Mercurial > repos > bgruening > sklearn_nn_classifier

comparison nn_classifier.xml @ 6:2a3c0a13e44c draft

Find changesets by keywords (author, files, the commit message), revision number or hash, or revset expression.
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 2a058459e6daf0486871f93845f00fdb4a4eaca1
author bgruening
date Sat, 29 Sep 2018 07:18:05 -0400
parents 51d406d4c643
children a2caa20a1583
comparison
equal deleted inserted replaced
5:51d406d4c643 6:2a3c0a13e44c
18 import json 18 import json
19 import numpy as np 19 import numpy as np
20 import sklearn.neighbors 20 import sklearn.neighbors
21 import pandas 21 import pandas
22 22
23 execfile("$__tool_directory__/sk_whitelist.py") 23 with open("$__tool_directory__/sk_whitelist.json", "r") as f:
24 execfile("$__tool_directory__/utils.py", globals()) 24 sk_whitelist = json.load(f)
25 exec(open("$__tool_directory__/utils.py").read(), globals())
25 26
26 input_json_path = sys.argv[1] 27 input_json_path = sys.argv[1]
27 with open(input_json_path, "r") as param_handler: 28 with open(input_json_path, "r") as param_handler:
28 params = json.load(param_handler) 29 params = json.load(param_handler)
29 30
30 #if $selected_tasks.selected_task == "load": 31 #if $selected_tasks.selected_task == "load":
31 32
32 with open("$infile_model", 'rb') as model_handler: 33 with open("$infile_model", 'rb') as model_handler:
33 classifier_object = SafePickler.load(model_handler) 34 classifier_object = load_model(model_handler)
34 35
35 header = 'infer' if params["selected_tasks"]["header"] else None 36 header = 'infer' if params["selected_tasks"]["header"] else None
36 data = pandas.read_csv("$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)
37 prediction = classifier_object.predict(data) 38 prediction = classifier_object.predict(data)
38 prediction_df = pandas.DataFrame(prediction) 39 prediction_df = pandas.DataFrame(prediction)
116 <param name="col2" value="5"/> 117 <param name="col2" value="5"/>
117 <param name="selected_task" value="train"/> 118 <param name="selected_task" value="train"/>
118 <param name="selected_algorithm" value="nneighbors"/> 119 <param name="selected_algorithm" value="nneighbors"/>
119 <param name="sampling_method" value="KNeighborsClassifier" /> 120 <param name="sampling_method" value="KNeighborsClassifier" />
120 <param name="algorithm" value="brute" /> 121 <param name="algorithm" value="brute" />
121 <output name="outfile_fit" file="nn_model01.txt"/> 122 <output name="outfile_fit" file="nn_model01"/>
122 </test> 123 </test>
123 <test> 124 <test>
124 <param name="infile1" value="train_set.tabular" ftype="tabular"/> 125 <param name="infile1" value="train_set.tabular" ftype="tabular"/>
125 <param name="infile2" value="train_set.tabular" ftype="tabular"/> 126 <param name="infile2" value="train_set.tabular" ftype="tabular"/>
126 <param name="header1" value="True"/> 127 <param name="header1" value="True"/>
127 <param name="header2" value="True"/> 128 <param name="header2" value="True"/>
128 <param name="col1" value="1,2,3,4"/> 129 <param name="col1" value="1,2,3,4"/>
129 <param name="col2" value="5"/> 130 <param name="col2" value="5"/>
130 <param name="selected_task" value="train"/> 131 <param name="selected_task" value="train"/>
131 <param name="selected_algorithm" value=""/>
132 <param name="selected_algorithm" value="nneighbors"/> 132 <param name="selected_algorithm" value="nneighbors"/>
133 <param name="sampling_method" value="RadiusNeighborsClassifier" /> 133 <param name="sampling_method" value="RadiusNeighborsClassifier" />
134 <output name="outfile_fit" file="nn_model02.txt"/> 134 <output name="outfile_fit" file="nn_model02"/>
135 </test> 135 </test>
136 <test> 136 <test>
137 <param name="infile1" value="train_set.tabular" ftype="tabular"/> 137 <param name="infile1" value="train_set.tabular" ftype="tabular"/>
138 <param name="infile2" value="train_set.tabular" ftype="tabular"/> 138 <param name="infile2" value="train_set.tabular" ftype="tabular"/>
139 <param name="header1" value="True"/> 139 <param name="header1" value="True"/>
140 <param name="header2" value="True"/> 140 <param name="header2" value="True"/>
141 <param name="col1" value="1,2,3,4"/> 141 <param name="col1" value="1,2,3,4"/>
142 <param name="col2" value="5"/> 142 <param name="col2" value="5"/>
143 <param name="selected_task" value="train"/> 143 <param name="selected_task" value="train"/>
144 <param name="selected_algorithm" value="ncentroid"/> 144 <param name="selected_algorithm" value="ncentroid"/>
145 <output name="outfile_fit" file="nn_model03.txt"/> 145 <output name="outfile_fit" file="nn_model03"/>
146 </test> 146 </test>
147 <test> 147 <test>
148 <param name="infile_model" value="nn_model01.txt" ftype="txt"/> 148 <param name="infile_model" value="nn_model01" ftype="zip"/>
149 <param name="infile_data" value="test_set.tabular" ftype="tabular"/> 149 <param name="infile_data" value="test_set.tabular" ftype="tabular"/>
150 <param name="header" value="True"/> 150 <param name="header" value="True"/>
151 <param name="selected_task" value="load"/> 151 <param name="selected_task" value="load"/>
152 <output name="outfile_predict" file="nn_prediction_result01.tabular"/> 152 <output name="outfile_predict" file="nn_prediction_result01.tabular"/>
153 </test> 153 </test>
154 <test> 154 <test>
155 <param name="infile_model" value="nn_model02.txt" ftype="txt"/> 155 <param name="infile_model" value="nn_model02" ftype="zip"/>
156 <param name="infile_data" value="test_set.tabular" ftype="tabular"/> 156 <param name="infile_data" value="test_set.tabular" ftype="tabular"/>
157 <param name="header" value="True"/> 157 <param name="header" value="True"/>
158 <param name="selected_task" value="load"/> 158 <param name="selected_task" value="load"/>
159 <output name="outfile_predict" file="nn_prediction_result02.tabular"/> 159 <output name="outfile_predict" file="nn_prediction_result02.tabular"/>
160 </test> 160 </test>
161 <test> 161 <test>
162 <param name="infile_model" value="nn_model03.txt" ftype="txt"/> 162 <param name="infile_model" value="nn_model03" ftype="zip"/>
163 <param name="infile_data" value="test_set.tabular" ftype="tabular"/> 163 <param name="infile_data" value="test_set.tabular" ftype="tabular"/>
164 <param name="header" value="True"/> 164 <param name="header" value="True"/>
165 <param name="selected_task" value="load"/> 165 <param name="selected_task" value="load"/>
166 <output name="outfile_predict" file="nn_prediction_result03.tabular"/> 166 <output name="outfile_predict" file="nn_prediction_result03.tabular"/>
167 </test> 167 </test>