plotting: warn about missing radii only once

navis/plotting/dd.py

@@ -550,7 +550,17 @@ def plot2d(
                     settings.radius = False
 
             if isinstance(neuron, core.TreeNeuron) and settings.radius:
-                _neuron = conversion.tree2meshneuron(neuron)
+                # Warn once if more than 5% of nodes have missing radii
+                if not getattr(fig, '_radius_warned', False):
+                    if ((neuron.nodes.radius.fillna(0).values <= 0).sum() / neuron.n_nodes) > 0.05:
+                        logger.warning(
+                            "Some skeleton nodes have radius <= 0. This may lead to "
+                            "rendering artifacts. Set `radius=False` to plot skeletons "
+                            "as single-width lines instead."
+                        )
+                        fig._radius_warned = True
+
+                _neuron = conversion.tree2meshneuron(neuron, warn_missing_radii=False)
                 _neuron.connectors = neuron.connectors
                 neuron = _neuron
 
@@ -883,7 +893,7 @@ def _plot_connectors(neuron, color, ax, settings):
                 inner_dict["color"] = settings.cn_colors
 
     if settings.method == "2d":
-        for c, this_cn in connectors.groupby('type'):
+        for c, this_cn in connectors.groupby("type"):
             x, y = _parse_view2d(this_cn[["x", "y", "z"]].values, settings.view)
 
             ax.scatter(
@@ -892,7 +902,7 @@ def _plot_connectors(neuron, color, ax, settings):
                 color=cn_layout[c]["color"],
                 edgecolor="none",
                 s=settings.cn_size if settings.cn_size else cn_layout["size"],
-                zorder=1000
+                zorder=1000,
             )
             ax.get_children()[-1].set_gid(f"CN_{neuron.id}")
     elif settings.method in ["3d", "3d_complex"]:

navis/plotting/k3d/k3d_objects.py

@@ -69,6 +69,7 @@ def neuron2k3d(x, colormap, settings):
     cn_lay.update(settings.cn_layout)
 
     trace_data = []
+    _radius_warned = False
     for i, neuron in enumerate(x):
         name = str(getattr(neuron, "name", neuron.id))
         color = colormap[i]
@@ -106,7 +107,17 @@ def neuron2k3d(x, colormap, settings):
                 settings.radius = False
 
         if isinstance(neuron, core.TreeNeuron) and settings.radius:
-            _neuron = conversion.tree2meshneuron(neuron)
+            # Warn once if more than 5% of nodes have missing radii
+            if not _radius_warned:
+                if ((neuron.nodes.radius.fillna(0).values <= 0).sum() / neuron.n_nodes) > 0.05:
+                    logger.warning(
+                        "Some skeleton nodes have radius <= 0. This may lead to "
+                        "rendering artifacts. Set `radius=False` to plot skeletons "
+                        "as single-width lines instead."
+                    )
+                    _radius_warned = True
+
+            _neuron = conversion.tree2meshneuron(neuron, warn_missing_radii=False)
             _neuron.connectors = neuron.connectors
             neuron = _neuron
 

navis/plotting/plotly/graph_objs.py

@@ -98,6 +98,7 @@ def neuron2plotly(x, colormap, settings):
     cn_lay.update(settings.cn_layout)
 
     trace_data = []
+    _radius_warned = False
     for i, neuron in enumerate(x):
         name = str(getattr(neuron, "name", neuron.id))
         color = colormap[i]
@@ -135,7 +136,17 @@ def neuron2plotly(x, colormap, settings):
                 settings.radius = False
 
         if isinstance(neuron, core.TreeNeuron) and settings.radius:
-            _neuron = conversion.tree2meshneuron(neuron)
+            # Warn once if more than 5% of nodes have missing radii
+            if not _radius_warned:
+                if ((neuron.nodes.radius.fillna(0).values <= 0).sum() / neuron.n_nodes) > 0.05:
+                    logger.warning(
+                        "Some skeleton nodes have radius <= 0. This may lead to "
+                        "rendering artifacts. Set `radius=False` to plot skeletons "
+                        "as single-width lines instead."
+                    )
+                    _radius_warned = True
+
+            _neuron = conversion.tree2meshneuron(neuron, warn_missing_radii=False)
             _neuron.connectors = neuron.connectors
             neuron = _neuron
 

navis/plotting/vispy/visuals.py

@@ -251,6 +251,7 @@ def neuron2vispy(x, settings):
 
     # List to fill with vispy visuals
     visuals = []
+    _radius_warned = False
     for i, neuron in enumerate(x):
         # Generate random ID -> we need this in case we have duplicate IDs
         object_id = uuid.uuid4()
@@ -263,7 +264,17 @@ def neuron2vispy(x, settings):
                 settings.radius = False
 
         if isinstance(neuron, core.TreeNeuron) and settings.radius:
-            _neuron = conversion.tree2meshneuron(neuron)
+            # Warn once if more than 5% of nodes have missing radii
+            if not _radius_warned:
+                if ((neuron.nodes.radius.fillna(0).values <= 0).sum() / neuron.n_nodes) > 0.05:
+                    logger.warning(
+                        "Some skeleton nodes have radius <= 0. This may lead to "
+                        "rendering artifacts. Set `radius=False` to plot skeletons "
+                        "as single-width lines instead."
+                    )
+                    _radius_warned = True
+
+            _neuron = conversion.tree2meshneuron(neuron, warn_missing_radii=False)
             _neuron.connectors = neuron.connectors
             neuron = _neuron