X-Git-Url: http://gitweb.michael.orlitzky.com/?a=blobdiff_plain;f=mjo%2Fcone%2Fcone.py;h=777d45e1a3e7a72a5ebbb167fd1ef6540c745282;hb=81a763e35b3e4322be6c60a815064be1f0dfcc3c;hp=6ade5e628f1035c99294048c7fb55b4b9c1204d9;hpb=7d2f3fba7f494158dbce5f7a3eca1d15ee7f577e;p=sage.d.git

diff --git a/mjo/cone/cone.py b/mjo/cone/cone.py
index 6ade5e6..777d45e 100644
--- a/mjo/cone/cone.py
+++ b/mjo/cone/cone.py
@@ -8,126 +8,6 @@ addsitedir(abspath('../../'))
 from sage.all import *
 
 
-def random_cone(min_dim=0, max_dim=None, min_rays=0, max_rays=None):
-    r"""
-    Generate a random rational convex polyhedral cone.
-
-    Lower and upper bounds may be provided for both the dimension of the
-    ambient space and the number of generating rays of the cone. If a
-    lower bound is left unspecified, it defaults to zero. Unspecified
-    upper bounds will be chosen randomly.
-
-    INPUT:
-
-    - ``min_dim`` (default: zero) -- A nonnegative integer representing the
-                                     minimum dimension of the ambient lattice.
-
-    - ``max_dim`` (default: random) -- A nonnegative integer representing
-                                       the maximum dimension of the ambient
-                                       lattice.
-
-    - ``min_rays`` (default: zero) -- A nonnegative integer representing the
-                                      minimum number of generating rays of the
-                                      cone.
-
-    - ``max_rays`` (default: random) -- A nonnegative integer representing the
-                                        maximum number of generating rays of the
-                                        cone.
-
-    OUTPUT:
-
-    A new, randomly generated cone.
-
-    EXAMPLES:
-
-    If we set the lower/upper bounds to zero, then our result is
-    predictable::
-
-        sage: random_cone(0,0,0,0)
-        0-d cone in 0-d lattice N
-
-    In fact, as long as we ask for zero rays, we should be able to predict
-    the output when ``min_dim == max_dim``::
-
-        sage: random_cone(min_dim=4, max_dim=4, min_rays=0, max_rays=0)
-        0-d cone in 4-d lattice N
-
-    TESTS:
-
-    It's hard to test the output of a random process, but we can at
-    least make sure that we get a cone back::
-
-        sage: from sage.geometry.cone import is_Cone # long time
-        sage: K = random_cone() # long time
-        sage: is_Cone(K)        # long time
-        True
-
-    Ensure that an exception is raised when either lower bound is greater
-    than its respective upper bound::
-
-        sage: random_cone(min_dim=5, max_dim=2)
-        Traceback (most recent call last):
-        ...
-        ValueError: max_dim must be greater than or equal to min_dim.
-
-        sage: random_cone(min_rays=5, max_rays=2)
-        Traceback (most recent call last):
-        ...
-        ValueError: max_rays must be greater than or equal to min_rays.
-
-    """
-
-    # Catch obvious mistakes so that we can generate clear error
-    # messages.
-
-    if min_dim < 0:
-        raise ValueError('min_dim must be nonnegative.')
-
-    if min_rays < 0:
-        raise ValueError('min_rays must be nonnegative.')
-
-    if max_dim is not None:
-        if max_dim < 0:
-            raise ValueError('max_dim must be nonnegative.')
-        if (min_dim > max_dim):
-            raise ValueError('max_dim must be greater than or equal to min_dim.')
-
-    if max_rays is not None:
-        if max_rays < 0:
-            raise ValueError('max_rays must be nonnegative.')
-        if (min_rays > max_rays):
-            raise ValueError('max_rays must be greater than or equal to min_rays.')
-
-
-    def random_min_max(l,u):
-        r"""
-        We need to handle two cases for the upper bounds, and we need to do
-        the same thing for max_dim/max_rays. So we consolidate the logic here.
-        """
-        if u is None:
-            # The upper bound is unspecified; return a random integer
-            # in [l,infinity).
-            return l + ZZ.random_element().abs()
-        else:
-            # We have an upper bound, and it's greater than or equal
-            # to our lower bound. So we generate a random integer in
-            # [0,u-l], and then add it to l to get something in
-            # [l,u]. To understand the "+1", check the
-            # ZZ.random_element() docs.
-            return l + ZZ.random_element(u - l + 1)
-
-
-    d = random_min_max(min_dim, max_dim)
-    r = random_min_max(min_rays, max_rays)
-
-    L = ToricLattice(d)
-    rays = [L.random_element() for i in range(0,r)]
-
-    # The lattice parameter is required when no rays are given, so we
-    # pass it just in case.
-    return Cone(rays, lattice=L)
-
-
 def discrete_complementarity_set(K):
     r"""
     Compute the discrete complementarity set of this cone.