[FIX] Fix color bar handling with color map with only 1 level

examples/01_plotting/plot_demo_glass_brain_extensive.py

@@ -102,6 +102,7 @@
     threshold=2,
     symmetric_cbar=False,
     cmap="viridis",
+    title="only plot positive values",
 )
 
 # %%
@@ -116,6 +117,7 @@
     threshold=2,
     symmetric_cbar=False,
     cmap="viridis",
+    title="vmin == threshold",
 )
 
 # %%

nilearn/plotting/displays/_slicers.py

@@ -396,6 +396,16 @@
         threshold = float(threshold) if threshold is not None else None
 
         affine = img.affine
+        if threshold is not None:
+            data = safe_get_data(img, ensure_finite=True)
+            if threshold == 0:
+                data = np.ma.masked_equal(data, 0, copy=False)
+            else:
+                data = np.ma.masked_inside(
+                    data, -threshold, threshold, copy=False
+                )
+            img = new_img_like(img, data, affine)
+
         data = safe_get_data(img, ensure_finite=True)
         data_bounds = get_bounds(data.shape, affine)
         (xmin, xmax), (ymin, ymax), (zmin, zmax) = data_bounds

nilearn/plotting/tests/test_img_plotting/test_plot_roi.py

@@ -69,3 +69,25 @@ def test_demo_plot_roi_output_file(tmp_path):
     with open(filename, "wb") as fp:
         out = demo_plot_roi(output_file=fp)
     assert out is None
+
+
+def test_cmap_with_one_level(shape_3d_default, affine_eye):
+    """Test we can handle cmap with only 1 level
+
+    Regression test for
+    https://github.com/nilearn/nilearn/issues/4255
+    """
+    array_data = np.zeros(shape_3d_default)
+    array_data[0, 1, 1] = 1
+
+    img = Nifti1Image(array_data, affine_eye)
+
+    clust_ids = list(np.unique(img.get_fdata())[1:])
+
+    try:
+        cmap = plt.colormaps["tab20"].resampled(len(clust_ids))
+    except TypeError:
+        # for older versions of matplotlib
+        cmap = plt.cm.get_cmap("tab20", len(clust_ids))
+
+    plot_roi(img, alpha=0.8, colorbar=True, cmap=cmap)