wip jensen demo add axis projection #6

790gradml · Jun 29, 2023 · 5f66baf · 5f66baf
1 parent 29c4594
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Showing 2 changed files with 64 additions and 17 deletions.
diff --git a/demos/Jensen.html b/demos/Jensen.html
diff --git a/demos/scripts/Jensen.py b/demos/scripts/Jensen.py
@@ -1,25 +1,45 @@
 import numpy as np
 import plotly.graph_objects as go
 
+n = 200
 # Generate random data
 f = lambda alpha, x: alpha * x * x + x + 3 * x
 
 # Create NumPy arrays
 alphas = np.linspace(-3, 3, 9)
-x = np.random.randn(200) + 1
+x = np.random.randn(n) + 1
+xbar = np.average(x)
+f_of_x_bar = f(alpha, xbar)
 y = {}
+ybar = {}
 for alpha in alphas:
-    # mean_of_x = np.average(x)
-    y[str(alpha)] = f(alpha, x)
+    this_y = f(alpha, x)
+    y[str(alpha)] = this_y
+    ybar[str(alpha)] = np.average(this_y)
 # Create figure and scatter plot
 fig = go.Figure(
-    data=go.Scatter(
-        x=x,
-        y=y[str(alphas[0])],
-        mode="markers",
-        marker=dict(size=10, colorscale="Viridis", showscale=True),
-        hovertemplate="x: %{x}<br>y: %{y}<br>scalar: %{marker.color}",
-    ),
+    data=[
+        go.Scatter(
+            x=x,
+            y=y[str(alphas[0])],
+            mode="markers",
+            marker=dict(size=10, colorscale="Viridis", showscale=False),
+            hovertemplate="x: %{x}<br>y: %{y}",
+        ),
+        go.Scatter(
+            x=x,
+            y=np.zeros(n),
+            mode="markers",
+            xaxis="x",
+            yaxis="y2",
+        ),
+        go.Scatter(
+            x=np.zeros(n),
+            y=y[str(alphas[0])],
+            xaxis="x2",
+            yaxis="y",
+        ),
+    ],
     layout=go.Layout(
         # title="Jensen's Inequality",
         # xaxis=dict(range=[0, 1]),
@@ -55,7 +75,7 @@
         sliders=[
             dict(
                 active=0,
-                currentvalue={"prefix": "Alpha: "},
+                currentvalue={"prefix": r"$\alpha$: "},
                 pad={"t": 50},
                 steps=[
                     dict(
@@ -85,16 +105,43 @@
                     marker=dict(
                         size=10,
                     ),
-                )
+                ),
+                go.Scatter(
+                    x=x,
+                    y=np.zeros(n),
+                    mode="markers",
+                    name="Subplot 1",
+                    xaxis="x",
+                    yaxis="y2",
+                ),
+                go.Scatter(
+                    x=np.zeros(n),
+                    y=y[str(i)],
+                    mode="markers",
+                    xaxis="x2",
+                    yaxis="y",
+                ),
             ],
         )
         for i in alphas
     ],
 )
 
 # Show the figure
-fig.update_layout(title_text="Jensen's Inequality")
-fig.show()
+fig.update_layout(
+    title="Jensen's Inequality",
+    xaxis=dict(title="Sampled x", domain=[0, 0.95]),
+    yaxis=dict(title=r"$f(x)$", domain=[0.1, 1], tickformat="$%s$"),
+    xaxis2=dict(
+        title=None, domain=[1 - 0.03, 1], range=(-0.1, 0.1), showticklabels=False
+    ),
+    yaxis2=dict(title=None, domain=[0, 0.03], range=(-0.1, 0.1), showticklabels=False),
+    showlegend=False,
+)
+
+
+# Create the figure
+# fig.show()
 
 import os