Mercurial > repos > bgruening > sklearn_discriminant_classifier
comparison discriminant.xml @ 21:56ddc98c484e draft
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 2a058459e6daf0486871f93845f00fdb4a4eaca1
author | bgruening |
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date | Sat, 29 Sep 2018 07:38:46 -0400 |
parents | f051d64eb12e |
children | 75bcb7c19fcf |
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20:f051d64eb12e | 21:56ddc98c484e |
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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"/> |