DOC: hide inherited methods

ci/templates/html.mako

@@ -1,6 +1,7 @@
 <%
   import re
   import sys
+  import inspect
 
   import markdown
   try:
@@ -296,6 +297,7 @@
       <%
       class_vars = c.class_variables()
       smethods = c.functions()
+      smethods = [f for f in smethods if inspect.getmodule(f.func).__name__.startswith("carl")]
       inst_vars = c.instance_variables()
       methods = c.methods()
       mro = c.module.mro(c)
@@ -362,7 +364,7 @@
   <div id="sidebar">
     <ul id="index">
     <li class="set"><h3><a href="${ root_url }">Index</a></h3></li>
-    
+
     % if len(variables) > 0:
     <li class="set"><h3><a href="#header-variables">Module variables</a></h3>
       ${show_column_list(map(lambda v: link(v.refname), variables))}

examples/Parameterized inference from multidimensional data.ipynb

@@ -10,13 +10,13 @@
     "\n",
     "For the sake of the illustration, we will assume 5-dimensional feature $\\mathbf{x}$ generated\n",
     "from the following process $p_0$:\n",
-    " - $\\mathbf{z} := (z_0, z_1, z_2, z_3, z_4)$, such that\n",
-    "   -        $z_0 \\sim {\\cal N}(\\mu=\\alpha, \\sigma=1)$,\n",
-    "   -         $z_1 \\sim {\\cal N}(\\mu=\\beta, \\sigma=3)$,\n",
-    "   -         $z_2 \\sim {\\text{Mixture}}(\\frac{1}{2}\\,{\\cal N}(\\mu=-2, \\sigma=1), \\frac{1}{2}\\,{\\cal N}(\\mu=2, \\sigma=0.5))$,\n",
-    "   -         $z_3 \\sim {\\text{Exponential}(\\lambda=3)}$, and\n",
-    "   -         $z_4 \\sim {\\text{Exponential}(\\lambda=0.5)}$;\n",
-    "   \n",
+    "\n",
+    " - $\\mathbf{z} := (z_0, z_1, z_2, z_3, z_4)$, such that \n",
+    "     $z_0 \\sim {\\cal N}(\\mu=\\alpha, \\sigma=1)$,\n",
+    "     $z_1 \\sim {\\cal N}(\\mu=\\beta, \\sigma=3)$,\n",
+    "     $z_2 \\sim {\\text{Mixture}}(\\frac{1}{2}\\,{\\cal N}(\\mu=-2, \\sigma=1), \\frac{1}{2}\\,{\\cal N}(\\mu=2, \\sigma=0.5))$,\n",
+    "     $z_3 \\sim {\\text{Exponential}(\\lambda=3)}$, and\n",
+    "     $z_4 \\sim {\\text{Exponential}(\\lambda=0.5)}$;\n",
     "   \n",
     " - $\\mathbf{x} := R  \\mathbf{z}$, where $R$ is a fixed semi-positive definite $5 \\times 5$ matrix defining a fixed projection of $\\mathbf{z}$ into the observed space.\n",
     "  "
@@ -128,7 +128,7 @@
     }
    ],
    "source": [
-    "#plot the data\n",
+    "# Plot the data\n",
     "import corner\n",
     "fig = corner.corner(X_true, bins=20, smooth=0.85, labels=[\"X0\", \"X1\", \"X2\", \"X3\", \"X4\"])\n",
     "#plt.savefig(\"fig3.pdf\")"
@@ -138,7 +138,7 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "# Exact likelihood setup"
+    "## Exact likelihood setup"
    ]
   },
   {
@@ -244,7 +244,7 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "# Likelihood-free setup\n",
+    "## Likelihood-free setup\n",
     "\n",
     "In this example we will build a parametrized classifier $s(x; \\theta_0, \\theta_1)$ with $\\theta_1$ fixed to $(\\alpha=0, \\beta=0)$."
    ]