Kernel¶

class
astropy.convolution.
Kernel
(array)[source] [edit on github]¶ Bases:
object
Convolution kernel base class.
Parameters: array :
ndarray
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
Deviation from the normalization to 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
¶ Deviation from the normalization to one.
Methods Documentation

normalize
(mode='integral')[source] [edit on github]¶ 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.
