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Code to generate kernels to move between JWST bands and between a JWST band and an arbitrary Gaussian PSF

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francbelf/jwst_kernels

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jwst_kernels

Make kernels to convolve JWST images taken in one band to the PSF of another, or to a Gaussian PSF of arbitrary FWHM. Implements the Aniano algorithm.

Installation

Install the code as a python package. Note that generating the PSFs on the fly requires the installation of webbpsf (which is not installed automatically).

python setup.py develop

Features

Generates PSFs of the relevant bands using webbpsf seemlessly. Note that this package does not automatically install webbpsf! You need to install it independently Also note that the latest version of webbpsf (v>1.0.0) is only available for python > 3.9.

Uses the Aniano+2011 algorithm to generate appropriate kernels for going between JWST bands and from a JWST band to a Gaussian. Example usage to go between two JWST bands:

from jwst_kernels.make_kernels import make_jwst_cross_kernel

input_filter = {'camera':'MIRI', 'filter':'F770W'}

target_filter = {'camera':'MIRI', 'filter':'F2100W'}

kk = make_jwst_cross_kernel(input_filter, target_filter)

Evaluate the kernels by finding the smallest safe Gaussian

input_filter = {'camera':'NIRCam', 'filter':'F200W'}

out = find_safe_kernel(input_filter, detector_effects=True)

print(out['safe'])

See examples for use of these functions in the example notebook <https://github.com/francbelf/jwst_kernels/blob/master/notebooks/examples.ipynb>

Note

This project has been set up using PyScaffold 4.5. For details and usage information on PyScaffold see https://pyscaffold.org/.

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Code to generate kernels to move between JWST bands and between a JWST band and an arbitrary Gaussian PSF

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