MAINT: Fix randint 0d limits and other 0d cleanups (numpy#15126)

* MAINT: only treat 0d case separately in randint, simplify some tests

Author: nschloe

numpy/core/tests/test_machar.py

@@ -16,7 +16,7 @@ def _run_machar_highprec(self):
         # underflow
         try:
             hiprec = ntypes.float96
-            MachAr(lambda v:array([v], hiprec))
+            MachAr(lambda v: array(v, hiprec))
         except AttributeError:
             # Fixme, this needs to raise a 'skip' exception.
             "Skipping test: no ntypes.float96 available on this platform."

numpy/core/tests/test_multiarray.py

@@ -7564,8 +7564,8 @@ def test_to_int_scalar(self):
         # gh-9972 means that these aren't always the same
         int_funcs = (int, lambda x: x.__int__())
         for int_func in int_funcs:
+            assert_equal(int_func(np.array(0)), 0)
             assert_equal(int_func(np.array([1])), 1)
-            assert_equal(int_func(np.array([0])), 0)
             assert_equal(int_func(np.array([[42]])), 42)
             assert_raises(TypeError, int_func, np.array([1, 2]))
 

numpy/random/_bounded_integers.pyx.in

@@ -314,8 +314,7 @@ cdef object _rand_{{nptype}}(object low, object high, object size,
     high_arr = <np.ndarray>np.array(high, copy=False)
     low_ndim = np.PyArray_NDIM(low_arr)
     high_ndim = np.PyArray_NDIM(high_arr)
-    if ((low_ndim == 0 or (low_ndim == 1 and low_arr.size == 1 and size is not None)) and
-            (high_ndim == 0 or (high_ndim == 1 and high_arr.size == 1 and size is not None))):
+    if low_ndim == 0 and high_ndim == 0:
         low = int(low_arr)
         high = int(high_arr)
         # Subtract 1 since internal generator produces on closed interval [low, high]

numpy/testing/tests/test_utils.py

@@ -608,9 +608,9 @@ class TestApproxEqual(object):
     def setup(self):
         self._assert_func = assert_approx_equal
 
-    def test_simple_arrays(self):
-        x = np.array([1234.22])
-        y = np.array([1234.23])
+    def test_simple_0d_arrays(self):
+        x = np.array(1234.22)
+        y = np.array(1234.23)
 
         self._assert_func(x, y, significant=5)
         self._assert_func(x, y, significant=6)