MNE: Magnetoencephalography (MEG) and Electroencephalography (EEG) in Python
This report presents the forensic synthetic code analysis of mne-tools/mne-python, a Python project with 3,497 GitHub stars. SynthScan v2.0 examined 680,007 lines of code across 8710 source files, recording 3772 pattern matches distributed across 20 syntactic categories. The overall adjusted score of 7.8 places this repository in the Low AI signal band.
The scanner applied 160+ deterministic lexical heuristics, multi-line block detectors, abstract syntax tree depth profilers, and a cross-file Jaccard similarity matrix to construct a statistically normalised synthetic code estimate. All matches are individually weighted by severity coefficient and contextual multiplier before summation, and the resulting headline score is temporally discounted to account for the repository's development history relative to the commercial emergence of large language model coding tooling (November 2022 onward).
Longitudinal tracking requires multiple scan runs. Once this repository is re-scanned after new commits land, this chart will visualise how the synthetic code signal evolves over time — enabling you to detect whether AI authorship is growing, stabilising, or being actively corrected by human engineers.
Classifies detected patterns by their diagnostic confidence and structural impact. CRITICAL patterns (coefficient 10) represent definitive synthetic signatures — hallucinated imports, explicit LLM attribution metadata — virtually never produced by human authors. HIGH (5) indicates strong structural tells such as cross-file repetition or cross-linguistic idioms. MEDIUM (2) covers recognisable conversational padding and AI-specific vocabulary. LOW (1) captures subtle indicators like tautological comments and generic boilerplate that require density to carry independent signal.
This horizontal bar chart decomposes the repository's raw synthetic code score by top-level directory, allowing you to pinpoint precisely which modules or components carry the highest AI authorship density. Directories with disproportionately high scores relative to their size warrant targeted manual review: concentrated AI signatures often trace back to mass-generated configuration layers, auto-ported test suites, LLM-scaffolded boilerplate classes, or entire subsystems authored under heavy copilot assistance. Use this view to prioritise your human code-review effort.
The scanner identified 3772 distinct pattern matches across 20 syntactic categories. Each entry below represents a discrete location in the source code where the engine recorded a statistically significant AI authorship indicator. Expand any category row to inspect the individual file paths, line numbers, code snippets, and the lexical context (CODE, COMMENT, or STRING) in which each match was detected.
Reading the findings table: The Severity column indicates the diagnostic confidence level (CRITICAL / HIGH / MEDIUM / LOW). The Context column identifies whether the match occurred inside executable code, an inline comment, or a string literal — comment-context matches receive a ×1.5 weight because LLMs systematically over-annotate. The ⚡ bolt icon marks clustered matches: three or more patterns within a 10-line window, each receiving an additional ×1.5 density multiplier as dense clusters constitute far stronger evidence of synthetic authorship than isolated hits.
| Severity | File | Line | Snippet | Context |
|---|---|---|---|---|
| MEDIUM | mne/io/edf/edf.py | 915 | # ------------------------------------------------------------------------- | COMMENT |
| MEDIUM | mne/io/edf/edf.py | 1371 | # --------------------------------------------------------------------- | COMMENT |
| MEDIUM | mne/io/edf/edf.py | 1483 | # ----------------------------------------------------------------- | COMMENT |
| MEDIUM | mne/io/edf/edf.py | 1509 | # --------------------------------------------------------------------- | COMMENT |
| MEDIUM | mne/io/edf/edf.py | 1736 | # ----------------------------------------------------------------- | COMMENT |
| MEDIUM | mne/io/kit/constants.py | 147 | # ----------------- | COMMENT |
| MEDIUM | mne/tests/test_annotations.py | 1510 | # ------------------------------------------------------------------------- | COMMENT |
| MEDIUM | mne/tests/test_annotations.py | 1522 | # ------------------------------------------------------------------------- | COMMENT |
| MEDIUM | mne/tests/test_annotations.py | 1536 | # ------------------------------------------------------------------------- | COMMENT |
| MEDIUM | mne/tests/test_annotations.py | 1550 | # ------------------------------------------------------------------------- | COMMENT |
| MEDIUM | mne/tests/test_annotations.py | 1564 | # ------------------------------------------------------------------------- | COMMENT |
| MEDIUM | mne/viz/ica.py | 307 | # ---------- | COMMENT |
| MEDIUM | mne/viz/ica.py | 548 | # ------------------------- | COMMENT |
| MEDIUM | mne/viz/ica.py | 591 | # ------------ | COMMENT |
| MEDIUM | mne/viz/backends/_qt.py | 805 | # ------------------------------------ | COMMENT |
| MEDIUM | mne/viz/backends/_qt.py | 807 | # ------------------------------------ | COMMENT |
| MEDIUM | mne/viz/backends/_abstract.py | 714 | # ------------------- | COMMENT |
| MEDIUM | mne/viz/backends/_abstract.py | 716 | # ------------------- | COMMENT |
| MEDIUM | mne/viz/backends/_abstract.py | 1024 | # ------------------- | COMMENT |
| MEDIUM | mne/viz/backends/_abstract.py | 1026 | # ------------------- | COMMENT |
| MEDIUM | mne/viz/backends/_abstract.py | 1062 | # ------------------------------------ | COMMENT |
| MEDIUM | mne/viz/backends/_abstract.py | 1064 | # ------------------------------------ | COMMENT |
| MEDIUM | mne/viz/backends/_notebook.py | 789 | # ------------------------------------ | COMMENT |
| MEDIUM | mne/viz/backends/_notebook.py | 791 | # ------------------------------------ | COMMENT |
| MEDIUM | mne/viz/tests/test_topomap.py | 395 | # --------------------------------------------------- | COMMENT |
| MEDIUM | mne/viz/tests/test_topomap.py | 1174 | # ----------- | COMMENT |
| MEDIUM | mne/viz/tests/test_ica.py | 130 | # ---------------- | COMMENT |
| MEDIUM | mne/viz/tests/test_ica.py | 145 | # --------------- | COMMENT |
| MEDIUM⚡ | mne/stats/cluster_level.py | 887 | # ------------------------------------------------------------- | COMMENT |
| MEDIUM⚡ | mne/stats/cluster_level.py | 999 | # ------------------------------------------------------------------- | COMMENT |
| MEDIUM | examples/inverse/mixed_norm_inverse.py | 168 | # ---------- | COMMENT |
| MEDIUM | examples/inverse/psf_ctf_vertices_lcmv.py | 83 | # ------------------------------------------------------------ | COMMENT |
| MEDIUM | examples/inverse/psf_ctf_vertices_lcmv.py | 115 | # -------------------------------------------------------- | COMMENT |
| MEDIUM | examples/inverse/rap_music.py | 60 | # ---------- | COMMENT |
| MEDIUM | examples/inverse/resolution_metrics_eegmeg.py | 99 | # ------------- | COMMENT |
| MEDIUM | examples/inverse/resolution_metrics_eegmeg.py | 197 | # ---------- | COMMENT |
| MEDIUM | examples/inverse/resolution_metrics.py | 90 | # ----------------- | COMMENT |
| MEDIUM | examples/inverse/resolution_metrics.py | 180 | # ---------- | COMMENT |
| MEDIUM | examples/inverse/psf_ctf_label_leakage.py | 41 | # ------------------------------------------ | COMMENT |
| MEDIUM | examples/inverse/psf_ctf_label_leakage.py | 65 | # -------------------------------------------------- | COMMENT |
| MEDIUM | examples/inverse/psf_ctf_label_leakage.py | 90 | # ------------------------------------------------------------ | COMMENT |
| MEDIUM | examples/inverse/psf_ctf_label_leakage.py | 119 | # --------------------------------------------------------- | COMMENT |
| MEDIUM | examples/inverse/psf_ctf_label_leakage.py | 158 | # -------------------------- | COMMENT |
| MEDIUM | examples/inverse/psf_ctf_label_leakage.py | 168 | # ------------------------------- | COMMENT |
| MEDIUM | examples/inverse/trap_music.py | 60 | # ---------- | COMMENT |
| MEDIUM | examples/inverse/mne_cov_power.py | 41 | # ----------------------------- | COMMENT |
| MEDIUM | examples/inverse/mne_cov_power.py | 55 | # -------------- | COMMENT |
| MEDIUM | examples/inverse/mne_cov_power.py | 82 | # ---------------------------- | COMMENT |
| MEDIUM | examples/inverse/mne_cov_power.py | 124 | # ------------------------------------ | COMMENT |
| MEDIUM | examples/inverse/mixed_source_space_inverse.py | 44 | # ----------------------- | COMMENT |
| MEDIUM | examples/inverse/mixed_source_space_inverse.py | 91 | # --------------------- | COMMENT |
| MEDIUM | examples/inverse/mixed_source_space_inverse.py | 108 | # ---------------------- | COMMENT |
| MEDIUM | examples/inverse/mixed_source_space_inverse.py | 136 | # ------------------------ | COMMENT |
| MEDIUM | examples/inverse/mixed_source_space_inverse.py | 154 | # ------------------------------ | COMMENT |
| MEDIUM⚡ | examples/inverse/mixed_source_space_inverse.py | 173 | # ---------------- | COMMENT |
| MEDIUM⚡ | examples/inverse/mixed_source_space_inverse.py | 179 | # --------------- | COMMENT |
| MEDIUM⚡ | examples/inverse/mixed_source_space_inverse.py | 185 | # -------------- | COMMENT |
| MEDIUM | examples/inverse/morph_surface_stc.py | 56 | # ----------------------------------------- | COMMENT |
| MEDIUM | examples/inverse/morph_surface_stc.py | 100 | # -------------------------------------- | COMMENT |
| MEDIUM | examples/inverse/morph_surface_stc.py | 109 | # ------------ | COMMENT |
| 423 more matches not shown… | ||||
| Severity | File | Line | Snippet | Context |
|---|---|---|---|---|
| LOW | mne/source_estimate.py | 468 | def _verify_source_estimate_compat(a, b): | CODE |
| LOW | mne/source_estimate.py | 597 | def extract_label_time_course( | CODE |
| LOW | mne/source_estimate.py | 831 | def _remove_kernel_sens_data_(self): | CODE |
| LOW | mne/source_estimate.py | 3104 | def _spatio_temporal_src_adjacency_vol(src, n_times): | CODE |
| LOW | mne/source_estimate.py | 3113 | def _spatio_temporal_src_adjacency_surf(src, n_times): | CODE |
| LOW | mne/source_estimate.py | 3157 | def spatio_temporal_src_adjacency(src, n_times, dist=None, verbose=None): | CODE |
| LOW | mne/source_estimate.py | 3221 | def spatio_temporal_tris_adjacency(tris, n_times, remap_vertices=False, verbose=None): | CODE |
| LOW | mne/source_estimate.py | 3256 | def spatio_temporal_dist_adjacency(src, n_times, dist, verbose=None): | CODE |
| LOW | mne/source_estimate.py | 3375 | def spatial_inter_hemi_adjacency(src, dist, verbose=None): | CODE |
| LOW | mne/source_estimate.py | 3409 | def _get_adjacency_from_edges(edges, n_times, verbose=None): | CODE |
| LOW | mne/source_estimate.py | 3494 | def _prepare_label_extraction(stc, labels, src, mode, allow_empty, use_sparse): | CODE |
| LOW | mne/source_estimate.py | 3723 | def _gen_extract_label_time_course( | CODE |
| LOW | mne/source_estimate.py | 3822 | def extract_label_time_course( | CODE |
| LOW | mne/source_estimate.py | 2481 | def extract_label_time_course( | STRING |
| LOW | mne/transforms.py | 697 | def get_ras_to_neuromag_trans(nasion, lpa, rpa): | CODE |
| LOW | mne/transforms.py | 750 | def _get_transforms_to_coord_frame(info, trans, coord_frame="mri"): | CODE |
| LOW | mne/transforms.py | 1332 | def angle_distance_between_rigid(a, b=None, *, angle_units="rad", distance_units="m"): | CODE |
| LOW | mne/transforms.py | 1661 | def compute_volume_registration( | CODE |
| LOW | mne/transforms.py | 1710 | def _compute_volume_registration( | CODE |
| LOW | mne/transforms.py | 1825 | def apply_volume_registration( | CODE |
| LOW | mne/transforms.py | 1912 | def apply_volume_registration_points( | CODE |
| LOW | mne/conftest.py | 269 | def pytest_collection_modifyitems(items: list[pytest.Item]): | STRING |
| LOW | mne/conftest.py | 761 | def renderer_interactive_pyvistaqt(request, options_3d, qt_windows_closed): | CODE |
| LOW | mne/conftest.py | 954 | def _all_src_types_inv_evoked(_evoked_cov_sphere, _all_src_types_fwd): | CODE |
| LOW | mne/conftest.py | 1377 | def pytest_runtest_makereport(item: pytest.Item, call: pytest.CallInfo): | CODE |
| LOW | mne/event.py | 1344 | def _categories_from_acq_pars(self): | CODE |
| LOW | mne/epochs.py | 722 | def _check_events_outside_data(self, on_outside, raw): | CODE |
| LOW | mne/epochs.py | 3335 | def _diff_input_strings_vs_event_id(input_strings, input_name, event_id): | CODE |
| LOW | mne/coreg.py | 1723 | def _nearest_transformed_high_res_mri_idx_hsp(self): | CODE |
| LOW | mne/coreg.py | 1774 | def _processed_high_res_mri_points(self): | CODE |
| LOW | mne/coreg.py | 1777 | def _get_processed_mri_points(self, res): | CODE |
| LOW | mne/coreg.py | 2091 | def compute_dig_mri_distances(self): | CODE |
| LOW | mne/coreg.py | 2141 | def _get_fiducials_distance_str(self): | CODE |
| LOW | mne/_freesurfer.py | 212 | def get_volume_labels_from_aseg(mgz_fname, return_colors=False, atlas_ids=None): | CODE |
| LOW | mne/_freesurfer.py | 510 | def _get_affine_from_lta_info(lines): | CODE |
| LOW | mne/bem.py | 291 | def _fwd_bem_ip_modify_solution(solution, ip_solution, ip_mult, n_tri): | CODE |
| LOW | mne/bem.py | 329 | def _fwd_bem_linear_collocation_solution(bem): | CODE |
| LOW | mne/bem.py | 381 | def _fwd_bem_openmeeg_solution(bem): | CODE |
| LOW | mne/bem.py | 717 | def _fwd_eeg_get_multi_sphere_model_coeffs(m, n_terms): | CODE |
| LOW | mne/bem.py | 757 | def _compose_linear_fitting_data(mu, u): | CODE |
| LOW | mne/bem.py | 771 | def _compute_linear_parameters(mu, u): | CODE |
| LOW | mne/bem.py | 1876 | def _write_bem_surfaces_block(fid, surfs): | CODE |
| LOW | mne/cov.py | 886 | def _unpack_covariance_inputs(inst): | CODE |
| LOW | mne/evoked.py | 1669 | def _check_evokeds_ch_names_times(all_evoked, inplace=False): | CODE |
| LOW | mne/chpi.py | 518 | def _magnetic_dipole_objective( | CODE |
| LOW | mne/chpi.py | 533 | def _magnetic_dipole_delta_multi(whitened_fwd_svd, B, B2): | CODE |
| LOW | mne/chpi.py | 594 | def _fit_coil_order_dev_head_trans( | CODE |
| LOW | mne/chpi.py | 658 | def _setup_hpi_amplitude_fitting( | CODE |
| LOW | mne/cuda.py | 189 | def _setup_cuda_fft_multiply_repeated(n_jobs, h, n_fft, kind="FFT FIR filtering"): | CODE |
| LOW | mne/label.py | 1907 | def _grow_nonoverlapping_labels( | CODE |
| LOW | mne/parallel.py | 157 | def _running_in_joblib_context(): | CODE |
| LOW | mne/annotations.py | 1169 | def _hed_extras_from_hed_annotations(annot): | CODE |
| LOW | mne/annotations.py | 1642 | def get_annotations_per_epoch(self, *, with_extras=False): | CODE |
| LOW | mne/annotations.py | 1728 | def add_annotations_to_metadata(self, overwrite=False, *, with_extras=True): | CODE |
| LOW | mne/annotations.py | 1882 | def _annotations_starts_stops(raw, kinds, name="skip_by_annotation", invert=False): | CODE |
| LOW | mne/annotations.py | 2182 | def _read_brainstorm_annotations(fname, orig_time=None): | STRING |
| LOW | mne/annotations.py | 2229 | def _read_annotations_txt_parse_header(fname): | STRING |
| LOW | mne/annotations.py | 2378 | def _select_annotations_based_on_description(descriptions, event_id, regexp): | CODE |
| LOW | mne/annotations.py | 2413 | def _select_events_based_on_id(events, event_desc): | CODE |
| LOW | mne/rank.py | 158 | def _estimate_rank_meeg_signals( | CODE |
| 942 more matches not shown… | ||||
| Severity | File | Line | Snippet | Context |
|---|---|---|---|---|
| LOW | mne/transforms.py | 961 | COMMENT | |
| LOW | mne/transforms.py | 981 | # | COMMENT |
| LOW | mne/transforms.py | 1441 | assert quats.ndim == 2 and quats.shape[1] in (3, 4) | COMMENT |
| LOW | mne/_transforms_numba.py | 81 | COMMENT | |
| LOW | mne/coreg.py | 1181 | mri_transforms_dirname.format(subjects_dir=subjects_dir, subject=subject_to), | COMMENT |
| LOW | mne/__init__.py | 1 | # Authors: The MNE-Python contributors. | COMMENT |
| LOW | mne/morph.py | 801 | ) | COMMENT |
| LOW | mne/_surface_numba.py | 101 | run_all=True, | COMMENT |
| LOW | mne/label.py | 3041 | vertices belonging to label ``li``. | COMMENT |
| LOW | mne/dipole.py | 1201 | def _fit_confidence(*, rd, Q, ori, whitener, fwd_data, sensors): | COMMENT |
| LOW | mne/dipole.py | 1361 | # Tested minimizers: | COMMENT |
| LOW | mne/dipole.py | 1681 | if "eeg" in ch_types: | COMMENT |
| LOW | mne/time_frequency/spectrum.py | 941 | data = _psd_from_mt(data, self.weights) | COMMENT |
| LOW | mne/time_frequency/psd.py | 21 | # | COMMENT |
| LOW | mne/time_frequency/multitaper.py | 141 | # the variance of the timeseries | COMMENT |
| LOW | mne/time_frequency/tests/__init__.py | 1 | # Authors: The MNE-Python contributors. | COMMENT |
| LOW | mne/beamformer/_compute_beamformer.py | 381 | # | COMMENT |
| LOW | mne/beamformer/tests/__init__.py | 1 | # Authors: The MNE-Python contributors. | COMMENT |
| LOW | mne/datasets/config.py | 101 | MNE_DATASETS = dict() | COMMENT |
| LOW | mne/datasets/_infant/base.py | 61 | # Code used to create the lists: | COMMENT |
| LOW | mne/datasets/_phantom/__init__.py | 1 | # Authors: The MNE-Python contributors. | COMMENT |
| LOW | mne/datasets/tests/__init__.py | 1 | # Authors: The MNE-Python contributors. | COMMENT |
| LOW | mne/datasets/_fsaverage/__init__.py | 1 | # Authors: The MNE-Python contributors. | COMMENT |
| LOW | mne/io/ant/tests/__init__.py | 1 | # Authors: The MNE-Python contributors. | COMMENT |
| LOW | mne/io/nirx/tests/__init__.py | 1 | # Authors: The MNE-Python contributors. | COMMENT |
| LOW | mne/io/curry/curry.py | 821 | if isinstance(events, np.ndarray): # if there are events | COMMENT |
| LOW | mne/io/curry/tests/__init__.py | 1 | # Authors: The MNE-Python contributors. | COMMENT |
| LOW | mne/io/egi/tests/__init__.py | 1 | # Authors: The MNE-Python contributors. | COMMENT |
| LOW | mne/io/edf/tests/__init__.py | 1 | # Authors: The MNE-Python contributors. | COMMENT |
| LOW | mne/io/boxy/boxy.py | 241 | COMMENT | |
| LOW | mne/io/boxy/tests/__init__.py | 1 | # Authors: The MNE-Python contributors. | COMMENT |
| LOW | mne/io/bci2k/__init__.py | 1 | # Authors: The MNE-Python contributors. | COMMENT |
| LOW | mne/io/bci2k/tests/__init__.py | 1 | # Authors: The MNE-Python contributors. | COMMENT |
| LOW | mne/io/nicolet/tests/__init__.py | 1 | # Authors: The MNE-Python contributors. | COMMENT |
| LOW | mne/io/artemis123/tests/__init__.py | 1 | # Authors: The MNE-Python contributors. | COMMENT |
| LOW | mne/io/array/tests/__init__.py | 1 | # Authors: The MNE-Python contributors. | COMMENT |
| LOW | mne/io/snirf/tests/__init__.py | 1 | # Authors: The MNE-Python contributors. | COMMENT |
| LOW | mne/io/persyst/tests/__init__.py | 1 | # Authors: The MNE-Python contributors. | COMMENT |
| LOW | mne/io/eximia/tests/__init__.py | 1 | # Authors: The MNE-Python contributors. | COMMENT |
| LOW | mne/io/ctf/tests/__init__.py | 1 | # Authors: The MNE-Python contributors. | COMMENT |
| LOW | mne/io/nedf/tests/__init__.py | 1 | # Authors: The MNE-Python contributors. | COMMENT |
| LOW | mne/io/tests/data/__init__.py | 1 | # Authors: The MNE-Python contributors. | COMMENT |
| LOW | mne/io/mef/tests/__init__.py | 1 | # Authors: The MNE-Python contributors. | COMMENT |
| LOW | mne/io/eeglab/tests/__init__.py | 1 | # Authors: The MNE-Python contributors. | COMMENT |
| LOW | mne/io/eyelink/tests/__init__.py | 1 | # Authors: The MNE-Python contributors. | COMMENT |
| LOW | mne/io/bti/tests/__init__.py | 1 | # Authors: The MNE-Python contributors. | COMMENT |
| LOW | mne/io/cnt/_utils.py | 61 | # unsigned char KeyBoard; /* range 0-11 corresponding to fcn keys +1 */ | COMMENT |
| LOW | mne/io/cnt/tests/__init__.py | 1 | # Authors: The MNE-Python contributors. | COMMENT |
| LOW | mne/io/fieldtrip/tests/__init__.py | 1 | # Authors: The MNE-Python contributors. | COMMENT |
| LOW | mne/io/fiff/raw.py | 121 | "properly and that split and original files were not " | COMMENT |
| LOW | mne/io/fiff/tests/__init__.py | 1 | # Authors: The MNE-Python contributors. | COMMENT |
| LOW | mne/io/brainvision/brainvision.py | 921 | # for newer BV files, the unit is specified for every channel separated by a | COMMENT |
| LOW | mne/io/brainvision/tests/__init__.py | 1 | # Authors: The MNE-Python contributors. | COMMENT |
| LOW | mne/io/neuralynx/tests/__init__.py | 1 | # Authors: The MNE-Python contributors. | COMMENT |
| LOW | mne/tests/__init__.py | 1 | # Authors: The MNE-Python contributors. | COMMENT |
| LOW | mne/tests/test_morph.py | 601 | ) | COMMENT |
| LOW | mne/simulation/metrics/tests/__init__.py | 1 | # Authors: The MNE-Python contributors. | COMMENT |
| LOW | mne/simulation/tests/__init__.py | 1 | # Authors: The MNE-Python contributors. | COMMENT |
| LOW | mne/utils/check.py | 141 | # | COMMENT |
| LOW | mne/decoding/time_delaying_ridge.py | 81 | # it's faster to create the Toeplitz ourselves than use | COMMENT |
| 771 more matches not shown… | ||||
| Severity | File | Line | Snippet | Context |
|---|---|---|---|---|
| LOW | mne/source_estimate.py | 236 | CODE | |
| LOW | mne/source_estimate.py | 392 | CODE | |
| LOW | mne/source_estimate.py | 3494 | CODE | |
| LOW | mne/source_estimate.py | 3723 | CODE | |
| LOW | mne/transforms.py | 578 | CODE | |
| LOW | mne/transforms.py | 1591 | CODE | |
| LOW | mne/transforms.py | 1710 | CODE | |
| LOW | mne/transforms.py | 2211 | CODE | |
| LOW | mne/misc.py | 6 | CODE | |
| LOW | mne/event.py | 36 | CODE | |
| LOW | mne/event.py | 85 | CODE | |
| LOW | mne/event.py | 1275 | CODE | |
| LOW | mne/fixes.py | 656 | CODE | |
| LOW | mne/fixes.py | 774 | CODE | |
| LOW | mne/baseline.py | 35 | CODE | |
| LOW | mne/baseline.py | 149 | CODE | |
| LOW | mne/epochs.py | 266 | CODE | |
| LOW | mne/epochs.py | 335 | CODE | |
| LOW | mne/epochs.py | 3116 | CODE | |
| LOW | mne/epochs.py | 4095 | CODE | |
| LOW | mne/epochs.py | 4160 | CODE | |
| LOW | mne/epochs.py | 4245 | CODE | |
| LOW | mne/epochs.py | 4727 | CODE | |
| LOW | mne/epochs.py | 852 | CODE | |
| LOW | mne/epochs.py | 1720 | CODE | |
| LOW | mne/epochs.py | 2075 | CODE | |
| LOW | mne/epochs.py | 2518 | CODE | |
| LOW | mne/coreg.py | 824 | CODE | |
| LOW | mne/coreg.py | 1041 | CODE | |
| LOW | mne/coreg.py | 1341 | CODE | |
| LOW | mne/morph_map.py | 112 | CODE | |
| LOW | mne/morph.py | 961 | CODE | |
| LOW | mne/morph.py | 1263 | CODE | |
| LOW | mne/morph.py | 605 | CODE | |
| LOW | mne/bem.py | 215 | CODE | |
| LOW | mne/bem.py | 1179 | CODE | |
| LOW | mne/bem.py | 2393 | CODE | |
| LOW | mne/cov.py | 902 | CODE | |
| LOW | mne/cov.py | 1311 | CODE | |
| LOW | mne/cov.py | 1984 | CODE | |
| LOW | mne/cov.py | 2452 | CODE | |
| LOW | mne/evoked.py | 1669 | CODE | |
| LOW | mne/evoked.py | 1886 | CODE | |
| LOW | mne/evoked.py | 289 | CODE | |
| LOW | mne/evoked.py | 1083 | CODE | |
| LOW | mne/_surface_numba.py | 88 | CODE | |
| LOW | mne/chpi.py | 419 | CODE | |
| LOW | mne/chpi.py | 905 | CODE | |
| LOW | mne/chpi.py | 1229 | CODE | |
| LOW | mne/proj.py | 380 | CODE | |
| LOW | mne/label.py | 1273 | CODE | |
| LOW | mne/label.py | 1551 | CODE | |
| LOW | mne/label.py | 2018 | CODE | |
| LOW | mne/label.py | 2675 | CODE | |
| LOW | mne/filter.py | 42 | CODE | |
| LOW | mne/filter.py | 671 | CODE | |
| LOW | mne/filter.py | 1067 | CODE | |
| LOW | mne/filter.py | 1450 | CODE | |
| LOW | mne/filter.py | 2169 | CODE | |
| LOW | mne/dipole.py | 692 | CODE | |
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| Severity | File | Line | Snippet | Context |
|---|---|---|---|---|
| MEDIUM | .extended_metadata.yaml | 1 | # This file contains additional metadata about MNE-Python, beyond what is contained in `pyproject.toml`. | COMMENT |
| MEDIUM | mne/cov.py | 1909 | # Create the projection operator | COMMENT |
| MEDIUM | mne/evoked.py | 2142 | # Create the file and save the essentials | COMMENT |
| MEDIUM | mne/annotations.py | 1807 | # Create a new Annotations column that is instantiated as an empty | COMMENT |
| MEDIUM | mne/beamformer/tests/test_dics.py | 77 | # Create an info object that holds information about the sensors | COMMENT |
| MEDIUM | mne/beamformer/tests/test_dics.py | 95 | # Define a single epoch (weird baseline but shouldn't matter) | COMMENT |
| MEDIUM | mne/beamformer/tests/test_dics.py | 730 | # Create a DICS beamformer and convert the EpochsTFR to source space. | COMMENT |
| MEDIUM | mne/datasets/utils.py | 331 | # This function is designed primarily to be used by CircleCI, to: | COMMENT |
| MEDIUM | mne/io/base.py | 3226 | # Create the file and save the essentials | COMMENT |
| MEDIUM | mne/io/snirf/tests/test_snirf.py | 652 | # Create a clean copy and ensure it loads without error | COMMENT |
| MEDIUM | mne/io/ctf/info.py | 197 | # Create the channel position information | COMMENT |
| MEDIUM⚡ | mne/io/ctf/tests/test_ctf.py | 81 | # Create a dummy .eeg file so we can test our reading/application of it | COMMENT |
| MEDIUM⚡ | mne/io/ctf/tests/test_ctf.py | 90 | # Create a bad file | COMMENT |
| MEDIUM⚡ | mne/io/ctf/tests/test_ctf.py | 94 | # Create a good file | COMMENT |
| MEDIUM | mne/io/ctf/tests/test_ctf.py | 115 | # Create a version with no hc, starting out *with* EEG pos (error) | COMMENT |
| MEDIUM | mne/io/kit/kit.py | 227 | # Create a synthetic stim channel | COMMENT |
| MEDIUM | mne/tests/test_source_estimate.py | 2066 | # Create a sample _BaseSourceEstimate object | COMMENT |
| MEDIUM | mne/utils/_bunch.py | 11 | # Create a Bunch class that acts like a struct (mybunch.key = val) | COMMENT |
| MEDIUM | mne/utils/tests/test_config.py | 302 | # Create a unique key/value pair. | COMMENT |
| MEDIUM | mne/decoding/receptive_field.py | 233 | # Define the slice that we should use in the middle | COMMENT |
| MEDIUM | mne/decoding/receptive_field.py | 553 | # Create a correlation scikit-learn-style scorer | COMMENT |
| MEDIUM | mne/decoding/tests/test_base.py | 129 | # Define a classifier, an invertible transformer and an non-invertible one. | COMMENT |
| MEDIUM | mne/viz/topomap.py | 789 | # Define the outline of the head, ears and nose | COMMENT |
| MEDIUM | mne/viz/evoked.py | 2153 | # The following functions are all helpers for plot_compare_evokeds. # | COMMENT |
| MEDIUM | mne/viz/ui_events.py | 291 | # Create the event channel if it doesn't exist yet | COMMENT |
| MEDIUM | mne/viz/topo.py | 243 | # Create a PolyCollection for the axis backgrounds | COMMENT |
| MEDIUM | mne/_fiff/proj.py | 1290 | # Create the projector | COMMENT |
| MEDIUM | mne/_fiff/compensator.py | 40 | # Create the preselector | COMMENT |
| MEDIUM | mne/_fiff/compensator.py | 50 | # Create the postselector (zero entries for channels not found) | COMMENT |
| MEDIUM | mne/_fiff/reference.py | 438 | # Creating an average reference may fail. In this case, make | COMMENT |
| MEDIUM | mne/gui/_dipolefit.py | 971 | # Create a coordinate system where X and Y are tangential to the helmet | COMMENT |
| MEDIUM | mne/report/report.py | 3497 | # Create the figure once and reuse it for performance reasons | COMMENT |
| MEDIUM | mne/preprocessing/_regress.py | 92 | # Create an EOGRegression object and load the given betas into it. | COMMENT |
| MEDIUM | mne/preprocessing/xdawn.py | 477 | # Define the components to keep | COMMENT |
| MEDIUM | mne/preprocessing/eyetracking/_pupillometry.py | 98 | # Create an empty boolean mask | COMMENT |
| MEDIUM | …e/preprocessing/eyetracking/tests/test_pupillometry.py | 34 | # Create a dummy stim channel | COMMENT |
| MEDIUM | mne/preprocessing/nirs/_tddr.py | 67 | # This function is the reference implementation for the TDDR algorithm for | COMMENT |
| MEDIUM | mne/source_space/_source_space.py | 2114 | # Define the sphere which fits the surface | COMMENT |
| MEDIUM | mne/source_space/_source_space.py | 2902 | # Create a list of Label | COMMENT |
| MEDIUM | mne/source_space/tests/test_source_space.py | 1047 | # The following code was used to generate small-src.fif.gz. | COMMENT |
| MEDIUM | mne/minimum_norm/inverse.py | 435 | # Create the file and save the essentials | COMMENT |
| MEDIUM⚡ | mne/minimum_norm/inverse.py | 678 | # Create the diagonal matrix for computing the regularized inverse | COMMENT |
| MEDIUM⚡ | mne/minimum_norm/inverse.py | 683 | # Create the projection operator | COMMENT |
| MEDIUM⚡ | mne/minimum_norm/inverse.py | 692 | # Create the whitener | COMMENT |
| MEDIUM | mne/stats/parametric.py | 12 | # The following function is a rewriting of scipy.stats.f_oneway | COMMENT |
| MEDIUM | mne/stats/cluster_level.py | 768 | # Create the leftmost column as 0,0,...,1,1,... | COMMENT |
| MEDIUM | mne/forward/_compute_forward.py | 359 | # The following code is equivalent to this, but saves memory | COMMENT |
| MEDIUM | mne/forward/_make_forward.py | 181 | # Create the result | COMMENT |
| MEDIUM | mne/forward/tests/test_make_forward.py | 779 | # Create a new Dipole object with the dipole fits | COMMENT |
| MEDIUM | mne/channels/interpolation.py | 549 | # Create a new instance for the interpolated EEG channels | COMMENT |
| MEDIUM | mne/channels/montage.py | 1852 | # Create a mapping from column name to index | STRING |
| MEDIUM | mne/channels/tests/test_interpolation.py | 518 | # Create a target montage | COMMENT |
| MEDIUM | mne/channels/tests/test_layout.py | 335 | # Create a grid of points. Box size should be (0.1, 0.1). | COMMENT |
| MEDIUM | mne/channels/tests/test_layout.py | 340 | # Create a random set of points. This should never break the function. | COMMENT |
| MEDIUM | examples/visualization/evoked_topomap.py | 132 | # Define a threshold and create the mask | COMMENT |
| MEDIUM | examples/visualization/brain.py | 127 | # Create a screenshot for exporting the brain image | COMMENT |
| MEDIUM | examples/datasets/hf_sef_data.py | 31 | # Create a highpass filtered version | COMMENT |
| MEDIUM | examples/datasets/limo_data.py | 166 | # Create a dictionary containing the evoked responses | COMMENT |
| MEDIUM⚡ | examples/simulation/plot_stc_metrics.py | 62 | # Define main parameters of sources | COMMENT |
| MEDIUM | examples/simulation/plot_stc_metrics.py | 95 | # Define the time course of the activity | COMMENT |
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| LOW | mne/datasets/limo/__init__.py | 7 | CODE | |
| LOW | mne/datasets/_infant/__init__.py | 5 | CODE | |
| LOW | mne/datasets/misc/__init__.py | 7 | CODE | |
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| LOW | mne/datasets/opm/__init__.py | 7 | CODE | |
| LOW | mne/datasets/sleep_physionet/__init__.py | 5 | CODE | |
| LOW | mne/datasets/sleep_physionet/__init__.py | 5 | CODE | |
| LOW | mne/datasets/sleep_physionet/__init__.py | 5 | CODE | |
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| LOW | mne/datasets/refmeg_noise/__init__.py | 7 | CODE | |
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| Severity | File | Line | Snippet | Context |
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| CRITICAL | mne/viz/_mpl_figure.py | 212 | self.mne.parent_fig.mne.child_figs.remove(self) | CODE |
| CRITICAL | mne/viz/_mpl_figure.py | 360 | self.mne.parent_fig.mne.child_figs.remove(self) | CODE |
| CRITICAL | mne/viz/_mpl_figure.py | 1443 | self.mne.fig_annotation.mne.radio_ax.set_title( | CODE |
| CRITICAL⚡ | mne/viz/utils.py | 1492 | self.cidpress = self.cbar.ax.figure.canvas.mpl_connect( | CODE |
| CRITICAL⚡ | mne/viz/utils.py | 1495 | self.cidrelease = self.cbar.ax.figure.canvas.mpl_connect( | CODE |
| CRITICAL⚡ | mne/viz/utils.py | 1498 | self.cidmotion = self.cbar.ax.figure.canvas.mpl_connect( | CODE |
| CRITICAL⚡ | mne/viz/utils.py | 1501 | self.keypress = self.cbar.ax.figure.canvas.mpl_connect( | CODE |
| CRITICAL⚡ | mne/viz/utils.py | 1504 | self.scroll = self.cbar.ax.figure.canvas.mpl_connect( | CODE |
| CRITICAL | mne/viz/utils.py | 1611 | self.cbar.ax.figure.canvas.draw() | CODE |
| CRITICAL | mne/viz/_figure.py | 217 | durations = self.mne.inst.annotations.duration.copy() | CODE |
| CRITICAL | mne/viz/_brain/tests/test_brain.py | 941 | fp = np.array(brain._renderer.figure.plotter.renderer.ComputeVisiblePropBounds()) | CODE |
| CRITICAL | mne/report/js_and_css/jquery-3.6.0.min.js | 2 | !function(e,t){"use strict";"object"==typeof module&&"object"==typeof module.exports?module.exports=e.document?t(e,!0):f | CODE |
| CRITICAL | …d_css/bootstrap-table/bootstrap-table-copy-rows.min.js | 10 | !function(t,e){"object"==typeof exports&&"undefined"!=typeof module?e(require("jquery")):"function"==typeof define&&defi | CODE |
| CRITICAL | …_and_css/bootstrap-table/bootstrap-table-export.min.js | 10 | !function(t,e){"object"==typeof exports&&"undefined"!=typeof module?e(require("jquery")):"function"==typeof define&&defi | CODE |
| Severity | File | Line | Snippet | Context |
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| MEDIUM | mne/transforms.py | 1453 | # But this is not robust to quaternions having sign ambiguity, | COMMENT |
| MEDIUM | mne/fixes.py | 442 | # sklearn uses np.linalg for this, but ours is more robust to zero eigenvalues | COMMENT |
| LOW | mne/epochs.py | 2632 | # 2b. for non-tag ids, just pass them directly | COMMENT |
| LOW | mne/rank.py | 321 | # one, so we cannot just use proc_history[0]. | COMMENT |
| MEDIUM | mne/time_frequency/tfr.py | 1287 | del self._shape # calculated from self._data henceforth | CODE |
| MEDIUM | mne/time_frequency/spectrum.py | 1224 | del self._shape # calculated from self._data henceforth | CODE |
| LOW | mne/beamformer/tests/test_lcmv.py | 172 | # just use grads | COMMENT |
| LOW | mne/io/curry/curry.py | 141 | # of the acquisition system (which is unknown); therefore, just set | COMMENT |
| MEDIUM | mne/io/persyst/persyst.py | 454 | # TODO: utilize state and var_type in code. | COMMENT |
| LOW | mne/io/tests/test_raw.py | 1101 | # tmin and tmax just use time_as_index under the hood | COMMENT |
| LOW | mne/io/fiff/raw.py | 433 | continue # just use zeros for gaps | CODE |
| MEDIUM | mne/tests/test_chpi.py | 652 | """Wrap to facilitate change diff.""" | STRING |
| MEDIUM | mne/tests/test_rank.py | 135 | # Now do some more comprehensive tests | COMMENT |
| MEDIUM | mne/utils/misc.py | 354 | # but this might be more robust to file-like objects not properly | COMMENT |
| MEDIUM | mne/utils/config.py | 516 | # This is a more robust way of getting the user's home folder on | COMMENT |
| LOW | mne/utils/numerics.py | 873 | # Adapted from sklearn and stripped down to just use linalg.svd | COMMENT |
| MEDIUM | mne/decoding/receptive_field.py | 527 | """Find the slice to be taken in order to remove missing values.""" | STRING |
| LOW | mne/viz/topomap.py | 1030 | # rare so for now just use the average value of all extras | COMMENT |
| LOW | mne/viz/evoked.py | 1959 | # simply create a new evoked object with the desired channel selection | COMMENT |
| LOW | mne/viz/_3d.py | 755 | trans = Transform("head", "mri") # not used so just use identity | CODE |
| LOW | mne/_fiff/meas_info.py | 672 | # whatever mapping was provided, now we can just use a dict | COMMENT |
| LOW | mne/_fiff/meas_info.py | 949 | # set does not preserve order but dict does, so let's just use it | COMMENT |
| MEDIUM | mne/_fiff/tests/test_meas_info.py | 485 | # Use assert_object_equal for comprehensive check | COMMENT |
| LOW | mne/preprocessing/ecg.py | 512 | # Raw has start param, can just use int | COMMENT |
| LOW | mne/preprocessing/ecg.py | 520 | # Raw has stop param, can just use int | COMMENT |
| LOW | mne/preprocessing/ica.py | 3258 | # Here we just use the median rather than the (transformed-back) mean of | COMMENT |
| MEDIUM | mne/preprocessing/eyetracking/tests/test_calibration.py | 262 | # Calibration reading should be robust to what we are about to do to this file | COMMENT |
| MEDIUM | mne/preprocessing/nirs/_tddr.py | 117 | # Step 3. Iterative estimation of robust weights | COMMENT |
| MEDIUM | mne/preprocessing/nirs/_tddr.py | 143 | # Step 4. Apply robust weights to centered derivative | COMMENT |
| LOW | mne/minimum_norm/spatial_resolution.py | 148 | # can be quite expensive in memory. So let's just use abs() in place below. | COMMENT |
| LOW | mne/minimum_norm/_eloreta.py | 156 | # to work. So let's just set to nan for now. | COMMENT |
| LOW | mne/stats/cluster_level.py | 805 | # Here we can just use the hash-table (w/collision detection) | COMMENT |
| MEDIUM | mne/forward/_lead_dots.py | 235 | # Accumulate the result, a little bit streamlined version | COMMENT |
| LOW | mne/channels/channels.py | 86 | # Our helmet does not match very well, so let's just create it | COMMENT |
| LOW | mne/channels/tests/test_layout.py | 365 | # Test specifying both width and height. The function should simply return | COMMENT |
| MEDIUM | examples/visualization/3d_to_2d.py | 70 | # with the electrode positions on that image. We use this in conjunction with | COMMENT |
| LOW | examples/time_frequency/source_power_spectrum_opm.py | 99 | # For speed, let's just use a 1-layer BEM | COMMENT |
| MEDIUM | examples/datasets/limo_data.py | 162 | # Since this is a "visual paradigm" it might be best to look at electrodes | COMMENT |
| LOW | examples/preprocessing/muscle_detection.py | 47 | raw.crop(130, 160).load_data() # just use a fraction of data for speed here | CODE |
| LOW | tutorials/inverse/30_mne_dspm_loreta.py | 67 | # Let's just use the MEG channels for simplicity. | COMMENT |
| MEDIUM | tutorials/intro/15_inplace.py | 76 | # Above we saw an example of using the `~mne.io.Raw.copy` method to facilitate | COMMENT |
| MEDIUM | tutorials/time-freq/20_sensors_time_frequency.py | 119 | # bias relative to the mean), which is a more robust measure. | COMMENT |
| MEDIUM | tutorials/time-freq/20_sensors_time_frequency.py | 304 | # units of baseline standard deviations. This can facilitate comparison across | COMMENT |
| LOW | …/stats-source-space/30_cluster_ftest_spatiotemporal.py | 78 | # just pass the spatial adjacency matrix (instead of spatio-temporal) | COMMENT |
| LOW | …tats-source-space/60_cluster_rmANOVA_spatiotemporal.py | 225 | # just pass the spatial adjacency matrix (instead of spatio-temporal). | COMMENT |
| LOW | …/stats-source-space/20_cluster_1samp_spatiotemporal.py | 176 | # just pass the spatial adjacency matrix (instead of spatio-temporal). | COMMENT |
| LOW | tutorials/epochs/50_epochs_to_data_frame.py | 82 | # :class:`~pandas.DataFrame` is simple: just call :meth:`epochs.to_data_frame() | COMMENT |
| LOW | tutorials/epochs/60_make_fixed_length_epochs.py | 49 | # To create fixed length epochs, we simply call the function and provide it | COMMENT |
| MEDIUM | tutorials/epochs/40_autogenerate_metadata.py | 204 | # present paradigm stimuli were presented in rapid succession, sometimes | COMMENT |
| MEDIUM | tutorials/epochs/40_autogenerate_metadata.py | 366 | # this paradigm; taking the last response (time point zero) and the last | COMMENT |
| MEDIUM | tutorials/epochs/40_autogenerate_metadata.py | 468 | # the ERN nicely in the given paradigm. | COMMENT |
| MEDIUM | tutorials/preprocessing/30_filtering_resampling.py | 284 | # The following section suggests best practices to mitigate both of these | COMMENT |
| MEDIUM | tutorials/preprocessing/30_filtering_resampling.py | 345 | # If for some reason you cannot follow the above-recommended best practices, | COMMENT |
| MEDIUM | tutorials/preprocessing/15_handling_bad_channels.py | 174 | # rejection thresholds, which in turn can lead to less robust estimation of the | COMMENT |
| MEDIUM | tutorials/preprocessing/20_rejecting_bad_data.py | 50 | # best practices for annotating *bad* data spans so that they will be excluded | COMMENT |
| LOW | tutorials/preprocessing/20_rejecting_bad_data.py | 190 | # of events: simply pass the array via the ``events`` parameter. Existing | COMMENT |
| LOW | tutorials/preprocessing/10_preprocessing_overview.py | 32 | raw.crop(0, 60).load_data() # just use a fraction of data for speed here | CODE |
| MEDIUM | tutorials/preprocessing/10_preprocessing_overview.py | 71 | # in the sensory response to a stimulus, but the experimental paradigm involves | COMMENT |
| MEDIUM | tutorials/preprocessing/40_artifact_correction_ica.py | 101 | # converge faster than FastICA and Infomax, and is more robust than other | COMMENT |
| MEDIUM | tutorials/preprocessing/25_background_filtering.py | 796 | # Similarly, in a P300 paradigm reported by | COMMENT |
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| Severity | File | Line | Snippet | Context |
|---|---|---|---|---|
| LOW | mne/conftest.py | 133 | except Exception: | CODE |
| LOW | mne/conftest.py | 243 | except Exception: | STRING |
| LOW | mne/conftest.py | 683 | except Exception: | CODE |
| LOW | mne/conftest.py | 1237 | except Exception as exc: | CODE |
| LOW | mne/conftest.py | 1274 | except Exception: | CODE |
| MEDIUM | mne/conftest.py | 1228 | def _nbclient(): | CODE |
| LOW | mne/fixes.py | 699 | except Exception: | CODE |
| LOW | mne/fixes.py | 704 | except Exception: | CODE |
| LOW | mne/fixes.py | 788 | except Exception: | CODE |
| LOW | mne/_numba.py | 28 | except Exception: # could be ImportError, SystemError, etc. | CODE |
| LOW | mne/coreg.py | 1259 | except Exception: | CODE |
| LOW | mne/morph_map.py | 70 | except Exception: | CODE |
| LOW | mne/morph_map.py | 151 | except Exception as exp: | CODE |
| LOW | mne/__init__.py | 27 | except Exception: | CODE |
| MEDIUM | mne/bem.py | 355 | def _import_openmeeg(what="compute a BEM solution using OpenMEEG"): | CODE |
| LOW | mne/bem.py | 358 | except Exception as exc: | CODE |
| LOW | mne/bem.py | 1502 | except Exception: # not our format | CODE |
| LOW | mne/cuda.py | 80 | except Exception: | CODE |
| LOW | mne/cuda.py | 137 | except Exception as exp: | CODE |
| LOW | mne/cuda.py | 243 | except Exception as exp: | CODE |
| LOW | mne/cuda.py | 345 | except Exception: | CODE |
| LOW | mne/filter.py | 1812 | except Exception: | CODE |
| LOW | mne/parallel.py | 136 | except Exception: | CODE |
| LOW | mne/time_frequency/tfr.py | 2043 | except Exception as e: | CODE |
| LOW | mne/io/_preload_cache.py | 63 | except Exception as exc: | CODE |
| LOW | mne/io/_read_raw.py | 195 | except Exception: | CODE |
| LOW | mne/io/base.py | 843 | except Exception: | CODE |
| LOW | mne/io/base.py | 1483 | except Exception: | CODE |
| LOW | mne/io/base.py | 1574 | except Exception: | CODE |
| LOW | mne/io/base.py | 3452 | except Exception: | CODE |
| LOW | mne/io/curry/curry.py | 166 | except Exception: | CODE |
| LOW | mne/io/egi/egimff.py | 86 | except Exception: | CODE |
| LOW | mne/io/egi/events.py | 47 | except Exception: | CODE |
| LOW | mne/io/egi/events.py | 61 | except Exception as exc: | CODE |
| LOW⚡ | mne/io/edf/edf.py | 1128 | except Exception: | CODE |
| LOW⚡ | mne/io/edf/edf.py | 1138 | except Exception: | CODE |
| LOW⚡ | mne/io/edf/edf.py | 1145 | except Exception: | CODE |
| LOW | mne/io/edf/edf.py | 270 | except Exception: | CODE |
| LOW | mne/io/edf/edf.py | 1400 | except Exception: | CODE |
| LOW | mne/io/artemis123/artemis123.py | 168 | except Exception: | CODE |
| LOW | mne/io/mef/_utils.py | 160 | except Exception: | CODE |
| LOW | mne/io/eeglab/_eeglab.py | 124 | except Exception: | STRING |
| LOW | mne/io/cnt/cnt.py | 548 | except Exception: | CODE |
| LOW | mne/io/fiff/raw.py | 571 | except Exception: | CODE |
| LOW | mne/io/hitachi/hitachi.py | 215 | except Exception: | CODE |
| LOW | mne/io/hitachi/hitachi.py | 221 | except Exception: | CODE |
| LOW | mne/tests/test_cov.py | 316 | except Exception as exp: | CODE |
| LOW | mne/tests/test_docstring_parameters.py | 296 | except Exception: # e.g., mne.export not having pybv | CODE |
| LOW | mne/utils/misc.py | 250 | except Exception: | CODE |
| LOW | mne/utils/_logging.py | 517 | except Exception: | STRING |
| LOW | mne/utils/config.py | 668 | except Exception as exc: | CODE |
| LOW | mne/utils/config.py | 695 | except Exception: | CODE |
| LOW | mne/utils/config.py | 735 | except Exception: # pragma: no cover | CODE |
| LOW | mne/utils/config.py | 824 | except Exception: # in case someone overrides sys.stdout in an unsafe way | CODE |
| LOW | mne/utils/config.py | 841 | except Exception as exc: | CODE |
| LOW | mne/utils/config.py | 848 | except Exception as exc: | CODE |
| LOW | mne/utils/config.py | 1004 | except Exception: | CODE |
| LOW | mne/utils/check.py | 309 | except Exception: | CODE |
| LOW | mne/utils/check.py | 1069 | except Exception: | CODE |
| LOW | mne/utils/check.py | 1082 | except Exception: | CODE |
| 74 more matches not shown… | ||||
| Severity | File | Line | Snippet | Context |
|---|---|---|---|---|
| LOW | mne/label.py | 2810 | # make sure to add no duplicate color | STRING |
| LOW | mne/utils/tests/test_check.py | 218 | # make sure to inform the user that 7 channels were dropped | COMMENT |
| LOW | mne/viz/topo.py | 1251 | # make sure to only modify the time courses, not the ticks | COMMENT |
| MEDIUM | mne/preprocessing/tests/test_css.py | 37 | # include test for gh-12373, that you can use MAG+EEG if you want | COMMENT |
| LOW | mne/channels/channels.py | 2154 | # create new instances and make sure to copy important attributes | COMMENT |
| MEDIUM⚡ | examples/visualization/brain.py | 75 | # To highlight a region on the brain you can use the ``add_label`` method. | COMMENT |
| MEDIUM | tutorials/inverse/21_interactive_dipole_fit.py | 53 | # sources. On the command line there are various options you can use to specify files | COMMENT |
| MEDIUM | tutorials/inverse/21_interactive_dipole_fit.py | 146 | # happy with the selection, you can use the "Fit dipole" button as before to fit a | COMMENT |
| MEDIUM | tutorials/intro/30_info.py | 181 | # channels in it, you can use the :func:`mne.pick_info` function to pick the | COMMENT |
| LOW | tutorials/intro/40_sensor_locations.py | 52 | # computed on a spherical head model, make sure to check out the `eeg_positions`_ | COMMENT |
| MEDIUM | tutorials/intro/50_configure_mne.py | 198 | # the current Python session, you can use :func:`mne.set_log_level` instead. | COMMENT |
| MEDIUM | tutorials/intro/50_configure_mne.py | 275 | # Or you can use :func:`mne.sys_info` directly, which prints to ``stdout`` by | COMMENT |
| MEDIUM | tutorials/time-freq/20_sensors_time_frequency.py | 180 | # but you can also use :func:`mne.time_frequency.tfr_multitaper` | COMMENT |
| MEDIUM | tutorials/time-freq/10_spectrum_class.py | 104 | # similar to :class:`~mne.Epochs` objects: you can use string values to select | COMMENT |
| MEDIUM | tutorials/io/60_ctf_bst_auditory.py | 223 | # saccades) you can use keyword ``reject_by_annotation=False``. | COMMENT |
| MEDIUM | tutorials/simulation/10_array_objs.py | 115 | # To create a `~mne.io.Raw` object from scratch, you can use the | COMMENT |
| MEDIUM | tutorials/simulation/10_array_objs.py | 137 | # To create an `~mne.Epochs` object from scratch, you can use the | COMMENT |
| MEDIUM | tutorials/simulation/10_array_objs.py | 197 | # If you already have data that was averaged across trials, you can use it to | COMMENT |
| MEDIUM | …/stats-source-space/20_cluster_1samp_spatiotemporal.py | 9 | conditions across subjects. Here just for demonstration purposes we simulate data from | STRING |
| MEDIUM | tutorials/epochs/30_epochs_metadata.py | 90 | # Like any :class:`pandas.DataFrame`, you can modify the data or add columns as | COMMENT |
| MEDIUM | tutorials/epochs/10_epochs_overview.py | 178 | # constructor, you can add it later by assigning to the ``event_id`` | COMMENT |
| MEDIUM | tutorials/epochs/10_epochs_overview.py | 313 | # To change the temporal extent of the :class:`~mne.Epochs`, you can use the | COMMENT |
| MEDIUM | tutorials/epochs/10_epochs_overview.py | 386 | # channel will appear in a separate column. Then you can use any of Pandas' | COMMENT |
| MEDIUM | tutorials/epochs/10_epochs_overview.py | 454 | # If you want to iterate over :class:`~mne.Epochs` objects, you can use an | COMMENT |
| MEDIUM | tutorials/preprocessing/60_maxwell_filtering_sss.py | 347 | # want to doublecheck, you can use :func:`mne.chpi.get_active_chpi` (currently | COMMENT |
| MEDIUM | tutorials/preprocessing/40_artifact_correction_ica.py | 430 | # you can use as a proxy for EOG. You can use a single channel, or create a | COMMENT |
| LOW | tutorials/preprocessing/40_artifact_correction_ica.py | 45 | # the artifacts in your data to make sure you choose the right repair tool. | COMMENT |
| MEDIUM | tutorials/preprocessing/45_projectors_background.py | 315 | # Python :class:`dict`, so you can use its ``.keys()`` method to see what | COMMENT |
| MEDIUM | tutorials/preprocessing/55_setting_eeg_reference.py | 79 | # earlobe or mastoid channels, so this is just for demonstration purposes: | COMMENT |
| MEDIUM | tutorials/preprocessing/55_setting_eeg_reference.py | 97 | # the signal at* ``Fp1``. In this situation, you can add back ``Fp1`` as a flat | COMMENT |
| MEDIUM | tutorials/preprocessing/55_setting_eeg_reference.py | 132 | # To set a "virtual reference" that is the average of all channels, you can use | COMMENT |
| MEDIUM | tutorials/preprocessing/55_setting_eeg_reference.py | 220 | # To create a bipolar reference, you can use :meth:`~mne.set_bipolar_reference` | COMMENT |
| MEDIUM⚡ | tutorials/preprocessing/25_background_filtering.py | 1056 | # were used through the 'auto' setting, you can use | COMMENT |
| MEDIUM | tutorials/preprocessing/50_artifact_correction_ssp.py | 251 | # To compute SSP projectors for the heartbeat artifact, you can use | COMMENT |
| MEDIUM | tutorials/preprocessing/50_artifact_correction_ssp.py | 268 | # end of the list). If you don't want that, you can change that behavior with | COMMENT |
| LOW | tutorials/preprocessing/50_artifact_correction_ssp.py | 40 | # the artifacts in your data to make sure you choose the right repair tool. | COMMENT |
| MEDIUM | tutorials/raw/20_event_arrays.py | 199 | # you can change that with the ``id`` parameter. It is also possible to specify | COMMENT |
| MEDIUM | tutorials/raw/10_raw_overview.py | 293 | # inaccurate, you can change the type of any channel with the | COMMENT |
| MEDIUM | tutorials/raw/10_raw_overview.py | 341 | # or combine two or more separate :class:`~mne.io.Raw` objects — you can use | COMMENT |
| MEDIUM | tutorials/evoked/30_eeg_erp.py | 108 | # system, you can add sensor locations to the data with | COMMENT |
| MEDIUM | tutorials/evoked/30_eeg_erp.py | 583 | # measures. First, you can use an *a priori* time window based on prior | COMMENT |
| MEDIUM | tutorials/evoked/10_evoked_overview.py | 128 | # If you've already created the :class:`~mne.Evoked` object, you can use the | COMMENT |
| MEDIUM | tutorials/evoked/10_evoked_overview.py | 281 | # you can use :meth:`~mne.Epochs.equalize_event_counts` prior to averaging. | COMMENT |
| LOW | tutorials/forward/25_automated_coreg.py | 103 | # Don't forget to save the resulting ``trans`` matrix! | COMMENT |
| MEDIUM | tutorials/forward/80_fix_bem_in_blender.py | 348 | # :ref:`tut-fix-meshes-smoothing` does not work, you can try fixing the mesh | COMMENT |
| LOW | tutorials/forward/80_fix_bem_in_blender.py | 257 | # When editing BEM surfaces/meshes in Blender, make sure to use | COMMENT |
| MEDIUM | tutorials/forward/30_forward.py | 151 | # you can use the following code. | COMMENT |
| MEDIUM | tutorials/forward/30_forward.py | 169 | # dipoles inside the brain (requires the :term:`BEM` surfaces) you can use the | COMMENT |
| MEDIUM | tutorials/forward/30_forward.py | 290 | # To save to disk a forward solution you can use | COMMENT |
| MEDIUM | tutorials/forward/35_eeg_no_mri.py | 98 | # To use an infant head model for M/EEG data, you can use | COMMENT |
| Severity | File | Line | Snippet | Context |
|---|---|---|---|---|
| HIGH | examples/visualization/brain.py | 21 | # In this example we use the ``sample`` data which is data from a subject | COMMENT |
| HIGH⚡ | examples/simulation/plot_stc_metrics.py | 58 | # In this example we simulate two types of cortical sources: a region and | COMMENT |
| HIGH | …simulation/simulated_raw_data_using_subject_anatomy.py | 30 | # In this example, raw data will be simulated for the sample subject, so its | COMMENT |
| HIGH | …simulation/simulated_raw_data_using_subject_anatomy.py | 128 | # Generate source time courses for each region. In this example, we want to | COMMENT |
| HIGH | examples/preprocessing/eeg_bridging.py | 398 | # In this example, we have shown a dataset where electrical bridging occurred | COMMENT |
| HIGH | tutorials/clinical/20_seeg.py | 230 | # In this example, it is simply the source with the largest raw signal value. | COMMENT |
| HIGH⚡ | tutorials/preprocessing/70_fnirs_processing.py | 106 | # In this example the data is clean and the coupling is good for all | COMMENT |
| HIGH⚡ | tutorials/preprocessing/70_fnirs_processing.py | 116 | # In this example we will mark all channels with a SCI less than 0.5 as bad | COMMENT |
| HIGH | …rials/stats-sensor-space/40_cluster_1samp_time_freq.py | 185 | # In this example, we wish to set the threshold for including data bins in | COMMENT |
| Severity | File | Line | Snippet | Context |
|---|---|---|---|---|
| LOW | mne/epochs.py | 296 | # Check if we already have an entry for merged keys of duplicate | COMMENT |
| LOW | mne/epochs.py | 1672 | # Check if indices and reasons are of the same length | COMMENT |
| LOW | mne/epochs.py | 4191 | # Check if criterion is a function and apply it | COMMENT |
| LOW | mne/bem.py | 1482 | # Open the file, create directory | COMMENT |
| LOW | mne/chpi.py | 1802 | # Set bads to empty list here. In theory flux jumps etc. or even flat channels | COMMENT |
| LOW | mne/time_frequency/tests/test_csd.py | 363 | # Check if the CSD matrices are hermitian | COMMENT |
| LOW | mne/io/nirx/nirx.py | 149 | # Check if required files exist and store names for later use | COMMENT |
| LOW | mne/io/eeglab/eeglab.py | 468 | # Check if data is embedded in the same .set file | STRING |
| LOW | mne/io/eeglab/eeglab.py | 515 | # Check if data is embedded in .set file | COMMENT |
| LOW | mne/io/eeglab/eeglab.py | 518 | # Check if we have already loaded and cached the embedded data | COMMENT |
| LOW | mne/tests/test_epochs.py | 589 | # Check if callable returns a tuple with reasons | COMMENT |
| LOW | mne/tests/test_morph.py | 519 | # Check if not morphed, but voxel size not boolean, raise ValueError. | COMMENT |
| LOW | mne/utils/tests/test_config.py | 77 | # Check if get_config with key=None returns all config | COMMENT |
| LOW | mne/decoding/tests/test_ssd.py | 316 | # Check if the 5 first 5 components are the same for both | COMMENT |
| LOW⚡ | mne/viz/tests/test_raw.py | 928 | # Check if single annotation toggle works | COMMENT |
| LOW⚡ | mne/viz/tests/test_raw.py | 933 | # Check if annotation filtering works - All annotations | COMMENT |
| LOW⚡ | mne/viz/tests/test_raw.py | 942 | # Check if annotation filtering works - filtering annotations | COMMENT |
| LOW | mne/viz/tests/test_ica.py | 504 | # Check if annotation filtering works - All annotations | COMMENT |
| LOW | mne/viz/tests/test_ica.py | 512 | # Check if annotation filtering works - filtering annotations | COMMENT |
| LOW | mne/viz/_brain/_brain.py | 1605 | # Check if limits have changed at all. | COMMENT |
| LOW | mne/_fiff/meas_info.py | 2238 | # Check if all elements are numbers - convert to numpy array | COMMENT |
| LOW | mne/_fiff/meas_info.py | 2252 | # Check if this is a tagged MNE type | COMMENT |
| LOW | mne/preprocessing/_peak_finder.py | 150 | # Check if we still need to add the last point | COMMENT |
| LOW | mne/preprocessing/_lof.py | 80 | # Check if there are different channel types | COMMENT |
| LOW | mne/preprocessing/eyetracking/tests/test_calibration.py | 107 | # Check if the copied object is an instance of Calibration | COMMENT |
| LOW | mne/preprocessing/eyetracking/tests/test_calibration.py | 109 | # Check if the an attribute of the copied object is equal to the original object | COMMENT |
| LOW | mne/minimum_norm/spatial_resolution.py | 79 | # Check if input options are valid | COMMENT |
| LOW | mne/minimum_norm/inverse.py | 207 | # Open the file, create directory | COMMENT |
| LOW | mne/minimum_norm/inverse.py | 431 | # Open the file, create directory | COMMENT |
| LOW | mne/forward/forward.py | 462 | # Check if a custom reference has been applied | COMMENT |
| LOW | mne/forward/forward.py | 571 | # Open the file, create directory | COMMENT |
| LOW | mne/channels/montage.py | 1917 | # Set device to head transform to identity (canonical positions) | STRING |
| LOW | mne/channels/channels.py | 2116 | # Check if channel indices are out of bounds | COMMENT |
| LOW | mne/channels/channels.py | 2119 | # Check if heterogeneous sensor type combinations | COMMENT |
| LOW | mne/channels/channels.py | 2134 | # Check if combining less than 2 channel | COMMENT |
| LOW | tutorials/inverse/35_dipole_orientations.py | 254 | # Set loose to 0.2, the default value | COMMENT |
| LOW | tutorials/evoked/30_eeg_erp.py | 474 | # Print output from the good time window that contains the peak | COMMENT |
| LOW | tutorials/evoked/30_eeg_erp.py | 499 | # Print output | COMMENT |
| LOW | tutorials/evoked/30_eeg_erp.py | 541 | # Print output | COMMENT |
| LOW | doc/sphinxext/directive_formatting.py | 92 | # Check if text resembling directives is present | COMMENT |
| LOW | doc/sphinxext/directive_formatting.py | 140 | # Check if previous line is part of another directive | COMMENT |
| Severity | File | Line | Snippet | Context |
|---|---|---|---|---|
| HIGH | mne/epochs.py | 0 | %(plot_psd_doc)s. parameters ---------- %(fmin_fmax_psd)s %(tmin_tmax_psd)s %(picks_good_data_noref)s %(proj_psd)s %(rej | STRING |
| HIGH | mne/evoked.py | 0 | %(plot_psd_doc)s. parameters ---------- %(fmin_fmax_psd)s %(tmin_tmax_psd)s %(picks_good_data_noref)s %(proj_psd)s %(rej | STRING |
| HIGH | mne/time_frequency/spectrum.py | 0 | %(plot_psd_doc)s. parameters ---------- %(fmin_fmax_psd)s %(tmin_tmax_psd)s %(picks_good_data_noref)s %(proj_psd)s %(rej | STRING |
| HIGH | mne/io/tests/test_raw.py | 0 | tests resampling doesn't affect data if sfreq is identical. | STRING |
| HIGH | mne/tests/test_source_estimate.py | 0 | tests resampling doesn't affect data if sfreq is identical. | STRING |
| HIGH | mne/tests/test_evoked.py | 0 | tests resampling doesn't affect data if sfreq is identical. | STRING |
| Severity | File | Line | Snippet | Context |
|---|---|---|---|---|
| HIGH | mne/conftest.py | 1246 | "execution_count": null, | STRING |
| HIGH | mne/annotations.py | 2650 | Annotations returned by this function will all have zero (null) duration. | STRING |
| HIGH | mne/stats/parametric.py | 99 | # If df is undefined, variances are zero (assumes n1 > 0 & n2 > 0). | COMMENT |
| HIGH⚡ | tutorials/stats-sensor-space/10_background_stats.py | 437 | # the null, no further inference on the cluster (e.g., peak location) can be | COMMENT |
| Severity | File | Line | Snippet | Context |
|---|---|---|---|---|
| LOW⚡ | mne/bem.py | 2069 | # Step 2 : Create the parameter maps | COMMENT |
| LOW⚡ | mne/bem.py | 2079 | # Step 3 : Synthesize the flash 5 images | COMMENT |
| LOW | mne/bem.py | 2183 | # Step 4 : Register with MPRAGE | COMMENT |
| LOW⚡ | mne/stats/cluster_level.py | 886 | # Step 1: Calculate t-stat for original data | COMMENT |
| LOW⚡ | mne/stats/cluster_level.py | 998 | # Step 2: If we have some clusters, repeat process on permuted data | COMMENT |
| LOW⚡ | mne/stats/cluster_level.py | 1000 | # Step 3: repeat permutations for step-down-in-jumps procedure | COMMENT |
| Severity | File | Line | Snippet | Context |
|---|---|---|---|---|
| LOW⚡ | mne/bem.py | 2069 | # Step 2 : Create the parameter maps | COMMENT |
| LOW⚡ | mne/bem.py | 2079 | # Step 3 : Synthesize the flash 5 images | COMMENT |
| LOW | mne/bem.py | 2183 | # Step 4 : Register with MPRAGE | COMMENT |
| LOW⚡ | mne/stats/cluster_level.py | 886 | # Step 1: Calculate t-stat for original data | COMMENT |
| LOW⚡ | mne/stats/cluster_level.py | 998 | # Step 2: If we have some clusters, repeat process on permuted data | COMMENT |
| LOW⚡ | mne/stats/cluster_level.py | 1000 | # Step 3: repeat permutations for step-down-in-jumps procedure | COMMENT |
| Severity | File | Line | Snippet | Context |
|---|---|---|---|---|
| LOW | mne/io/constants.py | 7 | __all__ = ["FIFF"] | CODE |
| LOW | mne/io/pick.py | 12 | __all__ = [ | CODE |
| LOW | mne/utils/_typing.py | 16 | __all__ = ["Color", "FileLike", "Self"] | CODE |
| LOW | mne/viz/_brain/__init__.py | 11 | __all__ = ["Brain"] | CODE |
| Severity | File | Line | Snippet | Context |
|---|---|---|---|---|
| LOW | mne/viz/backends/tests/test_abstract.py | 31 | text = backend._Text("test", "placeholder", callback) | CODE |
| LOW | mne/report/js_and_css/highlightjs/highlight.min.js | 421 | ;const e=["a","abbr","address","article","aside","audio","b","blockquote","body","button","canvas","caption","cite","cod | CODE |
| LOW | mne/report/js_and_css/highlightjs/highlight.min.js | 1035 | ;const e=["a","abbr","address","article","aside","audio","b","blockquote","body","button","canvas","caption","cite","cod | CODE |
| LOW | mne/report/js_and_css/highlightjs/highlight.min.js | 1061 | ;const e=["a","abbr","address","article","aside","audio","b","blockquote","body","button","canvas","caption","cite","cod | CODE |
| Severity | File | Line | Snippet | Context |
|---|---|---|---|---|
| LOW | mne/preprocessing/nirs/_tddr.py | 75 | # Usage: | COMMENT |