2.1.2.1.1. sf_tools.image.convolve module

CONVOLUTION ROUTINES

This module contains methods for convolution.

Author:Samuel Farrens <samuel.farrens@gmail.com>
Version:1.2
Date:23/10/2017
sf_tools.image.convolve.convolve_np(image, kernel)[source]

Convolve with Numpy FFT

This method convolves the input image with the input kernel

Parameters:
  • image (np.ndarray) – 2D image array
  • kernel (np.ndarray) – 2D kernel array
Returns:
Return type:

np.ndarray 2D convolved image array
sf_tools.image.convolve.deconvolve_np(image, kernel)[source]

Deconvolve with Numpy FFT

This method deconvolves the input image with the input kernel

Parameters:
  • image (np.ndarray) – 2D image array
  • kernel (np.ndarray) – 2D kernel array
Returns:
Return type:

np.ndarray 2D deconvolved image array
sf_tools.image.convolve.convolve(data, kernel, method='astropy')[source]

Convolve data with kernel

This method convolves the input data with a given kernel using FFT and is the default convolution used for all routines

Parameters:
  • data (np.ndarray) – Input data array, normally a 2D image
  • kernel (np.ndarray) – Input kernel array, normally a 2D kernel
  • method (str {'astropy', 'scipy'}, optional) –

    Convolution method (default is ‘astropy’)

    ’astropy’:
    Uses the astropy.convolution.convolve_fft method provided in Astropy (http://www.astropy.org/)
    ’scipy’:
    Uses the scipy.signal.fftconvolve method provided in SciPy (https://www.scipy.org/)
Returns:
Return type:

np.ndarray convolved data
Raises:
  • ValueError – If data and kernel do not have the same number of dimensions
  • ValueError – If method is not ‘astropy’ or ‘scipy’
sf_tools.image.convolve.convolve_stack(data, kernel, rot_kernel=False, method='astropy')[source]

Convolve stack of data with stack of kernels

This method convolves the input data with a given kernel using FFT and is the default convolution used for all routines

Parameters:
  • data (np.ndarray) – Input data array, normally a 2D image
  • kernel (np.ndarray) – Input kernel array, normally a 2D kernel
  • rot_kernel (bool) – Option to rotate kernels by 180 degrees
  • method (str {'astropy', 'scipy'}, optional) – Convolution method (default is ‘astropy’)
Returns:
Return type:

np.ndarray convolved data
sf_tools.image.convolve.psf_convolve(data, psf, psf_rot=False, psf_type='fixed', method='astropy')[source]

Convolve data with PSF

This method convolves an image with a PSF

Parameters:
  • data (np.ndarray) – Input data array, normally an array of 2D images
  • psf (np.ndarray) – Input PSF array, normally either a single 2D PSF or an array of 2D PSFs
  • psf_rot (bool) – Option to rotate PSF by 180 degrees
  • psf_type (str {'fixed', 'obj_var'}, optional) – PSF type (default is ‘fixed’)
  • method (str {'astropy', 'scipy'}, optional) –

    Convolution method (default is ‘astropy’)

    ’fixed’:
    The PSF is fixed, i.e. it is the same for each image
    ’obj_var’:
    The PSF is object variant, i.e. it is different for each image
Returns:
Return type:

np.ndarray convolved data
Raises:

ValueError – If psf_type is not ‘fixed’ or ‘obj_var’
sf_tools.image.convolve.pseudo_inverse(image, kernel, weight=None)[source]

Pseudo inverse

This method calculates the pseudo inverse of the input image for the given kernel using FFT

Parameters:
  • image (np.ndarray) – Input image, 2D array
  • kernel (np.ndarray) – Input kernel, 2D array
  • weight (np.ndarray, optional) – Optional weights, 2D array
Returns:
Return type:

np.ndarray result of the pseudo inverse