33 lines
1.3 KiB
Python
33 lines
1.3 KiB
Python
from nuwavdet import nuwavdet as nw
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INPUT_FOLDER = r'path_to_directory'
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OUTPUT_FOLDER = r'.//Output'
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if __name__ == '__main__':
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# BEGIN PROCESSING ALL THE OBSERVATIONS INSIDE THE FOLDER
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nw.process_folder(input_folder=INPUT_FOLDER,
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start_new_file='y',
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fits_folder=OUTPUT_FOLDER,
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thresh=(3, 2),
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cpu_num=10
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)
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# IF THE PROCESSING WAS INTERRUPTED YOU CAN CONTINUE IT WITH THE SAME CODE
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# BY CHANGING THE start_new_file TO 'n'.
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# THE STRUCTURE OF THE FOLDER IS
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# OUTPUT_FOLDER
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# __overview.csv csv-table with observations metadata
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# __overvies.fits fits-table with the same metadata
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# __overview_skipped.csv csv-table with the skipped observations
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# __Region folder for region mask images
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# ____<obsid><DET>_region.fits
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# __Region_raw folder for region masks in RAW coordinates
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# ____<obsid><DET>_reg_raw.fits
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# __Wav_sum folder for sum of wavelet layers
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# ____<obsid><DET>_wav_sum.fits
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# Note nw.process_folder uses multiprocessing with cpu_num cores.
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# The number of cores can be manually chosen or automatically
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# detected if cpu_num = 0. |