Mercurial > repos > bgruening > sklearn_generalized_linear

comparison generalized_linear.xml @ 31:a8c7b9fa426c draft

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"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
author bgruening
date Mon, 16 Dec 2019 05:29:33 -0500
parents 63417d0acc72
children 602edec75e1d
comparison
equal deleted inserted replaced
30:67881a837f46 31:a8c7b9fa426c
44 44
45 #else: 45 #else:
46 with open("$selected_tasks.infile_model", 'rb') as model_handler: 46 with open("$selected_tasks.infile_model", 'rb') as model_handler:
47 classifier_object = load_model(model_handler) 47 classifier_object = load_model(model_handler)
48 header = 'infer' if params["selected_tasks"]["header"] else None 48 header = 'infer' if params["selected_tasks"]["header"] else None
49 data = pandas.read_csv("$selected_tasks.infile_data", sep='\t', header=header, index_col=None, parse_dates=True, encoding=None, tupleize_cols=False) 49 data = pandas.read_csv("$selected_tasks.infile_data", sep='\t', header=header, index_col=None, parse_dates=True, encoding=None)
50 prediction = classifier_object.predict(data) 50 prediction = classifier_object.predict(data)
51 prediction_df = pandas.DataFrame(prediction, columns=["predicted"]) 51 prediction_df = pandas.DataFrame(prediction, columns=["predicted"])
52 res = pandas.concat([data, prediction_df], axis=1) 52 res = pandas.concat([data, prediction_df], axis=1)
53 res.to_csv(path_or_buf = "$outfile_predict", sep="\t", index=False, header=None) 53 res.to_csv(path_or_buf = "$outfile_predict", sep="\t", index=False, header=None)
54 #end if 54 #end if
80 </expand> 80 </expand>
81 <expand macro="penalty"/> 81 <expand macro="penalty"/>
82 <expand macro="alpha"/> 82 <expand macro="alpha"/>
83 <expand macro="l1_ratio"/> 83 <expand macro="l1_ratio"/>
84 <expand macro="fit_intercept"/> 84 <expand macro="fit_intercept"/>
85 <expand macro="n_iter" /> 85 <expand macro="n_iter_no_change" />
86 <expand macro="shuffle"/> 86 <expand macro="shuffle"/>
87 <expand macro="epsilon"/> 87 <expand macro="epsilon"/>
88 <expand macro="learning_rate_s" selected1="true"/> 88 <expand macro="learning_rate_s" selected1="true"/>
89 <expand macro="eta0"/> 89 <expand macro="eta0"/>
90 <expand macro="power_t"/> 90 <expand macro="power_t"/>
100 <expand macro="loss" select="true"/> 100 <expand macro="loss" select="true"/>
101 <expand macro="penalty"/> 101 <expand macro="penalty"/>
102 <expand macro="alpha"/> 102 <expand macro="alpha"/>
103 <expand macro="l1_ratio"/> 103 <expand macro="l1_ratio"/>
104 <expand macro="fit_intercept"/> 104 <expand macro="fit_intercept"/>
105 <expand macro="n_iter" /> 105 <expand macro="n_iter_no_change" />
106 <expand macro="shuffle"/> 106 <expand macro="shuffle"/>
107 <expand macro="epsilon"/> 107 <expand macro="epsilon"/>
108 <expand macro="learning_rate_s" selected2="true"/> 108 <expand macro="learning_rate_s" selected2="true"/>
109 <expand macro="eta0" default_value="0.01"/> 109 <expand macro="eta0" default_value="0.01"/>
110 <expand macro="power_t" default_value="0.25"/> 110 <expand macro="power_t" default_value="0.25"/>
189 <expand macro="sl_mixed_input"/> 189 <expand macro="sl_mixed_input"/>
190 <section name="options" title="Advanced Options" expanded="False"> 190 <section name="options" title="Advanced Options" expanded="False">
191 <expand macro="penalty" default_value="none"/> 191 <expand macro="penalty" default_value="none"/>
192 <expand macro="alpha"/> 192 <expand macro="alpha"/>
193 <expand macro="fit_intercept"/> 193 <expand macro="fit_intercept"/>
194 <expand macro="n_iter" /> 194 <expand macro="n_iter_no_change" />
195 <expand macro="shuffle"/> 195 <expand macro="shuffle"/>
196 <expand macro="eta0" default_value="1"/> 196 <expand macro="eta0" default_value="1"/>
197 <expand macro="warm_start" checked="false"/> 197 <expand macro="warm_start" checked="false"/>
198 <expand macro="random_state" default_value="0"/> 198 <expand macro="random_state" default_value="0"/>
199 <!--class_weight=None--> 199 <!--class_weight=None-->