Mercurial > repos > bgruening > sklearn_discriminant_classifier

comparison discriminant.xml @ 21:56ddc98c484e draft

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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
comparison
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20:f051d64eb12e 21:56ddc98c484e
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 23
24 execfile("$__tool_directory__/sk_whitelist.py") 24 with open("$__tool_directory__/sk_whitelist.json", "r") as f:
25 execfile("$__tool_directory__/utils.py", globals()) 25 sk_whitelist = json.load(f)
26 exec(open("$__tool_directory__/utils.py").read(), globals())
26 27
27 input_json_path = sys.argv[1] 28 input_json_path = sys.argv[1]
28 with open(input_json_path, "r") as param_handler: 29 with open(input_json_path, "r") as param_handler:
29 params = json.load(param_handler) 30 params = json.load(param_handler)
30 31
31 #if $selected_tasks.selected_task == "load": 32 #if $selected_tasks.selected_task == "load":
32 33
33 with open("$infile_model", 'rb') as model_handler: 34 with open("$infile_model", 'rb') as model_handler:
34 classifier_object = SafePickler.load(model_handler) 35 classifier_object = load_model(model_handler)
35 36
36 header = 'infer' if params["selected_tasks"]["header"] else None 37 header = 'infer' if params["selected_tasks"]["header"] else None
37 data = pandas.read_csv("$selected_tasks.infile_data", sep='\t', header=header, index_col=None, parse_dates=True, encoding=None, tupleize_cols=False) 38 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) 39 prediction = classifier_object.predict(data)
39 prediction_df = pandas.DataFrame(prediction) 40 prediction_df = pandas.DataFrame(prediction)
102 <param name="col1" value="1,2,3,4"/> 103 <param name="col1" value="1,2,3,4"/>
103 <param name="col2" value="5"/> 104 <param name="col2" value="5"/>
104 <param name="selected_task" value="train"/> 105 <param name="selected_task" value="train"/>
105 <param name="selected_algorithm" value="LinearDiscriminantAnalysis"/> 106 <param name="selected_algorithm" value="LinearDiscriminantAnalysis"/>
106 <param name="solver" value="svd" /> 107 <param name="solver" value="svd" />
107 <param name="store_covariances" value="True"/> 108 <param name="store_covariance" value="True"/>
108 <output name="outfile_fit" file="lda_model01" compare="sim_size" delta="500"/> 109 <output name="outfile_fit" file="lda_model01" compare="sim_size" delta="500"/>
109 </test> 110 </test>
110 <test> 111 <test>
111 <param name="infile1" value="train.tabular" ftype="tabular"/> 112 <param name="infile1" value="train.tabular" ftype="tabular"/>
112 <param name="infile2" value="train.tabular" ftype="tabular"/> 113 <param name="infile2" value="train.tabular" ftype="tabular"/>