# -*- coding: utf-8 -*-
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# Copyright (c) 2016-2024, Intel Corporation
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"""
Interface of the Trigonometric part of the DPNP
Notes
-----
This module is a face or public interface file for the library
it contains:
- Interface functions
- documentation for the functions
- The functions parameters check
"""
# pylint: disable=protected-access
# pylint: disable=c-extension-no-member
# pylint: disable=duplicate-code
# pylint: disable=no-name-in-module
import dpctl.tensor as dpt
import dpctl.tensor._tensor_elementwise_impl as ti
import dpctl.tensor._type_utils as dtu
import numpy
import dpnp
import dpnp.backend.extensions.vm._vm_impl as vmi
from .dpnp_algo import (
dpnp_degrees,
dpnp_radians,
dpnp_unwrap,
)
from .dpnp_algo.dpnp_elementwise_common import DPNPBinaryFunc, DPNPUnaryFunc
from .dpnp_utils import call_origin
from .dpnp_utils.dpnp_utils_reduction import dpnp_wrap_reduction_call
__all__ = [
"arccos",
"arccosh",
"arcsin",
"arcsinh",
"arctan",
"arctan2",
"arctanh",
"cbrt",
"cos",
"cosh",
"cumlogsumexp",
"deg2rad",
"degrees",
"exp",
"exp2",
"expm1",
"hypot",
"log",
"log10",
"log1p",
"log2",
"logaddexp",
"logsumexp",
"rad2deg",
"radians",
"reciprocal",
"reduce_hypot",
"rsqrt",
"sin",
"sinh",
"sqrt",
"square",
"tan",
"tanh",
"unwrap",
]
def _get_accumulation_res_dt(a, dtype, _out):
"""Get a dtype used by dpctl for result array in accumulation function."""
if dtype is None:
return dtu._default_accumulation_dtype_fp_types(a.dtype, a.sycl_queue)
dtype = dpnp.dtype(dtype)
return dtu._to_device_supported_dtype(dtype, a.sycl_device)
_ACOS_DOCSTRING = """
Computes inverse cosine for each element `x_i` for input array `x`.
For full documentation refer to :obj:`numpy.arccos`.
Parameters
----------
x : {dpnp.ndarray, usm_ndarray}
Input array, expected to have numeric data type.
out : {None, dpnp.ndarray}, optional
Output array to populate.
Array must have the correct shape and the expected data type.
order : {"C", "F", "A", "K"}, optional
Memory layout of the newly output array, if parameter `out` is ``None``.
Default: "K".
Returns
-------
out : dpnp.ndarray
An array containing the element-wise inverse cosine, in radians
and in the closed interval `[-pi/2, pi/2]`. The data type
of the returned array is determined by the Type Promotion Rules.
Limitations
-----------
Parameters `where` and `subok` are supported with their default values.
Keyword argument `kwargs` is currently unsupported.
Otherwise ``NotImplementedError`` exception will be raised.
See Also
--------
:obj:`dpnp.cos` : Trigonometric cosine, element-wise.
:obj:`dpnp.arctan` : Trigonometric inverse tangent, element-wise.
:obj:`dpnp.arcsin` : Trigonometric inverse sine, element-wise.
:obj:`dpnp.arccosh` : Hyperbolic inverse cosine, element-wise.
Examples
--------
>>> import dpnp as np
>>> x = np.array([1, -1])
>>> np.arccos(x)
array([0.0, 3.14159265])
"""
arccos = DPNPUnaryFunc(
"arccos",
ti._acos_result_type,
ti._acos,
_ACOS_DOCSTRING,
mkl_fn_to_call=vmi._mkl_acos_to_call,
mkl_impl_fn=vmi._acos,
)
_ACOSH_DOCSTRING = """
Computes inverse hyperbolic cosine for each element `x_i` for input array `x`.
For full documentation refer to :obj:`numpy.arccosh`.
Parameters
----------
x : {dpnp.ndarray, usm_ndarray}
Input array, expected to have numeric data type.
out : {None, dpnp.ndarray}, optional
Output array to populate.
Array must have the correct shape and the expected data type.
order : {"C", "F", "A", "K"}, optional
Memory layout of the newly output array, if parameter `out` is ``None``.
Default: "K".
Returns
-------
out : dpnp.ndarray
An array containing the element-wise inverse hyperbolic cosine, in
radians and in the half-closed interval `[0, inf)`. The data type
of the returned array is determined by the Type Promotion Rules.
Limitations
-----------
Parameters `where` and `subok` are supported with their default values.
Keyword argument `kwargs` is currently unsupported.
Otherwise ``NotImplementedError`` exception will be raised.
See Also
--------
:obj:`dpnp.cosh` : Hyperbolic cosine, element-wise.
:obj:`dpnp.arctanh` : Hyperbolic inverse tangent, element-wise.
:obj:`dpnp.arcsinh` : Hyperbolic inverse sine, element-wise.
:obj:`dpnp.arccos` : Trigonometric inverse cosine, element-wise.
Examples
--------
>>> import dpnp as np
>>> x = np.array([1.0, np.e, 10.0])
>>> np.arccosh(x)
array([0.0, 1.65745445, 2.99322285])
"""
arccosh = DPNPUnaryFunc(
"arccosh",
ti._acosh_result_type,
ti._acosh,
_ACOSH_DOCSTRING,
mkl_fn_to_call=vmi._mkl_acosh_to_call,
mkl_impl_fn=vmi._acosh,
)
_ASIN_DOCSTRING = """
Computes inverse sine for each element `x_i` for input array `x`.
For full documentation refer to :obj:`numpy.arcsin`.
Parameters
----------
x : {dpnp.ndarray, usm_ndarray}
Input array, expected to have numeric data type.
out : {None, dpnp.ndarray}, optional
Output array to populate.
Array must have the correct shape and the expected data type.
order : {"C", "F", "A", "K"}, optional
Memory layout of the newly output array, if parameter `out` is ``None``.
Default: "K".
Returns
-------
out : dpnp.ndarray
An array containing the element-wise inverse sine, in radians
and in the closed interval `[-pi/2, pi/2]`. The data type
of the returned array is determined by the Type Promotion Rules.
Limitations
-----------
Parameters `where` and `subok` are supported with their default values.
Keyword argument `kwargs` is currently unsupported.
Otherwise ``NotImplementedError`` exception will be raised.
See Also
--------
:obj:`dpnp.sin` : Trigonometric sine, element-wise.
:obj:`dpnp.arctan` : Trigonometric inverse tangent, element-wise.
:obj:`dpnp.arccos` : Trigonometric inverse cosine, element-wise.
:obj:`dpnp.arcsinh` : Hyperbolic inverse sine, element-wise.
Examples
--------
>>> import dpnp as np
>>> x = np.array([0, 1, -1])
>>> np.arcsin(x)
array([0.0, 1.5707963267948966, -1.5707963267948966])
"""
arcsin = DPNPUnaryFunc(
"arcsin",
ti._asin_result_type,
ti._asin,
_ASIN_DOCSTRING,
mkl_fn_to_call=vmi._mkl_asin_to_call,
mkl_impl_fn=vmi._asin,
)
_ASINH_DOCSTRING = """
Computes inverse hyperbolic sine for each element `x_i` for input array `x`.
For full documentation refer to :obj:`numpy.arcsinh`.
Parameters
----------
x : {dpnp.ndarray, usm_ndarray}
Input array, expected to have numeric data type.
out : {None, dpnp.ndarray}, optional
Output array to populate.
Array must have the correct shape and the expected data type..
order : {"C", "F", "A", "K"}, optional
Memory layout of the newly output array, if parameter `out` is ``None``.
Default: "K".
Returns
-------
out : dpnp.ndarray
An array containing the element-wise inverse hyperbolic sine.
The data type of the returned array is determined by
the Type Promotion Rules.
Limitations
-----------
Parameters `where` and `subok` are supported with their default values.
Keyword argument `kwargs` is currently unsupported.
Otherwise ``NotImplementedError`` exception will be raised.
See Also
--------
:obj:`dpnp.sinh` : Hyperbolic sine, element-wise.
:obj:`dpnp.arctanh` : Hyperbolic inverse tangent, element-wise.
:obj:`dpnp.arccosh` : Hyperbolic inverse cosine, element-wise.
:obj:`dpnp.arcsin` : Trigonometric inverse sine, element-wise.
Examples
--------
>>> import dpnp as np
>>> x = np.array([np.e, 10.0])
>>> np.arcsinh(x)
array([1.72538256, 2.99822295])
"""
arcsinh = DPNPUnaryFunc(
"arcsinh",
ti._asinh_result_type,
ti._asinh,
_ASINH_DOCSTRING,
mkl_fn_to_call=vmi._mkl_asinh_to_call,
mkl_impl_fn=vmi._asinh,
)
_ATAN_DOCSTRING = """
Computes inverse tangent for each element `x_i` for input array `x`.
For full documentation refer to :obj:`numpy.arctan`.
Parameters
----------
x : {dpnp.ndarray, usm_ndarray}
Input array, expected to have numeric data type.
out : {None, dpnp.ndarray}, optional
Output array to populate.
Array must have the correct shape and the expected data type..
order : {"C", "F", "A", "K"}, optional
Memory layout of the newly output array, if parameter `out` is ``None``.
Default: "K".
Returns
-------
out : dpnp.ndarray
An array containing the element-wise inverse tangent, in radians
and in the closed interval `[-pi/2, pi/2]`. The data type
of the returned array is determined by the Type Promotion Rules.
Limitations
-----------
Parameters `where` and `subok` are supported with their default values.
Keyword argument `kwargs` is currently unsupported.
Otherwise ``NotImplementedError`` exception will be raised.
See Also
--------
:obj:`dpnp.arctan2` : Element-wise arc tangent of `x1/x2` choosing the quadrant correctly.
:obj:`dpnp.angle` : Argument of complex values.
:obj:`dpnp.tan` : Trigonometric tangent, element-wise.
:obj:`dpnp.arcsin` : Trigonometric inverse sine, element-wise.
:obj:`dpnp.arccos` : Trigonometric inverse cosine, element-wise.
:obj:`dpnp.arctanh` : Inverse hyperbolic tangent, element-wise.
Examples
--------
>>> import dpnp as np
>>> x = np.array([0, 1])
>>> np.arctan(x)
array([0.0, 0.78539816])
"""
arctan = DPNPUnaryFunc(
"arctan",
ti._atan_result_type,
ti._atan,
_ATAN_DOCSTRING,
mkl_fn_to_call=vmi._mkl_atan_to_call,
mkl_impl_fn=vmi._atan,
)
_ATAN2_DOCSTRING = """
Calculates the inverse tangent of the quotient `x1_i/x2_i` for each element
`x1_i` of the input array `x1` with the respective element `x2_i` of the
input array `x2`. Each element-wise result is expressed in radians.
For full documentation refer to :obj:`numpy.arctan2`.
Parameters
----------
x1 : {dpnp.ndarray, usm_ndarray}
First input array, expected to have a real-valued floating-point
data type.
x2 : {dpnp.ndarray, usm_ndarray}
Second input array, also expected to have a real-valued
floating-point data type.
out : {None, dpnp.ndarray}, optional
Output array to populate.
Array must have the correct shape and the expected data type.
order : {"C", "F", "A", "K"}, optional
Memory layout of the newly output array, if parameter `out` is ``None``.
Default: "K".
Returns
-------
out : dpnp.ndarray
An array containing the inverse tangent of the quotient `x1`/`x2`.
The returned array must have a real-valued floating-point data type
determined by Type Promotion Rules.
Limitations
-----------
Parameters `where` and `subok` are supported with their default values.
Keyword arguments `kwargs` are currently unsupported.
Otherwise ``NotImplementedError`` exception will be raised.
See Also
--------
:obj:`dpnp.arctan` : Trigonometric inverse tangent, element-wise.
:obj:`dpnp.tan` : Compute tangent element-wise.
:obj:`dpnp.angle` : Return the angle of the complex argument.
:obj:`dpnp.arcsin` : Trigonometric inverse sine, element-wise.
:obj:`dpnp.arccos` : Trigonometric inverse cosine, element-wise.
:obj:`dpnp.arctanh` : Inverse hyperbolic tangent, element-wise.
Examples
--------
>>> import dpnp as np
>>> x1 = np.array([1., -1.])
>>> x2 = np.array([0., 0.])
>>> np.arctan2(x1, x2)
array([1.57079633, -1.57079633])
>>> x1 = np.array([0., 0., np.inf])
>>> x2 = np.array([+0., -0., np.inf])
>>> np.arctan2(x1, x2)
array([0.0 , 3.14159265, 0.78539816])
>>> x1 = np.array([-1, +1, +1, -1])
>>> x2 = np.array([-1, -1, +1, +1])
>>> np.arctan2(x1, x2) * 180 / np.pi
array([-135., -45., 45., 135.])
"""
arctan2 = DPNPBinaryFunc(
"arctan2",
ti._atan2_result_type,
ti._atan2,
_ATAN2_DOCSTRING,
mkl_fn_to_call=vmi._mkl_atan2_to_call,
mkl_impl_fn=vmi._atan2,
)
_ATANH_DOCSTRING = """
Computes hyperbolic inverse tangent for each element `x_i` for input array `x`.
For full documentation refer to :obj:`numpy.arctanh`.
Parameters
----------
x : {dpnp.ndarray, usm_ndarray}
Input array, expected to have numeric data type.
out : {None, dpnp.ndarray}, optional
Output array to populate.
Array must have the correct shape and the expected data type.
order : {"C", "F", "A", "K"}, optional
Memory layout of the newly output array, if parameter `out` is ``None``.
Default: "K".
Returns
-------
out : dpnp.ndarray
An array containing the element-wise hyperbolic inverse tangent.
The data type of the returned array is determined by
the Type Promotion Rules.
Limitations
-----------
Parameters `where` and `subok` are supported with their default values.
Keyword argument `kwargs` is currently unsupported.
Otherwise ``NotImplementedError`` exception will be raised.
See Also
--------
:obj:`dpnp.tanh` : Hyperbolic tangent, element-wise.
:obj:`dpnp.arcsinh` : Hyperbolic inverse sine, element-wise.
:obj:`dpnp.arccosh` : Hyperbolic inverse cosine, element-wise.
:obj:`dpnp.arctan` : Trigonometric inverse tangent, element-wise.
Examples
--------
>>> import dpnp as np
>>> x = np.array([0, -0.5])
>>> np.arctanh(x)
array([0.0, -0.54930614])
"""
arctanh = DPNPUnaryFunc(
"arctanh",
ti._atanh_result_type,
ti._atanh,
_ATANH_DOCSTRING,
mkl_fn_to_call=vmi._mkl_atanh_to_call,
mkl_impl_fn=vmi._atanh,
)
_CBRT_DOCSTRING = """
Computes positive cube-root for each element `x_i` for input array `x`.
For full documentation refer to :obj:`numpy.cbrt`.
Parameters
----------
x : {dpnp.ndarray, usm_ndarray}
Input array, expected to have a real-valued data type.
out : {None, dpnp.ndarray}, optional
Output array to populate.
Array must have the correct shape and the expected data type.
order : {"C", "F", "A", "K"}, optional
Memory layout of the newly output array, if parameter `out` is ``None``.
Default: "K".
Returns
-------
out : dpnp.ndarray
An array containing the element-wise positive cube-root.
The data type of the returned array is determined by
the Type Promotion Rules.
Limitations
-----------
Parameters `where` and `subok` are supported with their default values.
Keyword argument `kwargs` is currently unsupported.
Otherwise ``NotImplementedError`` exception will be raised.
See Also
--------
:obj:`dpnp.sqrt` : Return the positive square-root of an array, element-wise.
Examples
--------
>>> import dpnp as np
>>> x = np.array([1, 8, 27])
>>> np.cbrt(x)
array([1., 2., 3.])
"""
cbrt = DPNPUnaryFunc(
"cbrt",
ti._cbrt_result_type,
ti._cbrt,
_CBRT_DOCSTRING,
mkl_fn_to_call=vmi._mkl_cbrt_to_call,
mkl_impl_fn=vmi._cbrt,
)
_COS_DOCSTRING = """
Computes cosine for each element `x_i` for input array `x`.
For full documentation refer to :obj:`numpy.cos`.
Parameters
----------
x : {dpnp.ndarray, usm_ndarray}
Input array, expected to have numeric data type.
out : {None, dpnp.ndarray}, optional
Output array to populate.
Array must have the correct shape and the expected data type.
order : {"C", "F", "A", "K"}, optional
Memory layout of the newly output array, if parameter `out` is ``None``.
Default: "K".
Returns
-------
out : dpnp.ndarray
An array containing the element-wise cosine. The data type
of the returned array is determined by the Type Promotion Rules.
Limitations
-----------
Parameters `where` and `subok` are supported with their default values.
Keyword argument `kwargs` is currently unsupported.
Otherwise ``NotImplementedError`` exception will be raised.
See Also
--------
:obj:`dpnp.arccos` : Trigonometric inverse cosine, element-wise.
:obj:`dpnp.sin` : Trigonometric sine, element-wise.
:obj:`dpnp.tan` : Trigonometric tangent, element-wise.
:obj:`dpnp.cosh` : Hyperbolic cosine, element-wise.
Examples
--------
>>> import dpnp as np
>>> x = np.array([0, np.pi/2, np.pi])
>>> np.cos(x)
array([ 1.000000e+00, -4.371139e-08, -1.000000e+00])
"""
cos = DPNPUnaryFunc(
"cos",
ti._cos_result_type,
ti._cos,
_COS_DOCSTRING,
mkl_fn_to_call=vmi._mkl_cos_to_call,
mkl_impl_fn=vmi._cos,
)
_COSH_DOCSTRING = """
Computes hyperbolic cosine for each element `x_i` for input array `x`.
For full documentation refer to :obj:`numpy.cosh`.
Parameters
----------
x : {dpnp.ndarray, usm_ndarray}
Input array, expected to have numeric data type.
out : {None, dpnp.ndarray}, optional
Output array to populate.
Array must have the correct shape and the expected data type.
order : {"C", "F", "A", "K"}, optional
Memory layout of the newly output array, if parameter `out` is ``None``.
Default: "K".
Returns
-------
out : dpnp.ndarray
An array containing the element-wise hyperbolic cosine. The data type
of the returned array is determined by the Type Promotion Rules.
Limitations
-----------
Parameters `where` and `subok` are supported with their default values.
Keyword argument `kwargs` is currently unsupported.
Otherwise ``NotImplementedError`` exception will be raised.
See Also
--------
:obj:`dpnp.arccosh` : Hyperbolic inverse cosine, element-wise.
:obj:`dpnp.sinh` : Hyperbolic sine, element-wise.
:obj:`dpnp.tanh` : Hyperbolic tangent, element-wise.
:obj:`dpnp.cos` : Trigonometric cosine, element-wise.
Examples
--------
>>> import dpnp as np
>>> x = np.array([0, np.pi/2, np.pi])
>>> np.cosh(x)
array([1.0, 2.5091786, 11.591953])
"""
cosh = DPNPUnaryFunc(
"cosh",
ti._cosh_result_type,
ti._cosh,
_COSH_DOCSTRING,
mkl_fn_to_call=vmi._mkl_cosh_to_call,
mkl_impl_fn=vmi._cosh,
)
[docs]
def cumlogsumexp(
x, /, *, axis=None, dtype=None, include_initial=False, out=None
):
"""
Calculates the cumulative logarithm of the sum of elements in the input
array `x`.
Parameters
----------
x : {dpnp.ndarray, usm_ndarray}
Input array, expected to have a real-valued data type.
axis : {None, int}, optional
Axis or axes along which values must be computed. If a tuple of unique
integers, values are computed over multiple axes. If ``None``, the
result is computed over the entire array.
Default: ``None``.
dtype : {None, dtype}, optional
Data type of the returned array. If ``None``, the default data type is
inferred from the "kind" of the input array data type.
- If `x` has a real-valued floating-point data type, the returned array
will have the same data type as `x`.
- If `x` has a boolean or integral data type, the returned array will
have the default floating point data type for the device where input
array `x` is allocated.
- If `x` has a complex-valued floating-point data type, an error is
raised.
If the data type (either specified or resolved) differs from the data
type of `x`, the input array elements are cast to the specified data
type before computing the result.
Default: ``None``.
include_initial : {None, bool}, optional
A boolean indicating whether to include the initial value (i.e., the
additive identity, zero) as the first value along the provided axis in
the output.
Default: ``False``.
out : {None, dpnp.ndarray, usm_ndarray}, optional
The array into which the result is written. The data type of `out` must
match the expected shape and the expected data type of the result or
(if provided) `dtype`. If ``None`` then a new array is returned.
Default: ``None``.
Returns
-------
out : dpnp.ndarray
An array containing the results. If the result was computed over the
entire array, a zero-dimensional array is returned. The returned array
has the data type as described in the `dtype` parameter description
above.
Note
----
This function is equivalent of `numpy.logaddexp.accumulate`.
See Also
--------
:obj:`dpnp.logsumexp` : Logarithm of the sum of elements of the inputs,
element-wise.
Examples
--------
>>> import dpnp as np
>>> a = np.ones(10)
>>> np.cumlogsumexp(a)
array([1. , 1.69314718, 2.09861229, 2.38629436, 2.60943791,
2.79175947, 2.94591015, 3.07944154, 3.19722458, 3.30258509])
"""
dpnp.check_supported_arrays_type(x)
if x.ndim > 1 and axis is None:
usm_x = dpnp.ravel(x).get_array()
else:
usm_x = dpnp.get_usm_ndarray(x)
return dpnp_wrap_reduction_call(
x,
out,
dpt.cumulative_logsumexp,
_get_accumulation_res_dt,
usm_x,
axis=axis,
dtype=dtype,
include_initial=include_initial,
)
[docs]
def deg2rad(x1):
"""
Convert angles from degrees to radians.
For full documentation refer to :obj:`numpy.deg2rad`.
See Also
--------
:obj:`dpnp.rad2deg` : Convert angles from radians to degrees.
:obj:`dpnp.unwrap` : Remove large jumps in angle by wrapping.
Notes
-----
This function works exactly the same as :obj:`dpnp.radians`.
"""
return radians(x1)
[docs]
def degrees(x1, **kwargs):
"""
Convert angles from radians to degrees.
For full documentation refer to :obj:`numpy.degrees`.
Limitations
-----------
Input array is supported as :obj:`dpnp.ndarray`.
Input array data types are limited by supported DPNP :ref:`Data types`.
.. seealso:: :obj:`dpnp.rad2deg` convert angles from radians to degrees.
Examples
--------
>>> import dpnp as np
>>> rad = np.arange(6.) * np.pi/6
>>> out = np.degrees(rad)
>>> [i for i in out]
[0.0, 30.0, 60.0, 90.0, 120.0, 150.0]
"""
x1_desc = dpnp.get_dpnp_descriptor(
x1, copy_when_strides=False, copy_when_nondefault_queue=False
)
if kwargs:
pass
elif x1_desc:
return dpnp_degrees(x1_desc).get_pyobj()
return call_origin(numpy.degrees, x1, **kwargs)
_EXP_DOCSTRING = """
Computes the exponent for each element `x_i` of input array `x`.
For full documentation refer to :obj:`numpy.exp`.
Parameters
----------
x : {dpnp.ndarray, usm_ndarray}
Input array, expected to have numeric data type.
out : {None, dpnp.ndarray}, optional
Output array to populate.
Array must have the correct shape and the expected data type.
order : {"C", "F", "A", "K"}, optional
Memory layout of the newly output array, if parameter `out` is ``None``.
Default: "K".
Returns
-------
out : dpnp.ndarray
An array containing the element-wise exponent of `x`.
The data type of the returned array is determined by
the Type Promotion Rules.
Limitations
-----------
Parameters `where` and `subok` are supported with their default values.
Keyword argument `kwargs` is currently unsupported.
Otherwise ``NotImplementedError`` exception will be raised.
See Also
--------
:obj:`dpnp.expm1` : Calculate ``exp(x) - 1`` for all elements in the array.
:obj:`dpnp.exp2` : Calculate `2**x` for all elements in the array.
Examples
--------
>>> import dpnp as np
>>> x = np.arange(3.)
>>> np.exp(x)
array([1.0, 2.718281828, 7.389056099])
"""
exp = DPNPUnaryFunc(
"exp",
ti._exp_result_type,
ti._exp,
_EXP_DOCSTRING,
mkl_fn_to_call=vmi._mkl_exp_to_call,
mkl_impl_fn=vmi._exp,
)
_EXP2_DOCSTRING = """
Computes the base-2 exponent for each element `x_i` for input array `x`.
For full documentation refer to :obj:`numpy.exp2`.
Parameters
----------
x : {dpnp.ndarray, usm_ndarray}
Input array, expected to have a floating-point data type.
out : {None, dpnp.ndarray}, optional
Output array to populate.
Array must have the correct shape and the expected data type.
order : {"C", "F", "A", "K"}, optional
Memory layout of the newly output array, if parameter `out` is ``None``.
Default: "K".
Returns
-------
out : dpnp.ndarray
An array containing the element-wise base-2 exponents.
The data type of the returned array is determined by
the Type Promotion Rules.
Limitations
-----------
Parameters `where` and `subok` are supported with their default values.
Keyword argument `kwargs` is currently unsupported.
Otherwise ``NotImplementedError`` exception will be raised.
See Also
--------
:obj:`dpnp.exp` : Calculate exponent for all elements in the array.
:obj:`dpnp.expm1` : ``exp(x) - 1``, the inverse of :obj:`dpnp.log1p`.
:obj:`dpnp.power` : First array elements raised to powers from second array, element-wise.
Examples
--------
>>> import dpnp as np
>>> x = np.arange(3.)
>>> np.exp2(x)
array([1., 2., 4.])
"""
exp2 = DPNPUnaryFunc(
"exp2",
ti._exp2_result_type,
ti._exp2,
_EXP2_DOCSTRING,
mkl_fn_to_call=vmi._mkl_exp2_to_call,
mkl_impl_fn=vmi._exp2,
)
_EXPM1_DOCSTRING = """
Computes the exponent minus 1 for each element `x_i` of input array `x`.
This function calculates `exp(x) - 1.0` more accurately for small values of `x`.
For full documentation refer to :obj:`numpy.expm1`.
Parameters
----------
x : {dpnp.ndarray, usm_ndarray}
Input array, expected to have numeric data type.
out : {None, dpnp.ndarray}, optional
Output array to populate.
Array must have the correct shape and the expected data type.
order : {"C", "F", "A", "K"}, optional
Memory layout of the newly output array, if parameter `out` is ``None``.
Default: "K".
Returns
-------
out : dpnp.ndarray
An array containing the element-wise `exp(x) - 1` results.
The data type of the returned array is determined by the Type
Promotion Rules.
Limitations
-----------
Parameters `where` and `subok` are supported with their default values.
Keyword argument `kwargs` is currently unsupported.
Otherwise ``NotImplementedError`` exception will be raised.
See Also
--------
:obj:`dpnp.exp` : Calculate exponents for all elements in the array.
:obj:`dpnp.exp2` : Calculate `2**x` for all elements in the array.
:obj:`dpnp.log1p` : Calculate ``log(1 + x)``, the inverse of :obj:`dpnp.expm1`.
Examples
--------
>>> import dpnp as np
>>> x = np.arange(3.)
>>> np.expm1(x)
array([0.0, 1.718281828, 6.389056099])
>>> np.expm1(np.array(1e-10))
array(1.00000000005e-10)
>>> np.exp(np.array(1e-10)) - 1
array(1.000000082740371e-10)
"""
expm1 = DPNPUnaryFunc(
"expm1",
ti._expm1_result_type,
ti._expm1,
_EXPM1_DOCSTRING,
mkl_fn_to_call=vmi._mkl_expm1_to_call,
mkl_impl_fn=vmi._expm1,
)
_HYPOT_DOCSTRING = """
Calculates the hypotenuse for a right triangle with "legs" `x1_i` and `x2_i` of
input arrays `x1` and `x2`.
For full documentation refer to :obj:`numpy.hypot`.
Parameters
----------
x1 : {dpnp.ndarray, usm_ndarray}
First input array, expected to have a real-valued data type.
x2 : {dpnp.ndarray, usm_ndarray}
Second input array, also expected to have a real-valued data type.
out : {None, dpnp.ndarray}, optional
Output array to populate.
Array must have the correct shape and the expected data type.
order : {"C", "F", "A", "K"}, optional
Memory layout of the newly output array, if parameter `out` is ``None``.
Default: "K".
Returns
-------
out : dpnp.ndarray
An array containing the element-wise hypotenuse. The data type
of the returned array is determined by the Type Promotion Rules.
Limitations
-----------
Parameters `where` and `subok` are supported with their default values.
Keyword argument `kwargs` is currently unsupported.
Otherwise ``NotImplementedError`` exception will be raised.
See Also
--------
:obj:`dpnp.reduce_hypot` : The square root of the sum of squares of elements in the input array.
Examples
--------
>>> import dpnp as np
>>> x1 = 3 * np.ones((3, 3))
>>> x2 = 4 * np.ones((3, 3))
>>> np.hypot(x1, x2)
array([[5., 5., 5.],
[5., 5., 5.],
[5., 5., 5.]])
Example showing broadcast of scalar argument:
>>> np.hypot(x1, 4)
array([[ 5., 5., 5.],
[ 5., 5., 5.],
[ 5., 5., 5.]])
"""
hypot = DPNPBinaryFunc(
"hypot",
ti._hypot_result_type,
ti._hypot,
_HYPOT_DOCSTRING,
mkl_fn_to_call=vmi._mkl_hypot_to_call,
mkl_impl_fn=vmi._hypot,
)
_LOG_DOCSTRING = """
Computes the natural logarithm for each element `x_i` of input array `x`.
For full documentation refer to :obj:`numpy.log`.
Parameters
----------
x : {dpnp.ndarray, usm_ndarray}
Input array, expected to have numeric data type.
out : {None, dpnp.ndarray}, optional
Output array to populate.
Array must have the correct shape and the expected data type.
order : {"C", "F", "A", "K"}, optional
Memory layout of the newly output array, if parameter `out` is ``None``.
Default: "K".
Returns
-------
out : dpnp.ndarray
An array containing the element-wise natural logarithm values.
The data type of the returned array is determined by the Type
Promotion Rules.
Limitations
-----------
Parameters `where` and `subok` are supported with their default values.
Otherwise ``NotImplementedError`` exception will be raised.
See Also
--------
:obj:`dpnp.log10` : Return the base 10 logarithm of the input array,
element-wise.
:obj:`dpnp.log2` : Base-2 logarithm of x.
:obj:`dpnp.log1p` : Return the natural logarithm of one plus
the input array, element-wise.
Examples
--------
>>> import dpnp as np
>>> x = np.array([1, np.e, np.e**2, 0])
>>> np.log(x)
array([ 0., 1., 2., -inf])
"""
log = DPNPUnaryFunc(
"log",
ti._log_result_type,
ti._log,
_LOG_DOCSTRING,
mkl_fn_to_call=vmi._mkl_ln_to_call,
mkl_impl_fn=vmi._ln,
)
_LOG10_DOCSTRING = """
Computes the base-10 logarithm for each element `x_i` of input array `x`.
For full documentation refer to :obj:`numpy.log10`.
Parameters
----------
x : {dpnp.ndarray, usm_ndarray}
Input array, expected to have numeric data type.
out : {None, dpnp.ndarray}, optional
Output array to populate.
Array must have the correct shape and the expected data type.
order : {"C", "F", "A", "K"}, optional
Memory layout of the newly output array, if parameter `out` is ``None``.
Default: "K".
Returns
-------
out : dpnp.ndarray
An array containing the element-wise base-10 logarithm of `x`.
The data type of the returned array is determined by the
Type Promotion Rules.
Limitations
-----------
Parameters `where` and `subok` are supported with their default values.
Keyword argument `kwargs` is currently unsupported.
Otherwise ``NotImplementedError`` exception will be raised.
See Also
--------
:obj:`dpnp.log` : Natural logarithm, element-wise.
:obj:`dpnp.log2` : Return the base 2 logarithm of the input array, element-wise.
:obj:`dpnp.log1p` : Return the natural logarithm of one plus the input array, element-wise.
Examples
--------
>>> import dpnp as np
>>> x = np.arange(3.)
>>> np.log10(x)
array([-inf, 0.0, 0.30102999566])
>>> np.log10(np.array([1e-15, -3.]))
array([-15., nan])
"""
log10 = DPNPUnaryFunc(
"log10",
ti._log10_result_type,
ti._log10,
_LOG10_DOCSTRING,
mkl_fn_to_call=vmi._mkl_log10_to_call,
mkl_impl_fn=vmi._log10,
)
_LOG1P_DOCSTRING = """
Computes the natural logarithm of (1 + `x`) for each element `x_i` of input
array `x`.
This function calculates `log(1 + x)` more accurately for small values of `x`.
For full documentation refer to :obj:`numpy.log1p`.
Parameters
----------
x : {dpnp.ndarray, usm_ndarray}
Input array, expected to have numeric data type.
out : {None, dpnp.ndarray}, optional
Output array to populate.
Array must have the correct shape and the expected data type.
order : {"C", "F", "A", "K"}, optional
Memory layout of the newly output array, if parameter `out` is ``None``.
Default: "K".
Returns
-------
out : dpnp.ndarray
An array containing the element-wise `log(1 + x)` results. The data type
of the returned array is determined by the Type Promotion Rules.
Limitations
-----------
Parameters `where` and `subok` are supported with their default values.
Keyword argument `kwargs` is currently unsupported.
Otherwise ``NotImplementedError`` exception will be raised.
See Also
--------
:obj:`dpnp.expm1` : ``exp(x) - 1``, the inverse of :obj:`dpnp.log1p`.
:obj:`dpnp.log` : Natural logarithm, element-wise.
:obj:`dpnp.log10` : Return the base 10 logarithm of the input array, element-wise.
:obj:`dpnp.log2` : Return the base 2 logarithm of the input array, element-wise.
Examples
--------
>>> import dpnp as np
>>> x = np.arange(3.)
>>> np.log1p(x)
array([0.0, 0.69314718, 1.09861229])
>>> np.log1p(array(1e-99))
array(1e-99)
>>> np.log(array(1 + 1e-99))
array(0.0)
"""
log1p = DPNPUnaryFunc(
"log1p",
ti._log1p_result_type,
ti._log1p,
_LOG1P_DOCSTRING,
mkl_fn_to_call=vmi._mkl_log1p_to_call,
mkl_impl_fn=vmi._log1p,
)
_LOG2_DOCSTRING = """
Computes the base-2 logarithm for each element `x_i` of input array `x`.
For full documentation refer to :obj:`numpy.log2`.
Parameters
----------
x : {dpnp.ndarray, usm_ndarray}
Input array, expected to have numeric data type.
out : {None, dpnp.ndarray}, optional
Output array to populate.
Array must have the correct shape and the expected data type.
order : {"C", "F", "A", "K"}, optional
Memory layout of the newly output array, if parameter `out` is ``None``.
Default: "K".
Returns
-------
out : dpnp.ndarray
An array containing the element-wise base-2 logarithm of `x`.
The data type of the returned array is determined by the
Type Promotion Rules.
Limitations
-----------
Parameters `where` and `subok` are supported with their default values.
Keyword argument `kwargs` is currently unsupported.
Otherwise ``NotImplementedError`` exception will be raised.
See Also
--------
:obj:`dpnp.log` : Natural logarithm, element-wise.
:obj:`dpnp.log10` : Return the base 10 logarithm of the input array, element-wise.
:obj:`dpnp.log1p` : Return the natural logarithm of one plus the input array, element-wise.
Examples
--------
>>> import dpnp as np
>>> x = np.array([0, 1, 2, 2**4])
>>> np.log2(x)
array([-inf, 0.0, 1.0, 4.0])
>>> xi = np.array([0+1.j, 1, 2+0.j, 4.j])
>>> np.log2(xi)
array([ 0.+2.26618007j, 0.+0.j , 1.+0.j , 2.+2.26618007j])
"""
log2 = DPNPUnaryFunc(
"log2",
ti._log2_result_type,
ti._log2,
_LOG2_DOCSTRING,
mkl_fn_to_call=vmi._mkl_log2_to_call,
mkl_impl_fn=vmi._log2,
)
_LOGADDEXP_DOCSTRING = """
Calculates the natural logarithm of the sum of exponents for each element `x1_i`
of the input array `x1` with the respective element `x2_i` of the input
array `x2`.
This function calculates `log(exp(x1) + exp(x2))` more accurately for small
values of `x`.
For full documentation refer to :obj:`numpy.logaddexp`.
Parameters
----------
x1 : {dpnp.ndarray, usm_ndarray}
First input array, expected to have a real-valued floating-point
data type.
x2 : {dpnp.ndarray, usm_ndarray}
Second input array, also expected to have a real-valued
floating-point data type.
out : {None, dpnp.ndarray}, optional
Output array to populate.
Array must have the correct shape and the expected data type.
order : {"C", "F", "A", "K"}, optional
Memory layout of the newly output array, if parameter `out` is ``None``.
Default: "K".
Returns
-------
out : dpnp.ndarray
An array containing the element-wise results. The data type
of the returned array is determined by the Type Promotion Rules.
Limitations
-----------
Parameters `where` and `subok` are supported with their default values.
Keyword arguments `kwargs` are currently unsupported.
Otherwise ``NotImplementedError`` exception will be raised.
See Also
--------
:obj:`dpnp.log` : Natural logarithm, element-wise.
:obj:`dpnp.exp` : Exponential, element-wise.
:obj:`dpnp.logsumdexp` : Logarithm of the sum of exponents of elements in the input array.
Examples
--------
>>> import dpnp as np
>>> prob1 = np.log(np.array(1e-50))
>>> prob2 = np.log(np.array(2.5e-50))
>>> prob12 = np.logaddexp(prob1, prob2)
>>> prob12
array(-113.87649168)
>>> np.exp(prob12)
array(3.5e-50)
"""
logaddexp = DPNPBinaryFunc(
"logaddexp",
ti._logaddexp_result_type,
ti._logaddexp,
_LOGADDEXP_DOCSTRING,
)
[docs]
def logsumexp(x, /, *, axis=None, dtype=None, keepdims=False, out=None):
"""
Calculates the logarithm of the sum of exponents of elements in
the input array.
Parameters
----------
x : {dpnp.ndarray, usm_ndarray}
Input array, expected to have a real-valued data type.
axis : {None, int or tuple of ints}, optional
Axis or axes along which values must be computed. If a tuple of unique
integers, values are computed over multiple axes. If ``None``, the
result is computed over the entire array.
Default: ``None``.
dtype : {None, dtype}, optional
Data type of the returned array. If ``None``, the default data type is
inferred from the "kind" of the input array data type.
- If `x` has a real-valued floating-point data type, the returned array
will have the same data type as `x`.
- If `x` has a boolean or integral data type, the returned array will
have the default floating point data type for the device where input
array `x` is allocated.
- If `x` has a complex-valued floating-point data type, an error is
raised.
If the data type (either specified or resolved) differs from the data
type of `x`, the input array elements are cast to the specified data
type before computing the result.
Default: ``None``.
keepdims : {None, bool}, optional
If ``True``, the reduced axes (dimensions) are included in the result
as singleton dimensions, so that the returned array remains compatible
with the input arrays according to Array Broadcasting rules. Otherwise,
if ``False``, the reduced axes are not included in the returned array.
Default: ``False``.
out : {None, dpnp.ndarray, usm_ndarray}, optional
The array into which the result is written. The data type of `out` must
match the expected shape and the expected data type of the result or
(if provided) `dtype`. If ``None`` then a new array is returned.
Default: ``None``.
Returns
-------
out : dpnp.ndarray
An array containing the results. If the result was computed over the
entire array, a zero-dimensional array is returned. The returned array
has the data type as described in the `dtype` parameter description
above.
Note
----
This function is equivalent of `numpy.logaddexp.reduce`.
See Also
--------
:obj:`dpnp.log` : Natural logarithm, element-wise.
:obj:`dpnp.exp` : Exponential, element-wise.
:obj:`dpnp.logaddexp` : Logarithm of the sum of exponents of
the inputs, element-wise.
Examples
--------
>>> import dpnp as np
>>> a = np.ones(10)
>>> np.logsumexp(a)
array(3.30258509)
>>> np.log(np.sum(np.exp(a)))
array(3.30258509)
"""
usm_x = dpnp.get_usm_ndarray(x)
return dpnp_wrap_reduction_call(
x,
out,
dpt.logsumexp,
_get_accumulation_res_dt,
usm_x,
axis=axis,
dtype=dtype,
keepdims=keepdims,
)
_RECIPROCAL_DOCSTRING = """
Computes the reciprocal square-root for each element `x_i` for input array `x`.
For full documentation refer to :obj:`numpy.reciprocal`.
Parameters
----------
x : {dpnp.ndarray, usm_ndarray}
Input array, expected to have a real-valued floating-point data type.
out : {None, dpnp.ndarray}, optional
Output array to populate.
Array must have the correct shape and the expected data type.
order : {"C", "F", "A", "K"}, optional
Memory layout of the newly output array, if parameter `out` is ``None``.
Default: "K".
Returns
-------
out : dpnp.ndarray
An array containing the element-wise reciprocals.
The returned array has a floating-point data type determined
by the Type Promotion Rules.
Limitations
-----------
Parameters `where` and `subok` are supported with their default values.
Keyword argument `kwargs` is currently unsupported.
Otherwise ``NotImplementedError`` exception will be raised.
See Also
--------
:obj:`dpnp.rsqrt` : Return the reciprocal square-root of an array, element-wise.
Examples
--------
>>> import dpnp as np
>>> x = np.array([1, 2., 3.33])
>>> np.reciprocal(x)
array([1.0, 0.5, 0.3003003])
"""
reciprocal = DPNPUnaryFunc(
"reciprocal",
ti._reciprocal_result_type,
ti._reciprocal,
_RECIPROCAL_DOCSTRING,
)
[docs]
def reduce_hypot(x, /, *, axis=None, dtype=None, keepdims=False, out=None):
"""
Calculates the square root of the sum of squares of elements in
the input array.
Parameters
----------
x : {dpnp.ndarray, usm_ndarray}
Input array, expected to have a real-valued data type.
axis : {None, int or tuple of ints}, optional
Axis or axes along which values must be computed. If a tuple of unique
integers, values are computed over multiple axes. If ``None``, the
result is computed over the entire array.
Default: ``None``.
dtype : {None, dtype}, optional
Data type of the returned array. If ``None``, the default data type is
inferred from the "kind" of the input array data type.
- If `x` has a real-valued floating-point data type, the returned array
will have the same data type as `x`.
- If `x` has a boolean or integral data type, the returned array will
have the default floating point data type for the device where input
array `x` is allocated.
- If `x` has a complex-valued floating-point data type, an error is
raised.
If the data type (either specified or resolved) differs from the data
type of `x`, the input array elements are cast to the specified data
type before computing the result.
Default: ``None``.
keepdims : {None, bool}, optional
If ``True``, the reduced axes (dimensions) are included in the result
as singleton dimensions, so that the returned array remains compatible
with the input arrays according to Array Broadcasting rules. Otherwise,
if ``False``, the reduced axes are not included in the returned array.
Default: ``False``.
out : {None, dpnp.ndarray, usm_ndarray}, optional
The array into which the result is written. The data type of `out` must
match the expected shape and the expected data type of the result or
(if provided) `dtype`. If ``None`` then a new array is returned.
Default: ``None``.
Returns
-------
out : dpnp.ndarray
An array containing the results. If the result was computed over the
entire array, a zero-dimensional array is returned. The returned array
has the data type as described in the `dtype` parameter description
above.
Note
----
This function is equivalent of `numpy.hypot.reduce`.
See Also
--------
:obj:`dpnp.hypot` : Given the "legs" of a right triangle, return its
hypotenuse.
Examples
--------
>>> import dpnp as np
>>> a = np.ones(10)
>>> np.reduce_hypot(a)
array(3.16227766)
>>> np.sqrt(np.sum(np.square(a)))
array(3.16227766)
"""
usm_x = dpnp.get_usm_ndarray(x)
return dpnp_wrap_reduction_call(
x,
out,
dpt.reduce_hypot,
_get_accumulation_res_dt,
usm_x,
axis=axis,
dtype=dtype,
keepdims=keepdims,
)
_RSQRT_DOCSTRING = """
Computes the reciprocal square-root for each element `x_i` for input array `x`.
Parameters
----------
x : {dpnp.ndarray, usm_ndarray}
Input array, expected to have a real floating-point data type.
out : ({None, dpnp.ndarray, usm_ndarray}, optional):
Output array to populate.
Array must have the correct shape and the expected data type.
order : ({'C', 'F', 'A', 'K'}, optional):
Memory layout of the newly output array, if parameter `out` is `None`.
Default: "K"
Returns
-------
out : dpnp.ndarray
An array containing the element-wise reciprocal square-root.
The returned array has a floating-point data type determined by
the Type Promotion Rules.
Limitations
-----------
Parameters `where` and `subok` are supported with their default values.
Keyword argument `kwargs` is currently unsupported.
Otherwise ``NotImplementedError`` exception will be raised.
See Also
--------
:obj:`dpnp.sqrt` : Return the positive square-root of an array, element-wise.
:obj:`dpnp.reciprocal` : Return the reciprocal of an array, element-wise.
Examples
--------
>>> import dpnp as np
>>> x = np.array([1, 8, 27])
>>> np.rsqrt(x)
array([1. , 0.35355338, 0.19245009])
"""
rsqrt = DPNPUnaryFunc(
"rsqrt",
ti._rsqrt_result_type,
ti._rsqrt,
_RSQRT_DOCSTRING,
)
[docs]
def rad2deg(x1):
"""
Convert angles from radians to degrees.
For full documentation refer to :obj:`numpy.rad2deg`.
See Also
--------
:obj:`dpnp.deg2rad` : Convert angles from degrees to radians.
:obj:`dpnp.unwrap` : Remove large jumps in angle by wrapping.
Notes
-----
This function works exactly the same as :obj:`dpnp.degrees`.
"""
return degrees(x1)
[docs]
def radians(x1, **kwargs):
"""
Convert angles from degrees to radians.
For full documentation refer to :obj:`numpy.radians`.
Limitations
-----------
Input array is supported as :obj:`dpnp.ndarray`.
Input array data types are limited by supported DPNP :ref:`Data types`.
.. seealso:: :obj:`dpnp.deg2rad` equivalent function.
Examples
--------
>>> import dpnp as np
>>> deg = np.arange(6.) * 30.
>>> out = np.radians(deg)
>>> [i for i in out]
[0.0, 0.52359878, 1.04719755, 1.57079633, 2.0943951, 2.61799388]
"""
x1_desc = dpnp.get_dpnp_descriptor(
x1, copy_when_strides=False, copy_when_nondefault_queue=False
)
if kwargs:
pass
elif x1_desc:
return dpnp_radians(x1_desc).get_pyobj()
return call_origin(numpy.radians, x1, **kwargs)
_SIN_DOCSTRING = """
Computes sine for each element `x_i` of input array `x`.
For full documentation refer to :obj:`numpy.sin`.
Parameters
----------
x : {dpnp.ndarray, usm_ndarray}
Input array, expected to have numeric data type.
out : {None, dpnp.ndarray}, optional
Output array to populate.
Array must have the correct shape and the expected data type.
order : {"C", "F", "A", "K"}, optional
Memory layout of the newly output array, if parameter `out` is ``None``.
Default: "K".
Returns
-------
out : dpnp.ndarray
An array containing the element-wise sine. The data type of the
returned array is determined by the Type Promotion Rules.
Limitations
-----------
Parameters `where` and `subok` are supported with their default values.
Keyword argument `kwargs` is currently unsupported.
Otherwise ``NotImplementedError`` exception will be raised.
See Also
--------
:obj:`dpnp.arcsin` : Trigonometric inverse sine, element-wise.
:obj:`dpnp.cos` : Trigonometric cosine, element-wise.
:obj:`dpnp.tan` : Trigonometric tangent, element-wise.
:obj:`dpnp.sinh` : Hyperbolic sine, element-wise.
Examples
--------
>>> import dpnp as np
>>> x = np.array([0, np.pi/2, np.pi])
>>> np.sin(x)
array([ 0.000000e+00, 1.000000e+00, -8.742278e-08])
"""
sin = DPNPUnaryFunc(
"sin",
ti._sin_result_type,
ti._sin,
_SIN_DOCSTRING,
mkl_fn_to_call=vmi._mkl_sin_to_call,
mkl_impl_fn=vmi._sin,
)
_SINH_DOCSTRING = """
Computes hyperbolic sine for each element `x_i` for input array `x`.
For full documentation refer to :obj:`numpy.sinh`.
Parameters
----------
x : {dpnp.ndarray, usm_ndarray}
Input array, expected to have numeric data type.
out : {None, dpnp.ndarray}, optional
Output array to populate.
Array must have the correct shape and the expected data type.
order : {"C", "F", "A", "K"}, optional
Memory layout of the newly output array, if parameter `out` is ``None``.
Default: "K".
Returns
-------
out : dpnp.ndarray
An array containing the element-wise hyperbolic sine. The data type
of the returned array is determined by the Type Promotion Rules.
Limitations
-----------
Keyword argument `kwargs` is currently unsupported.
Otherwise ``NotImplementedError`` exception will be raised.
See Also
--------
:obj:`dpnp.arcsinh` : Hyperbolic inverse sine, element-wise.
:obj:`dpnp.cosh` : Hyperbolic cosine, element-wise.
:obj:`dpnp.tanh` : Hyperbolic tangent, element-wise.
:obj:`dpnp.sin` : Trigonometric sine, element-wise.
Examples
--------
>>> import dpnp as np
>>> x = np.array([0, np.pi/2, np.pi])
>>> np.sinh(x)
array([0.0, 2.3012989, 11.548739])
"""
sinh = DPNPUnaryFunc(
"sinh",
ti._sinh_result_type,
ti._sinh,
_SINH_DOCSTRING,
mkl_fn_to_call=vmi._mkl_sinh_to_call,
mkl_impl_fn=vmi._sinh,
)
_SQRT_DOCSTRING = """
Computes the positive square-root for each element `x_i` of input array `x`.
For full documentation refer to :obj:`numpy.sqrt`.
Parameters
----------
x : {dpnp.ndarray, usm_ndarray}
Input array.
out : {None, dpnp.ndarray}, optional
Output array to populate.
Array must have the correct shape and the expected data type.
order : {"C", "F", "A", "K"}, optional
Memory layout of the newly output array, if parameter `out` is ``None``.
Default: "K".
Returns
-------
out : dpnp.ndarray
An array containing the element-wise positive square-roots of `x`. The
data type of the returned array is determined by the Type Promotion
Rules.
Limitations
-----------
Parameters `where` and `subok` are supported with their default values.
Otherwise ``NotImplementedError`` exception will be raised.
See Also
--------
:obj:`dpnp.cbrt` : Return the cube-root of an array, element-wise.
:obj:`dpnp.rsqrt` : Return the reciprocal square-root of an array, element-wise.
Examples
--------
>>> import dpnp as np
>>> x = np.array([1, 4, 9])
>>> np.sqrt(x)
array([1., 2., 3.])
>>> x2 = np.array([4, -1, np.inf])
>>> np.sqrt(x2)
array([ 2., nan, inf])
"""
sqrt = DPNPUnaryFunc(
"sqrt",
ti._sqrt_result_type,
ti._sqrt,
_SQRT_DOCSTRING,
mkl_fn_to_call=vmi._mkl_sqrt_to_call,
mkl_impl_fn=vmi._sqrt,
)
_SQUARE_DOCSTRING = """
Squares each element `x_i` of input array `x`.
For full documentation refer to :obj:`numpy.square`.
Parameters
----------
x : {dpnp.ndarray, usm_ndarray}
Input array.
out : {None, dpnp.ndarray}, optional
Output array to populate.
Array must have the correct shape and the expected data type.
order : {"C", "F", "A", "K"}, optional
Memory layout of the newly output array, if parameter `out` is ``None``.
Default: "K".
Returns
-------
out : dpnp.ndarray
An array containing the element-wise squares of `x`. The data type of
the returned array is determined by the Type Promotion Rules.
Limitations
-----------
Parameters `where` and `subok` are supported with their default values.
Otherwise ``NotImplementedError`` exception will be raised.
See Also
--------
:obj:`dpnp..linalg.matrix_power` : Raise a square matrix
to the (integer) power `n`.
:obj:`dpnp.sqrt` : Return the positive square-root of an array,
element-wise.
:obj:`dpnp.power` : First array elements raised to powers
from second array, element-wise.
Examples
--------
>>> import dpnp as np
>>> x = np.array([-1j, 1])
>>> np.square(x)
array([-1.+0.j, 1.+0.j])
"""
square = DPNPUnaryFunc(
"square",
ti._square_result_type,
ti._square,
_SQUARE_DOCSTRING,
mkl_fn_to_call=vmi._mkl_sqr_to_call,
mkl_impl_fn=vmi._sqr,
)
_TAN_DOCSTRING = """
Computes tangent for each element `x_i` for input array `x`.
For full documentation refer to :obj:`numpy.tan`.
Parameters
----------
x : {dpnp.ndarray, usm_ndarray}
Input array, expected to have numeric data type.
out : {None, dpnp.ndarray}, optional
Output array to populate.
Array must have the correct shape and the expected data type.
order : {"C", "F", "A", "K"}, optional
Memory layout of the newly output array, if parameter `out` is ``None``.
Default: "K".
Returns
-------
out : dpnp.ndarray
An array containing the element-wise tangent. The data type
of the returned array is determined by the Type Promotion Rules.
Limitations
-----------
Parameters `where` and `subok` are supported with their default values.
Keyword argument `kwargs` is currently unsupported.
Otherwise ``NotImplementedError`` exception will be raised.
See Also
--------
:obj:`dpnp.arctan` : Trigonometric inverse tangent, element-wise.
:obj:`dpnp.sin` : Trigonometric sine, element-wise.
:obj:`dpnp.cos` : Trigonometric cosine, element-wise.
:obj:`dpnp.tanh` : Hyperbolic tangent, element-wise.
Examples
--------
>>> import dpnp as np
>>> x = np.array([-np.pi, np.pi/2, np.pi])
>>> np.tan(x)
array([1.22460635e-16, 1.63317787e+16, -1.22460635e-16])
"""
tan = DPNPUnaryFunc(
"tan",
ti._tan_result_type,
ti._tan,
_TAN_DOCSTRING,
mkl_fn_to_call=vmi._mkl_tan_to_call,
mkl_impl_fn=vmi._tan,
)
_TANH_DOCSTRING = """
Computes hyperbolic tangent for each element `x_i` for input array `x`.
For full documentation refer to :obj:`numpy.tanh`.
Parameters
----------
x : {dpnp.ndarray, usm_ndarray}
Input array, expected to have numeric data type.
out : {None, dpnp.ndarray}, optional
Output array to populate.
Array must have the correct shape and the expected data type.
order : {"C", "F", "A", "K"}, optional
Memory layout of the newly output array, if parameter `out` is ``None``.
Default: "K".
Returns
-------
out : dpnp.ndarray
An array containing the element-wise hyperbolic tangent. The data type
of the returned array is determined by the Type Promotion Rules.
Limitations
-----------
Parameters `where` and `subok` are supported with their default values.
Keyword argument `kwargs` is currently unsupported.
Otherwise ``NotImplementedError`` exception will be raised.
See Also
--------
:obj:`dpnp.arctanh` : Hyperbolic inverse tangent, element-wise.
:obj:`dpnp.sinh` : Hyperbolic sine, element-wise.
:obj:`dpnp.cosh` : Hyperbolic cosine, element-wise.
:obj:`dpnp.tan` : Trigonometric tangent, element-wise.
Examples
--------
>>> import dpnp as np
>>> x = np.array([0, -np.pi, np.pi/2, np.pi])
>>> np.tanh(x)
array([0.0, -0.996272, 0.917152, 0.996272])
"""
tanh = DPNPUnaryFunc(
"tanh",
ti._tanh_result_type,
ti._tanh,
_TANH_DOCSTRING,
mkl_fn_to_call=vmi._mkl_tanh_to_call,
mkl_impl_fn=vmi._tanh,
)
[docs]
def unwrap(x1, **kwargs):
"""
Unwrap by changing deltas between values to 2*pi complement.
For full documentation refer to :obj:`numpy.unwrap`.
Limitations
-----------
Input array is supported as :class:`dpnp.ndarray`.
Input array data types are limited by supported DPNP :ref:`Data types`.
See Also
--------
:obj:`dpnp.rad2deg` : Convert angles from radians to degrees.
:obj:`dpnp.deg2rad` : Convert angles from degrees to radians.
Examples
--------
>>> import dpnp as np
>>> phase = np.linspace(0, np.pi, num=5)
>>> for i in range(3, 5):
>>> phase[i] += np.pi
>>> out = np.unwrap(phase)
>>> [i for i in out]
[0.0, 0.78539816, 1.57079633, 5.49778714, 6.28318531]
"""
x1_desc = dpnp.get_dpnp_descriptor(x1, copy_when_nondefault_queue=False)
if kwargs:
pass
elif x1_desc:
return dpnp_unwrap(x1_desc).get_pyobj()
return call_origin(numpy.unwrap, x1, **kwargs)