test_math.py

import numpy as np
from numba.cuda.testing import (skip_unless_cc_53,
                                unittest,
                                CUDATestCase,
                                skip_on_cudasim)
from numba.np import numpy_support
from numba import cuda, float32, float64, int32, vectorize, void, int64
import math


def math_acos(A, B):
    i = cuda.grid(1)
    B[i] = math.acos(A[i])


def math_asin(A, B):
    i = cuda.grid(1)
    B[i] = math.asin(A[i])


def math_atan(A, B):
    i = cuda.grid(1)
    B[i] = math.atan(A[i])


def math_acosh(A, B):
    i = cuda.grid(1)
    B[i] = math.acosh(A[i])


def math_asinh(A, B):
    i = cuda.grid(1)
    B[i] = math.asinh(A[i])


def math_atanh(A, B):
    i = cuda.grid(1)
    B[i] = math.atanh(A[i])


def math_cos(A, B):
    i = cuda.grid(1)
    B[i] = math.cos(A[i])


def math_sin(A, B):
    i = cuda.grid(1)
    B[i] = math.sin(A[i])


def math_tan(A, B):
    i = cuda.grid(1)
    B[i] = math.tan(A[i])


def math_cosh(A, B):
    i = cuda.grid(1)
    B[i] = math.cosh(A[i])


def math_sinh(A, B):
    i = cuda.grid(1)
    B[i] = math.sinh(A[i])


def math_tanh(A, B):
    i = cuda.grid(1)
    B[i] = math.tanh(A[i])


def math_atan2(A, B, C):
    i = cuda.grid(1)
    C[i] = math.atan2(A[i], B[i])


def math_exp(A, B):
    i = cuda.grid(1)
    B[i] = math.exp(A[i])


def math_erf(A, B):
    i = cuda.grid(1)
    B[i] = math.erf(A[i])


def math_erfc(A, B):
    i = cuda.grid(1)
    B[i] = math.erfc(A[i])


def math_expm1(A, B):
    i = cuda.grid(1)
    B[i] = math.expm1(A[i])


def math_fabs(A, B):
    i = cuda.grid(1)
    B[i] = math.fabs(A[i])


def math_gamma(A, B):
    i = cuda.grid(1)
    B[i] = math.gamma(A[i])


def math_lgamma(A, B):
    i = cuda.grid(1)
    B[i] = math.lgamma(A[i])


def math_log(A, B):
    i = cuda.grid(1)
    B[i] = math.log(A[i])


def math_log2(A, B):
    i = cuda.grid(1)
    B[i] = math.log2(A[i])


def math_log10(A, B):
    i = cuda.grid(1)
    B[i] = math.log10(A[i])


def math_log1p(A, B):
    i = cuda.grid(1)
    B[i] = math.log1p(A[i])


def math_remainder(A, B, C):
    i = cuda.grid(1)
    C[i] = math.remainder(A[i], B[i])


def math_sqrt(A, B):
    i = cuda.grid(1)
    B[i] = math.sqrt(A[i])


def math_hypot(A, B, C):
    i = cuda.grid(1)
    C[i] = math.hypot(A[i], B[i])


def math_pow(A, B, C):
    i = cuda.grid(1)
    C[i] = math.pow(A[i], B[i])


def math_ceil(A, B):
    i = cuda.grid(1)
    B[i] = math.ceil(A[i])


def math_floor(A, B):
    i = cuda.grid(1)
    B[i] = math.floor(A[i])


def math_copysign(A, B, C):
    i = cuda.grid(1)
    C[i] = math.copysign(A[i], B[i])


def math_fmod(A, B, C):
    i = cuda.grid(1)
    C[i] = math.fmod(A[i], B[i])


def math_modf(A, B, C):
    i = cuda.grid(1)
    B[i], C[i] = math.modf(A[i])


def math_isnan(A, B):
    i = cuda.grid(1)
    B[i] = math.isnan(A[i])


def math_isinf(A, B):
    i = cuda.grid(1)
    B[i] = math.isinf(A[i])


def math_isfinite(A, B):
    i = cuda.grid(1)
    B[i] = math.isfinite(A[i])


def math_degrees(A, B):
    i = cuda.grid(1)
    B[i] = math.degrees(A[i])


def math_radians(A, B):
    i = cuda.grid(1)
    B[i] = math.radians(A[i])


def math_trunc(A, B):
    i = cuda.grid(1)
    B[i] = math.trunc(A[i])


def math_pow_binop(A, B, C):
    i = cuda.grid(1)
    C[i] = A[i] ** B[i]


def math_mod_binop(A, B, C):
    i = cuda.grid(1)
    C[i] = A[i] % B[i]


class TestCudaMath(CUDATestCase):
    def unary_template_float16(self, func, npfunc, start=0, stop=1):
        self.unary_template(func, npfunc, np.float16, np.float16, start, stop)

    def unary_template_float32(self, func, npfunc, start=0, stop=1):
        self.unary_template(func, npfunc, np.float32, np.float32, start, stop)

    def unary_template_float64(self, func, npfunc, start=0, stop=1):
        self.unary_template(func, npfunc, np.float64, np.float64, start, stop)

    def unary_template_int64(self, func, npfunc, start=0, stop=50):
        self.unary_template(func, npfunc, np.int64, np.float64, start, stop)

    def unary_template_uint64(self, func, npfunc, start=0, stop=50):
        self.unary_template(func, npfunc, np.uint64, np.float64, start, stop)

    def unary_template(self, func, npfunc, npdtype, nprestype, start, stop):
        nelem = 50
        A = np.linspace(start, stop, nelem).astype(npdtype)
        B = np.empty_like(A).astype(nprestype)
        arytype = numpy_support.from_dtype(npdtype)[::1]
        restype = numpy_support.from_dtype(nprestype)[::1]
        cfunc = cuda.jit((arytype, restype))(func)
        cfunc[1, nelem](A, B)

        # When this test was originally written it used
        # assertTrue(np.allclose(...), which has different default tolerance
        # values to assert_allclose. The tolerance values here are chosen as
        # the tightest under which the tests will pass.
        if npdtype == np.float64:
            rtol = 1e-13
        elif npdtype == np.float32:
            rtol = 1e-6
        else:
            rtol = 1e-3
        np.testing.assert_allclose(npfunc(A), B, rtol=rtol)

    def unary_bool_special_values(self, func, npfunc, npdtype, npmtype):
        fi = np.finfo(npdtype)
        denorm = fi.tiny / 4
        A = np.array([0., denorm, fi.tiny, 0.5, 1., fi.max, np.inf, np.nan],
                     dtype=npdtype)
        B = np.empty_like(A, dtype=np.int32)
        cfunc = cuda.jit((npmtype[::1], int32[::1]))(func)

        cfunc[1, A.size](A, B)
        np.testing.assert_array_equal(B, npfunc(A))

        cfunc[1, A.size](-A, B)
        np.testing.assert_array_equal(B, npfunc(-A))

    def unary_bool_special_values_float32(self, func, npfunc):
        self.unary_bool_special_values(func, npfunc, np.float32, float32)

    def unary_bool_special_values_float64(self, func, npfunc):
        self.unary_bool_special_values(func, npfunc, np.float64, float64)

    def unary_bool_template_float32(self, func, npfunc, start=0, stop=1):
        self.unary_template(func, npfunc, np.float32, np.float32, start, stop)

    def unary_bool_template_float64(self, func, npfunc, start=0, stop=1):
        self.unary_template(func, npfunc, np.float64, np.float64, start, stop)

    def unary_bool_template_int32(self, func, npfunc, start=0, stop=49):
        self.unary_template(func, npfunc, np.int32, np.int32, start, stop)

    def unary_bool_template_int64(self, func, npfunc, start=0, stop=49):
        self.unary_template(func, npfunc, np.int64, np.int64, start, stop)

    def unary_bool_template(self, func, npfunc, npdtype, npmtype, start, stop):
        nelem = 50
        A = np.linspace(start, stop, nelem).astype(npdtype)
        B = np.empty(A.shape, dtype=np.int32)
        iarytype = npmtype[::1]
        oarytype = int32[::1]
        cfunc = cuda.jit((iarytype, oarytype))(func)
        cfunc[1, nelem](A, B)
        np.testing.assert_allclose(npfunc(A), B)

    def binary_template_float32(self, func, npfunc, start=0, stop=1):
        self.binary_template(func, npfunc, np.float32, np.float32, start, stop)

    def binary_template_float64(self, func, npfunc, start=0, stop=1):
        self.binary_template(func, npfunc, np.float64, np.float64, start, stop)

    def binary_template_int64(self, func, npfunc, start=0, stop=50):
        self.binary_template(func, npfunc, np.int64, np.float64, start, stop)

    def binary_template_uint64(self, func, npfunc, start=0, stop=50):
        self.binary_template(func, npfunc, np.uint64, np.float64, start, stop)

    def binary_template(self, func, npfunc, npdtype, nprestype, start, stop):
        nelem = 50
        A = np.linspace(start, stop, nelem).astype(npdtype)
        B = np.empty_like(A).astype(nprestype)
        arytype = numpy_support.from_dtype(npdtype)[::1]
        restype = numpy_support.from_dtype(nprestype)[::1]
        cfunc = cuda.jit((arytype, arytype, restype))(func)
        cfunc[1, nelem](A, A, B)
        np.testing.assert_allclose(npfunc(A, A), B)

    #---------------------------------------------------------------------------
    # test_math_acos

    def test_math_acos(self):
        self.unary_template_float32(math_acos, np.arccos)
        self.unary_template_float64(math_acos, np.arccos)
        # For integers we can only test with zero, since <=-1 and >=1 result in
        # invalid values.
        self.unary_template_int64(math_acos, np.arccos, start=0, stop=0)
        self.unary_template_uint64(math_acos, np.arccos, start=0, stop=0)

    #---------------------------------------------------------------------------
    # test_math_asin

    def test_math_asin(self):
        self.unary_template_float32(math_asin, np.arcsin)
        self.unary_template_float64(math_asin, np.arcsin)
        # For integers we can only test with zero, since <=-1 and >=1 result in
        # invalid values.
        self.unary_template_int64(math_asin, np.arcsin, start=0, stop=0)
        self.unary_template_uint64(math_asin, np.arcsin, start=0, stop=0)

    #---------------------------------------------------------------------------
    # test_math_atan

    def test_math_atan(self):
        self.unary_template_float32(math_atan, np.arctan)
        self.unary_template_float64(math_atan, np.arctan)
        self.unary_template_int64(math_atan, np.arctan)
        self.unary_template_uint64(math_atan, np.arctan)

    #---------------------------------------------------------------------------
    # test_math_acosh

    def test_math_acosh(self):
        self.unary_template_float32(math_acosh, np.arccosh, start=1, stop=2)
        self.unary_template_float64(math_acosh, np.arccosh, start=1, stop=2)
        self.unary_template_int64(math_acosh, np.arccosh, start=1, stop=2)
        self.unary_template_uint64(math_acosh, np.arccosh, start=1, stop=2)

    #---------------------------------------------------------------------------
    # test_math_asinh

    def test_math_asinh(self):
        self.unary_template_float32(math_asinh, np.arcsinh)
        self.unary_template_float64(math_asinh, np.arcsinh)
        self.unary_template_int64(math_asinh, np.arcsinh)
        self.unary_template_uint64(math_asinh, np.arcsinh)

    #---------------------------------------------------------------------------
    # test_math_atanh

    def test_math_atanh(self):
        self.unary_template_float32(math_atanh, np.arctanh, start=0, stop=.9)
        self.unary_template_float64(math_atanh, np.arctanh, start=0, stop=.9)
        self.unary_template_int64(math_atanh, np.arctanh, start=0, stop=.9)
        self.unary_template_uint64(math_atanh, np.arctanh, start=0, stop=.9)

    #---------------------------------------------------------------------------
    # test_math_cos

    def test_math_cos(self):
        self.unary_template_float32(math_cos, np.cos)
        self.unary_template_float64(math_cos, np.cos)
        self.unary_template_int64(math_cos, np.cos)
        self.unary_template_uint64(math_cos, np.cos)

    @skip_unless_cc_53
    def test_math_fp16(self):
        self.unary_template_float16(math_sin, np.sin)
        self.unary_template_float16(math_cos, np.cos)
        self.unary_template_float16(math_exp, np.exp)
        self.unary_template_float16(math_log, np.log, start=1)
        self.unary_template_float16(math_log2, np.log2, start=1)
        self.unary_template_float16(math_log10, np.log10, start=1)
        self.unary_template_float16(math_fabs, np.fabs, start=-1)
        self.unary_template_float16(math_sqrt, np.sqrt)
        self.unary_template_float16(math_ceil, np.ceil)
        self.unary_template_float16(math_floor, np.floor)

    @skip_on_cudasim("numpy does not support trunc for float16")
    @skip_unless_cc_53
    def test_math_fp16_trunc(self):
        self.unary_template_float16(math_trunc, np.trunc)

    #---------------------------------------------------------------------------
    # test_math_sin

    def test_math_sin(self):
        self.unary_template_float32(math_sin, np.sin)
        self.unary_template_float64(math_sin, np.sin)
        self.unary_template_int64(math_sin, np.sin)
        self.unary_template_uint64(math_sin, np.sin)

    #---------------------------------------------------------------------------
    # test_math_tan

    def test_math_tan(self):
        self.unary_template_float32(math_tan, np.tan)
        self.unary_template_float64(math_tan, np.tan)
        self.unary_template_int64(math_tan, np.tan)
        self.unary_template_uint64(math_tan, np.tan)

    #---------------------------------------------------------------------------
    # test_math_cosh

    def test_math_cosh(self):
        self.unary_template_float32(math_cosh, np.cosh)
        self.unary_template_float64(math_cosh, np.cosh)
        self.unary_template_int64(math_cosh, np.cosh)
        self.unary_template_uint64(math_cosh, np.cosh)

    #---------------------------------------------------------------------------
    # test_math_sinh

    def test_math_sinh(self):
        self.unary_template_float32(math_sinh, np.sinh)
        self.unary_template_float64(math_sinh, np.sinh)
        self.unary_template_int64(math_sinh, np.sinh)
        self.unary_template_uint64(math_sinh, np.sinh)

    #---------------------------------------------------------------------------
    # test_math_tanh

    def test_math_tanh(self):
        self.unary_template_float32(math_tanh, np.tanh)
        self.unary_template_float64(math_tanh, np.tanh)
        self.unary_template_int64(math_tanh, np.tanh)
        self.unary_template_uint64(math_tanh, np.tanh)

    #---------------------------------------------------------------------------
    # test_math_atan2

    def test_math_atan2(self):
        self.binary_template_float32(math_atan2, np.arctan2)
        self.binary_template_float64(math_atan2, np.arctan2)
        self.binary_template_int64(math_atan2, np.arctan2)
        self.binary_template_uint64(math_atan2, np.arctan2)

    #---------------------------------------------------------------------------
    # test_math_erf

    def test_math_erf(self):
        @vectorize
        def ufunc(x):
            return math.erf(x)
        self.unary_template_float32(math_erf, ufunc)
        self.unary_template_float64(math_erf, ufunc)
        self.unary_template_int64(math_erf, ufunc)
        self.unary_template_uint64(math_erf, ufunc)

    #---------------------------------------------------------------------------
    # test_math_erfc

    def test_math_erfc(self):
        @vectorize
        def ufunc(x):
            return math.erfc(x)
        self.unary_template_float32(math_erfc, ufunc)
        self.unary_template_float64(math_erfc, ufunc)
        self.unary_template_int64(math_erfc, ufunc)
        self.unary_template_uint64(math_erfc, ufunc)

    #---------------------------------------------------------------------------
    # test_math_exp

    def test_math_exp(self):
        self.unary_template_float32(math_exp, np.exp)
        self.unary_template_float64(math_exp, np.exp)
        self.unary_template_int64(math_exp, np.exp)
        self.unary_template_uint64(math_exp, np.exp)

    #---------------------------------------------------------------------------
    # test_math_expm1

    def test_math_expm1(self):
        self.unary_template_float32(math_expm1, np.expm1)
        self.unary_template_float64(math_expm1, np.expm1)
        self.unary_template_int64(math_expm1, np.expm1)
        self.unary_template_uint64(math_expm1, np.expm1)

    #---------------------------------------------------------------------------
    # test_math_fabs

    def test_math_fabs(self):
        self.unary_template_float32(math_fabs, np.fabs, start=-1)
        self.unary_template_float64(math_fabs, np.fabs, start=-1)
        self.unary_template_int64(math_fabs, np.fabs, start=-1)
        self.unary_template_uint64(math_fabs, np.fabs, start=-1)

    #---------------------------------------------------------------------------
    # test_math_gamma

    def test_math_gamma(self):
        @vectorize
        def ufunc(x):
            return math.gamma(x)
        self.unary_template_float32(math_gamma, ufunc, start=0.1)
        self.unary_template_float64(math_gamma, ufunc, start=0.1)
        self.unary_template_int64(math_gamma, ufunc, start=1)
        self.unary_template_uint64(math_gamma, ufunc, start=1)

    #---------------------------------------------------------------------------
    # test_math_lgamma

    def test_math_lgamma(self):
        @vectorize
        def ufunc(x):
            return math.lgamma(x)
        self.unary_template_float32(math_lgamma, ufunc, start=0.1)
        self.unary_template_float64(math_lgamma, ufunc, start=0.1)
        self.unary_template_int64(math_lgamma, ufunc, start=1)
        self.unary_template_uint64(math_lgamma, ufunc, start=1)

    #---------------------------------------------------------------------------
    # test_math_log

    def test_math_log(self):
        self.unary_template_float32(math_log, np.log, start=1)
        self.unary_template_float64(math_log, np.log, start=1)
        self.unary_template_int64(math_log, np.log, start=1)
        self.unary_template_uint64(math_log, np.log, start=1)

    #---------------------------------------------------------------------------
    # test_math_log2

    def test_math_log2(self):
        self.unary_template_float32(math_log2, np.log2, start=1)
        self.unary_template_float64(math_log2, np.log2, start=1)
        self.unary_template_int64(math_log2, np.log2, start=1)
        self.unary_template_uint64(math_log2, np.log2, start=1)

    #---------------------------------------------------------------------------
    # test_math_log10

    def test_math_log10(self):
        self.unary_template_float32(math_log10, np.log10, start=1)
        self.unary_template_float64(math_log10, np.log10, start=1)
        self.unary_template_int64(math_log10, np.log10, start=1)
        self.unary_template_uint64(math_log10, np.log10, start=1)

    #---------------------------------------------------------------------------
    # test_math_log1p

    def test_math_log1p(self):
        self.unary_template_float32(math_log1p, np.log1p)
        self.unary_template_float64(math_log1p, np.log1p)
        self.unary_template_int64(math_log1p, np.log1p)
        self.unary_template_uint64(math_log1p, np.log1p)

    #---------------------------------------------------------------------------
    # test_math_remainder

    def test_math_remainder(self):
        self.binary_template_float32(math_remainder, np.remainder, start=1e-11)
        self.binary_template_float64(math_remainder, np.remainder, start=1e-11)
        self.binary_template_int64(math_remainder, np.remainder, start=1)
        self.binary_template_uint64(math_remainder, np.remainder, start=1)

    @skip_on_cudasim('math.remainder(0, 0) raises a ValueError on CUDASim')
    def test_math_remainder_0_0(self):
        @cuda.jit(void(float64[::1], int64, int64))
        def test_0_0(r, x, y):
            r[0] = math.remainder(x, y)
        r = np.zeros(1, np.float64)
        test_0_0[1, 1](r, 0, 0)
        self.assertTrue(np.isnan(r[0]))

    #---------------------------------------------------------------------------
    # test_math_sqrt

    def test_math_sqrt(self):
        self.unary_template_float32(math_sqrt, np.sqrt)
        self.unary_template_float64(math_sqrt, np.sqrt)
        self.unary_template_int64(math_sqrt, np.sqrt)
        self.unary_template_uint64(math_sqrt, np.sqrt)

    #---------------------------------------------------------------------------
    # test_math_hypot

    def test_math_hypot(self):
        self.binary_template_float32(math_hypot, np.hypot)
        self.binary_template_float64(math_hypot, np.hypot)
        self.binary_template_int64(math_hypot, np.hypot)
        self.binary_template_uint64(math_hypot, np.hypot)

    #---------------------------------------------------------------------------
    # test_math_pow

    def pow_template_int32(self, npdtype):
        nelem = 50
        A = np.linspace(0, 25, nelem).astype(npdtype)
        B = np.arange(nelem, dtype=np.int32)
        C = np.empty_like(A)
        arytype = numpy_support.from_dtype(npdtype)[::1]
        cfunc = cuda.jit((arytype, int32[::1], arytype))(math_pow)
        cfunc[1, nelem](A, B, C)

        # NumPy casting rules result in a float64 output always, which doesn't
        # match the overflow to inf of math.pow and libdevice.powi for large
        # values of float32, so we compute the reference result with math.pow.
        Cref = np.empty_like(A)
        for i in range(len(A)):
            Cref[i] = math.pow(A[i], B[i])
        np.testing.assert_allclose(np.power(A, B).astype(npdtype), C, rtol=1e-6)

    def test_math_pow(self):
        self.binary_template_float32(math_pow, np.power)
        self.binary_template_float64(math_pow, np.power)
        self.pow_template_int32(np.float32)
        self.pow_template_int32(np.float64)

    #---------------------------------------------------------------------------
    # test_math_pow_binop

    def test_math_pow_binop(self):
        self.binary_template_float32(math_pow_binop, np.power)
        self.binary_template_float64(math_pow_binop, np.power)

    #---------------------------------------------------------------------------
    # test_math_ceil

    def test_math_ceil(self):
        self.unary_template_float32(math_ceil, np.ceil)
        self.unary_template_float64(math_ceil, np.ceil)
        self.unary_template_int64(math_ceil, np.ceil)
        self.unary_template_uint64(math_ceil, np.ceil)

    #---------------------------------------------------------------------------
    # test_math_floor

    def test_math_floor(self):
        self.unary_template_float32(math_floor, np.floor)
        self.unary_template_float64(math_floor, np.floor)
        self.unary_template_int64(math_floor, np.floor)
        self.unary_template_uint64(math_floor, np.floor)

    #---------------------------------------------------------------------------
    # test_math_trunc
    #
    # Note that math.trunc() is only supported on NumPy float64s, and not
    # other float types or int types. See NumPy Issue #13375:
    #
    # - https://github.com/numpy/numpy/issues/13375 - "Add methods from the
    #   builtin float types to the numpy floating point types"

    def test_math_trunc(self):
        self.unary_template_float64(math_trunc, np.trunc)

    @skip_on_cudasim('trunc only supported on NumPy float64')
    def test_math_trunc_non_float64(self):
        self.unary_template_float32(math_trunc, np.trunc)
        self.unary_template_int64(math_trunc, np.trunc)
        self.unary_template_uint64(math_trunc, np.trunc)

    #---------------------------------------------------------------------------
    # test_math_copysign

    def test_math_copysign(self):
        self.binary_template_float32(math_copysign, np.copysign, start=-1)
        self.binary_template_float64(math_copysign, np.copysign, start=-1)

    #---------------------------------------------------------------------------
    # test_math_modf

    def test_math_modf(self):
        def modf_template_nan(dtype, arytype):
            A = np.array([np.nan], dtype=dtype)
            B = np.zeros_like(A)
            C = np.zeros_like(A)
            cfunc = cuda.jit((arytype, arytype, arytype))(math_modf)
            cfunc[1, len(A)](A, B, C)
            self.assertTrue(np.isnan(B))
            self.assertTrue(np.isnan(C))

        def modf_template_compare(A, dtype, arytype):
            A = A.astype(dtype)
            B = np.zeros_like(A)
            C = np.zeros_like(A)
            cfunc = cuda.jit((arytype, arytype, arytype))(math_modf)
            cfunc[1, len(A)](A, B, C)
            D, E = np.modf(A)
            self.assertTrue(np.array_equal(B,D))
            self.assertTrue(np.array_equal(C,E))

        nelem = 50
        #32 bit float
        with self.subTest("float32 modf on simple float"):
            modf_template_compare(np.linspace(0, 10, nelem), dtype=np.float32,
                                  arytype=float32[:])
        with self.subTest("float32 modf on +- infinity"):
            modf_template_compare(np.array([np.inf, -np.inf]), dtype=np.float32,
                                  arytype=float32[:])
        with self.subTest("float32 modf on nan"):
            modf_template_nan(dtype=np.float32, arytype=float32[:])

        #64 bit float
        with self.subTest("float64 modf on simple float"):
            modf_template_compare(np.linspace(0, 10, nelem), dtype=np.float64,
                                  arytype=float64[:])
        with self.subTest("float64 modf on +- infinity"):
            modf_template_compare(np.array([np.inf, -np.inf]), dtype=np.float64,
                                  arytype=float64[:])
        with self.subTest("float64 modf on nan"):
            modf_template_nan(dtype=np.float64, arytype=float64[:])

    #---------------------------------------------------------------------------
    # test_math_fmod

    def test_math_fmod(self):
        self.binary_template_float32(math_fmod, np.fmod, start=1)
        self.binary_template_float64(math_fmod, np.fmod, start=1)

    #---------------------------------------------------------------------------
    # test_math_mod_binop

    def test_math_mod_binop(self):
        self.binary_template_float32(math_mod_binop, np.fmod, start=1)
        self.binary_template_float64(math_mod_binop, np.fmod, start=1)

    #---------------------------------------------------------------------------
    # test_math_isnan

    def test_math_isnan(self):
        self.unary_bool_template_float32(math_isnan, np.isnan)
        self.unary_bool_template_float64(math_isnan, np.isnan)
        self.unary_bool_template_int32(math_isnan, np.isnan)
        self.unary_bool_template_int64(math_isnan, np.isnan)
        self.unary_bool_special_values_float32(math_isnan, np.isnan)
        self.unary_bool_special_values_float64(math_isnan, np.isnan)

    #---------------------------------------------------------------------------
    # test_math_isinf

    def test_math_isinf(self):
        self.unary_bool_template_float32(math_isinf, np.isinf)
        self.unary_bool_template_float64(math_isinf, np.isinf)
        self.unary_bool_template_int32(math_isinf, np.isinf)
        self.unary_bool_template_int64(math_isinf, np.isinf)
        self.unary_bool_special_values_float32(math_isinf, np.isinf)
        self.unary_bool_special_values_float64(math_isinf, np.isinf)

    #---------------------------------------------------------------------------
    # test_math_isfinite

    def test_math_isfinite(self):
        self.unary_bool_template_float32(math_isfinite, np.isfinite)
        self.unary_bool_template_float64(math_isfinite, np.isfinite)
        self.unary_bool_template_int32(math_isfinite, np.isfinite)
        self.unary_bool_template_int64(math_isfinite, np.isfinite)
        self.unary_bool_special_values_float32(math_isfinite, np.isfinite)
        self.unary_bool_special_values_float64(math_isfinite, np.isfinite)

    #---------------------------------------------------------------------------
    # test_math_degrees

    def test_math_degrees(self):
        self.unary_bool_template_float32(math_degrees, np.degrees)
        self.unary_bool_template_float64(math_degrees, np.degrees)

    #---------------------------------------------------------------------------
    # test_math_radians

    def test_math_radians(self):
        self.unary_bool_template_float32(math_radians, np.radians)
        self.unary_bool_template_float64(math_radians, np.radians)


if __name__ == '__main__':
    unittest.main()