47 lines
1.4 KiB
Python
47 lines
1.4 KiB
Python
import numpy as np
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from thunderhopper.filetools import search_files
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from thunderhopper.modeltools import load_data, save_data
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from misc_functions import sort_files_by_rec
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from IPython import embed
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# GENERAL SETTINGS:
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target_species = [
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'Chorthippus_biguttulus',
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'Chorthippus_mollis',
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'Chrysochraon_dispar',
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'Euchorthippus_declivus',
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'Gomphocerippus_rufus',
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'Omocestus_rufipes',
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'Pseudochorthippus_parallelus',
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]
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search_path = '../data/inv/log_hp/'
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save_path = '../data/inv/log_hp/collected/'
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# EXECUTION:
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for i, species in enumerate(target_species):
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print(f'Processing {species}')
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# Fetch all species-specific song files:
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all_paths = search_files(species, incl='noise', ext='npz', dir=search_path)
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# Run through files:
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for j, path in enumerate(all_paths):
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# Load invariance data:
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data, config = load_data(path, ['scales', 'measure_inv'])
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scales, measure = data['scales'], data['measure_inv']
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if j == 0:
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# Prepare species-specific storage:
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spec_data = np.zeros((measure.shape + (len(all_paths),)), dtype=float)
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# Log file data:
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spec_data[..., j] = measure
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# Save collected file data:
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save_name = save_path + species
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archive = dict(scales=scales, measure_inv=spec_data)
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save_data(save_name, archive, config, overwrite=True)
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print('Done.')
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