import torch
from .constants import pi
from .operations import __local_op as local_op
from .operations import __binary_op as binary_op
from . import types
__all__ = [
"arccos",
"arcsin",
"arctan",
"arctan2",
"cos",
"cosh",
"deg2rad",
"degrees",
"rad2deg",
"radians",
"sin",
"sinh",
"tan",
"tanh",
]
def arccos(x, out=None):
"""
Return the trigonometric arccos, element-wise.
Parameters
----------
x : ht.DNDarray
The value for which to compute the trigonometric cosine.
out : ht.DNDarray or None, optional
A location in which to store the results. If provided, it must have a broadcastable shape. If not provided
or set to None, a fresh tensor is allocated.
Returns
-------
arccos : ht.DNDarray
A tensor of the same shape as x, containing the trigonometric arccos of each element in this tensor.
Input elements outside [-1., 1.] are returned as nan. If out was provided, arccos is a reference to it.
Examples
--------
>>> ht.arccos(ht.array([-1.,-0., 0.83]))
tensor([3.1416, 1.5708, 0.5917])
"""
return local_op(torch.acos, x, out)
def arcsin(x, out=None):
"""
Return the trigonometric arcsin, element-wise.
Parameters
----------
x : ht.DNDarray
The value for which to compute the trigonometric cosine.
out : ht.DNDarray or None, optional
A location in which to store the results. If provided, it must have a broadcastable shape. If not provided
or set to None, a fresh tensor is allocated.
Returns
-------
arcsin : ht.DNDarray
A tensor of the same shape as x, containing the trigonometric arcsin of each element in this tensor.
Input elements outside [-1., 1.] are returned as nan. If out was provided, arcsin is a reference to it.
Examples
--------
>>> ht.arcsin(ht.array([-1.,-0., 0.83]))
tensor([-1.5708, 0.0000, 0.9791])
"""
return local_op(torch.asin, x, out)
def arctan(x, out=None):
"""
Return the trigonometric arctan, element-wise.
Parameters
----------
x : ht.DNDarray
The value for which to compute the trigonometric cosine.
out : ht.DNDarray or None, optional
A location in which to store the results. If provided, it must have a broadcastable shape. If not provided
or set to None, a fresh tensor is allocated.
Returns
-------
arcstan : ht.DNDarray
A tensor of the same shape as x, containing the trigonometric arctan of each element in this tensor.
If out was provided, arctan is a reference to it.
Examples
--------
>>> ht.arctan(ht.arange(-6, 7, 2))
tensor([-1.4056, -1.3258, -1.1071, 0.0000, 1.1071, 1.3258, 1.4056],
dtype=torch.float64)
"""
return local_op(torch.atan, x, out)
def arctan2(x1, x2):
"""
Element-wise arc tangent of ``x1/x2`` choosing the quadrant correctly.
Returns a new ``DNDarray`` with the signed angles in radians between vector (``x2``,``x1``) and vector (1,0)
Parameters
----------
x1 : DNDarray
y-coordinates
x2 : DNDarray
x-coordinates. If ``x1.shape!=x2.shape``, they must be broadcastable to a common shape (which becomes the shape of the output).
Returns
-------
DNDarray
Examples
--------
>>> x = ht.array([-1, +1, +1, -1])
>>> y = ht.array([-1, -1, +1, +1])
>>> ht.arctan2(y, x) * 180 / ht.pi
tensor([-135.0000, -45.0000, 45.0000, 135.0000], dtype=torch.float64)
"""
# Cast integer to float because torch.atan2() only supports integer types on PyTorch 1.5.0.
x1 = x1.astype(types.promote_types(x1.dtype, types.float))
x2 = x2.astype(types.promote_types(x2.dtype, types.float))
return binary_op(torch.atan2, x1, x2)
def cos(x, out=None):
"""
Return the trigonometric cosine, element-wise.
Parameters
----------
x : ht.DNDarray
The value for which to compute the trigonometric cosine.
out : ht.DNDarray or None, optional
A location in which to store the results. If provided, it must have a broadcastable shape. If not provided
or set to None, a fresh tensor is allocated.
Returns
-------
cosine : ht.DNDarray
A tensor of the same shape as x, containing the trigonometric cosine of each element in this tensor.
Negative input elements are returned as nan. If out was provided, square_roots is a reference to it.
Examples
--------
>>> ht.cos(ht.arange(-6, 7, 2))
tensor([0.96017029, -0.65364362, -0.41614684, 1., -0.41614684, -0.65364362, 0.96017029])
"""
return local_op(torch.cos, x, out)
def cosh(x, out=None):
"""
Return the hyperbolic cosine, element-wise.
Parameters
----------
x : ht.DNDarray
The value for which to compute the hyperbolic cosine.
out : ht.DNDarray or None, optional
A location in which to store the results. If provided, it must have a broadcastable shape. If not provided
or set to None, a fresh tensor is allocated.
Returns
-------
hyperbolic cosine : ht.DNDarray
A tensor of the same shape as x, containing the hyperbolic cosine of each element in this tensor.
Negative input elements are returned as nan. If out was provided, square_roots is a reference to it.
Examples
--------
>>> ht.cosh(ht.arange(-6, 7, 2))
tensor([201.7156, 27.3082, 3.7622, 1.0000, 3.7622, 27.3082, 201.7156])
"""
return local_op(torch.cosh, x, out)
def deg2rad(x, out=None):
"""
Convert angles from degrees to radians.
Parameters
----------
x : ht.DNDarray
The value for which to compute the angles in radians.
out : ht.DNDarray or None, optional
A location in which to store the results. If provided, it must have a broadcastable shape. If not provided
or set to None, a fresh tensor is allocated.
Returns
-------
y : ht.DNDarray
The corresponding angle in radians
Examples elements =
--------
>>> ht.deg2rad(ht.array([0.,20.,45.,78.,94.,120.,180., 270., 311.]))
tensor([0.0000, 0.3491, 0.7854, 1.3614, 1.6406, 2.0944, 3.1416, 4.7124, 5.4280])
"""
# deg2rad torch version
def torch_deg2rad(torch_tensor):
if not torch.is_tensor(torch_tensor):
raise TypeError("Input is not a torch tensor but {}".format(type(torch_tensor)))
return torch_tensor * pi / 180.0
return local_op(torch_deg2rad, x, out)
def degrees(x, out=None):
"""
Convert angles from radians to degrees.
Parameters
----------
x : ht.DNDarray
The value for which to compute the angles in degrees.
out : ht.DNDarray or None, optional
A location in which to store the results. If provided, it must have a broadcastable shape. If not provided
or set to None, a fresh tensor is allocated.
Returns
-------
y : ht.DNDarray
The corresponding angle in degrees
Examples
--------
>>> ht.degrees(ht.array([0.,0.2,0.6,0.9,1.2,2.7,3.14]))
tensor([ 0.0000, 11.4592, 34.3775, 51.5662, 68.7549, 154.6986, 179.9088])
"""
return rad2deg(x, out=out)
def rad2deg(x, out=None):
"""
Convert angles from radians to degrees.
Parameters
----------
x : ht.DNDarray
The value for which to compute the angles in degrees.
out : ht.DNDarray or None, optional
A location in which to store the results. If provided, it must have a broadcastable shape. If not provided
or set to None, a fresh tensor is allocated.
Returns
-------
y : ht.DNDarray
The corresponding angle in degrees
Examples
--------
>>> ht.rad2deg(ht.array([0.,0.2,0.6,0.9,1.2,2.7,3.14]))
tensor([ 0.0000, 11.4592, 34.3775, 51.5662, 68.7549, 154.6986, 179.9088])
"""
# rad2deg torch version
def torch_rad2deg(torch_tensor):
if not torch.is_tensor(torch_tensor):
raise TypeError("Input is not a torch tensor but {}".format(type(torch_tensor)))
return 180.0 * torch_tensor / pi
return local_op(torch_rad2deg, x, out=out)
def radians(x, out=None):
"""
Convert angles from degrees to radians.
Parameters
----------
x : ht.DNDarray
The value for which to compute the angles in radians.
out : ht.DNDarray or None, optional
A location in which to store the results. If provided, it must have a broadcastable shape. If not provided
or set to None, a fresh tensor is allocated.
Returns
-------
y : ht.DNDarray
The corresponding angle in radians
Examples
--------
>>> ht.radians(ht.array([0., 20., 45., 78., 94., 120., 180., 270., 311.]))
tensor([0.0000, 0.3491, 0.7854, 1.3614, 1.6406, 2.0944, 3.1416, 4.7124, 5.4280])
"""
return deg2rad(x, out=None)
def sin(x, out=None):
"""
Return the trigonometric sine, element-wise.
Parameters
----------
x : ht.DNDarray
The value for which to compute the trigonometric tangent.
out : ht.DNDarray or None, optional
A location in which to store the results. If provided, it must have a broadcastable shape. If not provided
or set to None, a fresh tensor is allocated.
Returns
-------
sine : ht.DNDarray
A tensor of the same shape as x, containing the trigonometric sine of each element in this tensor.
Negative input elements are returned as nan. If out was provided, square_roots is a reference to it.
Examples
--------
>>> ht.sin(ht.arange(-6, 7, 2))
tensor([ 0.2794, 0.7568, -0.9093, 0.0000, 0.9093, -0.7568, -0.2794])
"""
return local_op(torch.sin, x, out)
def sinh(x, out=None):
"""
Return the hyperbolic sine, element-wise.
Parameters
----------
x : ht.DNDarray
The value for which to compute the hyperbolic sine.
out : ht.DNDarray or None, optional
A location in which to store the results. If provided, it must have a broadcastable shape. If not provided
or set to None, a fresh tensor is allocated.
Returns
-------
hyperbolic sine : ht.DNDarray
A tensor of the same shape as x, containing the trigonometric sine of each element in this tensor.
Negative input elements are returned as nan. If out was provided, square_roots is a reference to it.
Examples
--------
>>> ht.sinh(ht.arange(-6, 7, 2))
tensor([[-201.7132, -27.2899, -3.6269, 0.0000, 3.6269, 27.2899, 201.7132])
"""
return local_op(torch.sinh, x, out)
def tan(x, out=None):
"""
Compute tangent element-wise.
Equivalent to ht.sin(x) / ht.cos(x) element-wise.
Parameters
----------
x : ht.DNDarray
The value for which to compute the trigonometric tangent.
out : ht.DNDarray or None, optional
A location in which to store the results. If provided, it must have a broadcastable shape. If not provided
or set to None, a fresh tensor is allocated.
Returns
-------
tangent : ht.DNDarray
A tensor of the same shape as x, containing the trigonometric tangent of each element in this tensor.
Examples
--------
>>> ht.tan(ht.arange(-6, 7, 2))
tensor([ 0.29100619, -1.15782128, 2.18503986, 0., -2.18503986, 1.15782128, -0.29100619])
"""
return local_op(torch.tan, x, out)
def tanh(x, out=None):
"""
Return the hyperbolic tangent, element-wise.
Parameters
----------
x : ht.DNDarray
The value for which to compute the hyperbolic tangent.
out : ht.DNDarray or None, optional
A location in which to store the results. If provided, it must have a broadcastable shape. If not provided
or set to None, a fresh tensor is allocated.
Returns
-------
hyperbolic tangent : ht.DNDarray
A tensor of the same shape as x, containing the hyperbolic tangent of each element in this tensor.
Examples
--------
>>> ht.tanh(ht.arange(-6, 7, 2))
tensor([-1.0000, -0.9993, -0.9640, 0.0000, 0.9640, 0.9993, 1.0000])
"""
return local_op(torch.tanh, x, out)
