Merge pull request #116 from bashtage/rls-1.13.3

UPD: Update with upstream changes in NumPy

Author: bashtage

doc/source/change-log.rst

@@ -2,8 +2,10 @@
 
 Change Log
 ==========
-Since 1.13.2
-------------
+
+Version 1.13.3
+--------------
+* Build Linux wheel using manylinux1
 * Allow (:meth:`~randomstate.prng.mt19937.randint`) to broadcast inputs
 * Sync with upstream NumPy changes
 * Add protection against negative inputs in (:meth:`~randomstate.prng.mt19937.dirichlet`)

randomstate/randomstate.pyx

@@ -2288,10 +2288,10 @@ cdef class RandomState:
 
         Parameters
         ----------
-        dfnum : int or array_like of ints
-            Degrees of freedom in numerator. Should be greater than zero.
-        dfden : int or array_like of ints
-            Degrees of freedom in denominator. Should be greater than zero.
+        dfnum : float or array_like of floats
+            Degrees of freedom in numerator, should be > 0.
+        dfden : float or array_like of float
+            Degrees of freedom in denominator, should be > 0.
         size : int or tuple of ints, optional
             Output shape.  If the given shape is, e.g., ``(m, n, k)``, then
             ``m * n * k`` samples are drawn.  If size is ``None`` (default),
@@ -2371,12 +2371,16 @@ cdef class RandomState:
 
         Parameters
         ----------
-        dfnum : int or array_like of ints
-            Parameter, should be > 1.
-        dfden : int or array_like of ints
-            Parameter, should be > 1.
+        dfnum : float or array_like of floats
+            Numerator degrees of freedom, should be > 0.
+
+            .. versionchanged:: 1.14.0
+               Earlier NumPy versions required dfnum > 1.
+        dfden : float or array_like of floats
+            Denominator degrees of freedom, should be > 0.
         nonc : float or array_like of floats
-            Parameter, should be >= 0.
+            Non-centrality parameter, the sum of the squares of the numerator
+            means, should be >= 0.
         size : int or tuple of ints, optional
             Output shape.  If the given shape is, e.g., ``(m, n, k)``, then
             ``m * n * k`` samples are drawn.  If size is ``None`` (default),
@@ -2443,8 +2447,8 @@ cdef class RandomState:
 
         Parameters
         ----------
-        df : int or array_like of ints
-             Number of degrees of freedom.
+        df : float or array_like of floats
+             Number of degrees of freedom, should be > 0.
         size : int or tuple of ints, optional
             Output shape.  If the given shape is, e.g., ``(m, n, k)``, then
             ``m * n * k`` samples are drawn.  If size is ``None`` (default),
@@ -2509,9 +2513,11 @@ cdef class RandomState:
 
         Parameters
         ----------
-        df : int or array_like of ints
-            Degrees of freedom, should be > 0 as of NumPy 1.10.0,
-            should be > 1 for earlier versions.
+        df : float or array_like of floats
+            Degrees of freedom, should be > 0.
+
+            .. versionchanged:: 1.10.0
+               Earlier NumPy versions required dfnum > 1.
         nonc : float or array_like of floats
             Non-centrality, should be non-negative.
         size : int or tuple of ints, optional
@@ -2660,7 +2666,7 @@ cdef class RandomState:
 
         Parameters
         ----------
-        df : int or array_like of ints
+        df : float or array_like of floats
             Degrees of freedom, should be > 0.
         size : int or tuple of ints, optional
             Output shape.  If the given shape is, e.g., ``(m, n, k)``, then
@@ -4624,6 +4630,11 @@ cdef class RandomState:
         samples : ndarray,
             The drawn samples, of shape (size, alpha.ndim).
 
+        Raises
+        -------
+        ValueError
+            If any value in alpha is less than or equal to zero
+
         Notes
         -----
         .. math:: X \\approx \\prod_{i=1}^{k}{x^{\\alpha_i-1}_i}

randomstate/tests/test_numpy_mt19937.py

@@ -1220,6 +1220,13 @@ def test_noncentral_f(self):
         assert_raises(ValueError, nonc_f, dfnum, bad_dfden, nonc * 3)
         assert_raises(ValueError, nonc_f, dfnum, dfden, bad_nonc * 3)
 
+    def test_noncentral_f_small_df(self):
+        self.set_seed()
+
+        desired = np.array([6.869638627492048, 0.785880199263955])
+        actual = random.noncentral_f(0.9, 0.9, 2, size=2)
+        assert_array_almost_equal(actual, desired, decimal=14)
+
     def test_chisquare(self):
         df = [1]
         bad_df = [-1]