48 lines
1.6 KiB
Python
48 lines
1.6 KiB
Python
# from email_test import *
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from cont_modules import *
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start = time.perf_counter()
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# write cleaned and prepped api report (general collection) to csv with identifier
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# csv_wrapper = read_api_to_wrapper()
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# write_csv_from_list(construct_ID('api_out', 'ALL'), csv_wrapper)
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# loads in test and training data, splits them by collection to feed into algorithm
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A = time.perf_counter() - start
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print('A: ' + str(A))
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training_wrapper = read_csv_to_list_wrapper('./data/training_data/training_ALL_api_out.csv')
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B = time.perf_counter() - A
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print('B: ' + str(B))
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test_wrapper = read_csv_to_list_wrapper('./2020-08-18_ALL_api_out.csv')
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# test_wrapper = read_api_to_wrapper()
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# too slow for now
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C = time.perf_counter() - B
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print('C: ' + str(C))
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training_collections = split_collection(training_wrapper)
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D = time.perf_counter() - C
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print('D: ' + str(D))
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test_collections = split_collection(test_wrapper)
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E = time.perf_counter() - D
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print('E: ' + str(E))
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# run algorithm on split dataset
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# for collection_code in training_collections:
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# run_algorithm(collection_code, test_collections[collection_code], training_collections[collection_code])
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# # sends human readable data to email
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# sendmail('data/predictions/%s' % construct_ID('predictions', collection_code))
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collection_code = 'B_PHILPSYR'
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run_algorithm(collection_code, test_collections[collection_code], training_collections[collection_code])
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F = time.perf_counter() - E
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print('F: ' + str(F))
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print('*****')
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print('total: ' + str(F+E+D+C+B+A))
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# sends human readable data to email
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# sendmail('data/predictions/%s' % construct_ID('predictions', collection_code))
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