Easy Matplotlib output.

examples/matplotlib_example.py

@@ -0,0 +1,34 @@
+# From https://matplotlib.org/stable/gallery/images_contours_and_fields/contour_corner_mask.html
+import matplotlib.pyplot as plt
+import numpy as np
+from lynxkite.core.ops import op
+
+
+@op("LynxKite Graph Analytics", "Matplotlib example", view="matplotlib")
+def example():
+    # Data to plot.
+    x, y = np.meshgrid(np.arange(7), np.arange(10))
+    z = np.sin(0.5 * x) * np.cos(0.52 * y)
+
+    # Mask various z values.
+    mask = np.zeros_like(z, dtype=bool)
+    mask[2, 3:5] = True
+    mask[3:5, 4] = True
+    mask[7, 2] = True
+    mask[5, 0] = True
+    mask[0, 6] = True
+    z = np.ma.array(z, mask=mask)
+    print(z)
+
+    corner_masks = [False, True]
+    fig, axs = plt.subplots(ncols=2)
+    for ax, corner_mask in zip(axs, corner_masks):
+        cs = ax.contourf(x, y, z, corner_mask=corner_mask)
+        ax.contour(cs, colors="k")
+        ax.set_title(f"{corner_mask=}")
+
+        # Plot grid.
+        ax.grid(c="k", ls="-", alpha=0.3)
+
+        # Indicate masked points with red circles.
+        ax.plot(np.ma.array(x, mask=~mask), y, "ro")

examples/requirements.txt

@@ -1,2 +1,3 @@
 # Example of a requirements.txt file. LynxKite will automatically install anything you put here.
 faker
+matplotlib

lynxkite-core/src/lynxkite/core/ops.py

@@ -221,13 +221,17 @@ def op(env: str, name: str, *, view="basic", outputs=None, params=None, slow=Fal
             _outputs = {name: Output(name=name, type=None) for name in outputs}
         else:
             _outputs = {"output": Output(name="output", type=None)} if view == "basic" else {}
+        _view = view
+        if view == "matplotlib":
+            _view = "image"
+            func = matplotlib_to_image(func)
         op = Op(
             func=func,
             name=name,
             params=_params,
             inputs=inputs,
             outputs=_outputs,
-            type=view,
+            type=_view,
         )
         CATALOGS.setdefault(env, {})
         CATALOGS[env][name] = op
@@ -237,6 +241,23 @@ def op(env: str, name: str, *, view="basic", outputs=None, params=None, slow=Fal
     return decorator
 
 
+def matplotlib_to_image(func):
+    import matplotlib.pyplot as plt
+    import base64
+    import io
+
+    @functools.wraps(func)
+    def wrapper(*args, **kwargs):
+        func(*args, **kwargs)
+        buf = io.BytesIO()
+        plt.savefig(buf, format="png")
+        buf.seek(0)
+        image_base64 = base64.b64encode(buf.read()).decode("utf-8")
+        return f"data:image/png;base64,{image_base64}"
+
+    return wrapper
+
+
 def input_position(**kwargs):
     """Decorator for specifying unusual positions for the inputs."""