ai-content-maker/.venv/Lib/site-packages/numba/cuda/tests/cudapy/test_math.py

787 lines
27 KiB
Python

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()