MNT: make all of the properties on LineWrapper mappable

Author: tacaswell

data_prototype/wrappers.py

@@ -187,7 +187,8 @@ def draw(self, renderer):
         return self._wrapped_instance.draw(renderer)
 
     def _update_wrapped(self, data):
-        self._wrapped_instance.set_data(data["x"], data["y"])
+        for k, v in data.items():
+            getattr(self._wrapped_instance, f"set_{k}")(v)
 
 
 class ImageWrapper(ProxyWrapper):

examples/mapped.py

@@ -0,0 +1,57 @@
+"""
+=======================
+Mapping Line Properties
+=======================
+
+Leveraging the nu functions to transform users space data to visualization data.
+
+"""
+
+import matplotlib.pyplot as plt
+import numpy as np
+import pandas as pd
+
+from matplotlib.colors import Normalize
+
+from data_prototype.wrappers import LineWrapper
+from data_prototype.containers import ArrayContainer
+
+cmap = plt.colormaps["viridis"]
+cmap.set_over("k")
+cmap.set_under("r")
+norm = Normalize(1, 8)
+
+nus = {
+    # arbitrary functions
+    "lw": lambda lw: min(1 + lw, 5),
+    # standard color mapping
+    "color": lambda color: cmap(norm(color)),
+    # categorical
+    "ls": lambda ls: {"A": "-", "B": ":", "C": "--"}[ls[()]],
+}
+
+th = np.linspace(0, 2 * np.pi, 128)
+delta = np.pi / 9
+
+fig, ax = plt.subplots()
+
+for j in range(10):
+    ax.add_artist(
+        LineWrapper(
+            ArrayContainer(
+                **{
+                    "x": th,
+                    "y": np.sin(th + j * delta) + j,
+                    "color": np.asarray(j),
+                    "lw": np.asarray(j),
+                    "ls": np.asarray({0: "A", 1: "B", 2: "C"}[j % 3]),
+                }
+            ),
+            nus,
+        )
+    )
+
+ax.set_xlim(0, np.pi * 2)
+ax.set_ylim(-1.1, 10.1)
+
+plt.show()