dpnp.blackman¶

dpnp.blackman(M, *, device=None, usm_type=None, sycl_queue=None)[source]¶

Return the Blackman window.

The Blackman window is a taper formed by using the first three terms of a summation of cosines. It was designed to have close to the minimal leakage possible. It is close to optimal, only slightly worse than a Kaiser window.

For full documentation refer to numpy.blackman.

Parameters:

Mint

Number of points in the output window. If zero or less, an empty array is returned.

device{None, string, SyclDevice, SyclQueue, Device}, optional

An array API concept of device where the output array is created. device can be None, a oneAPI filter selector string, an instance of dpctl.SyclDevice corresponding to a non-partitioned SYCL device, an instance of dpctl.SyclQueue, or a dpnp.tensor.Device object returned by dpnp.ndarray.device.

Default: None.

usm_type{None, "device", "shared", "host"}, optional

The type of SYCL USM allocation for the output array.

Default: None.

sycl_queue{None, SyclQueue}, optional

A SYCL queue to use for output array allocation and copying. The sycl_queue can be passed as None (the default), which means to get the SYCL queue from device keyword if present or to use a default queue.

Default: None.

Returns:

outdpnp.ndarray of shape (M,): The window, with the maximum value normalized to one (the value one appears only if the number of samples is odd).

See also

dpnp.bartlett: Return the Bartlett window.
dpnp.hamming: Return the Hamming window.
dpnp.hanning: Return the Hanning window.
dpnp.kaiser: Return the Kaiser window.

Notes

The Blackman window is defined as

\[w(n) = 0.42 - 0.5\cos\left(\frac{2\pi{n}}{M-1}\right) + 0.08\cos\left(\frac{4\pi{n}}{M-1}\right) \qquad 0 \leq n \leq M-1\]

Examples

>>> import dpnp as np
>>> np.blackman(12)
array([-1.38777878e-17,  3.26064346e-02,  1.59903635e-01,  4.14397981e-01,
        7.36045180e-01,  9.67046769e-01,  9.67046769e-01,  7.36045180e-01,
        4.14397981e-01,  1.59903635e-01,  3.26064346e-02, -1.38777878e-17])

Creating the output array on a different device or with a specified usm_type:

>>> x = np.blackman(3) # default case
>>> x, x.device, x.usm_type
(array([-1.38777878e-17,  1.00000000e+00, -1.38777878e-17]),
 Device(level_zero:gpu:0),
 'device')

>>> y = np.blackman(3, device="cpu")
>>> y, y.device, y.usm_type
(array([-1.38777878e-17,  1.00000000e+00, -1.38777878e-17]),
 Device(opencl:cpu:0),
 'device')

>>> z = np.blackman(3, usm_type="host")
>>> z, z.device, z.usm_type
(array([-1.38777878e-17,  1.00000000e+00, -1.38777878e-17]),
 Device(level_zero:gpu:0),
 'host')