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- Convolution and filtering (`astropy.convolution`) »
- TrapezoidDisk2DKernel

# TrapezoidDisk2DKernel

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

  Bases: `astropy.convolution.Kernel2D`

  2D trapezoid kernel.

  Parameters:

  radius : number

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

  slope : number

  > Slope of the filter kernel’s tails

  mode : str, 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.

  factor : number, optional

  > Factor of oversampling. Default factor = 10.

  See also

  `Gaussian2DKernel`, `Box2DKernel`, `Tophat2DKernel`, `MexicanHat2DKernel`, `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()

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