Simple Shaun Example

A simple example showing how to apply Shaun to correct for atmospheric seeing in a region of an SST/CRISP image.

import matplotlib.pyplot as plt
import numpy as np
from crispy import CRISP
from smug.shaun_inference import pretrained_shaun_corrector

Load data, rotate it to fill the frame, and select sub-region to work on.

data = CRISP("crisp_l2_20140906_152724_6563_r00447_3wavelengths.fits")
data.rotate_crop()

crisp_sub_region = data[:, 200:500, 200:500]

/opt/hostedtoolcache/Python/3.9.13/x64/lib/python3.9/site-packages/astropy/wcs/wcs.py:725: FITSFixedWarning: 'datfix' made the change 'Set MJD-AVG to 56906.703926 from DATE-AVG'.
  warnings.warn(
/opt/hostedtoolcache/Python/3.9.13/x64/lib/python3.9/site-packages/astropy/io/fits/card.py:264: VerifyWarning: Keyword name 'frame_dims' is greater than 8 characters or contains characters not allowed by the FITS standard; a HIERARCH card will be created.
  warnings.warn(
/opt/hostedtoolcache/Python/3.9.13/x64/lib/python3.9/site-packages/astropy/wcs/wcs.py:725: FITSFixedWarning: 'datfix' made the change 'Set MJD-AVG to 56906.703926 from DATE-AVG'.
  warnings.warn(

Construct Shaun model and apply to image.

corrector = pretrained_shaun_corrector("Halpha")
shaun_im = corrector.correct_image(crisp_sub_region.data)

Downloading: "https://www.astro.gla.ac.uk/users/USER-MANAGED/solar_model_weights/Shaun_Halpha_1.0.0.pth.tar" to /home/runner/.cache/torch/hub/checkpoints/Shaun_Halpha_1.0.0.pth.tar

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loading Shaun model
=> model loaded.

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Segmenting image cube: 100%|##########| 3/3 [00:00<00:00, 1402.31it/s]

Compare line-core corrected image to one with original atmospheric seeing.

fig, ax = plt.subplots(1, 2)
ax[0].imshow(crisp_sub_region[1].data, cmap="Greys_r")
ax[0].set_title("Original Data")
ax[1].imshow(shaun_im[1], cmap="Greys_r")
ax[1].set_title("Shaun Corrected")

Text(0.5, 1.0, 'Shaun Corrected')