Kernel

class astropy.convolution.Kernel(array)

Bases: object

Convolution kernel base class.

Parameters:

arrayndarray

Kernel array.

Attributes Summary

array	Filter kernel array.
center	Index of the kernel center.
dimension	Kernel dimension.
is_bool	Indicates if kernel is bool.
model	Kernel response model.
separable	Indicates if the filter kernel is separable.
shape	Shape of the kernel array.
truncation	Absolute deviation of the sum of the kernel array values from one.

Methods Summary

normalize([mode])

Normalize the filter kernel.

Attributes Documentation

array

Filter kernel array.

center

Index of the kernel center.

dimension

Kernel dimension.

is_bool

Indicates if kernel is bool.

If the kernel is bool the multiplication in the convolution could be omitted, to increase the performance.

model

Kernel response model.

separable

Indicates if the filter kernel is separable.

A 2D filter is separable, when its filter array can be written as the outer product of two 1D arrays.

If a filter kernel is separable, higher dimension convolutions will be performed by applying the 1D filter array consecutively on every dimension. This is significantly faster, than using a filter array with the same dimension.

shape

Shape of the kernel array.

truncation

Absolute deviation of the sum of the kernel array values from one.

Methods Documentation

normalize(mode='integral')

Normalize the filter kernel.

Parameters:

mode{‘integral’, ‘peak’}

One of the following modes:

• ‘integral’ (default)

  Kernel is normalized such that its integral = 1.

• ‘peak’

  Kernel is normalized such that its peak = 1.