Mercurial > repos > bgruening > sklearn_nn_classifier
comparison nn_classifier.xml @ 17:699024d5c451 draft
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
author | bgruening |
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date | Mon, 16 Dec 2019 05:31:46 -0500 |
parents | d0efc68a3ddb |
children | 1d3447c2203c |
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16:55c7d3e58eae | 17:699024d5c451 |
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32 | 32 |
33 with open("$infile_model", 'rb') as model_handler: | 33 with open("$infile_model", 'rb') as model_handler: |
34 classifier_object = load_model(model_handler) | 34 classifier_object = load_model(model_handler) |
35 | 35 |
36 header = 'infer' if params["selected_tasks"]["header"] else None | 36 header = 'infer' if params["selected_tasks"]["header"] else None |
37 data = pandas.read_csv("$selected_tasks.infile_data", sep='\t', header=header, index_col=None, parse_dates=True, encoding=None, tupleize_cols=False) | 37 data = pandas.read_csv("$selected_tasks.infile_data", sep='\t', header=header, index_col=None, parse_dates=True, encoding=None) |
38 prediction = classifier_object.predict(data) | 38 prediction = classifier_object.predict(data) |
39 prediction_df = pandas.DataFrame(prediction) | 39 prediction_df = pandas.DataFrame(prediction) |
40 res = pandas.concat([data, prediction_df], axis=1) | 40 res = pandas.concat([data, prediction_df], axis=1) |
41 res.to_csv(path_or_buf = "$outfile_predict", sep="\t", index=False) | 41 res.to_csv(path_or_buf = "$outfile_predict", sep="\t", index=False) |
42 | 42 |