ENH: allow per-channel colors in raw.plot via channel name dict keys (#13765)

Author: HansujaB

doc/changes/dev/13765.newfeature.rst

@@ -0,0 +1 @@
+Allow per-channel color overrides in :func:`mne.viz.plot_raw` via channel name keys in the ``color`` dict, by :newcontrib:`Hansuja Budhiraja`.

mne/viz/_mpl_figure.py

@@ -2006,8 +2006,13 @@ def _draw_traces(self):
         )
         offsets = self.mne.trace_offsets[offset_ixs]
         bad_bool = np.isin(ch_names, self.mne.info["bads"])
-        # colors
-        good_ch_colors = [self.mne.ch_color_dict[_type] for _type in ch_types]
+        # colors: allow overrides by channel name, then by channel type
+        good_ch_colors = []
+        for _name, _type in zip(ch_names, ch_types):
+            if _name in self.mne.ch_color_dict:
+                good_ch_colors.append(self.mne.ch_color_dict[_name])
+            else:
+                good_ch_colors.append(self.mne.ch_color_dict[_type])
         ch_colors = to_rgba_array(
             [
                 self.mne.ch_color_bad if _bad else _color

mne/viz/raw.py

@@ -96,6 +96,10 @@ def plot_raw(
                  emg='k', ref_meg='steelblue', misc='k', stim='k',
                  resp='k', chpi='k')
 
+        If a dict, keys can be channel *types* (e.g., ``'eeg'``) and/or
+        channel *names* (e.g., ``'SFG, Left'``); name-based entries
+        take precedence over type-based ones.
+
     bad_color : color object
         Color to make bad channels.
     %(event_color)s

mne/viz/tests/test_raw.py

@@ -7,6 +7,7 @@
 from copy import deepcopy
 from pathlib import Path
 
+import matplotlib.colors as mcolors
 import matplotlib.pyplot as plt
 import numpy as np
 import pytest
@@ -317,6 +318,31 @@ def test_scale_bar(browser_backend):
         bar_lims = bar.get_ydata()
         assert_allclose(y_lims, bar_lims, atol=1e-4)
 
+    # Per-channel color overrides via channel names (matplotlib only).
+    if ismpl:
+        sfreq = 100.0
+        ch_names = ["SFG, Left", "SFG, Right", "MFG, Left"]
+        info = create_info(ch_names=ch_names, sfreq=sfreq, ch_types="eeg")
+        data = np.zeros((len(ch_names), int(sfreq)))  # 1 second of zeros
+        raw2 = RawArray(data, info)
+
+        color = {"eeg": "k", "SFG, Left": "red"}
+        browser_backend._close_all()
+        fig2 = plot_raw(raw2, color=color, show=False)
+
+        # ch_colors stores the "good" (non-bad) colors, in visible channel order
+        assert fig2.mne.ch_colors[0] == "red"
+        assert fig2.mne.ch_colors[1] == "k"
+        assert fig2.mne.ch_colors[2] == "k"
+
+        # check colours on the plot are also correct
+        for trace, ch_color in zip(fig2.mne.traces, fig2.mne.ch_colors):
+            assert np.allclose(
+                mcolors.to_rgba(trace.get_color()), mcolors.to_rgba(ch_color)
+            ), f"Expected {ch_color}, got {trace.get_color()}"
+
+        browser_backend._close_all()
+
 
 def test_plot_raw_selection(raw, browser_backend):
     """Test selection mode of plot_raw()."""