TrapezoidDisk2DKernel

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

Bases: astropy.convolution.Kernel2D

2D trapezoid kernel.

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

modestr, 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()

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