Add a few SymmetricCone examples.

diff --git a/src/dunshire/cones.py b/src/dunshire/cones.py
index b60811e548de76d95abe0933a245b5a52141b606..18e6a1b9254f1675f56f1998396e13b0636153fc 100644 (file)
--- a/src/dunshire/cones.py
+++ b/src/dunshire/cones.py
@@ -12,11 +12,9 @@ class SymmetricCone:
 
     There are three types of symmetric cones supported by CVXOPT:
 
-      * The nonnegative orthant in the real n-space.
-
-      * The Lorentz "ice cream" cone, or the second-order cone.
-
-      * The cone of symmetric positive-semidefinite matrices.
+      1. The nonnegative orthant in the real n-space.
+      2. The Lorentz "ice cream" cone, or the second-order cone.
+      3. The cone of symmetric positive-semidefinite matrices.
 
     This class is intended to encompass them all.
     """
@@ -28,6 +26,11 @@ class SymmetricCone:
         product of them), the only information that we need is its
         dimension. We take that dimension as a parameter, and store it
         for later.
+
+        INPUT:
+
+        - ``dimension`` -- the dimension of this cone.
+
         """
         if dimension <= 0:
             raise ValueError('cones must have dimension greater than zero')
@@ -37,6 +40,15 @@ class SymmetricCone:
     def __contains__(self, point):
         """
         Return whether or not ``point`` belongs to this cone.
+
+        EXAMPLES:
+
+            >>> K = SymmetricCone(5)
+            >>> matrix([1,2]) in K
+            Traceback (most recent call last):
+            ...
+            NotImplementedError
+
         """
         raise NotImplementedError
 
@@ -44,6 +56,14 @@ class SymmetricCone:
         """
         Return whether or not ``point`` belongs to the interior
         of this cone.
+
+        EXAMPLES:
+
+            >>> K = SymmetricCone(5)
+            >>> K.contains_strict(matrix([1,2]))
+            Traceback (most recent call last):
+            ...
+            NotImplementedError
         """
         raise NotImplementedError
 
@@ -56,6 +76,13 @@ class SymmetricCone:
         should not need to be overridden in subclasses. We prefer to do
         any special computation in ``__init__()`` and record the result
         in ``self._dimension``.
+
+        EXAMPLES:
+
+            >>> K = SymmetricCone(5)
+            >>> K.dimension()
+            5
+
         """
         return self._dimension