Mercurial > repos > bgruening > sklearn_discriminant_classifier
diff discriminant.xml @ 21:56ddc98c484e draft
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 2a058459e6daf0486871f93845f00fdb4a4eaca1
author | bgruening |
---|---|
date | Sat, 29 Sep 2018 07:38:46 -0400 |
parents | f051d64eb12e |
children | 75bcb7c19fcf |
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--- a/discriminant.xml Thu Aug 23 16:19:35 2018 -0400 +++ b/discriminant.xml Sat Sep 29 07:38:46 2018 -0400 @@ -21,8 +21,9 @@ import sklearn.discriminant_analysis import pandas -execfile("$__tool_directory__/sk_whitelist.py") -execfile("$__tool_directory__/utils.py", globals()) +with open("$__tool_directory__/sk_whitelist.json", "r") as f: + sk_whitelist = json.load(f) +exec(open("$__tool_directory__/utils.py").read(), globals()) input_json_path = sys.argv[1] with open(input_json_path, "r") as param_handler: @@ -31,7 +32,7 @@ #if $selected_tasks.selected_task == "load": with open("$infile_model", 'rb') as model_handler: - classifier_object = SafePickler.load(model_handler) + classifier_object = load_model(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) @@ -104,7 +105,7 @@ <param name="selected_task" value="train"/> <param name="selected_algorithm" value="LinearDiscriminantAnalysis"/> <param name="solver" value="svd" /> - <param name="store_covariances" value="True"/> + <param name="store_covariance" value="True"/> <output name="outfile_fit" file="lda_model01" compare="sim_size" delta="500"/> </test> <test>