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torch.signal.windows.blackman
torch.signal.windows.blackman(M, *, sym=True, dtype=None, layout=torch.strided, device=None, requires_grad=False)
[source]-
Computes the Blackman window.
The Blackman window is defined as follows:
The window is normalized to 1 (maximum value is 1). However, the 1 doesn’t appear if
M
is even andsym
isTrue
.- Parameters
-
M (int) – the length of the window. In other words, the number of points of the returned window.
- Keyword Arguments
-
- sym (bool, optional) – If
False
, returns a periodic window suitable for use in spectral analysis. IfTrue
, returns a symmetric window suitable for use in filter design. Default:True
. - dtype (
torch.dtype
, optional) – the desired data type of returned tensor. Default: ifNone
, uses a global default (seetorch.set_default_tensor_type()
). - layout (
torch.layout
, optional) – the desired layout of returned Tensor. Default:torch.strided
. - device (
torch.device
, optional) – the desired device of returned tensor. Default: ifNone
, uses the current device for the default tensor type (seetorch.set_default_tensor_type()
).device
will be the CPU for CPU tensor types and the current CUDA device for CUDA tensor types. - requires_grad (bool, optional) – If autograd should record operations on the returned tensor. Default:
False
.
- sym (bool, optional) – If
- Return type
Examples:
>>> # Generates a symmetric Blackman window. >>> torch.signal.windows.blackman(5) tensor([-1.4901e-08, 3.4000e-01, 1.0000e+00, 3.4000e-01, -1.4901e-08]) >>> # Generates a periodic Blackman window. >>> torch.signal.windows.blackman(5, sym=False) tensor([-1.4901e-08, 2.0077e-01, 8.4923e-01, 8.4923e-01, 2.0077e-01])
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https://pytorch.org/docs/2.1/generated/torch.signal.windows.blackman.html