# HG changeset patch
# User bgruening
# Date 1531468351 14400
# Node ID ba786fa81783130b5005b36231f24b4e9d038c48
# Parent  251ef8b8fbd076b0cd98d0b2c152449e7b89538c
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit f54ff2ba2f8e7542d68966ce5a6b17d7f624ac48
diff -r 251ef8b8fbd0 -r ba786fa81783 discriminant.xml
--- a/discriminant.xml	Tue Jul 10 03:08:39 2018 -0400
+++ b/discriminant.xml	Fri Jul 13 03:52:31 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 251ef8b8fbd0 -r ba786fa81783 main_macros.xml
--- a/main_macros.xml	Tue Jul 10 03:08:39 2018 -0400
+++ b/main_macros.xml	Fri Jul 13 03:52:31 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 @@
 
 
   
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@@ -553,11 +541,6 @@
     
   
 
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diff -r 251ef8b8fbd0 -r ba786fa81783 test-data/mv_result07.tabular
--- a/test-data/mv_result07.tabular	Tue Jul 10 03:08:39 2018 -0400
+++ /dev/null	Thu Jan 01 00:00:00 1970 +0000
@@ -1,1 +0,0 @@
-0.7824428015300172