class astropy.convolution.Trapezoid1DKernel(width, slope=1.0, **kwargs)[source]#

Bases: Kernel1D

1D trapezoid kernel.

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


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


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.

factornumber, optional

Factor of oversampling. Default factor = 10.


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.xlim(-1, 28)

(png, svg, pdf)