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# Trapezoid1DKernel

class astropy.convolution.Trapezoid1DKernel(width, slope=1.0, **kwargs)

  Bases: `Kernel1D`

  1D trapezoid kernel.

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

  Parameters:
    width 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{‘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 linearly interpolating 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

  `Box1DKernel`, `Gaussian1DKernel`, `RickerWavelet1DKernel`

  Examples

  Kernel response:

  >     import matplotlib.pyplot as plt
  >     from astropy.convolution import Trapezoid1DKernel
  >     trapezoid_1D_kernel = Trapezoid1DKernel(17, slope=0.2)
  >     plt.plot(trapezoid_1D_kernel, drawstyle='steps')
  >     plt.xlabel('x [pixels]')
  >     plt.ylabel('amplitude')
  >     plt.xlim(-1, 28)
  >     plt.show()

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