remove plotting abs as the defauls for plotting volumetric

mne/viz/_3d.py

@@ -2723,6 +2723,9 @@ def _plot_and_correct(*, params, cut_coords):
         symmetric_cbar=True,
         title="",
     )
+    if mode == "glass_brain":
+        # signed MIP (value with max abs) for diverging colormaps
+        plot_kwargs["plot_abs"] = not params["diverging"]
     params["axes"].clear()
     if params.get("fig_anat") is not None and plot_kwargs["colorbar"]:
         params["fig_anat"]._cbar.ax.clear()
@@ -2776,8 +2779,14 @@ def plot_volume_source_estimates(
         If ``None``, ``stc.subject`` will be used.
     %(subjects_dir)s
     mode : ``'stat_map'`` | ``'glass_brain'``
-        The plotting mode to use. For ``'glass_brain'``, activation absolute values are
-        displayed after being transformed to a standard MNI brain.
+        The plotting mode to use. For ``'glass_brain'``, activations are displayed
+        after being transformed to a standard MNI brain. With a diverging colormap
+        (e.g., ``clim=dict(pos_lims=...)``), the signed value with the maximum
+        absolute value along each projection is shown; otherwise, absolute values
+        are shown.
+
+        .. versionchanged:: 1.13.1
+           Signed values can be shown in ``'glass_brain'`` mode.
     bg_img : instance of SpatialImage | str
         The background image used in the nilearn plotting function.
         Can also be a string to use the ``bg_img`` file in the subject's
@@ -2954,8 +2963,7 @@ def plot_volume_source_estimates(
     lx = ax_time.axvline(stc.times[time_idx], color="g")
     params.update(fig=fig, ax_time=ax_time, lx=lx, axes=axes)
 
-    allow_pos_lims = mode != "glass_brain"
-    mapdata = _process_clim(clim, colormap, transparent, stc.data, allow_pos_lims)
+    mapdata = _process_clim(clim, colormap, transparent, stc.data)
     _separate_map(mapdata)
     diverging = "pos_lims" in mapdata["clim"]
     ticks = _get_map_ticks(mapdata)
@@ -2968,7 +2976,7 @@ def plot_volume_source_estimates(
     dup_neg = False
     if stc.data.min() < 0:
         ax_time.axhline(0.0, color="0.5", ls="-", lw=0.5, zorder=2)
-        dup_neg = not diverging  # glass brain with signed data
+        dup_neg = not diverging  # signed data with one-sided colormap
     yticks = list(ticks)
     if dup_neg:
         yticks += [0] + list(-np.array(ticks))

mne/viz/tests/test_3d_mpl.py

@@ -111,6 +111,36 @@ def test_plot_volume_source_estimates_basic(
     assert use_ax is not None
     label = use_ax.get_legend().get_texts()[0].get_text()
     assert re.match("[0-9]*", label) is not None, label
+    if mode != "glass_brain" or stype != "s":
+        return
+
+    # signed data: diverging colormap (default) shows signed MIP, one-sided abs
+    stc.data -= 0.5
+    for clim, signed in (
+        ("auto", True),
+        (dict(kind="value", lims=[0.1, 0.2, 0.5]), False),
+    ):
+        with _record_warnings():
+            fig = stc.plot(
+                sample_src,
+                subject="sample",
+                subjects_dir=subjects_dir,
+                mode=mode,
+                clim=clim,
+            )
+        mips = [
+            np.ma.asarray(im.get_array())
+            for ax in fig.axes
+            for im in ax.images
+            if im.get_array().ndim == 2
+        ]
+        assert len(mips) == 3
+        for mip in mips:
+            assert mip.max() > 0.4
+            if signed:
+                assert mip.min() < -0.4
+            else:
+                assert mip.min() >= 0
 
 
 @pytest.mark.slowtest  # can be slow on OSX

tutorials/inverse/50_beamformer_lcmv.py

@@ -252,7 +252,7 @@
 # On MNI glass brain (orthoview; 2D)
 # ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
 
-stc.plot(mode="glass_brain", clim=dict(kind="value", lims=lims), **kwargs)
+stc.plot(mode="glass_brain", clim=dict(kind="value", pos_lims=lims), **kwargs)
 
 # %%
 # Volumetric rendering (3D) with vectors