Mercurial > repos > bgruening > sklearn_data_preprocess
annotate train_test_eval.py @ 36:b75cae00f980 draft
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 208a8d348e7c7a182cfbe1b6f17868146428a7e2"
author | bgruening |
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date | Tue, 13 Apr 2021 22:16:07 +0000 |
parents | 0e5fcf7ddc75 |
children | 1bef885255e0 |
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planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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1 import argparse |
685046e0381a
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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2 import json |
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"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
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3 import os |
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planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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4 import pickle |
685046e0381a
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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5 import warnings |
685046e0381a
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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6 from itertools import chain |
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"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
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7 |
0e5fcf7ddc75
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
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8 import joblib |
0e5fcf7ddc75
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
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9 import numpy as np |
0e5fcf7ddc75
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
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10 import pandas as pd |
0e5fcf7ddc75
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
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11 from galaxy_ml.model_validations import train_test_split |
0e5fcf7ddc75
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
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12 from galaxy_ml.utils import ( |
0e5fcf7ddc75
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
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13 get_module, |
0e5fcf7ddc75
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
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14 get_scoring, |
0e5fcf7ddc75
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
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15 load_model, |
0e5fcf7ddc75
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
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16 read_columns, |
0e5fcf7ddc75
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
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17 SafeEval, |
0e5fcf7ddc75
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
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18 try_get_attr, |
0e5fcf7ddc75
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
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19 ) |
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planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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20 from scipy.io import mmread |
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"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
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21 from sklearn import pipeline |
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planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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22 from sklearn.metrics.scorer import _check_multimetric_scoring |
685046e0381a
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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23 from sklearn.model_selection import _search, _validation |
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"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
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24 from sklearn.model_selection._validation import _score |
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planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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25 from sklearn.utils import indexable, safe_indexing |
685046e0381a
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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26 |
685046e0381a
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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27 |
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"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
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28 _fit_and_score = try_get_attr("galaxy_ml.model_validations", "_fit_and_score") |
0e5fcf7ddc75
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
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29 setattr(_search, "_fit_and_score", _fit_and_score) |
0e5fcf7ddc75
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
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30 setattr(_validation, "_fit_and_score", _fit_and_score) |
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planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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31 |
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"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
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32 N_JOBS = int(os.environ.get("GALAXY_SLOTS", 1)) |
0e5fcf7ddc75
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
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33 CACHE_DIR = os.path.join(os.getcwd(), "cached") |
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"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
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34 del os |
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"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
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35 NON_SEARCHABLE = ("n_jobs", "pre_dispatch", "memory", "_path", "nthread", "callbacks") |
0e5fcf7ddc75
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
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36 ALLOWED_CALLBACKS = ( |
0e5fcf7ddc75
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
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37 "EarlyStopping", |
0e5fcf7ddc75
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
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38 "TerminateOnNaN", |
0e5fcf7ddc75
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
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39 "ReduceLROnPlateau", |
0e5fcf7ddc75
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
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40 "CSVLogger", |
0e5fcf7ddc75
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
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41 "None", |
0e5fcf7ddc75
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
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42 ) |
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43 |
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44 |
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45 def _eval_swap_params(params_builder): |
685046e0381a
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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46 swap_params = {} |
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47 |
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48 for p in params_builder["param_set"]: |
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"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
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49 swap_value = p["sp_value"].strip() |
0e5fcf7ddc75
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
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50 if swap_value == "": |
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51 continue |
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52 |
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53 param_name = p["sp_name"] |
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54 if param_name.lower().endswith(NON_SEARCHABLE): |
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55 warnings.warn( |
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56 "Warning: `%s` is not eligible for search and was " |
0e5fcf7ddc75
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57 "omitted!" % param_name |
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"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
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58 ) |
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59 continue |
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60 |
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61 if not swap_value.startswith(":"): |
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62 safe_eval = SafeEval(load_scipy=True, load_numpy=True) |
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63 ev = safe_eval(swap_value) |
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64 else: |
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65 # Have `:` before search list, asks for estimator evaluatio |
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66 safe_eval_es = SafeEval(load_estimators=True) |
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67 swap_value = swap_value[1:].strip() |
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68 # TODO maybe add regular express check |
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69 ev = safe_eval_es(swap_value) |
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70 |
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71 swap_params[param_name] = ev |
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72 |
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73 return swap_params |
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74 |
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75 |
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76 def train_test_split_none(*arrays, **kwargs): |
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77 """extend train_test_split to take None arrays |
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78 and support split by group names. |
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79 """ |
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80 nones = [] |
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81 new_arrays = [] |
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82 for idx, arr in enumerate(arrays): |
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83 if arr is None: |
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84 nones.append(idx) |
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85 else: |
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86 new_arrays.append(arr) |
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87 |
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88 if kwargs["shuffle"] == "None": |
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89 kwargs["shuffle"] = None |
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90 |
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91 group_names = kwargs.pop("group_names", None) |
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92 |
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93 if group_names is not None and group_names.strip(): |
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94 group_names = [name.strip() for name in group_names.split(",")] |
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95 new_arrays = indexable(*new_arrays) |
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96 groups = kwargs["labels"] |
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97 n_samples = new_arrays[0].shape[0] |
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98 index_arr = np.arange(n_samples) |
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99 test = index_arr[np.isin(groups, group_names)] |
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100 train = index_arr[~np.isin(groups, group_names)] |
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101 rval = list( |
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102 chain.from_iterable( |
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103 (safe_indexing(a, train), safe_indexing(a, test)) for a in new_arrays |
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104 ) |
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105 ) |
26
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106 else: |
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107 rval = train_test_split(*new_arrays, **kwargs) |
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108 |
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109 for pos in nones: |
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110 rval[pos * 2: 2] = [None, None] |
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111 |
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112 return rval |
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113 |
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114 |
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115 def main( |
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116 inputs, |
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117 infile_estimator, |
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118 infile1, |
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119 infile2, |
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120 outfile_result, |
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121 outfile_object=None, |
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122 outfile_weights=None, |
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123 groups=None, |
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124 ref_seq=None, |
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125 intervals=None, |
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126 targets=None, |
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127 fasta_path=None, |
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128 ): |
26
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129 """ |
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130 Parameter |
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131 --------- |
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132 inputs : str |
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133 File path to galaxy tool parameter |
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134 |
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135 infile_estimator : str |
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136 File path to estimator |
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137 |
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138 infile1 : str |
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139 File path to dataset containing features |
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140 |
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141 infile2 : str |
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142 File path to dataset containing target values |
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143 |
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144 outfile_result : str |
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145 File path to save the results, either cv_results or test result |
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146 |
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147 outfile_object : str, optional |
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148 File path to save searchCV object |
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149 |
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150 outfile_weights : str, optional |
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151 File path to save deep learning model weights |
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152 |
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153 groups : str |
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154 File path to dataset containing groups labels |
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155 |
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156 ref_seq : str |
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157 File path to dataset containing genome sequence file |
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158 |
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159 intervals : str |
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160 File path to dataset containing interval file |
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161 |
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162 targets : str |
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163 File path to dataset compressed target bed file |
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164 |
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165 fasta_path : str |
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166 File path to dataset containing fasta file |
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167 """ |
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168 warnings.simplefilter("ignore") |
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169 |
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170 with open(inputs, "r") as param_handler: |
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171 params = json.load(param_handler) |
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172 |
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173 # load estimator |
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174 with open(infile_estimator, "rb") as estimator_handler: |
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175 estimator = load_model(estimator_handler) |
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176 |
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177 # swap hyperparameter |
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178 swapping = params["experiment_schemes"]["hyperparams_swapping"] |
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179 swap_params = _eval_swap_params(swapping) |
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180 estimator.set_params(**swap_params) |
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181 |
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182 estimator_params = estimator.get_params() |
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183 |
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184 # store read dataframe object |
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185 loaded_df = {} |
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186 |
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187 input_type = params["input_options"]["selected_input"] |
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188 # tabular input |
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189 if input_type == "tabular": |
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190 header = "infer" if params["input_options"]["header1"] else None |
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191 column_option = params["input_options"]["column_selector_options_1"][ |
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192 "selected_column_selector_option" |
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193 ] |
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194 if column_option in [ |
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195 "by_index_number", |
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196 "all_but_by_index_number", |
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197 "by_header_name", |
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198 "all_but_by_header_name", |
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199 ]: |
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200 c = params["input_options"]["column_selector_options_1"]["col1"] |
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201 else: |
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202 c = None |
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203 |
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204 df_key = infile1 + repr(header) |
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205 df = pd.read_csv(infile1, sep="\t", header=header, parse_dates=True) |
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206 loaded_df[df_key] = df |
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207 |
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208 X = read_columns(df, c=c, c_option=column_option).astype(float) |
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209 # sparse input |
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210 elif input_type == "sparse": |
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211 X = mmread(open(infile1, "r")) |
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212 |
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213 # fasta_file input |
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214 elif input_type == "seq_fasta": |
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215 pyfaidx = get_module("pyfaidx") |
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216 sequences = pyfaidx.Fasta(fasta_path) |
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217 n_seqs = len(sequences.keys()) |
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218 X = np.arange(n_seqs)[:, np.newaxis] |
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219 for param in estimator_params.keys(): |
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220 if param.endswith("fasta_path"): |
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221 estimator.set_params(**{param: fasta_path}) |
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222 break |
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223 else: |
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224 raise ValueError( |
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225 "The selected estimator doesn't support " |
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226 "fasta file input! Please consider using " |
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227 "KerasGBatchClassifier with " |
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228 "FastaDNABatchGenerator/FastaProteinBatchGenerator " |
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229 "or having GenomeOneHotEncoder/ProteinOneHotEncoder " |
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230 "in pipeline!" |
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231 ) |
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232 |
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233 elif input_type == "refseq_and_interval": |
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234 path_params = { |
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235 "data_batch_generator__ref_genome_path": ref_seq, |
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236 "data_batch_generator__intervals_path": intervals, |
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237 "data_batch_generator__target_path": targets, |
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238 } |
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239 estimator.set_params(**path_params) |
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240 n_intervals = sum(1 for line in open(intervals)) |
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241 X = np.arange(n_intervals)[:, np.newaxis] |
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242 |
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243 # Get target y |
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244 header = "infer" if params["input_options"]["header2"] else None |
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"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
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245 column_option = params["input_options"]["column_selector_options_2"][ |
0e5fcf7ddc75
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
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246 "selected_column_selector_option2" |
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"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
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247 ] |
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248 if column_option in [ |
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"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
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249 "by_index_number", |
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"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
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250 "all_but_by_index_number", |
0e5fcf7ddc75
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
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251 "by_header_name", |
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"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
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252 "all_but_by_header_name", |
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"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
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253 ]: |
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254 c = params["input_options"]["column_selector_options_2"]["col2"] |
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255 else: |
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256 c = None |
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257 |
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258 df_key = infile2 + repr(header) |
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259 if df_key in loaded_df: |
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260 infile2 = loaded_df[df_key] |
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261 else: |
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262 infile2 = pd.read_csv(infile2, sep="\t", header=header, parse_dates=True) |
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263 loaded_df[df_key] = infile2 |
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264 |
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265 y = read_columns(infile2, |
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266 c=c, |
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267 c_option=column_option, |
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"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
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268 sep='\t', |
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"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
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269 header=header, |
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"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
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270 parse_dates=True) |
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271 if len(y.shape) == 2 and y.shape[1] == 1: |
685046e0381a
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272 y = y.ravel() |
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273 if input_type == "refseq_and_interval": |
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274 estimator.set_params(data_batch_generator__features=y.ravel().tolist()) |
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275 y = None |
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276 # end y |
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277 |
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278 # load groups |
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279 if groups: |
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280 groups_selector = ( |
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"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
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281 params["experiment_schemes"]["test_split"]["split_algos"] |
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282 ).pop("groups_selector") |
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283 |
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284 header = "infer" if groups_selector["header_g"] else None |
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"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
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285 column_option = groups_selector["column_selector_options_g"][ |
0e5fcf7ddc75
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
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286 "selected_column_selector_option_g" |
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"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
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287 ] |
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288 if column_option in [ |
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"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
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289 "by_index_number", |
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"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
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290 "all_but_by_index_number", |
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"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
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291 "by_header_name", |
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"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
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292 "all_but_by_header_name", |
0e5fcf7ddc75
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
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293 ]: |
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294 c = groups_selector["column_selector_options_g"]["col_g"] |
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295 else: |
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296 c = None |
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297 |
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298 df_key = groups + repr(header) |
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299 if df_key in loaded_df: |
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300 groups = loaded_df[df_key] |
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301 |
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302 groups = read_columns(groups, |
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303 c=c, |
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304 c_option=column_option, |
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305 sep='\t', |
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306 header=header, |
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307 parse_dates=True) |
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308 groups = groups.ravel() |
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309 |
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310 # del loaded_df |
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311 del loaded_df |
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312 |
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313 # handle memory |
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314 memory = joblib.Memory(location=CACHE_DIR, verbose=0) |
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315 # cache iraps_core fits could increase search speed significantly |
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316 if estimator.__class__.__name__ == "IRAPSClassifier": |
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317 estimator.set_params(memory=memory) |
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318 else: |
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319 # For iraps buried in pipeline |
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320 new_params = {} |
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321 for p, v in estimator_params.items(): |
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322 if p.endswith("memory"): |
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323 # for case of `__irapsclassifier__memory` |
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324 if len(p) > 8 and p[:-8].endswith("irapsclassifier"): |
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325 # cache iraps_core fits could increase search |
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326 # speed significantly |
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327 new_params[p] = memory |
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328 # security reason, we don't want memory being |
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329 # modified unexpectedly |
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330 elif v: |
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331 new_params[p] = None |
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332 # handle n_jobs |
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333 elif p.endswith("n_jobs"): |
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334 # For now, 1 CPU is suggested for iprasclassifier |
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335 if len(p) > 8 and p[:-8].endswith("irapsclassifier"): |
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336 new_params[p] = 1 |
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337 else: |
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338 new_params[p] = N_JOBS |
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339 # for security reason, types of callback are limited |
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340 elif p.endswith("callbacks"): |
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341 for cb in v: |
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342 cb_type = cb["callback_selection"]["callback_type"] |
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343 if cb_type not in ALLOWED_CALLBACKS: |
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344 raise ValueError("Prohibited callback type: %s!" % cb_type) |
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345 |
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346 estimator.set_params(**new_params) |
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347 |
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348 # handle scorer, convert to scorer dict |
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349 # Check if scoring is specified |
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350 scoring = params["experiment_schemes"]["metrics"].get("scoring", None) |
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351 if scoring is not None: |
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"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
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352 # get_scoring() expects secondary_scoring to be a comma separated string (not a list) |
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"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
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353 # Check if secondary_scoring is specified |
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354 secondary_scoring = scoring.get("secondary_scoring", None) |
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355 if secondary_scoring is not None: |
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"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
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356 # If secondary_scoring is specified, convert the list into comman separated string |
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"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
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357 scoring["secondary_scoring"] = ",".join(scoring["secondary_scoring"]) |
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358 scorer = get_scoring(scoring) |
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359 scorer, _ = _check_multimetric_scoring(estimator, scoring=scorer) |
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360 |
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361 # handle test (first) split |
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362 test_split_options = params["experiment_schemes"]["test_split"]["split_algos"] |
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363 |
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364 if test_split_options["shuffle"] == "group": |
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"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
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365 test_split_options["labels"] = groups |
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"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
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366 if test_split_options["shuffle"] == "stratified": |
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367 if y is not None: |
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368 test_split_options["labels"] = y |
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369 else: |
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"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
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370 raise ValueError( |
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"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
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371 "Stratified shuffle split is not " "applicable on empty target values!" |
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"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
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372 ) |
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373 |
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374 X_train, X_test, y_train, y_test, groups_train, _groups_test = train_test_split_none( |
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375 X, y, groups, **test_split_options |
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"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
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376 ) |
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377 |
35
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378 exp_scheme = params["experiment_schemes"]["selected_exp_scheme"] |
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379 |
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380 # handle validation (second) split |
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381 if exp_scheme == "train_val_test": |
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"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
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382 val_split_options = params["experiment_schemes"]["val_split"]["split_algos"] |
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383 |
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384 if val_split_options["shuffle"] == "group": |
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"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
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385 val_split_options["labels"] = groups_train |
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"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
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386 if val_split_options["shuffle"] == "stratified": |
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387 if y_train is not None: |
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388 val_split_options["labels"] = y_train |
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389 else: |
35
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390 raise ValueError( |
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"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
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391 "Stratified shuffle split is not " |
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"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
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392 "applicable on empty target values!" |
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"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
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393 ) |
26
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394 |
35
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395 ( |
0e5fcf7ddc75
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
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396 X_train, |
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"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
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397 X_val, |
0e5fcf7ddc75
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
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398 y_train, |
0e5fcf7ddc75
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
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399 y_val, |
0e5fcf7ddc75
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
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400 groups_train, |
0e5fcf7ddc75
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
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401 _groups_val, |
0e5fcf7ddc75
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
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402 ) = train_test_split_none(X_train, y_train, groups_train, **val_split_options) |
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403 |
685046e0381a
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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404 # train and eval |
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"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
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405 if hasattr(estimator, "validation_data"): |
0e5fcf7ddc75
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
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406 if exp_scheme == "train_val_test": |
0e5fcf7ddc75
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
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407 estimator.fit(X_train, y_train, validation_data=(X_val, y_val)) |
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planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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408 else: |
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"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
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409 estimator.fit(X_train, y_train, validation_data=(X_test, y_test)) |
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685046e0381a
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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410 else: |
685046e0381a
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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411 estimator.fit(X_train, y_train) |
685046e0381a
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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412 |
35
0e5fcf7ddc75
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
bgruening
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413 if hasattr(estimator, "evaluate"): |
0e5fcf7ddc75
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
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414 scores = estimator.evaluate( |
0e5fcf7ddc75
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
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415 X_test, y_test=y_test, scorer=scorer, is_multimetric=True |
0e5fcf7ddc75
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
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416 ) |
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planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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417 else: |
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0e5fcf7ddc75
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
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418 scores = _score(estimator, X_test, y_test, scorer, is_multimetric=True) |
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419 # handle output |
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420 for name, score in scores.items(): |
685046e0381a
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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421 scores[name] = [score] |
685046e0381a
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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422 df = pd.DataFrame(scores) |
685046e0381a
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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423 df = df[sorted(df.columns)] |
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"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
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424 df.to_csv(path_or_buf=outfile_result, sep="\t", header=True, index=False) |
26
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425 |
685046e0381a
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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426 memory.clear(warn=False) |
685046e0381a
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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427 |
685046e0381a
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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428 if outfile_object: |
685046e0381a
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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429 main_est = estimator |
685046e0381a
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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430 if isinstance(estimator, pipeline.Pipeline): |
685046e0381a
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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431 main_est = estimator.steps[-1][-1] |
685046e0381a
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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432 |
35
0e5fcf7ddc75
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
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433 if hasattr(main_est, "model_") and hasattr(main_est, "save_weights"): |
26
685046e0381a
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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434 if outfile_weights: |
685046e0381a
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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435 main_est.save_weights(outfile_weights) |
35
0e5fcf7ddc75
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
bgruening
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436 if getattr(main_est, "model_", None): |
0e5fcf7ddc75
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
bgruening
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437 del main_est.model_ |
0e5fcf7ddc75
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
bgruening
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438 if getattr(main_est, "fit_params", None): |
0e5fcf7ddc75
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
bgruening
parents:
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|
439 del main_est.fit_params |
0e5fcf7ddc75
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
bgruening
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440 if getattr(main_est, "model_class_", None): |
0e5fcf7ddc75
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
bgruening
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441 del main_est.model_class_ |
0e5fcf7ddc75
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
bgruening
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442 if getattr(main_est, "validation_data", None): |
0e5fcf7ddc75
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
bgruening
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443 del main_est.validation_data |
0e5fcf7ddc75
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
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444 if getattr(main_est, "data_generator_", None): |
26
685046e0381a
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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445 del main_est.data_generator_ |
685046e0381a
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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446 |
35
0e5fcf7ddc75
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
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447 with open(outfile_object, "wb") as output_handler: |
0e5fcf7ddc75
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
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448 pickle.dump(estimator, output_handler, pickle.HIGHEST_PROTOCOL) |
26
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449 |
685046e0381a
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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450 |
35
0e5fcf7ddc75
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
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451 if __name__ == "__main__": |
26
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452 aparser = argparse.ArgumentParser() |
685046e0381a
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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453 aparser.add_argument("-i", "--inputs", dest="inputs", required=True) |
685046e0381a
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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454 aparser.add_argument("-e", "--estimator", dest="infile_estimator") |
685046e0381a
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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455 aparser.add_argument("-X", "--infile1", dest="infile1") |
685046e0381a
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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456 aparser.add_argument("-y", "--infile2", dest="infile2") |
685046e0381a
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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457 aparser.add_argument("-O", "--outfile_result", dest="outfile_result") |
685046e0381a
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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458 aparser.add_argument("-o", "--outfile_object", dest="outfile_object") |
685046e0381a
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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459 aparser.add_argument("-w", "--outfile_weights", dest="outfile_weights") |
685046e0381a
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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460 aparser.add_argument("-g", "--groups", dest="groups") |
685046e0381a
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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461 aparser.add_argument("-r", "--ref_seq", dest="ref_seq") |
685046e0381a
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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462 aparser.add_argument("-b", "--intervals", dest="intervals") |
685046e0381a
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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463 aparser.add_argument("-t", "--targets", dest="targets") |
685046e0381a
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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464 aparser.add_argument("-f", "--fasta_path", dest="fasta_path") |
685046e0381a
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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465 args = aparser.parse_args() |
685046e0381a
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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466 |
35
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"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
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467 main( |
0e5fcf7ddc75
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
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468 args.inputs, |
0e5fcf7ddc75
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
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469 args.infile_estimator, |
0e5fcf7ddc75
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
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470 args.infile1, |
0e5fcf7ddc75
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
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471 args.infile2, |
0e5fcf7ddc75
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
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472 args.outfile_result, |
0e5fcf7ddc75
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
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473 outfile_object=args.outfile_object, |
0e5fcf7ddc75
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
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474 outfile_weights=args.outfile_weights, |
0e5fcf7ddc75
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
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475 groups=args.groups, |
0e5fcf7ddc75
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
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476 ref_seq=args.ref_seq, |
0e5fcf7ddc75
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
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477 intervals=args.intervals, |
0e5fcf7ddc75
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
bgruening
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478 targets=args.targets, |
0e5fcf7ddc75
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
bgruening
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479 fasta_path=args.fasta_path, |
0e5fcf7ddc75
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
bgruening
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480 ) |