Added script to generate scaled images and movie

environment.yml

@@ -19,5 +19,6 @@ dependencies:
   - h5netcdf=1.1.0
   - bottleneck=1.3.7
   - pillow-jpls=1.2.0
+  - imageio-ffmpeg=2.19.3
 
 prefix: ~/anaconda3

requirements.txt

@@ -11,4 +11,5 @@ xarray==2022.6.0
 netCDF4==1.6.0
 h5netcdf==1.1.0
 bottleneck==1.3.7
-pillow-jpls==1.2.0
+pillow-jpls==1.2.0
+imageio-ffmpeg==2.19.3

suncet_instrument_simulator/make_movie.py

@@ -0,0 +1,58 @@
+import matplotlib.pyplot as plt
+import numpy as np
+from astropy.io import fits
+import os
+from glob import glob
+import imageio
+
+def apply_radial_filter(data, sigma):
+    # Determine the center of the image
+    xc, yc = data.shape[1] / 2, data.shape[0] / 2
+
+    # Create a radial distance array
+    Y, X = np.ogrid[:data.shape[0], :data.shape[1]]
+    r = np.sqrt((X - xc)**2 + (Y - yc)**2)
+
+    # Define a radial filter function, e.g., a Gaussian
+    # Adjust sigma to control the spread of the Gaussian
+    radial_filter = np.exp(-(r**2 / (2. * sigma**2)))
+
+    # Apply the filter
+    filtered_data = data * radial_filter
+
+    return filtered_data
+
+
+def plot_scaled_image(data, title, output_filename, scale=None):
+    plt.figure(figsize=(24, 24))
+    scale_funcs = {
+        'log': lambda x: np.log10(np.clip(x, 0.1, None)),
+        'sqrt': np.sqrt,
+        '1/4': lambda x: x**(1/4),
+        '1/8': lambda x: np.clip(x**(1/8), 0.5, None),
+    }
+    scale_func = scale_funcs.get(scale, lambda x: x)  # Default to no scaling if not found
+
+    plt.imshow(scale_func(data), cmap='inferno')
+    plt.axis('off')
+    plt.savefig(output_filename, bbox_inches='tight', pad_inches=0)
+    plt.close()
+
+path = os.getenv('suncet_data') + '/synthetic/level0_raw/fits/'
+filenames = 'config_default_OBS_2023-02-14T17:00:00.000_*.fits'
+fits_files = sorted(glob(path + filenames))
+image_files = []
+
+for file in fits_files:
+    with fits.open(file) as hdul:
+        data = hdul[0].data
+        filtered_data = apply_radial_filter(data, 300)
+
+    output_filename = os.getenv('suncet_data')+ '/synthetic/images and movies/' + f"{file.split('.')[1]}.png"
+    plot_scaled_image(filtered_data, '', output_filename, scale='1/4')
+    image_files.append(output_filename)
+
+with imageio.get_writer(os.getenv('suncet_data')+ '/synthetic/images and movies/movie.mp4', fps=10) as writer:
+    for filename in image_files:
+        image = imageio.imread(filename)
+        writer.append_data(image)