# 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"]
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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