def create_math_ufunc(math_name, nargs, name, doc):
assert 1 <= nargs <= 2
if nargs == 1:
return core.create_ufunc(
name, ('e->e', 'f->f', 'd->d'),
'out0 = %s(in0)' % math_name, doc=doc)
else:
return core.create_ufunc(
name, ('ee->e', 'ff->f', 'dd->d'),
'out0 = %s(in0, in1)' % math_name, doc=doc)
def create_math_ufunc(math_name, nargs, name, doc):
assert 1 <= nargs <= 2
if nargs == 1:
return core.create_ufunc(name, ('e->e', 'f->f', 'd->d'),
'out0 = %s(in0)' % math_name,
doc=doc)
else:
return core.create_ufunc(name, ('ee->e', 'ff->f', 'dd->d'),
'out0 = %s(in0, in1)' % math_name,
doc=doc)
r = in0 % in1;
in0 = in1;
in1 = r;
}
if (in0 < 0)
return -in0;
return in0;
}
'''
gcd = core.create_ufunc(
'cupy_gcd',
(('??->?', _negative_gcd_error), 'bb->b', 'BB->B', 'hh->h', 'HH->H',
'ii->i', 'II->I', 'll->l', 'LL->L', 'qq->q', 'QQ->Q'),
'out0 = gcd(in0, in1)',
preamble=_gcd_preamble,
doc='''Computes gcd of ``x1`` and ``x2`` elementwise.
.. seealso:: :data:`numpy.gcd`
''')
_lcm_preamble = '''
template <typename T> inline __device__ T lcm(T in0, T in1) {
T r = gcd(in0, in1);
if (r == 0)
return 0;
r = in0 / r * in1;
if (r < 0)
return -r;
return r;
.. seealso:: :data:`numpy.exp`
''')
expm1 = ufunc.create_math_ufunc(
'expm1', 1, 'cupy_expm1', '''Computes ``exp(x) - 1`` elementwise.
.. seealso:: :data:`numpy.expm1`
''')
exp2 = core.create_ufunc('cupy_exp2', ('e->e', 'f->f', 'd->d', 'F->F', 'D->D'),
'out0 = pow(in0_type(2), in0)',
doc='''Elementwise exponentiation with base 2.
.. seealso:: :data:`numpy.exp2`
''')
log = ufunc.create_math_ufunc(
'log', 1, 'cupy_log', '''Elementwise natural logarithm function.
.. seealso:: :data:`numpy.log`
''')
log10 = ufunc.create_math_ufunc(
'log10', 1, 'cupy_log10', '''Elementwise common logarithm function.
.. seealso:: :data:`numpy.log10`
logical_or = core.create_comparison(
'logical_or', '||',
'''Computes the logical OR of two arrays.
.. seealso:: :data:`numpy.logical_or`
''')
logical_not = core.create_ufunc(
'cupy_logical_not',
('?->?', 'b->?', 'B->?', 'h->?', 'H->?', 'i->?', 'I->?', 'l->?', 'L->?',
'q->?', 'Q->?', 'e->?', 'f->?', 'd->?'),
'out0 = !in0',
doc='''Computes the logical NOT of an array.
.. seealso:: :data:`numpy.logical_not`
''')
logical_xor = core.create_ufunc(
'cupy_logical_xor',
('??->?', 'bb->?', 'BB->?', 'hh->?', 'HH->?', 'ii->?', 'II->?', 'll->?',
'LL->?', 'qq->?', 'QQ->?', 'ee->?', 'ff->?', 'dd->?'),
'out0 = !in0 != !in1',
doc='''Computes the logical XOR of two arrays.
.. seealso:: :data:`numpy.logical_xor`
.. seealso:: :func:`numpy.where`
"""
missing = (x is None, y is None).count(True)
if missing == 1:
raise ValueError("Must provide both 'x' and 'y' or neither.")
if missing == 2:
return nonzero(condition)
return _where_ufunc(condition.astype('?'), x, y)
_where_ufunc = core.create_ufunc(
'cupy_where',
('???->?', '?bb->b', '?BB->B', '?hh->h', '?HH->H', '?ii->i', '?II->I',
'?ll->l', '?LL->L', '?qq->q', '?QQ->Q', '?ee->e', '?ff->f',
# On CUDA 6.5 these combinations don't work correctly (on CUDA >=7.0, it
# works).
# See issue #551.
'?hd->d', '?Hd->d',
'?dd->d'),
'out0 = in0 ? in1 : in2')
# TODO(okuta): Implement searchsorted
# TODO(okuta): Implement extract
import ast
import numpy
from cupy._logic import ops
from cupy._math import arithmetic
from cupy._logic import comparison
from cupy._binary import elementwise
from cupy import core
from cupyx.jit import _types
_numpy_scalar_true_divide = core.create_ufunc(
'numpy_scalar_true_divide',
('??->d', '?i->d', 'i?->d', 'bb->f', 'bi->d', 'BB->f', 'Bi->d', 'hh->f',
'HH->f', 'ii->d', 'II->d', 'll->d', 'LL->d', 'qq->d', 'QQ->d', 'ee->e',
'ff->f', 'dd->d', 'FF->F', 'DD->D'),
'out0 = (out0_type)in0 / (out0_type)in1',
)
_numpy_scalar_invert = core.create_ufunc(
'numpy_scalar_invert',
('?->?', 'b->b', 'B->B', 'h->h', 'H->H', 'i->i', 'I->I', 'l->l', 'L->L',
'q->q', 'Q->Q'),
'out0 = ~in0',
)
_numpy_scalar_logical_not = core.create_ufunc(
'numpy_scalar_logical_not',
('?->?', 'b->?', 'B->?', 'h->?', 'H->?', 'i->?', 'I->?', 'l->?', 'L->?',
'q->?', 'Q->?', 'e->?', 'f->?', 'd->?',
''')
ceil = ufunc.create_math_ufunc(
'ceil', 1, 'cupy_ceil',
'''Rounds each element of an array to its ceiling integer.
.. seealso:: :data:`numpy.ceil`
''')
trunc = ufunc.create_math_ufunc(
'trunc', 1, 'cupy_trunc',
'''Rounds each element of an array towards zero.
.. seealso:: :data:`numpy.trunc`
''')
fix = core.create_ufunc(
'cupy_fix', ('e->e', 'f->f', 'd->d'),
'out0 = (in0 >= 0.0) ? floor(in0): ceil(in0)',
doc='''If given value x is positive, it return floor(x).
Else, it return ceil(x).
.. seealso:: :data:`numpy.fix`
''')
from cupy import core
erf = core.create_ufunc('cupyx_scipy_erf', ('f->f', 'd->d'),
'out0 = erf(in0)',
doc='''Error function.
.. seealso:: :meth:`scipy.special.erf`
''')
erfc = core.create_ufunc('cupyx_scipy_erfc', ('f->f', 'd->d'),
'out0 = erfc(in0)',
doc='''Complementary error function.
.. seealso:: :meth:`scipy.special.erfc`
''')
erfcx = core.create_ufunc('cupyx_scipy_erfcx', ('f->f', 'd->d'),
'out0 = erfcx(in0)',
doc='''Scaled complementary error function.
.. seealso:: :meth:`scipy.special.erfcx`
''')
"""
# TODO(okuta): check type
return a.clip(a_min, a_max, out=out)
# sqrt_fixed is deprecated.
# numpy.sqrt is fixed in numpy 1.11.2.
sqrt = sqrt_fixed = core.sqrt
square = core.create_ufunc(
'cupy_square',
('b->b', 'B->B', 'h->h', 'H->H', 'i->i', 'I->I', 'l->l', 'L->L', 'q->q',
'Q->Q', 'e->e', 'f->f', 'd->d'),
'out0 = in0 * in0',
doc='''Elementwise square function.
.. seealso:: :data:`numpy.square`
''')
absolute = core.absolute
# TODO(beam2d): Implement it
# fabs
_unsigned_sign = 'out0 = in0 > 0'
sign = core.create_ufunc(
from cupy import core
add = core.add
reciprocal = core.create_ufunc(
'cupy_reciprocal',
('b', 'B', 'h', 'H', 'i', 'I', 'l', 'L', 'q', 'Q',
('e', 'out0 = 1 / in0'),
('f', 'out0 = 1 / in0'),
('d', 'out0 = 1 / in0')),
'out0 = in0 == 0 ? 0 : (1 / in0)',
doc='''Computes ``1 / x`` elementwise.
.. seealso:: :data:`numpy.reciprocal`
''')
negative = core.negative
multiply = core.multiply
divide = core.divide
power = core.power
expm1 = ufunc.create_math_ufunc(
'expm1', 1, 'cupy_expm1',
'''Computes ``exp(x) - 1`` elementwise.
.. seealso:: :data:`numpy.expm1`
''')
exp2 = core.create_ufunc(
'cupy_exp2',
('e->e', 'f->f', ('d->d', 'out0 = pow(2., in0)')),
'out0 = powf(2.f, in0)',
doc='''Elementwise exponentiation with base 2.
.. seealso:: :data:`numpy.exp2`
''')
log = ufunc.create_math_ufunc(
'log', 1, 'cupy_log',
'''Elementwise natural logarithm function.
.. seealso:: :data:`numpy.log`
''')
.. seealso:: :func:`numpy.clip`
"""
# TODO(okuta): check type
return a.clip(a_min, a_max, out=out)
# sqrt_fixed is deprecated.
# numpy.sqrt is fixed in numpy 1.11.2.
sqrt = sqrt_fixed = core.sqrt
square = core.create_ufunc(
'cupy_square',
('b->b', 'B->B', 'h->h', 'H->H', 'i->i', 'I->I', 'l->l', 'L->L', 'q->q',
'Q->Q', 'e->e', 'f->f', 'd->d', 'F->F', 'D->D'),
'out0 = in0 * in0',
doc='''Elementwise square function.
.. seealso:: :data:`numpy.square`
''')
absolute = core.absolute
# TODO(beam2d): Implement it
# fabs
_unsigned_sign = 'out0 = in0 > 0'
_complex_sign = '''
if (in0.real() == 0) {
out0 = (in0.imag() > 0) - (in0.imag() < 0);
} else {
from cupy import core
erf = core.create_ufunc('cupyx_scipy_erf', ('f->f', 'd->d'),
'out0 = erf(in0)',
doc='''Error function.
.. seealso:: :meth:`scipy.special.erf`
''')
erfc = core.create_ufunc('cupyx_scipy_erfc', ('f->f', 'd->d'),
'out0 = erfc(in0)',
doc='''Complementary error function.
.. seealso:: :meth:`scipy.special.erfc`
''')
erfcx = core.create_ufunc('cupyx_scipy_erfcx', ('f->f', 'd->d'),
'out0 = erfcx(in0)',
doc='''Scaled complementary error function.
.. seealso:: :meth:`scipy.special.erfcx`
''')
erfinv = core.create_ufunc('cupyx_scipy_erfinv', ('f->f', 'd->d'),
'out0 = erfinv(in0);',
doc='''Inverse function of error function.
.. seealso:: :meth:`scipy.special.erfinv`
if retstep:
return ret, step
else:
return ret
# TODO(okuta): Implement logspace
# TODO(okuta): Implement meshgrid
# mgrid
# ogrid
_arange_ufunc = core.create_ufunc(
'cupy_arange',
('bb->b', 'BB->B', 'hh->h', 'HH->H', 'ii->i', 'II->I', 'll->l', 'LL->L',
'qq->q', 'QQ->Q', 'ee->e', 'ff->f', 'dd->d'),
'out0 = in0 + i * in1')
_float_linspace = 'out0 = in0 + i * in1 / in2'
_linspace_ufunc = core.create_ufunc(
'cupy_linspace',
('bbb->b', 'Bbb->B', 'hhh->h', 'Hhh->H', 'iii->i', 'Iii->I', 'lll->l',
'Lll->L', 'qqq->q', 'Qqq->Q', ('eel->e', _float_linspace),
('ffl->f', _float_linspace), ('ddl->d', _float_linspace)),
'out0 = (in0_type)(in0 + _floor_divide(in1_type(i * in1), in2))')
from cupy import core
ndtr = core.create_ufunc(
'cupyx_scipy_ndtr', ('f->f', 'd->d'),
'out0 = normcdf(in0)',
doc='''Cumulative distribution function of normal distribution.
.. seealso:: :meth:`scipy.special.ndtr`
''')
from cupy import core
_is_close = core.create_ufunc(
'cupy_is_close', ('eeee?->?', 'ffff?->?', 'dddd?->?'), '''
bool equal_nan = in4;
if (isfinite(in0) && isfinite(in1)) {
out0 = fabs(in0 - in1) <= in3 + in2 * fabs(in1);
} else if (equal_nan) {
out0 = (in0 == in1) || (isnan(in0) && isnan(in1));
} else {
out0 = (in0 == in1);
}
''')
def allclose(a, b, rtol=1.e-5, atol=1.e-8, equal_nan=False):
"""Returns True if two arrays are element-wise equal within a tolerance.
Two values in ``a`` and ``b`` are considiered equal when the following
equation is satisfied.
.. math::
|a - b| \\le \\mathrm{atol} + \\mathrm{rtol} |b|
Args:
a (cupy.ndarray): Input array to compare.
b (cupy.ndarray): Input array to compare.
rtol (float): The relative tolerance.
atol (float): The absolute tolerance.
equal_nan (bool): If ``True``, NaN's in ``a`` will be considered equal
from cupy import core
add = core.add
reciprocal = core.create_ufunc(
'cupy_reciprocal',
('b', 'B', 'h', 'H', 'i', 'I', 'l', 'L', 'q', 'Q',
('e', 'out0 = 1 / in0'),
('f', 'out0 = 1 / in0'),
('d', 'out0 = 1 / in0'),
('F', 'out0 = in0_type(1) / in0'),
('D', 'out0 = in0_type(1) / in0')),
'out0 = in0 == 0 ? 0 : (1 / in0)',
doc='''Computes ``1 / x`` elementwise.
.. seealso:: :data:`numpy.reciprocal`
''')
negative = core.negative
conj = core.conj
angle = core.angle
from cupy import core
from cupy.math import ufunc
i0 = ufunc.create_math_ufunc(
'cyl_bessel_i0', 1, 'cupy_i0',
'''Modified Bessel function of the first kind, order 0.
.. seealso:: :func:`numpy.i0`
''')
sinc = core.create_ufunc(
'cupy_sinc', ('e->e', 'f->f', 'd->d'),
'out0 = abs(in0) > 1e-9 ? sinpi(in0) / (M_PI * in0) : 1',
doc='''Elementwise sinc function.
.. seealso:: :func:`numpy.sinc`
''')
return a.ravel().nonzero()[0]
_where_ufunc = core.create_ufunc(
'cupy_where',
(
'???->?',
'?bb->b',
'?BB->B',
'?hh->h',
'?HH->H',
'?ii->i',
'?II->I',
'?ll->l',
'?LL->L',
'?qq->q',
'?QQ->Q',
'?ee->e',
'?ff->f',
# On CUDA 6.5 these combinations don't work correctly (on CUDA >=7.0, it
# works).
# See issue #551.
'?hd->d',
'?Hd->d',
'?dd->d',
'?FF->F',
'?DD->D'),
'out0 = in0 ? in1 : in2')
def where(condition, x=None, y=None):
.. seealso:: :func:`numpy.clip`
'''
# TODO(okuta): check type
return a.clip(a_min, a_max, out=out)
sqrt = core.create_ufunc(
'cupy_sqrt',
# I think this order is a bug of NumPy, though we select this "buggy"
# behavior for compatibility with NumPy.
('f->f', 'd->d', 'e->e'),
'out0 = sqrt(in0)',
doc='''Elementwise positive square-root function.
.. note::
This ufunc outputs float32 arrays for float16 arrays input by default as
well as NumPy 1.9. If you want to override this behavior, specify the
dtype argument explicitly, or use ``cupy.math.misc.sqrt_fixed`` instead.
.. seealso:: :data:`numpy.sqrt`
''')
sqrt_fixed = core.sqrt_fixed
square = core.create_ufunc(
'cupy_square', ('b->b', 'B->B', 'h->h', 'H->H', 'i->i', 'I->I', 'l->l',
'L->L', 'q->q', 'Q->Q', 'e->e', 'f->f', 'd->d'),
'out0 = in0 * in0',
doc='''Elementwise square function.
'ceil',
1,
'cupy_ceil',
'''Rounds each element of an array to its ceiling integer.
.. seealso:: :data:`numpy.ceil`
''',
support_complex=False)
trunc = ufunc.create_math_ufunc(
'trunc',
1,
'cupy_trunc',
'''Rounds each element of an array towards zero.
.. seealso:: :data:`numpy.trunc`
''',
support_complex=False)
fix = core.create_ufunc(
'cupy_fix', ('e->e', 'f->f', 'd->d'),
'out0 = (in0 >= 0.0) ? floor(in0): ceil(in0)',
doc='''If given value x is positive, it return floor(x).
Else, it return ceil(x).
.. seealso:: :func:`numpy.fix`
''')
from cupy import core
gamma = core.create_ufunc(
'cupyx_scipy_gamma', ('f->f', 'd->d'),
'''
if (isinf(in0) && in0 < 0) {
out0 = -1.0 / 0.0;
} else if (in0 < 0. && in0 == floor(in0)) {
out0 = 1.0 / 0.0;
} else {
out0 = tgamma(in0);
}
''',
doc="""Gamma function.
Args:
z (cupy.ndarray): The input of gamma function.
Returns:
cupy.ndarray: Computed value of gamma function.
.. seealso:: :data:`scipy.special.gamma`
""")
return CUDART_INF;
} else if (delta == 0 || r == 0) {
return 0;
} else {
double u = delta;
double v = r / delta;
return u * u * (sqrt(1 + v * v) - 1);
}
}
'''
entr = core.create_ufunc('cupyx_scipy_entr', ('f->f', 'd->d'),
'out0 = out0_type(entr(in0));',
preamble=_float_preamble,
doc='''Elementwise function for computing entropy.
.. seealso:: :meth:`scipy.special.entr`
''')
kl_div = core.create_ufunc(
'cupyx_scipy_kl_div', ('ff->f', 'dd->d'),
'out0 = out0_type(kl_div(in0, in1));',
preamble=_float_preamble,
doc='''Elementwise function for computing Kullback-Leibler divergence.
.. seealso:: :meth:`scipy.special.kl_div`
''')
rel_entr = core.create_ufunc(
arctan2 = ufunc.create_math_ufunc(
'atan2', 2, 'cupy_arctan2',
'''Elementwise inverse-tangent of the ratio of two arrays.
.. seealso:: :data:`numpy.arctan2`
''')
deg2rad = core.create_ufunc(
'cupy_deg2rad',
('e->e', 'f->f', 'd->d'),
'out0 = in0 * (out0_type)(M_PI / 180)',
doc='''Converts angles from degrees to radians elementwise.
.. seealso:: :data:`numpy.deg2rad`, :data:`numpy.radians`
''')
rad2deg = core.create_ufunc(
'cupy_rad2deg',
('e->e', 'f->f', 'd->d'),
'out0 = in0 * (out0_type)(180 / M_PI)',
doc='''Converts angles from radians to degrees elementwise.
.. seealso:: :data:`numpy.rad2deg`, :data:`numpy.degrees`
''')
.. seealso:: :func:`numpy.clip`
'''
# TODO(okuta): check type
return a(a_min, a_max, out=out)
sqrt = core.create_ufunc(
'cupy_sqrt',
# I think this order is a bug of NumPy, though we select this "buggy"
# behavior for compatibility with NumPy.
('f->f', 'd->d', 'e->e'),
'out0 = sqrt(in0)',
doc='''Elementwise positive square-root function.
.. note::
This ufunc outputs float32 arrays for float16 arrays input by default as
well as NumPy 1.9. If you want to override this behavior, specify the
dtype argument explicitly, or use ``cupy.math.misc.sqrt_fixed`` instead.
.. seealso:: :data:`numpy.sqrt`
''')
sqrt_fixed = core.sqrt_fixed
square = core.create_ufunc(
'cupy_square',
('b->b', 'B->B', 'h->h', 'H->H', 'i->i', 'I->I', 'l->l', 'L->L', 'q->q',
from cupy import core
erf = core.create_ufunc(
'cupyx_scipy_erf', ('f->f', 'd->d'),
'out0 = erf(in0)',
doc='''Error function.
.. seealso:: :meth:`scipy.special.erf`
''')
erfc = core.create_ufunc(
'cupyx_scipy_erfc', ('f->f', 'd->d'),
'out0 = erfc(in0)',
doc='''Complementary error function.
.. seealso:: :meth:`scipy.special.erfc`
''')
erfcx = core.create_ufunc(
'cupyx_scipy_erfcx', ('f->f', 'd->d'),
'out0 = erfcx(in0)',
doc='''Scaled complementary error function.
.. seealso:: :meth:`scipy.special.erfcx`
''')
from cupy import core
from cupy.math import ufunc
signbit = core.create_ufunc(
'cupy_signbit', ('e->?', 'f->?', 'd->?'),
'out0 = signbit(in0)',
doc='''Tests elementwise if the sign bit is set (i.e. less than zero).
.. seealso:: :data:`numpy.signbit`
''')
copysign = ufunc.create_math_ufunc(
'copysign', 2, 'cupy_copysign',
'''Returns the first argument with the sign bit of the second elementwise.
.. seealso:: :data:`numpy.copysign`
''')
ldexp = core.create_ufunc(
'cupy_ldexp', ('ei->e', 'fi->f', 'el->e', 'fl->f', 'di->d', 'dl->d'),
'out0 = ldexp(in0, in1)',
doc='''Computes ``x1 * 2 ** x2`` elementwise.
.. seealso:: :data:`numpy.ldexp`
''')
frexp = core.create_ufunc(
'cupy_frexp', ('e->ei', 'f->fi', 'd->di'),
def _create_float_test_ufunc(name, doc):
return core.create_ufunc('cupy_' + name, ('e->?', 'f->?', 'd->?'),
'out0 = %s(in0)' % name,
doc=doc)
arctan2 = ufunc.create_math_ufunc(
'atan2', 2, 'cupy_arctan2',
'''Elementwise inverse-tangent of the ratio of two arrays.
.. seealso:: :data:`numpy.arctan2`
''')
deg2rad = core.create_ufunc(
'cupy_deg2rad',
('e->e', 'f->f', 'd->d'),
'out0 = in0 * (out0_type)(M_PI / 180)',
doc='''Converts angles from degrees to radians elementwise.
.. seealso:: :data:`numpy.deg2rad`, :data:`numpy.radians`
''')
rad2deg = core.create_ufunc(
'cupy_rad2deg',
('e->e', 'f->f', 'd->d'),
'out0 = in0 * (out0_type)(180 / M_PI)',
doc='''Converts angles from radians to degrees elementwise.
.. seealso:: :data:`numpy.rad2deg`, :data:`numpy.degrees`
''')
.. seealso:: :data:`numpy.logical_and`
''')
logical_or = core.create_comparison(
'logical_or', '||', '''Computes the logical OR of two arrays.
.. seealso:: :data:`numpy.logical_or`
''')
logical_not = core.create_ufunc(
'cupy_logical_not',
('?->?', 'b->?', 'B->?', 'h->?', 'H->?', 'i->?', 'I->?', 'l->?', 'L->?',
'q->?', 'Q->?', 'e->?', 'f->?', 'd->?'),
'out0 = !in0',
doc='''Computes the logical NOT of an array.
.. seealso:: :data:`numpy.logical_not`
''')
logical_xor = core.create_ufunc(
'cupy_logical_xor',
('??->?', 'bb->?', 'BB->?', 'hh->?', 'HH->?', 'ii->?', 'II->?', 'll->?',
'LL->?', 'qq->?', 'QQ->?', 'ee->?', 'ff->?', 'dd->?'),
'out0 = !in0 != !in1',
doc='''Computes the logical XOR of two arrays.
.. seealso:: :data:`numpy.logical_xor`
''')
from cupy import core
from cupy.math import ufunc
signbit = core.create_ufunc(
'cupy_signbit',
('e->?', 'f->?', 'd->?'),
'out0 = signbit(in0)',
doc='''Tests elementwise if the sign bit is set (i.e. less than zero).
.. seealso:: :data:`numpy.signbit`
''')
copysign = ufunc.create_math_ufunc(
'copysign', 2, 'cupy_copysign',
'''Returns the first arugment with the sign bit of the second elementwise.
.. seealso:: :data:`numpy.copysign`
''')
ldexp = core.create_ufunc(
'cupy_ldexp',
('ei->e', 'fi->f', 'el->e', 'fl->f', 'di->d', 'dl->d'),
'out0 = ldexp(in0, in1)',
doc='''Computes ``x1 * 2 ** x2`` elementwise.
.. seealso:: :data:`numpy.ldexp`
t = a * b / A[i];
s = s + t;
t = fabs(t / s);
if (t < MACHEP){
return s;
}
k += 1.0;
a *= x + k;
b /= w;
k += 1.0;
}
return s;
}
'''
zeta = core.create_ufunc('cupyx_scipy_zeta', ('ff->f', 'dd->d'),
'out0 = zeta(in0, in1)',
preamble=zeta_definition,
doc="""Hurwitz zeta function.
Args:
x (cupy.ndarray): Input data, must be real.
q (cupy.ndarray): Input data, must be real.
Returns:
cupy.ndarray: Values of zeta(x, q).
.. seealso:: :data:`scipy.special.zeta`
""")
return _where_ufunc(condition.astype("?"), x, y)
_where_ufunc = core.create_ufunc(
"cupy_where",
(
"???->?",
"?bb->b",
"?BB->B",
"?hh->h",
"?HH->H",
"?ii->i",
"?II->I",
"?ll->l",
"?LL->L",
"?qq->q",
"?QQ->Q",
"?ee->e",
"?ff->f",
# On CUDA 6.5 these combinations don't work correctly (on CUDA >=7.0, it
# works).
# See issue #551.
"?hd->d",
"?Hd->d",
"?dd->d",
),
"out0 = in0 ? in1 : in2",
)
# TODO(okuta): Implement searchsorted
from cupy import core
j0 = core.create_ufunc(
'cupyx_scipy_j0', ('f->f', 'd->d'),
'out0 = j0(in0)',
doc='''Bessel function of the first kind of order 0.
.. seealso:: :meth:`scipy.special.j0`
''')
j1 = core.create_ufunc(
'cupyx_scipy_j1', ('f->f', 'd->d'),
'out0 = j1(in0)',
doc='''Bessel function of the first kind of order 1.
.. seealso:: :meth:`scipy.special.j1`
''')
y0 = core.create_ufunc(
'cupyx_scipy_y0', ('f->f', 'd->d'),
'out0 = y0(in0)',
doc='''Bessel function of the second kind of order 0.
.. seealso:: :meth:`scipy.special.y0`
''')
def _create_float_test_ufunc(name, doc):
return core.create_ufunc(
'cupy_' + name, ('e->?', 'f->?', 'd->?'), 'out0 = %s(in0)' % name,
doc=doc)
while (x > 2.0) {
x -= 1.0;
y += 1.0 / x;
}
}
if ((1.0 <= x) && (x <= 2.0)) {
y += digamma_imp_1_2(x);
return y;
}
/* x is large, use the asymptotic series */
y += psi_asy(x);
return y;
}
'''
digamma = core.create_ufunc('cupyx_scipy_digamma', ('f->f', 'd->d'),
'out0 = psi(in0)',
preamble=polevl_definition + psi_definition,
doc="""The digamma function.
Args:
x (cupy.ndarray): The input of digamma function.
Returns:
cupy.ndarray: Computed value of digamma function.
.. seealso:: :data:`scipy.special.digamma`
""")
if step != 1:
step = (key[k].stop - start) / float(step - 1)
nn[k] = (nn[k] * step + start)
if self.sparse:
slobj = [cupy.newaxis] * len(size)
for k in range(len(size)):
slobj[k] = slice(None, None)
nn[k] = nn[k][tuple(slobj)]
slobj[k] = cupy.newaxis
return nn
def __len__(self):
return 0
mgrid = nd_grid(sparse=False)
ogrid = nd_grid(sparse=True)
_arange_ufunc = core.create_ufunc(
'cupy_arange',
('bb->b', 'BB->B', 'hh->h', 'HH->H', 'ii->i', 'II->I', 'll->l', 'LL->L',
'qq->q', 'QQ->Q', 'ee->e', 'ff->f', 'dd->d',
('FF->F', 'out0 = in0 + float(i) * in1'),
('DD->D', 'out0 = in0 + double(i) * in1')), 'out0 = in0 + i * in1')
_linspace_ufunc = core.create_ufunc('cupy_linspace', ('dd->d', ),
'out0 = in0 + i * in1')
_linspace_ufunc_underflow = core.create_ufunc('cupy_linspace', ('ddd->d', ),
'out0 = in0 + i * in1 / in2')
from cupy import core
from cupy._math import ufunc
i0 = ufunc.create_math_ufunc(
'cyl_bessel_i0', 1, 'cupy_i0',
'''Modified Bessel function of the first kind, order 0.
.. seealso:: :func:`numpy.i0`
''')
sinc = core.create_ufunc(
'cupy_sinc', ('e->e', 'f->f', 'd->d',
('F->F', 'in0_type pi_in0 = (in0_type) M_PI * in0;'
'out0 = abs(in0) > 1e-9 ? sin(pi_in0) / (pi_in0) : 1'),
('D->D', 'in0_type pi_in0 = (in0_type) M_PI * in0;'
'out0 = abs(in0) > 1e-9 ? sin(pi_in0) / (pi_in0) : 1')),
'out0 = abs(in0) > 1e-9 ? sinpi(in0) / (M_PI * in0) : 1',
doc='''Elementwise sinc function.
.. seealso:: :func:`numpy.sinc`
''')
"""
if fusion._is_fusing():
return fusion._call_ufunc(_math.clip, a, a_min, a_max, out=out)
# TODO(okuta): check type
return a.clip(a_min, a_max, out=out)
# sqrt_fixed is deprecated.
# numpy.sqrt is fixed in numpy 1.11.2.
sqrt = sqrt_fixed = core.sqrt
cbrt = core.create_ufunc('cupy_cbrt', ('e->e', 'f->f', 'd->d'),
'out0 = cbrt(in0)',
doc='''Elementwise cube root function.
.. seealso:: :data:`numpy.cbrt`
''')
square = core.create_ufunc(
'cupy_square',
('b->b', 'B->B', 'h->h', 'H->H', 'i->i', 'I->I', 'l->l', 'L->L', 'q->q',
'Q->Q', 'e->e', 'f->f', 'd->d', 'F->F', 'D->D'),
'out0 = in0 * in0',
doc='''Elementwise square function.
.. seealso:: :data:`numpy.square`
''')
return 0;
} else {
u = delta;
v = r / delta;
return u * u * (sqrt(1 + v * v) - 1);
}
}
"""
entr = core.create_ufunc(
"cupyx_scipy_entr",
("f->f", "d->d"),
"out0 = out0_type(entr(in0));",
preamble=_float_preamble,
doc="""Elementwise function for computing entropy.
.. seealso:: :meth:`scipy.special.entr`
""",
)
kl_div = core.create_ufunc(
"cupyx_scipy_kl_div",
("ff->f", "dd->d"),
"out0 = out0_type(kl_div(in0, in1));",
preamble=_float_preamble,
doc="""Elementwise function for computing Kullback-Leibler divergence.
.. seealso:: :meth:`scipy.special.kl_div`
else:
return ret
# TODO(okuta): Implement logspace
# TODO(okuta): Implement meshgrid
# mgrid
# ogrid
_arange_ufunc = core.create_ufunc(
'cupy_arange',
('bb->b', 'BB->B', 'hh->h', 'HH->H', 'ii->i', 'II->I', 'll->l', 'LL->L',
'qq->q', 'QQ->Q', 'ee->e', 'ff->f', 'dd->d'),
'out0 = in0 + i * in1')
_linspace_ufunc = core.create_ufunc(
'cupy_linspace',
('dd->d',),
'out0 = in0 + i * in1')
_linspace_ufunc_underflow = core.create_ufunc(
'cupy_linspace',
('ddd->d',),
'out0 = in0 + i * in1 / in2')
from cupy import core
gammaln = core.create_ufunc(
'cupyx_scipy_gammaln', ('f->f', 'd->d'),
'''
if (isinf(in0) && in0 < 0) {
out0 = -1.0 / 0.0;
} else {
out0 = lgamma(in0);
}
''',
doc="""Logarithm of the absolute value of the Gamma function.
Args:
x (cupy.ndarray): Values on the real line at which to compute
``gammaln``.
Returns:
cupy.ndarray: Values of ``gammaln`` at x.
.. seealso:: :data:`scipy.special.gammaln`
""")
