# HG changeset patch # User bgruening # Date 1531468456 14400 # Node ID eaccbf2c28915ee0470509ee2ff23daee5ce4efb # Parent 973ffe8fe4f1eddf3f5006c0575e6205a32c8432 planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit f54ff2ba2f8e7542d68966ce5a6b17d7f624ac48 diff -r 973ffe8fe4f1 -r eaccbf2c2891 main_macros.xml --- a/main_macros.xml Tue Jul 10 03:10:31 2018 -0400 +++ b/main_macros.xml Fri Jul 13 03:54:16 2018 -0400 @@ -35,7 +35,8 @@ if not options['threshold'] or options['threshold'] == 'None': options['threshold'] = None if 'extra_estimator' in inputs and inputs['extra_estimator']['has_estimator'] == 'no_load': - fitted_estimator = pickle.load(open("inputs['extra_estimator']['fitted_estimator']", 'r')) + with open("inputs['extra_estimator']['fitted_estimator']", 'rb') as model_handler: + fitted_estimator = pickle.load(model_handler) new_selector = selector(fitted_estimator, prefit=True, **options) else: estimator=inputs["estimator"] @@ -83,7 +84,7 @@ parse_dates=True ) else: - X = mmread(open(file1, 'r')) + X = mmread(file1) header = 'infer' if params["selected_tasks"]["selected_algorithms"]["input_options"]["header2"] else None column_option = params["selected_tasks"]["selected_algorithms"]["input_options"]["column_selector_options_2"]["selected_column_selector_option2"] @@ -432,19 +433,6 @@ - - - - - - - - - - - - - @@ -472,13 +460,13 @@ - + - + @@ -553,11 +541,6 @@ - - - - -
@@ -822,9 +805,17 @@ + + + + + + + + + -
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@@ -885,6 +872,41 @@ + + + + +
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+ @@ -892,6 +914,7 @@ + @@ -1014,6 +1037,7 @@ + @@ -1023,6 +1047,7 @@ + @@ -1032,6 +1057,7 @@ + @@ -1039,6 +1065,7 @@ + @@ -1047,6 +1074,7 @@ + diff -r 973ffe8fe4f1 -r eaccbf2c2891 svm.xml --- a/svm.xml Tue Jul 10 03:10:31 2018 -0400 +++ b/svm.xml Fri Jul 13 03:54:16 2018 -0400 @@ -26,11 +26,13 @@ @GET_X_y_FUNCTION@ input_json_path = sys.argv[1] -params = json.load(open(input_json_path, "r")) +with open(input_json_path, "r") as param_handler: + params = json.load(param_handler) #if $selected_tasks.selected_task == "load": -classifier_object = pickle.load(open("$infile_model", 'rb')) +with open("$infile_model", 'rb') as model_handler: + classifier_object = pickle.load(model_handler) header = 'infer' if params["selected_tasks"]["header"] else None data = pandas.read_csv("$selected_tasks.infile_data", sep='\t', header=header, index_col=None, parse_dates=True, encoding=None, tupleize_cols=False) @@ -54,7 +56,8 @@ classifier_object = my_class(**options) classifier_object.fit(X, y) -pickle.dump(classifier_object,open("$outfile_fit", 'w+')) +with open("$outfile_fit", 'wb') as out_handler: + pickle.dump(classifier_object, out_handler) #end if diff -r 973ffe8fe4f1 -r eaccbf2c2891 test-data/mv_result07.tabular --- a/test-data/mv_result07.tabular Tue Jul 10 03:10:31 2018 -0400 +++ /dev/null Thu Jan 01 00:00:00 1970 +0000 @@ -1,1 +0,0 @@ -0.7824428015300172