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47 lines
1.6 KiB
47 lines
1.6 KiB
# 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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