Mercurial > repos > bgruening > sklearn_ensemble
comparison ensemble.xml @ 10:cd595710f0c0 draft
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 97c4f22cdcfa6cddeeffc7b102c418a7ff12a888
author | bgruening |
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date | Tue, 05 Jun 2018 06:46:22 -0400 |
parents | f1761288587e |
children | f4d8a82e167c |
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9:1b23a97c3ff1 | 10:cd595710f0c0 |
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47 if "min_samples_split" in options and options["min_samples_split"] > 1.0: | 47 if "min_samples_split" in options and options["min_samples_split"] > 1.0: |
48 options["min_samples_split"] = int(options["min_samples_split"]) | 48 options["min_samples_split"] = int(options["min_samples_split"]) |
49 input_type = params["selected_tasks"]["selected_algorithms"]["input_options"]["selected_input"] | 49 input_type = params["selected_tasks"]["selected_algorithms"]["input_options"]["selected_input"] |
50 if input_type=="tabular": | 50 if input_type=="tabular": |
51 header = 'infer' if params["selected_tasks"]["selected_algorithms"]["input_options"]["header1"] else None | 51 header = 'infer' if params["selected_tasks"]["selected_algorithms"]["input_options"]["header1"] else None |
52 column_option = params["selected_tasks"]["selected_algorithms"]["input_options"]["column_selector_options_1"]["selected_column_selector_option"] | |
53 if column_option == "by_index_number": | |
54 c = params["selected_tasks"]["selected_algorithms"]["input_options"]["column_selector_options_1"]["col1"] | |
55 else: | |
56 c = None | |
52 X = read_columns( | 57 X = read_columns( |
53 "$selected_tasks.selected_algorithms.input_options.infile1", | 58 "$selected_tasks.selected_algorithms.input_options.infile1", |
54 "$selected_tasks.selected_algorithms.input_options.col1", | 59 c = c, |
60 c_option = column_option, | |
55 sep='\t', | 61 sep='\t', |
56 header=header, | 62 header=header, |
57 parse_dates=True | 63 parse_dates=True |
58 ) | 64 ) |
59 else: | 65 else: |
60 X = mmread(open("$selected_tasks.selected_algorithms.input_options.infile1", 'r')) | 66 X = mmread(open("$selected_tasks.selected_algorithms.input_options.infile1", 'r')) |
61 | 67 |
62 header = 'infer' if params["selected_tasks"]["selected_algorithms"]["input_options"]["header2"] else None | 68 header = 'infer' if params["selected_tasks"]["selected_algorithms"]["input_options"]["header2"] else None |
69 column_option = params["selected_tasks"]["selected_algorithms"]["input_options"]["column_selector_options_2"]["selected_column_selector_option2"] | |
70 if column_option == "by_index_number": | |
71 c = params["selected_tasks"]["selected_algorithms"]["input_options"]["column_selector_options_2"]["col2"] | |
72 else: | |
73 c = None | |
63 y = read_columns( | 74 y = read_columns( |
64 "$selected_tasks.selected_algorithms.input_options.infile2", | 75 "$selected_tasks.selected_algorithms.input_options.infile2", |
65 "$selected_tasks.selected_algorithms.input_options.col2", | 76 c = c, |
77 c_option = column_option, | |
66 sep='\t', | 78 sep='\t', |
67 header=header, | 79 header=header, |
68 parse_dates=True | 80 parse_dates=True |
69 ) | 81 ) |
70 y=y.ravel() | 82 y=y.ravel() |
260 </test> | 272 </test> |
261 <test> | 273 <test> |
262 <param name="infile1" value="regression_X.tabular" ftype="tabular"/> | 274 <param name="infile1" value="regression_X.tabular" ftype="tabular"/> |
263 <param name="infile2" value="regression_y.tabular" ftype="tabular"/> | 275 <param name="infile2" value="regression_y.tabular" ftype="tabular"/> |
264 <param name="header1" value="True"/> | 276 <param name="header1" value="True"/> |
265 <param name="col1" value="1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17"/> | 277 <param name="selected_column_selector_option" value="all_columns"/> |
266 <param name="header2" value="True"/> | 278 <param name="header2" value="True"/> |
267 <param name="col2" value="1"/> | 279 <param name="col2" value="1"/> |
268 <param name="selected_task" value="train"/> | 280 <param name="selected_task" value="train"/> |
269 <param name="selected_algorithm" value="GradientBoostingRegressor"/> | 281 <param name="selected_algorithm" value="GradientBoostingRegressor"/> |
270 <param name="max_features" value="number_input"/> | 282 <param name="max_features" value="number_input"/> |