TrapezoidDisk2DKernel

class astropy.convolution.TrapezoidDisk2DKernel(radius, slope=1.0, **kwargs)

Bases: Kernel2D

2D trapezoid kernel.

The generated kernel is normalized so that it integrates to 1.

Parameters:

radiusnumber

Width of the filter kernel, defined as the width of the constant part, before it begins to slope down.

slopenumber

Slope of the filter kernel’s tails

mode{‘center’, ‘linear_interp’, ‘oversample’, ‘integrate’}, optional

One of the following discretization modes:

• ‘center’ (default)

  Discretize model by taking the value at the center of the bin.

• ‘linear_interp’

  Discretize model by performing a bilinear interpolation between the values at the corners of the bin.

• ‘oversample’

  Discretize model by taking the average on an oversampled grid.

• ‘integrate’

  Discretize model by integrating the model over the bin.

factornumber, optional

Factor of oversampling. Default factor = 10.

See also

Gaussian2DKernel, Box2DKernel, Tophat2DKernel, RickerWavelet2DKernel

Ring2DKernel, AiryDisk2DKernel, Moffat2DKernel

Examples

Kernel response:

import matplotlib.pyplot as plt
from astropy.convolution import TrapezoidDisk2DKernel
trapezoid_2D_kernel = TrapezoidDisk2DKernel(20, slope=0.2)
plt.imshow(trapezoid_2D_kernel, interpolation='none', origin='lower')
plt.xlabel('x [pixels]')
plt.ylabel('y [pixels]')
plt.colorbar()
plt.show()

(png, svg, pdf)