`skimage.filters._window:window`

source: /dev/scikit-image/src/skimage/filters/_window.py :10

Signature

def window ( window_type , shape , warp_kwargs = None )

Summary

Return an n-dimensional window of a given size and dimensionality.

Parameters

window_type : str or float or tuple: The type of window to be created. Any window type supported by scipy.signal.get_window is allowed here. See notes below for a current list, or the SciPy documentation for the version of SciPy on your machine.
shape : int or tuple of (int, ...): The shape of the window along each axis. If an integer is provided, a 1D window is generated.
warp_kwargs : dict of {str: Any}: Keyword arguments passed to skimage.transform.warp (e.g., warp_kwargs={'order':3} to change interpolation method).

Returns

nd_window : ndarray: A window of the specified shape. dtype is np.float64.

Notes

This function is based on scipy.signal.get_window and thus can access all of the window types available to that function (e.g., "hann", "boxcar"). Note that certain window types require parameters that have to be supplied with the window name as a tuple (e.g., ("tukey", 0.8)). If only a float is supplied, it is interpreted as the beta parameter of the Kaiser window.

See https://docs.scipy.org/doc/scipy/reference/generated/scipy.signal.windows.get_window.html for more details.

Note that this function generates a double precision array of the specified shape and can thus generate very large arrays that consume a large amount of available memory.

The approach taken here to create nD windows is to first calculate the Euclidean distance from the center of the intended nD window to each position in the array. That distance is used to sample, with interpolation, from a 1D window returned from scipy.signal.get_window. The method of interpolation can be changed with the order keyword argument passed to skimage.transform.warp.

Some coordinates in the output window will be outside of the original signal; these will be filled in with zeros.

Window types: - boxcar - triang - blackman - hamming - hann - bartlett - flattop - parzen - bohman - blackmanharris - nuttall - barthann - kaiser (needs beta) - gaussian (needs standard deviation) - general_gaussian (needs power, width) - slepian (needs width) - dpss (needs normalized half-bandwidth) - chebwin (needs attenuation) - exponential (needs decay scale) - tukey (needs taper fraction)

Examples

Return a Hann window with shape (512, 512):

from skimage.filters import window
w = window('hann', (512, 512))

✓

Return a Kaiser window with beta parameter of 16 and shape (256, 256, 35):

w = window(16, (256, 256, 35))

✓

Return a Tukey window with an alpha parameter of 0.8 and shape (100, 300):

w = window(('tukey', 0.8), (100, 300))

✓

Aliases

skimage.filters.window