From 751d8d1a90a2e8ab29bd42647ce73f9e304a1669 Mon Sep 17 00:00:00 2001
From: Philipp Holl <philipp.holl@tum.de>
Date: Sun, 6 Oct 2024 14:01:21 +0200
Subject: [PATCH] [vis] Fix Matplotlib color handling

---
 phi/vis/_matplotlib/_matplotlib_plots.py | 14 +++++++-------
 1 file changed, 7 insertions(+), 7 deletions(-)

diff --git a/phi/vis/_matplotlib/_matplotlib_plots.py b/phi/vis/_matplotlib/_matplotlib_plots.py
index d3896c8b2..e7e6ecbd9 100644
--- a/phi/vis/_matplotlib/_matplotlib_plots.py
+++ b/phi/vis/_matplotlib/_matplotlib_plots.py
@@ -22,7 +22,7 @@
 from phi.geom._transform import _EmbeddedGeometry
 from phi.math import Tensor, channel, spatial, instance, non_channel, Shape, reshaped_numpy, shape
 from phi.vis._vis_base import display_name, PlottingLibrary, Recipe, index_label, only_stored_elements, to_field
-
+from phiml.math import wrap
 
 colormaps = matplotlib.colormaps if hasattr(matplotlib.colormaps, 'get_cmap') else matplotlib.cm
 
@@ -400,7 +400,7 @@ def plot(self, data: Field, figure, subplot, space: Box, min_val: float, max_val
         xyz = StaggeredGrid(lambda x: x, math.extrapolation.BOUNDARY, data.geometry.bounds, data.resolution).staggered_tensor().numpy(dims + ('vector',))[:-1, :-1, :-1, :]
         xyz = xyz.reshape(-1, 3)
         values = data.values.numpy(dims).flatten()
-        if color == 'cmap':
+        if wrap(color == 'cmap').all:
             color = 0
         col = matplotlib.colors.to_rgba(_plt_col(color))
         colors = np.zeros_like(values)[..., None] + col
@@ -451,7 +451,7 @@ def plot(self, data: Field, figure, subplot, space: Box, min_val: float, max_val
             x, y = reshaped_numpy(c_data.center[dims], [vector, c_data.shape.without('vector')])
             u, v = reshaped_numpy(c_data.values.vector[dims], [vector, c_data.shape.without('vector')])
             color_i = color[idx]
-            if color[idx] == 'cmap':
+            if (color[idx] == 'cmap').all:
                 col = _next_line_color(subplot, kind='collections')  # ToDo
             elif color[idx].shape:
                 col = [_plt_col(c) for c in color_i.numpy(c_data.shape.non_channel).reshape(-1)]
@@ -494,7 +494,7 @@ def plot(self, data: Field, figure, subplot, space: Box, min_val: float, max_val
         x = x[:, 0]
         y = y[0, :]
         u, v = reshaped_numpy(data.values.vector[vector.item_names[0]], [vector, *data.shape.without('vector')])
-        if color == 'cmap':
+        if wrap(color == 'cmap').all:
             col = reshaped_numpy(math.vec_length(data.values), [*data.shape.without('vector')]).T
         elif color.shape:
             col = [_plt_col(c) for c in color.numpy(data.shape.non_channel).reshape(-1)]
@@ -619,7 +619,7 @@ def _plot_points(axis: Axes, data: Field, dims: tuple, vector: Shape, color: Ten
                 data = Field(sdf_grid, math.NAN, 0)
         data = only_stored_elements(data)
         x, y = reshaped_numpy(data.points.vector[dims], ['vector', non_channel(data)])
-        if color == 'cmap':
+        if wrap(color == 'cmap').all:
             values = reshaped_numpy(data.values, [non_channel(data)])
             mpl_colors = add_color_bar(axis, values, min_val, max_val)
             single_color = False
@@ -690,7 +690,7 @@ def _plot_points(axis: Axes, data: Field, dims: tuple, vector: Shape, color: Ten
                 p1, p2 = edges.index
                 x1, y1 = reshaped_numpy(data.graph.center[p1], ['vector', instance])
                 x2, y2 = reshaped_numpy(data.graph.center[p2], ['vector', instance])
-                if color == 'cmap':
+                if wrap(color == 'cmap').all:
                     edge_val = reshaped_numpy(edge_val, [instance])
                     edge_colors = add_color_bar(axis, edge_val, min_val, max_val)
                     if edge_val.min() == edge_val.max():
@@ -877,7 +877,7 @@ def _plt_col(col):
 
 
 def matplotlib_colors(color: Tensor, dims: Shape, default=None) -> Union[list, None]:
-    if color.rank == 0 and color == 'cmap':
+    if color.rank == 0 and wrap(color == 'cmap').all:
         if default is None:
             return None
         else: