from mne import BaseEpochs +from mne._fiff.pick import _picks_to_idx +from mne import BaseEpochs, pick_info from mne.io import BaseRaw from mne.parallel import parallel_func -from scipy.linalg import eigh from ..sensai.sensai import ( _eigen_to_sensai, @@ -14,11 +14,11 @@ _sensai_optimize, _sensai_to_eigen, ) -from ..utils._checks import _check_n_jobs, check_type +from ..utils._checks import _check_n_jobs, check_type, _check_picks_uniqueness from ..utils._docs import fill_doc -from ..utils.logs import logger +from ..utils.logs import logger, verbose from ..wavelet.transform import epochs_to_wavelet -from .covariances import _compute_refcov +from .covariances import _ensure_cov, _pick_cov def create_cosine_weights(n_samples): @@ -45,7 +45,6 @@ def compute_required_duration(wavelet_level, sfreq): """ if wavelet_level == 0: return 1.0 # Default for no decomposition - # For SWT, minimum length is 2^(level+1) min_samples = 2 ** (wavelet_level + 1) duration = min_samples / sfreq @@ -109,16 +108,6 @@ def _check_sensai_method(method): f"Method must be either 'gridsearch' or 'optimize', got '{method}' instead." ) - -def _check_reference_cov(reference_cov): - check_type(reference_cov, (str,), "reference_cov") - if reference_cov not in ["leadfield"]: - raise ValueError( - "Reference covariance must be 'leadfield' for now, " - f"got '{reference_cov}' instead." - ) - - @fill_doc class Gedai: """Generalized Eigenvalue De-Artifacting Instrument (GEDAI). @@ -151,14 +140,44 @@ class Gedai: """ def __init__(self, wavelet_type="haar", wavelet_level=0, wavelet_low_cutoff=None): + self.fitted = False self.wavelet_type = wavelet_type self.wavelet_level = wavelet_level self.wavelet_low_cutoff = wavelet_low_cutoff + self._wavelets_fits = None + self._reference_cov = None + self._levels = None + + def _check_fit(self): + """Check if the Gedai is fitted.""" + if not self.fitted: + raise RuntimeError( + "Gedai must be fitted before using " + f"{self.__class__.__name__}" + ) + # sanity-check + assert self._wavelets_fits is not None + assert self._reference_cov is not None + assert self._levels is not None + + def _check_unfitted(self): + """Check if the Gedai is unfitted.""" + if self.fitted: + raise RuntimeError( + "Gedai must be unfitted before using " + f"{self.__class__.__name__}." + ) + assert self._wavelets_fits is None + assert self._reference_cov is None + assert self._levels is None + @fill_doc + @verbose def fit_epochs( self, epochs: BaseEpochs, + picks: list | str = "eeg", reference_cov: str = "leadfield", sensai_method: str = "optimize", noise_multiplier: float = 3.0, @@ -171,43 +190,56 @@ def fit_epochs( ---------- epochs : mne.Epochs The epochs data to fit the model to. + picks : str | list | slice + Channels to include. Note that all channels selected must have the same + type. Slices and lists of integers will be interpreted as channel indices. + In lists, channel name strings (e.g. ``['Fp1', 'Fp2']``) will pick the given + channels. Can also be the string values ``“all”`` to pick all channels, or + ``“data”`` to pick data channels. The default is ``“eeg”`` to pick all EEG channels. %(reference_cov)s %(sensai_method)s %(noise_multiplier)s %(n_jobs)s %(verbose)s """ + self._check_unfitted() check_type(epochs, (BaseEpochs,), "epochs") - _check_reference_cov(reference_cov) + _ensure_cov(reference_cov) _check_sensai_method(sensai_method) check_type(noise_multiplier, (float,), "noise_multiplier") n_jobs = _check_n_jobs(n_jobs) - # Set average reference - logger.info("Setting average reference.") + # Data + picks = _picks_to_idx(epochs.info, picks, none="all", exclude=[]) + _check_picks_uniqueness(epochs.info, picks) epochs = epochs.copy() epochs.load_data() + epochs = epochs.pick(picks) + logger.info("Setting average reference.") epochs.set_eeg_reference("average", projection=False) + data = epochs.get_data() - mat = os.path.abspath( - os.path.join(os.path.dirname(__file__), "../data/fsavLEADFIELD_4_GEDAI.mat") - ) - reference_cov, ch_names = _compute_refcov(epochs, mat) - + # reference covariance + cov = _ensure_cov(reference_cov) + cov = _pick_cov(cov, epochs.info["ch_names"]) + reference_cov = cov.data # Tikhonov Regularization based on average diagonal power + # TODO. move ? avg_diag_power = np.trace(reference_cov) / reference_cov.shape[0] regularization_lambda = 0.05 epsilon = regularization_lambda * avg_diag_power reference_cov = reference_cov + epsilon * np.eye(reference_cov.shape[0]) - # Broadband data + # Wavelet Decomposition epochs_wavelet, freq_bands, levels = epochs_to_wavelet( - epochs, wavelet=self.wavelet_type, level=self.wavelet_level, n_jobs=n_jobs + data, + sfreq=epochs.info["sfreq"], + wavelet=self.wavelet_type, + level=self.wavelet_level, + n_jobs=n_jobs ) # Store the actual levels used for consistency in transform - self.levels_used = levels - wavelets_fits = [] for w, (fmin, fmax) in enumerate(freq_bands): wavelet_epochs_data = epochs_wavelet[:, :, w, :] @@ -272,7 +304,6 @@ def fit_epochs( "fmin": fmin, "fmax": fmax, "threshold": threshold, - "reference_cov": reference_cov, "epochs_eigenvalues": epochs_eigenvalues, "sensai_runs": runs, } @@ -289,12 +320,18 @@ def fit_epochs( ) wavelet_fit["ignore"] = ignore wavelets_fits.append(wavelet_fit) - self.wavelets_fits = wavelets_fits + + self._levels = levels + self._wavelets_fits = wavelets_fits + self._reference_cov = cov + self.fitted = True @fill_doc + @verbose def fit_raw( self, raw: BaseRaw, + picks: list | str = "eeg", duration: float = 1.0, overlap: float = 0.5, reject_by_annotation: bool | None = False, @@ -310,6 +347,12 @@ def fit_raw( ---------- raw : mne.io.BaseRaw The raw data to fit the model to. + picks : str | list | slice + Channels to include. Note that all channels selected must have the same + type. Slices and lists of integers will be interpreted as channel indices. + In lists, channel name strings (e.g. ``['Fp1', 'Fp2']``) will pick the given + channels. Can also be the string values ``“all”`` to pick all channels, or + ``“data”`` to pick data channels. The default is ``“eeg”`` to pick all EEG channels. duration : float Duration of each epoch in seconds (default 1.0). Will be automatically adjusted to the closest valid duration for the wavelet level. @@ -344,7 +387,7 @@ def fit_raw( if not (0 <= overlap < 1): raise ValueError(f"overlap must be between 0 and 1, got {overlap}") check_type(reject_by_annotation, (bool,), "reject_by_annotation") - _check_reference_cov(reference_cov) + reference_cov = _ensure_cov(reference_cov) _check_sensai_method(sensai_method) check_type(noise_multiplier, (float,), "noise_multiplier") n_jobs = _check_n_jobs(n_jobs) @@ -370,18 +413,20 @@ def fit_raw( overlap=overlap_seconds, reject_by_annotation=reject_by_annotation, preload=True, - verbose=False, + verbose=verbose, ) self.fit_epochs( epochs, + picks=picks, noise_multiplier=noise_multiplier, reference_cov=reference_cov, sensai_method=sensai_method, n_jobs=n_jobs, - verbose=False, + verbose=verbose, ) @fill_doc + @verbose def transform_epochs( self, epochs: BaseEpochs, n_jobs: int = None, verbose: str | None = None ): @@ -399,37 +444,58 @@ def transform_epochs( epochs : mne.Epochs The transformed epochs. """ + self._check_fit() check_type(epochs, (BaseEpochs,), "epochs") n_jobs = _check_n_jobs(n_jobs) - # Set average reference - logger.info("Setting average reference to match leadfield covariance.") + # Data + missing_ch = set(self.ch_names) - set(epochs.info["ch_names"]) + if len(missing_ch) > 0: + raise ValueError( + f"The following channels are missing in the input inst but were present " + f"during fitting: {missing_ch}. \n" + f"Please make sure to include the same channels during transform as were used during fit. \n" + f"See {self.__class__.__name__}.ch_names for the list of channels used during fit.") + extra_ch = set(epochs.info["ch_names"]) - set(self.ch_names) + if len(extra_ch) > 0: + raise ValueError( + f"The following channels are present in the input inst but were not present " + f"during fitting: {extra_ch}. \n" + f"These channels will be ignored during transformation. \n" + f"Please make sure to include the same channels during transform as were used during fit. \n" + f"See {self.__class__.__name__}.ch_names for the list of channels used during fit.") + + picks = _picks_to_idx(epochs.info, self.ch_names, none="all", exclude=[]) epochs = epochs.copy() epochs.load_data() + epochs = epochs.pick(picks) + logger.info("Setting average reference.") epochs.set_eeg_reference("average", projection=False) + data = epochs.get_data() - # Check if model was fitted - if not hasattr(self, "wavelets_fits"): - raise RuntimeError( - "Model has not been fitted yet. Call fit_epochs() or fit_raw() first." - ) + # reference covariance + reference_cov = self._reference_cov.data epochs_wavelet, freq_bands, levels = epochs_to_wavelet( - epochs, wavelet=self.wavelet_type, level=self.wavelet_level, n_jobs=n_jobs + data, + sfreq=epochs.info["sfreq"], + wavelet=self.wavelet_type, + level=self.wavelet_level, + n_jobs=n_jobs ) # Validate that the decomposition matches the fitted model - if levels != self.levels_used: + if levels != self._levels: raise ValueError( f"Wavelet decomposition levels mismatch. \n" - f"Model was fitted with levels {self.levels_used}, " + f"Model was fitted with levels {self._levels}, " f"but transform got levels {levels}. \n" f"This may happen if epoch lengths differ between fit and transform." ) cleaned_epochs_wavelet = epochs_wavelet.copy() - for wavelet_fit in self.wavelets_fits: + for wavelet_fit in self._wavelets_fits: band_idx = wavelet_fit["band_index"] ignore = wavelet_fit["ignore"] @@ -438,7 +504,6 @@ def transform_epochs( cleaned_epochs_wavelet[:, :, band_idx, :] = 0 else: wavelet_epochs_data = epochs_wavelet[:, :, band_idx, :] - reference_cov = wavelet_fit["reference_cov"] threshold = wavelet_fit["threshold"] if n_jobs == 1: @@ -466,6 +531,7 @@ def transform_epochs( return cleaned_epochs @fill_doc + @verbose def transform_raw( self, raw: BaseRaw, @@ -537,13 +603,13 @@ def transform_raw( # Convert to epochs array (n_epochs, n_channels, n_times) all_segments_array = np.array(all_segments) - segments_epochs = mne.EpochsArray(all_segments_array, raw.info, verbose=False) + segments_epochs = mne.EpochsArray(all_segments_array, raw.info, verbose=verbose) # Process all segments at once with parallelization corrected_segments_epochs = self.transform_epochs( - segments_epochs, n_jobs=n_jobs, verbose=False + segments_epochs, n_jobs=n_jobs, verbose=verbose ) - corrected_segments = corrected_segments_epochs.get_data(verbose=False) + corrected_segments = corrected_segments_epochs.get_data(verbose=verbose) # Apply windowing and reconstruct for s, start in enumerate(starts): @@ -555,7 +621,7 @@ def transform_raw( weight_sum[weight_sum == 0] = 1 # Avoid division by zero raw_corrected /= weight_sum - raw_corrected = mne.io.RawArray(raw_corrected, raw.info, verbose=False) + raw_corrected = mne.io.RawArray(raw_corrected, raw.info, verbose=verbose) return raw_corrected def plot_fit(self): @@ -566,7 +632,7 @@ def plot_fit(self): figs : list of matplotlib.figure.Figure The list of figures showing the fitting results. """ - wavelet_fits = self.wavelets_fits + wavelet_fits = self._wavelets_fits figs = [] for w, wavelet_fit in enumerate(wavelet_fits): if wavelet_fit["ignore"]: @@ -626,6 +692,12 @@ def plot_fit(self): ) figs.append(fig) return figs + + @property + def ch_names(self): + """Get the channel names used during fitting.""" + self._check_fit() + return self._reference_cov.ch_names def _process_single_epoch(epoch_data, reference_cov, threshold): diff --git a/gedai/gedai/tests/test_gedai.py b/gedai/gedai/tests/test_gedai.py index 2bf6f4b..918cf26 100644 --- a/gedai/gedai/tests/test_gedai.py +++ b/gedai/gedai/tests/test_gedai.py @@ -7,6 +7,7 @@ from gedai import Gedai, logger, set_log_level from gedai.gedai.gedai import compute_closest_valid_duration +import pytest set_log_level("INFO") logger.propagate = True @@ -20,7 +21,7 @@ # make channel names follow standard conventions eegbci.standardize(raw) raw.crop(0, 15) -raw.pick("eeg").load_data().apply_proj() +raw.load_data().apply_proj() # epochs wavelet_level = 5 @@ -69,3 +70,31 @@ def test_gedai_transform_epochs(): gedai = Gedai(wavelet_level=wavelet_level) gedai.fit_epochs(epochs_eeg) gedai.transform_epochs(epochs_eeg) + + +def test_gedai_epochs_picks(): + """Test Gedai fit on epochs data.""" + gedai = Gedai(wavelet_level=0) + gedai.fit_epochs(epochs_eeg, picks="all") + assert gedai.ch_names == epochs_eeg.ch_names + + gedai = Gedai(wavelet_level=0) + gedai.fit_epochs(epochs_eeg, picks="data") + assert gedai.ch_names == epochs_eeg.ch_names + + gedai = Gedai(wavelet_level=0) + gedai.fit_epochs(epochs_eeg, picks=raw.ch_names[:10]) + assert gedai.ch_names == raw.ch_names[:10] + with pytest.raises(ValueError, match="The following channels are present in the input inst but were not present"): + gedai.transform_epochs(epochs_eeg) + + with pytest.raises(ValueError, match="The following channels are missing in the input inst but were present"): + epochs_test = epochs_eeg.copy() + epochs_test.load_data() + epochs_test.pick_channels(raw.ch_names[:5]) + gedai.transform_epochs(epochs_test) + + epochs_test = epochs_eeg.copy() + epochs_test.load_data() + epochs_test.pick_channels(raw.ch_names[:10]) + gedai.transform_epochs(epochs_test) \ No newline at end of file diff --git a/gedai/utils/_checks.py b/gedai/utils/_checks.py index 9e85745..5b80c6e 100644 --- a/gedai/utils/_checks.py +++ b/gedai/utils/_checks.py @@ -10,6 +10,7 @@ from typing import TYPE_CHECKING import numpy as np +from mne import pick_info from ._docs import fill_doc @@ -134,6 +135,19 @@ def check_type(item: Any, types: tuple, item_name: str | None = None) -> None: f"{item_name} must be an instance of {type_name}, got {type(item)} instead." ) +def _check_picks_uniqueness(info, picks): + """Check that the provided picks yield a single channel type.""" + info = pick_info(info, picks, copy=True) + if len(info.get_channel_types(unique=True)) != 1: + ch_types = info.get_channel_types(unique=False) + ch_types, counts = np.unique(ch_types, return_counts=True) + channels_msg = ", ".join( + "%s '%s' channel(s)" % t # noqa: UP031 + for t in zip(counts, ch_types, strict=False) + ) + raise ValueError( + f"Only one datatype can be selected, but 'picks' results in {channels_msg}." + ) def check_value( item: Any, diff --git a/gedai/wavelet/transform.py b/gedai/wavelet/transform.py index 0fec466..fe4bf95 100644 --- a/gedai/wavelet/transform.py +++ b/gedai/wavelet/transform.py @@ -36,13 +36,15 @@ def _process_epoch_wavelet(epoch_data, wavelet, level): @fill_doc -def epochs_to_wavelet(epochs, wavelet, level, n_jobs=None, verbose=None): +def epochs_to_wavelet(data, sfreq, wavelet, level, n_jobs=None, verbose=None): """Apply MODWT to each epoch in the epochs object. Parameters ---------- - epochs : mne.Epochs - The epochs to transform. + data : np.ndarray + The epochs data with shape (n_epochs, n_channels, n_times). + sfreq : float + The sampling frequency of the data. wavelet : str The type of wavelet to use (e.g., 'haar', 'db4', etc.). level : int @@ -60,14 +62,11 @@ def epochs_to_wavelet(epochs, wavelet, level, n_jobs=None, verbose=None): The actual decomposition level used. """ n_jobs = _check_n_jobs(n_jobs) - - epochs_data = epochs.get_data() # shape (n_epochs, n_channels, n_times) - n_epochs, n_channels, n_times = epochs_data.shape - sfreq = epochs.info["sfreq"] + n_epochs, n_channels, n_times = data.shape if level == 0: # No wavelet decomposition - return original data as single band - transformed_data = epochs_data[:, :, np.newaxis, :] + transformed_data = data[:, :, np.newaxis, :] freq_bands = [(0, sfreq / 2)] levels = 0 else: @@ -86,13 +85,13 @@ def epochs_to_wavelet(epochs, wavelet, level, n_jobs=None, verbose=None): if n_jobs == 1: # Sequential processing transformed_data = np.zeros((n_epochs, n_channels, level + 1, n_times)) - for e, epoch in enumerate(epochs_data): + for e, epoch in enumerate(data): transformed_data[e] = _process_epoch_wavelet(epoch, wavelet, level) else: # Parallel processing using MNE's parallel_func parallel, p_fun, n_jobs = parallel_func(_process_epoch_wavelet, n_jobs) transformed_epochs = parallel( - p_fun(epoch, wavelet, level) for epoch in epochs_data + p_fun(epoch, wavelet, level) for epoch in data ) transformed_data = np.array(transformed_epochs) diff --git a/pyproject.toml b/pyproject.toml index 801abe3..8d0232b 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -20,10 +20,10 @@ classifiers = [ ] dependencies = [ 'click', - 'h5py', - 'joblib', - 'mne>=1.9.0', 'numpy>=1.23,<3', + 'mne>=1.9.0', + 'pywavelets>=1.8.0', + 'scikit-learn>=1.6.1', 'packaging', 'psutil', 'pywavelets>=1.8.0',