Mercurial > repos > bgruening > sklearn_discriminant_classifier

comparison discriminant.xml @ 20:f051d64eb12e draft

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planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 8cf3d813ec755166ee0bd517b4ecbbd4f84d4df1
author bgruening
date Thu, 23 Aug 2018 16:19:35 -0400
parents 98b632c407ae
children 56ddc98c484e
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19:98b632c407ae 20:f051d64eb12e
18 import sys 18 import sys
19 import json 19 import json
20 import numpy as np 20 import numpy as np
21 import sklearn.discriminant_analysis 21 import sklearn.discriminant_analysis
22 import pandas 22 import pandas
23 import pickle 23
24 24 execfile("$__tool_directory__/sk_whitelist.py")
25 execfile("$__tool_directory__/utils.py") 25 execfile("$__tool_directory__/utils.py", globals())
26 26
27 input_json_path = sys.argv[1] 27 input_json_path = sys.argv[1]
28 with open(input_json_path, "r") as param_handler: 28 with open(input_json_path, "r") as param_handler:
29 params = json.load(param_handler) 29 params = json.load(param_handler)
30 30
31 #if $selected_tasks.selected_task == "load": 31 #if $selected_tasks.selected_task == "load":
32 32
33 with open("$infile_model", 'rb') as model_handler: 33 with open("$infile_model", 'rb') as model_handler:
34 classifier_object = pickle.load(model_handler) 34 classifier_object = SafePickler.load(model_handler)
35 35
36 header = 'infer' if params["selected_tasks"]["header"] else None 36 header = 'infer' if params["selected_tasks"]["header"] else None
37 data = pandas.read_csv("$selected_tasks.infile_data", sep='\t', header=header, index_col=None, parse_dates=True, encoding=None, tupleize_cols=False) 37 data = pandas.read_csv("$selected_tasks.infile_data", sep='\t', header=header, index_col=None, parse_dates=True, encoding=None, tupleize_cols=False)
38 prediction = classifier_object.predict(data) 38 prediction = classifier_object.predict(data)
39 prediction_df = pandas.DataFrame(prediction) 39 prediction_df = pandas.DataFrame(prediction)