Mercurial > repos > bgruening > sklearn_numeric_clustering
comparison train_test_split.py @ 36:73e7f1c76ece draft
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ea12f973df4b97a2691d9e4ce6bf6fae59d57717"
author | bgruening |
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date | Sat, 01 May 2021 00:48:46 +0000 |
parents | e7f047a9dca9 |
children | 06d772036a62 |
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35:e7f047a9dca9 | 36:73e7f1c76ece |
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26 | 26 |
27 nth_split = params["mode_selection"]["nth_split"] | 27 nth_split = params["mode_selection"]["nth_split"] |
28 | 28 |
29 # read groups | 29 # read groups |
30 if infile_groups: | 30 if infile_groups: |
31 header = "infer" if (params["mode_selection"]["cv_selector"]["groups_selector"]["header_g"]) else None | 31 header = ( |
32 column_option = params["mode_selection"]["cv_selector"]["groups_selector"]["column_selector_options_g"][ | 32 "infer" |
33 "selected_column_selector_option_g" | 33 if (params["mode_selection"]["cv_selector"]["groups_selector"]["header_g"]) |
34 ] | 34 else None |
35 ) | |
36 column_option = params["mode_selection"]["cv_selector"]["groups_selector"][ | |
37 "column_selector_options_g" | |
38 ]["selected_column_selector_option_g"] | |
35 if column_option in [ | 39 if column_option in [ |
36 "by_index_number", | 40 "by_index_number", |
37 "all_but_by_index_number", | 41 "all_but_by_index_number", |
38 "by_header_name", | 42 "by_header_name", |
39 "all_but_by_header_name", | 43 "all_but_by_header_name", |
40 ]: | 44 ]: |
41 c = params["mode_selection"]["cv_selector"]["groups_selector"]["column_selector_options_g"]["col_g"] | 45 c = params["mode_selection"]["cv_selector"]["groups_selector"][ |
46 "column_selector_options_g" | |
47 ]["col_g"] | |
42 else: | 48 else: |
43 c = None | 49 c = None |
44 | 50 |
45 groups = read_columns( | 51 groups = read_columns( |
46 infile_groups, | 52 infile_groups, |
65 # construct the cv splitter object | 71 # construct the cv splitter object |
66 splitter, groups = get_cv(params["mode_selection"]["cv_selector"]) | 72 splitter, groups = get_cv(params["mode_selection"]["cv_selector"]) |
67 | 73 |
68 total_n_splits = splitter.get_n_splits(array.values, y=y, groups=groups) | 74 total_n_splits = splitter.get_n_splits(array.values, y=y, groups=groups) |
69 if nth_split > total_n_splits: | 75 if nth_split > total_n_splits: |
70 raise ValueError("Total number of splits is {}, but got `nth_split` " "= {}".format(total_n_splits, nth_split)) | 76 raise ValueError( |
77 "Total number of splits is {}, but got `nth_split` " | |
78 "= {}".format(total_n_splits, nth_split) | |
79 ) | |
71 | 80 |
72 i = 1 | 81 i = 1 |
73 for train_index, test_index in splitter.split(array.values, y=y, groups=groups): | 82 for train_index, test_index in splitter.split(array.values, y=y, groups=groups): |
74 # suppose nth_split >= 1 | 83 # suppose nth_split >= 1 |
75 if i == nth_split: | 84 if i == nth_split: |
135 | 144 |
136 train, test = train_test_split(array, **options) | 145 train, test = train_test_split(array, **options) |
137 | 146 |
138 # cv splitter | 147 # cv splitter |
139 else: | 148 else: |
140 train, test = _get_single_cv_split(params, array, infile_labels=infile_labels, infile_groups=infile_groups) | 149 train, test = _get_single_cv_split( |
150 params, array, infile_labels=infile_labels, infile_groups=infile_groups | |
151 ) | |
141 | 152 |
142 print("Input shape: %s" % repr(array.shape)) | 153 print("Input shape: %s" % repr(array.shape)) |
143 print("Train shape: %s" % repr(train.shape)) | 154 print("Train shape: %s" % repr(train.shape)) |
144 print("Test shape: %s" % repr(test.shape)) | 155 print("Test shape: %s" % repr(test.shape)) |
145 train.to_csv(outfile_train, sep="\t", header=input_header, index=False) | 156 train.to_csv(outfile_train, sep="\t", header=input_header, index=False) |