ENH: Better event count rep and noise_cov_method (#854)

docs/source/settings/source/inverse.md

@@ -10,5 +10,6 @@ tags:
         - depth
         - inverse_method
         - noise_cov
+        - noise_cov_method
         - source_info_path_update
         - inverse_targets

docs/source/v1.6.md.inc

@@ -8,6 +8,7 @@
 - Chosen `reject` parameters are now saved in the generated HTML reports (#839 by @larsoner)
 - Added saving of clean raw data in addition to epochs (#840 by @larsoner)
 - Added saving of detected blink and cardiac events used to calculate SSP projectors (#840 by @larsoner)
+- Added [`noise_cov_method`][mne_bids_pipeline._config.noise_cov_method] to allow for the use of methods other than `"shrunk"` for noise covariance estimation (#854 by @larsoner)
 
 [//]: # (### :warning: Behavior changes)
 
@@ -27,6 +28,7 @@
 - Fix bug where raw, empty-room, and custom noise covariances were errantly calculated on data without ICA or SSP applied (#840 by @larsoner)
 - Fix bug where multiple channel types (e.g., MEG and EEG) were not handled correctly in decoding (#853 by @larsoner)
 - Fix bug where the previous default for [`ica_n_components`][mne_bids_pipeline._config.ica_n_components] of `0.8` was too conservative, changed the default to `None` to match MNE-Python (#853 by @larsoner)
+- Fix bug where the events table for the average subject could overflow in reports (#854 by @larsoner)
 
 ### :medical_symbol: Code health
 

mne_bids_pipeline/_config.py

@@ -2050,6 +2050,22 @@ def noise_cov(bids_path):
     ```
 """
 
+noise_cov_method: Literal[
+    "shrunk",
+    "empirical",
+    "diagonal_fixed",
+    "oas",
+    "ledoit_wolf",
+    "factor_analysis",
+    "shrinkage",
+    "pca",
+    "auto",
+] = "shrunk"
+"""
+The noise covariance estimation method to use. See the MNE-Python documentation
+of `mne.compute_covariance` for details.
+"""
+
 source_info_path_update: Optional[dict[str, str]] = dict(suffix="ave")
 """
 When computing the forward and inverse solutions, by default the pipeline

mne_bids_pipeline/_main.py

@@ -94,7 +94,11 @@ def main():
         help="Enable interactive mode.",
     )
     parser.add_argument(
-        "--debug", dest="debug", action="store_true", help="Enable debugging on error."
+        "--debug",
+        "--pdb",
+        dest="debug",
+        action="store_true",
+        help="Enable debugging on error.",
     )
     parser.add_argument(
         "--no-cache",

mne_bids_pipeline/_report.py

@@ -1,4 +1,5 @@
 import contextlib
+import re
 from functools import lru_cache
 from io import StringIO
 from types import SimpleNamespace
@@ -472,30 +473,13 @@ def add_event_counts(
     logger.info(**gen_log_kwargs(message="Adding event counts to report …"))
 
     if df_events is not None:
-        css_classes = ("table", "table-striped", "table-borderless", "table-hover")
+        df_events.reset_index(drop=False, inplace=True, col_level=1)
         report.add_html(
-            f'<div class="event-counts">\n'
-            f"{df_events.to_html(classes=css_classes, border=0)}\n"
-            f"</div>",
+            _df_bootstrap_table(df=df_events, data_id="events"),
             title="Event counts",
             tags=("events",),
             replace=True,
         )
-        css = (
-            ".event-counts {\n"
-            "  display: -webkit-box;\n"
-            "  display: -ms-flexbox;\n"
-            "  display: -webkit-flex;\n"
-            "  display: flex;\n"
-            "  justify-content: center;\n"
-            "  text-align: center;\n"
-            "}\n\n"
-            "th, td {\n"
-            "  text-align: center;\n"
-            "}\n"
-        )
-        if css not in report.include:
-            report.add_custom_css(css=css)
 
 
 def _finalize(
@@ -906,3 +890,65 @@ def _render_bem(
         replace=True,
         n_jobs=1,  # prevent automatic parallelization
     )
+
+
+# Copied from mne/report/report.py
+
+try:
+    from mne.report.report import _df_bootstrap_table
+except ImportError:  # MNE < 1.7
+
+    def _df_bootstrap_table(*, df, data_id):
+        html = df.to_html(
+            border=0,
+            index=False,
+            show_dimensions=True,
+            justify="unset",
+            float_format=lambda x: f"{x:.3f}",
+            classes="table table-hover table-striped table-sm table-responsive small",
+            na_rep="",
+        )
+        htmls = html.split("\n")
+        header_pattern = "<th>(.*)</th>"
+
+        for idx, html in enumerate(htmls):
+            if "<table" in html:
+                htmls[idx] = html.replace(
+                    "<table",
+                    "<table "
+                    'id="mytable" '
+                    'data-toggle="table" '
+                    f'data-unique-id="{data_id}" '
+                    'data-search="true" '  # search / filter
+                    'data-search-highlight="true" '
+                    'data-show-columns="true" '  # show/hide columns
+                    'data-show-toggle="true" '  # allow card view
+                    'data-show-columns-toggle-all="true" '
+                    'data-click-to-select="true" '
+                    'data-show-copy-rows="true" '
+                    'data-show-export="true" '  # export to a file
+                    'data-export-types="[csv]" '
+                    'data-export-options=\'{"fileName": "metadata"}\' '
+                    'data-icon-size="sm" '
+                    'data-height="400"',
+                )
+                continue
+            elif "<tr" in html:
+                # Add checkbox for row selection
+                htmls[idx] = (
+                    f"{html}\n" f'<th data-field="state" data-checkbox="true"></th>'
+                )
+                continue
+
+            col_headers = re.findall(pattern=header_pattern, string=html)
+            if col_headers:
+                # Make columns sortable
+                assert len(col_headers) == 1
+                col_header = col_headers[0]
+                htmls[idx] = html.replace(
+                    "<th>",
+                    f'<th data-field="{col_header.lower()}" ' f'data-sortable="true">',
+                )
+
+        html = "\n".join(htmls)
+        return html

mne_bids_pipeline/steps/sensor/_06_make_cov.py

@@ -116,7 +116,7 @@ def compute_cov_from_epochs(
         epochs,
         tmin=tmin,
         tmax=tmax,
-        method="shrunk",
+        method=cfg.noise_cov_method,
         rank="info",
         verbose="error",  # TODO: not baseline corrected, maybe problematic?
     )
@@ -292,6 +292,7 @@ def get_config(
         conditions=config.conditions,
         contrasts=config.contrasts,
         analyze_channels=config.analyze_channels,
+        noise_cov_method=config.noise_cov_method,
         **_bids_kwargs(config=config),
     )
     return cfg