Typo, parameter checks and tests

src/sage/graphs/hypergraph_generators.py

@@ -179,7 +179,7 @@ def CompleteUniform(self, n, k):
 
     def UniformRandomUniform(self, n, k, m):
         r"""
-        Retrun a uniformly sampled `k`-uniform hypergraph on `n` points with
+        Return a uniformly sampled `k`-uniform hypergraph on `n` points with
         `m` hyperedges.
 
         - ``n`` -- number of nodes of the graph
@@ -188,24 +188,59 @@ def UniformRandomUniform(self, n, k, m):
 
         - ``m`` -- number of edges
 
-        TESTS::
+        EXAMPLES::
 
             sage: H = hypergraphs.UniformRandomUniform(52, 3, 17)
             sage: H
             Incidence structure with 52 points and 17 blocks
             sage: H.is_connected()
             False
+
+        TESTS::
+            sage: hypergraphs.UniformRandomUniform(-52, 3, 17)
+            Traceback (most recent call last):
+            ...
+            ValueError: number of vertices should be non-negative
+            sage: hypergraphs.UniformRandomUniform(52.9, 3, 17)
+            Traceback (most recent call last):
+            ...
+            ValueError: number of vertices should be an integer
+            sage: hypergraphs.UniformRandomUniform(52, -3, 17)
+            Traceback (most recent call last):
+            ...
+            ValueError: the uniformity should be non-negative
+            sage: hypergraphs.UniformRandomUniform(52, I, 17)
+            Traceback (most recent call last):
+            ...
+            ValueError: the uniformity should be an integer
         """
+        from sage.rings.integer import Integer
         from sage.combinat.subset import Subsets
         from sage.misc.prandom import sample
-        vertices = list(range(n))
-        all_edges = Subsets(vertices, k)
+
+        # Construct the vertex set
+        if n < 0:
+            raise ValueError("number of vertices should be non-negative")
+        try:
+            nverts = Integer(n)
+        except TypeError:
+            raise ValueError("number of vertices should be an integer")
+        vertices = range(nverts)
+
+        # Construct the edge set
+        if k < 0:
+            raise ValueError("the uniformity should be non-negative")
+        try:
+            uniformity = Integer(k)
+        except TypeError:
+            raise ValueError("the uniformity should be an integer")
+        all_edges = Subsets(vertices, uniformity)
         try:
             edges = sample(all_edges, m)
         except OverflowError:
             raise OverflowError("binomial({},{}) too large to be treated".format(n,k))
         except ValueError:
-            raise ValueError("number of edges m must between 0 and binomial({},{})".format(n,k))
+            raise ValueError("number of edges m must be between 0 and binomial({},{})".format(n,k))
 
         from sage.combinat.designs.incidence_structures import IncidenceStructure
         return IncidenceStructure(vertices, edges)
@@ -221,16 +256,58 @@ def BinomialRandomUniform(self, n, k, p):
 
         - ``p`` -- probability of an edge
 
-        TESTS::
+        EXAMPLES::
 
             sage: hypergraphs.BinomialRandomUniform(50, 3, 1).num_blocks()
             19600
             sage: hypergraphs.BinomialRandomUniform(50, 3, 0).num_blocks()
             0
+
+        TESTS::
+            sage: hypergraphs.BinomialRandomUniform(50, 3, -0.1)
+            Traceback (most recent call last):
+            ...
+            ValueError: edge probability should be in [0,1]
+            sage: hypergraphs.BinomialRandomUniform(50, 3, 1.1)
+            Traceback (most recent call last):
+            ...
+            ValueError: edge probability should be in [0,1]
+            sage: hypergraphs.BinomialRandomUniform(-50, 3, 0.17)
+            Traceback (most recent call last):
+            ...
+            ValueError: number of vertices should be non-negative
+            sage: hypergraphs.BinomialRandomUniform(50.9, 3, 0.17)
+            Traceback (most recent call last):
+            ...
+            ValueError: number of vertices should be an integer
+            sage: hypergraphs.BinomialRandomUniform(50, -3, 0.17)
+            Traceback (most recent call last):
+            ...
+            ValueError: the uniformity should be non-negative
+            sage: hypergraphs.BinomialRandomUniform(50, I, 0.17)
+            Traceback (most recent call last):
+            ...
+            ValueError: the uniformity should be an integer
         """
+        from sage.rings.integer import Integer
+        if n < 0:
+            raise ValueError("number of vertices should be non-negative")
+        try:
+            nverts = Integer(n)
+        except TypeError:
+            raise ValueError("number of vertices should be an integer")
+        if k < 0:
+            raise ValueError("the uniformity should be non-negative")
+        try:
+            uniformity = Integer(k)
+        except TypeError:
+            raise ValueError("the uniformity should be an integer")
+        if not 0 <= p <= 1:
+            raise ValueError("edge probability should be in [0,1]")
+
         import numpy.random as nrn
         from sage.functions.other import binomial
-        m = nrn.binomial(binomial(n, k), p)
+        m = nrn.binomial(binomial(nverts, uniformity), p)
         return hypergraphs.UniformRandomUniform(n, k, m)