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# Tophat2DKernel

class astropy.convolution.Tophat2DKernel(radius, **kwargs)

  Bases: `Kernel2D`

  2D Tophat filter kernel.

  The Tophat filter is an isotropic smoothing filter. It can produce artifacts when applied repeatedly on the same data.

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

  Parameters:
    radius `python:int`

      Radius of the filter kernel.

    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.

    factor number, optional

      Factor of oversampling. Default factor = 10.

  See also

  `Gaussian2DKernel`, `Box2DKernel`, `RickerWavelet2DKernel`, `Ring2DKernel`
  `TrapezoidDisk2DKernel`, `AiryDisk2DKernel`, `Moffat2DKernel`

  Examples

  Kernel response:

  >     import matplotlib.pyplot as plt
  >     from astropy.convolution import Tophat2DKernel
  >     tophat_2D_kernel = Tophat2DKernel(40)
  >     plt.imshow(tophat_2D_kernel, interpolation='none', origin='lower')
  >     plt.xlabel('x [pixels]')
  >     plt.ylabel('y [pixels]')
  >     plt.colorbar()
  >     plt.show()

  > (`png`, `svg`, `pdf`)