tensorplay.signal.windows.cosine

tensorplay.signal.windows.cosine(M: int, *, sym: bool = True, dtype: dtype | None = None, layout: Layout = tensorplay.strided, device: device | None = None, requires_grad: bool = False) → Tensor[source]

Computes a window with a simple cosine waveform, also known as the sine window.

The samples follow

$$w_n = \sin\left(\frac{\pi (n + 0.5)}{M}\right)$$

The 0.5 in the numerator shifts the sample positions by half a step, so the window starts and ends at non-zero values (for a symmetric window the first and last samples equal sin(pi / (2M))).

The window is scaled so that its largest value is 1. The value 1 itself does not occur when M is even and sym is True.

Parameters:

M (int) – number of points of the returned window.

Keyword Arguments:

• sym (bool, optional) – if False, returns a periodic window, which is the usual choice for spectral analysis. If True, returns a symmetric window, which is the usual choice for filter design. Default: True.

• dtype (tensorplay.dtype, optional) – the desired data type of the returned tensor. Default: if None, uses the global default (see tensorplay.set_default_dtype()).

• layout (tensorplay.Layout, optional) – the desired layout of the returned tensor. Default: tensorplay.strided.

• device (tensorplay.device, optional) – the desired device of the returned tensor. Default: if None, uses the current default tensor device (see tensorplay.set_default_device()).

• requires_grad (bool, optional) – whether autograd should record operations on the returned tensor. Default: False.

Examples:

>>> # Symmetric cosine window.
>>> tensorplay.signal.windows.cosine(10)
tensor([0.1564, 0.454, 0.7071, 0.891, 0.9877, 0.9877, 0.891, 0.7071, 0.454, 0.1564])

>>> # Periodic cosine window.
>>> tensorplay.signal.windows.cosine(10, sym=False)
tensor([0.1423, 0.4154, 0.6549, 0.8413, 0.9595, 1., 0.9595, 0.8413, 0.6549, 0.4154])