# Copyright 2022 Huawei Technologies Co., Ltd
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# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
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# http://www.apache.org/licenses/LICENSE-2.0
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# ============================================================================
"""Defines spectral operators with functional form."""
from mindspore.ops import operations as P
from mindspore.common import dtype as mstype
from .._primitive_cache import _get_cache_prim
[docs]def blackman_window(window_length, periodic=True, *, dtype=None):
r"""
Blackman window function, usually used to extract finite signal segment for FFT.
The `window_length` is a input tensor which determines the returned window size, and its data should be
an integer. In particular, if `window_length` is equal to `1`, only a single value `1` exists in the
returned window.
Attr `periodic` determines whether the returned window removes the last duplicate value
from the symmetric window and prepares to be a periodic window with functions.
Therefore, if attr `periodic` is true, the :math:`N` in formula is :math:`window\_length + 1`.
.. math::
w[n] = 0.42 - 0.5 cos(\frac{2\pi n}{N - 1}) + 0.08 cos(\frac{4\pi n}{N - 1})
where :math:`N` is the full window size, and n is natural number less than :math:`N` :[0, 1, ..., N-1].
Args:
window_length (Tensor): The size of returned window, with data type int32, int64.
The input data should be an integer with a value of [0, 1000000].
periodic (bool, optional): Indicates whether to returns a window to be used as periodic function or
a symmetric window. Default: ``True`` .
Keyword Args:
dtype (mindspore.dtype, optional): The data type of returned tensor.
Only float16, float32 and float64 is allowed. Default: ``None`` .
Returns:
A 1-D tensor of size `window_length` containing the window. Its datatype is set by the attr `dtype`.
If 'dtype' is None, output datatype is float32.
Raises:
TypeError: If `window_length` is not a Tensor.
TypeError: If `periodic` is not a bool.
TypeError: If `dtype` is not one of: float16, float32, float64.
TypeError: If the type of `window_length` is not one of: int32, int64.
ValueError: If the value range of `window_length` is not [0, 1000000].
ValueError: If the dimension of `window_length` is not 0.
Supported Platforms:
``Ascend`` ``GPU`` ``CPU``
Examples:
>>> import mindspore
>>> from mindspore import Tensor, ops
>>> window_length = Tensor(10, mindspore.int32)
>>> output = ops.blackman_window(window_length, periodic=True, dtype=mindspore.float32)
>>> print(output)
[-2.9802322e-08 4.0212840e-02 2.0077014e-01 5.0978714e-01
8.4922993e-01 1.0000000e+00 8.4922981e-01 5.0978690e-01
2.0077008e-01 4.0212870e-02]
"""
if dtype is None:
dtype = mstype.float32
blackman_window_op = _get_cache_prim(P.BlackmanWindow)(periodic, dtype)
return blackman_window_op(window_length)
[docs]def bartlett_window(window_length, periodic=True, *, dtype=None):
r"""
Bartlett window function is a triangular-shaped weighting function used for smoothing or frequency analysis of
signals in digital signal processing.
The `window_length` is a input tensor which determines the returned window size, and its data should be
an integer. In particular, if `window_length` is equal to `1`, only a single value 1 exists in the
returned window.
Attr `periodic` determines whether the returned window removes the last duplicate value from the symmetric
window and prepares to be a periodic window with functions. Therefore, if attr `periodic` is true,
the :math:`N` in formula is :math:`window\_length + 1`.
.. math::
w[n] = 1 - \left| \frac{2n}{N-1} - 1 \right| = \begin{cases}
\frac{2n}{N - 1} & \text{if } 0 \leq n \leq \frac{N - 1}{2} \\
2 - \frac{2n}{N - 1} & \text{if } \frac{N - 1}{2} < n < N \\
\end{cases},
where N is the full window size.
Args:
window_length (Tensor): The size of returned window, with data type int32, int64.
The input data should be an integer with a value of [0, 1000000].
periodic (bool, optional): Indicates whether to returns a window to be used as periodic function or
a symmetric window. Default: ``True`` .
Keyword Args:
dtype (mindspore.dtype, optional): The datatype of returned tensor.
Only float16, float32 and float64 are allowed. Default: ``None`` .
Returns:
A 1-D tensor of size `window_length` containing the window. Its datatype is set by the attr `dtype`.
If `dtype` is None, output datatype is float32.
Raises:
TypeError: If `window_length` is not a Tensor.
TypeError: If the type of `window_length` is not one of: int32, int64.
TypeError: If `periodic` is not a bool.
TypeError: If `dtype` is not one of: float16, float32, float64.
ValueError: If the value range of `window_length` is not [0, 1000000].
ValueError: If the dimension of `window_length` is not 0.
Supported Platforms:
``Ascend`` ``GPU`` ``CPU``
Examples:
>>> from mindspore import Tensor, ops
>>> from mindspore import dtype as mstype
>>> window_length = Tensor(5, mstype.int32)
>>> output = ops.bartlett_window(window_length, periodic=True, dtype=mstype.float32)
>>> print(output)
[0. 0.4 0.8 0.8 0.4]
"""
if dtype is None:
dtype = mstype.float32
bartlett_window_op = _get_cache_prim(P.BartlettWindow)(periodic, dtype)
return bartlett_window_op(window_length)
__all__ = [
'blackman_window',
'bartlett_window',
]
__all__.sort()