TopHatWindow

class photutils.psf_matching.TopHatWindow(beta)

Bases: SplitCosineBellWindow

Class to define a 2D top hat window function.

This window equals 1.0 inside a circular region defined by beta and drops sharply to 0.0 outside, with no smooth transition. It is also known as a rectangular or boxcar window.

This window preserves the most data (everything inside the cutoff radius is untouched), but the sharp edge creates strong ringing artifacts in Fourier space. Use this only when you need to strictly preserve data within a specific region and can tolerate significant artifacts, or when the sharp cutoff is explicitly desired.

For most PSF matching applications, TukeyWindow is preferred as it provides much better artifact suppression while still preserving a large central region. Use TopHatWindow primarily for masking or when studying the effects of abrupt truncation.

Parameters:

betafloat, optional

The inner diameter as a fraction of the array size beyond which the window drops to zero. Must be between 0.0 and 1.0, inclusive.

Notes

Equivalent to SplitCosineBellWindow(alpha=0.0, beta=beta).

Examples

import matplotlib.pyplot as plt
from photutils.psf_matching import TopHatWindow

taper = TopHatWindow(beta=0.4)
data = taper((101, 101))
fig, ax = plt.subplots()
axim = ax.imshow(data, origin='lower')
fig.colorbar(axim)

(Source code, png, hires.png, pdf, svg)

A 1D cut across the image center:

import matplotlib.pyplot as plt
from photutils.psf_matching import TopHatWindow

taper = TopHatWindow(beta=0.4)
data = taper((101, 101))
fig, ax = plt.subplots()
ax.plot(data[50, :])

(Source code, png, hires.png, pdf, svg)

Methods Summary

__call__(shape)

Generate the window function for the given shape.

Methods Documentation

__call__(shape)

Generate the window function for the given shape.

Parameters:

shapetuple of int

The size of the output array along each axis.

Returns:

result2D ndarray

The window function as a 2D array.