Mercurial > repos > bgruening > sklearn_svm_classifier
comparison svm.xml @ 15:2df8f5c30edc draft
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
| author | bgruening |
|---|---|
| date | Mon, 16 Dec 2019 05:21:05 -0500 |
| parents | 153f237ddb36 |
| children | d67dcd63f6cb |
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| 14:da0a22cdcce7 | 15:2df8f5c30edc |
|---|---|
| 29 params = json.load(param_handler) | 29 params = json.load(param_handler) |
| 30 | 30 |
| 31 #if $selected_tasks.selected_task == "load": | 31 #if $selected_tasks.selected_task == "load": |
| 32 | 32 |
| 33 header = 'infer' if params["selected_tasks"]["header"] else None | 33 header = 'infer' if params["selected_tasks"]["header"] else None |
| 34 data = pandas.read_csv("$selected_tasks.infile_data", sep='\t', header=header, index_col=None, parse_dates=True, encoding=None, tupleize_cols=False) | 34 data = pandas.read_csv("$selected_tasks.infile_data", sep='\t', header=header, index_col=None, parse_dates=True, encoding=None) |
| 35 | 35 |
| 36 with open("$infile_model", 'rb') as model_handler: | 36 with open("$infile_model", 'rb') as model_handler: |
| 37 classifier_object = load_model(model_handler) | 37 classifier_object = load_model(model_handler) |
| 38 | 38 |
| 39 prediction = classifier_object.predict(data) | 39 prediction = classifier_object.predict(data) |