# HG changeset patch # User bgruening # Date 1531468581 14400 # Node ID fb232caca397ccb276b4b375a947779ead625f65 # Parent 6ffb5d3bfc08284ed70f34f579970784770a2f7e planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit f54ff2ba2f8e7542d68966ce5a6b17d7f624ac48 diff -r 6ffb5d3bfc08 -r fb232caca397 discriminant.xml --- a/discriminant.xml Tue Jul 10 03:12:48 2018 -0400 +++ b/discriminant.xml Fri Jul 13 03:56:21 2018 -0400 @@ -26,12 +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", 'r')) +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) @@ -50,7 +51,8 @@ my_class = getattr(sklearn.discriminant_analysis, selected_algorithm) classifier_object = my_class(**options) classifier_object.fit(X, y) -pickle.dump(classifier_object,open("$outfile_fit", 'w+'), pickle.HIGHEST_PROTOCOL) +with open("$outfile_fit", 'wb') as out_handler: + pickle.dump(classifier_object, out_handler, pickle.HIGHEST_PROTOCOL) #end if ]]> diff -r 6ffb5d3bfc08 -r fb232caca397 main_macros.xml --- a/main_macros.xml Tue Jul 10 03:12:48 2018 -0400 +++ b/main_macros.xml Fri Jul 13 03:56:21 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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+ @@ -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 6ffb5d3bfc08 -r fb232caca397 test-data/mv_result07.tabular --- a/test-data/mv_result07.tabular Tue Jul 10 03:12:48 2018 -0400 +++ /dev/null Thu Jan 01 00:00:00 1970 +0000 @@ -1,1 +0,0 @@ -0.7824428015300172