provide "context" with a shared param

core.py

@@ -10,7 +10,12 @@ from interactive_pipe import Curve, SingleCurve
 def gen_color(
     frequency: int = 0,  # discrete slider (int)
     isotropy: float = 0.,  # continuous slider (float)
+    context={}  # global parameters (dict)
 ) -> np.ndarray:
+    # context allows sharing information between processing blocks.
+    # Let's share the frequency value for further use.
+    context["freq"] = frequency
+    print(context.get("initialized_param", "Wrongly initialized context!"))
     lin_coord = np.linspace(0, 1., 256)
     X, Y = np.meshgrid(lin_coord, isotropy*lin_coord)
     radius = 0.5+0.5*np.cos(frequency*np.sqrt(X**2 + Y**2))
@@ -47,14 +52,20 @@ def compare_by_splitting(
     return out
 
 
-def extract_profile(img: np.ndarray,) -> Curve:
+def extract_profile(img: np.ndarray, context={}) -> Curve:
+    # context allows sharing information between processing blocks
+    frequency = context.get('freq', 0)
+    init_shared_param = context.get(
+        'initialized_param', "Wrongly initialized context!")
     luma = img.mean(axis=-1)
-    h_profile = SingleCurve(y=luma[0, :], label="H profile")
+    h_profile = SingleCurve(
+        y=luma[0, :], label=f"H profile f={frequency}")
     v_profile = SingleCurve(y=luma[:, 0], label="V profile")
     return Curve(
         [h_profile, v_profile],
         xlabel="Position", ylabel="Luminance",
-        grid=True
+        grid=True,
+        title=f"Luminance profiles\n(global context parameter {init_shared_param})"
     )
 
 # -------------------

interactivity.py

@@ -31,7 +31,10 @@ def run_interactive_pipeline(
     playable_tutorial_pipeline = interactive_pipeline(
         gui=backend,
         cache=True,
-        markdown_description=markdown_description
+        markdown_description=markdown_description,
+        context={"initialized_param": 42}
+        # context is shared between processing blocks.
+        # Initialization allow to pre-load a neural network for example.
     )(tutorial_pipeline)
     playable_tutorial_pipeline()