MAINT: Remove duplicate randint helpers code.

Continuation of gh-8071 by removing the duplicate
randint Cython code that is not generated via Tempita.

1 files changed, 0 insertions, 277 deletions

diff --git a/numpy/random/mtrand/mtrand.pyx b/numpy/random/mtrand/mtrand.pyx
index eab8e59b3..1c7ffe9d5 100644
--- a/numpy/random/mtrand/mtrand.pyx
+++ b/numpy/random/mtrand/mtrand.pyx
@@ -573,283 +573,6 @@ def _shape_from_size(size, d):
            shape = tuple(size) + (d,)
     return shape
 
-
-# Set up dictionary of integer types and relevant functions.
-#
-# The dictionary is keyed by dtype(...).name and the values
-# are a tuple (low, high, function), where low and high are
-# the bounds of the largest half open interval `[low, high)`
-# and the function is the relevant function to call for
-# that precision.
-#
-# The functions are all the same except for changed types in
-# a few places. It would be easy to template them.
-
-def _rand_bool(low, high, size, rngstate):
-    """
-    _rand_bool(low, high, size, rngstate)
-
-    See `_rand_int32` for documentation, only the return type changes.
-
-    """
-    cdef npy_bool off, rng, buf
-    cdef npy_bool *out
-    cdef ndarray array "arrayObject"
-    cdef npy_intp cnt
-    cdef rk_state *state = <rk_state *>PyCapsule_GetPointer(rngstate, NULL)
-
-    rng = <npy_bool>(high - low)
-    off = <npy_bool>(low)
-    if size is None:
-        rk_random_bool(off, rng, 1, &buf, state)
-        return np.bool_(<npy_bool>buf)
-    else:
-        array = <ndarray>np.empty(size, np.bool_)
-        cnt = PyArray_SIZE(array)
-        out = <npy_bool *>PyArray_DATA(array)
-        with nogil:
-            rk_random_bool(off, rng, cnt, out, state)
-        return array
-
-
-def _rand_int8(low, high, size, rngstate):
-    """
-    _rand_int8(low, high, size, rngstate)
-
-    See `_rand_int32` for documentation, only the return type changes.
-
-    """
-    cdef npy_uint8 off, rng, buf
-    cdef npy_uint8 *out
-    cdef ndarray array "arrayObject"
-    cdef npy_intp cnt
-    cdef rk_state *state = <rk_state *>PyCapsule_GetPointer(rngstate, NULL)
-
-    rng = <npy_uint8>(high - low)
-    off = <npy_uint8>(<npy_int8>low)
-    if size is None:
-        rk_random_uint8(off, rng, 1, &buf, state)
-        return np.int8(<npy_int8>buf)
-    else:
-        array = <ndarray>np.empty(size, np.int8)
-        cnt = PyArray_SIZE(array)
-        out = <npy_uint8 *>PyArray_DATA(array)
-        with nogil:
-            rk_random_uint8(off, rng, cnt, out, state)
-        return array
-
-
-def _rand_int16(low, high, size, rngstate):
-    """
-    _rand_int16(low, high, size, rngstate)
-
-    See `_rand_int32` for documentation, only the return type changes.
-
-    """
-    cdef npy_uint16 off, rng, buf
-    cdef npy_uint16 *out
-    cdef ndarray array "arrayObject"
-    cdef npy_intp cnt
-    cdef rk_state *state = <rk_state *>PyCapsule_GetPointer(rngstate, NULL)
-
-    rng = <npy_uint16>(high - low)
-    off = <npy_uint16>(<npy_int16>low)
-    if size is None:
-        rk_random_uint16(off, rng, 1, &buf, state)
-        return np.int16(<npy_int16>buf)
-    else:
-        array = <ndarray>np.empty(size, np.int16)
-        cnt = PyArray_SIZE(array)
-        out = <npy_uint16 *>PyArray_DATA(array)
-        with nogil:
-            rk_random_uint16(off, rng, cnt, out, state)
-        return array
-
-
-def _rand_int32(low, high, size, rngstate):
-    """
-    _rand_int32(self, low, high, size, rngstate)
-
-    Return random np.int32 integers between `low` and `high`, inclusive.
-
-    Return random integers from the "discrete uniform" distribution in the
-    closed interval [`low`, `high`]. On entry the arguments are presumed
-    to have been validated for size and order for the np.int32 type.
-
-    Parameters
-    ----------
-    low : int
-        Lowest (signed) integer to be drawn from the distribution.
-    high : int
-        Highest (signed) integer to be drawn from the distribution.
-    size : int or tuple of ints
-        Output shape.  If the given shape is, e.g., ``(m, n, k)``, then
-        ``m * n * k`` samples are drawn.  Default is None, in which case a
-        single value is returned.
-    rngstate : encapsulated pointer to rk_state
-        The specific type depends on the python version. In Python 2 it is
-        a PyCObject, in Python 3 a PyCapsule object.
-
-    Returns
-    -------
-    out : python scalar or ndarray of np.int32
-          `size`-shaped array of random integers from the appropriate
-          distribution, or a single such random int if `size` not provided.
-
-    """
-    cdef npy_uint32 off, rng, buf
-    cdef npy_uint32 *out
-    cdef ndarray array "arrayObject"
-    cdef npy_intp cnt
-    cdef rk_state *state = <rk_state *>PyCapsule_GetPointer(rngstate, NULL)
-
-    rng = <npy_uint32>(high - low)
-    off = <npy_uint32>(<npy_int32>low)
-    if size is None:
-        rk_random_uint32(off, rng, 1, &buf, state)
-        return np.int32(<npy_int32>buf)
-    else:
-        array = <ndarray>np.empty(size, np.int32)
-        cnt = PyArray_SIZE(array)
-        out = <npy_uint32 *>PyArray_DATA(array)
-        with nogil:
-            rk_random_uint32(off, rng, cnt, out, state)
-        return array
-
-
-def _rand_int64(low, high, size, rngstate):
-    """
-    _rand_int64(low, high, size, rngstate)
-
-    See `_rand_int32` for documentation, only the return type changes.
-
-    """
-    cdef npy_uint64 off, rng, buf
-    cdef npy_uint64 *out
-    cdef ndarray array "arrayObject"
-    cdef npy_intp cnt
-    cdef rk_state *state = <rk_state *>PyCapsule_GetPointer(rngstate, NULL)
-
-    rng = <npy_uint64>(high - low)
-    off = <npy_uint64>(<npy_int64>low)
-    if size is None:
-        rk_random_uint64(off, rng, 1, &buf, state)
-        return np.int64(<npy_int64>buf)
-    else:
-        array = <ndarray>np.empty(size, np.int64)
-        cnt = PyArray_SIZE(array)
-        out = <npy_uint64 *>PyArray_DATA(array)
-        with nogil:
-            rk_random_uint64(off, rng, cnt, out, state)
-        return array
-
-def _rand_uint8(low, high, size, rngstate):
-    """
-    _rand_uint8(low, high, size, rngstate)
-
-    See `_rand_int32` for documentation, only the return type changes.
-
-    """
-    cdef npy_uint8 off, rng, buf
-    cdef npy_uint8 *out
-    cdef ndarray array "arrayObject"
-    cdef npy_intp cnt
-    cdef rk_state *state = <rk_state *>PyCapsule_GetPointer(rngstate, NULL)
-
-    rng = <npy_uint8>(high - low)
-    off = <npy_uint8>(low)
-    if size is None:
-        rk_random_uint8(off, rng, 1, &buf, state)
-        return np.uint8(<npy_uint8>buf)
-    else:
-        array = <ndarray>np.empty(size, np.uint8)
-        cnt = PyArray_SIZE(array)
-        out = <npy_uint8 *>PyArray_DATA(array)
-        with nogil:
-            rk_random_uint8(off, rng, cnt, out, state)
-        return array
-
-
-def _rand_uint16(low, high, size, rngstate):
-    """
-    _rand_uint16(low, high, size, rngstate)
-
-    See `_rand_int32` for documentation, only the return type changes.
-
-    """
-    cdef npy_uint16 off, rng, buf
-    cdef npy_uint16 *out
-    cdef ndarray array "arrayObject"
-    cdef npy_intp cnt
-    cdef rk_state *state = <rk_state *>PyCapsule_GetPointer(rngstate, NULL)
-
-    rng = <npy_uint16>(high - low)
-    off = <npy_uint16>(low)
-    if size is None:
-        rk_random_uint16(off, rng, 1, &buf, state)
-        return np.uint16(<npy_uint16>buf)
-    else:
-        array = <ndarray>np.empty(size, np.uint16)
-        cnt = PyArray_SIZE(array)
-        out = <npy_uint16 *>PyArray_DATA(array)
-        with nogil:
-            rk_random_uint16(off, rng, cnt, out, state)
-        return array
-
-
-def _rand_uint32(low, high, size, rngstate):
-    """
-    _rand_uint32(self, low, high, size, rngstate)
-
-    See `_rand_int32` for documentation, only the return type changes.
-
-    """
-    cdef npy_uint32 off, rng, buf
-    cdef npy_uint32 *out
-    cdef ndarray array "arrayObject"
-    cdef npy_intp cnt
-    cdef rk_state *state = <rk_state *>PyCapsule_GetPointer(rngstate, NULL)
-
-    rng = <npy_uint32>(high - low)
-    off = <npy_uint32>(low)
-    if size is None:
-        rk_random_uint32(off, rng, 1, &buf, state)
-        return np.uint32(<npy_uint32>buf)
-    else:
-        array = <ndarray>np.empty(size, np.uint32)
-        cnt = PyArray_SIZE(array)
-        out = <npy_uint32 *>PyArray_DATA(array)
-        with nogil:
-            rk_random_uint32(off, rng, cnt, out, state)
-        return array
-
-
-def _rand_uint64(low, high, size, rngstate):
-    """
-    _rand_uint64(low, high, size, rngstate)
-
-    See `_rand_int32` for documentation, only the return type changes.
-
-    """
-    cdef npy_uint64 off, rng, buf
-    cdef npy_uint64 *out
-    cdef ndarray array "arrayObject"
-    cdef npy_intp cnt
-    cdef rk_state *state = <rk_state *>PyCapsule_GetPointer(rngstate, NULL)
-
-    rng = <npy_uint64>(high - low)
-    off = <npy_uint64>(low)
-    if size is None:
-        rk_random_uint64(off, rng, 1, &buf, state)
-        return np.uint64(<npy_uint64>buf)
-    else:
-        array = <ndarray>np.empty(size, np.uint64)
-        cnt = PyArray_SIZE(array)
-        out = <npy_uint64 *>PyArray_DATA(array)
-        with nogil:
-            rk_random_uint64(off, rng, cnt, out, state)
-        return array
-
 # Look up table for randint functions keyed by type name. The stored data
 # is a tuple (lbnd, ubnd, func), where lbnd is the smallest value for the
 # type, ubnd is one greater than the largest value, and func is the