Mercurial > repos > bgruening > sklearn_generalized_linear
comparison generalized_linear.xml @ 14:10a8543142fc draft
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 7c2fd140e89605fe689c39e21d70a400545e38cf
author | bgruening |
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date | Tue, 10 Jul 2018 03:13:00 -0400 |
parents | cf635edf37d2 |
children | f0e215cbade3 |
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13:cf635edf37d2 | 14:10a8543142fc |
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42 | 42 |
43 #else: | 43 #else: |
44 classifier_object = pickle.load(open("$selected_tasks.infile_model", 'r')) | 44 classifier_object = pickle.load(open("$selected_tasks.infile_model", 'r')) |
45 data = pandas.read_csv("$selected_tasks.infile_data", sep='\t', header=None, index_col=None, parse_dates=True, encoding=None, tupleize_cols=False ) | 45 data = pandas.read_csv("$selected_tasks.infile_data", sep='\t', header=None, index_col=None, parse_dates=True, encoding=None, tupleize_cols=False ) |
46 prediction = classifier_object.predict(data) | 46 prediction = classifier_object.predict(data) |
47 prediction_df = pandas.DataFrame(prediction) | 47 prediction_df = pandas.DataFrame(prediction, columns=["predicted"]) |
48 res = pandas.concat([data, prediction_df], axis=1) | 48 res = pandas.concat([data, prediction_df], axis=1) |
49 res.to_csv(path_or_buf = "$outfile_predict", sep="\t", index=False, header=None) | 49 res.to_csv(path_or_buf = "$outfile_predict", sep="\t", index=False, header=None) |
50 #end if | 50 #end if |
51 | 51 |
52 ]]> | 52 ]]> |