57 lines
1.7 KiB
Python
57 lines
1.7 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 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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stages = ['filt', 'env', 'log', 'inv', 'conv', 'feat']
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search_path = '../data/inv/full/'
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save_path = '../data/inv/full/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, ext='npz', dir=search_path)
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if not all_paths:
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continue
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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', 'thresh'])
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if j == 0:
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# Prepare species-specific storage:
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species_data = dict(
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scales=data['scales'],
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thresh_rel=data['thresh_rel'],
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thresh_abs=data['thresh_abs']
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)
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for stage in stages:
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mkey = f'measure_{stage}'
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shape = data[mkey].shape + (len(all_paths),)
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species_data[mkey] = np.zeros(shape, dtype=float)
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# Log species data:
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for stage in stages:
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mkey = f'measure_{stage}'
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species_data[mkey][..., j] = data[mkey]
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# Save collected file data:
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save_name = save_path + species
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save_data(save_name, species_data, config, overwrite=True)
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print('Done.')
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