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:

widthnumber

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

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.

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)