Mercurial > repos > bgruening > sklearn_ensemble
annotate train_test_eval.py @ 40:a07ab242b0b5 draft
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit f031d8ddfb73cec24572648666ac44ee47f08aad
author | bgruening |
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date | Thu, 11 Aug 2022 09:18:09 +0000 |
parents | 4ecc0ce9d0a2 |
children | 6546d7c9f08b |
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dde0f1654d18
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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1 import argparse |
dde0f1654d18
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 |
dde0f1654d18
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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5 import warnings |
dde0f1654d18
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 |
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"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
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8 import joblib |
19d6c2745d34
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
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9 import numpy as np |
19d6c2745d34
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
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10 import pandas as pd |
19d6c2745d34
"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 |
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"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ea12f973df4b97a2691d9e4ce6bf6fae59d57717"
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12 from galaxy_ml.utils import (get_module, get_scoring, load_model, |
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"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ea12f973df4b97a2691d9e4ce6bf6fae59d57717"
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13 read_columns, SafeEval, try_get_attr) |
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planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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14 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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15 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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16 from sklearn.metrics.scorer import _check_multimetric_scoring |
dde0f1654d18
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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17 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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18 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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19 from sklearn.utils import indexable, safe_indexing |
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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 |
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"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
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21 _fit_and_score = try_get_attr("galaxy_ml.model_validations", "_fit_and_score") |
19d6c2745d34
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
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22 setattr(_search, "_fit_and_score", _fit_and_score) |
19d6c2745d34
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
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23 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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24 |
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"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
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25 N_JOBS = int(os.environ.get("GALAXY_SLOTS", 1)) |
19d6c2745d34
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
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26 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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27 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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28 NON_SEARCHABLE = ("n_jobs", "pre_dispatch", "memory", "_path", "nthread", "callbacks") |
19d6c2745d34
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
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29 ALLOWED_CALLBACKS = ( |
19d6c2745d34
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
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30 "EarlyStopping", |
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"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
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31 "TerminateOnNaN", |
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"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
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32 "ReduceLROnPlateau", |
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"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
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33 "CSVLogger", |
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"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
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34 "None", |
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"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
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35 ) |
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planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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36 |
dde0f1654d18
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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37 |
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planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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38 def _eval_swap_params(params_builder): |
dde0f1654d18
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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39 swap_params = {} |
dde0f1654d18
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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40 |
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41 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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42 swap_value = p["sp_value"].strip() |
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"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
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43 if swap_value == "": |
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planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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44 continue |
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45 |
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46 param_name = p["sp_name"] |
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47 if param_name.lower().endswith(NON_SEARCHABLE): |
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48 warnings.warn( |
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49 "Warning: `%s` is not eligible for search and was " |
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"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
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50 "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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51 ) |
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52 continue |
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53 |
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54 if not swap_value.startswith(":"): |
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55 safe_eval = SafeEval(load_scipy=True, load_numpy=True) |
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56 ev = safe_eval(swap_value) |
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57 else: |
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58 # Have `:` before search list, asks for estimator evaluatio |
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59 safe_eval_es = SafeEval(load_estimators=True) |
dde0f1654d18
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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60 swap_value = swap_value[1:].strip() |
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61 # TODO maybe add regular express check |
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62 ev = safe_eval_es(swap_value) |
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63 |
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64 swap_params[param_name] = ev |
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65 |
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66 return swap_params |
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67 |
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68 |
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69 def train_test_split_none(*arrays, **kwargs): |
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70 """extend train_test_split to take None arrays |
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71 and support split by group names. |
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72 """ |
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73 nones = [] |
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74 new_arrays = [] |
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75 for idx, arr in enumerate(arrays): |
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76 if arr is None: |
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77 nones.append(idx) |
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78 else: |
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79 new_arrays.append(arr) |
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80 |
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81 if kwargs["shuffle"] == "None": |
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82 kwargs["shuffle"] = None |
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83 |
35
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84 group_names = kwargs.pop("group_names", None) |
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85 |
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86 if group_names is not None and group_names.strip(): |
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87 group_names = [name.strip() for name in group_names.split(",")] |
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88 new_arrays = indexable(*new_arrays) |
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89 groups = kwargs["labels"] |
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90 n_samples = new_arrays[0].shape[0] |
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91 index_arr = np.arange(n_samples) |
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92 test = index_arr[np.isin(groups, group_names)] |
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93 train = index_arr[~np.isin(groups, group_names)] |
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94 rval = list( |
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95 chain.from_iterable( |
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96 (safe_indexing(a, train), safe_indexing(a, test)) for a in new_arrays |
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97 ) |
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98 ) |
26
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99 else: |
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100 rval = train_test_split(*new_arrays, **kwargs) |
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101 |
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102 for pos in nones: |
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103 rval[pos * 2: 2] = [None, None] |
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104 |
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105 return rval |
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106 |
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107 |
35
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108 def main( |
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109 inputs, |
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110 infile_estimator, |
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111 infile1, |
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112 infile2, |
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113 outfile_result, |
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114 outfile_object=None, |
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"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
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115 outfile_weights=None, |
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"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
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116 groups=None, |
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117 ref_seq=None, |
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"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
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118 intervals=None, |
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119 targets=None, |
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120 fasta_path=None, |
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121 ): |
26
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122 """ |
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123 Parameter |
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124 --------- |
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125 inputs : str |
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126 File path to galaxy tool parameter |
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127 |
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128 infile_estimator : str |
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129 File path to estimator |
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130 |
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131 infile1 : str |
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132 File path to dataset containing features |
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133 |
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134 infile2 : str |
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135 File path to dataset containing target values |
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136 |
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137 outfile_result : str |
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138 File path to save the results, either cv_results or test result |
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139 |
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140 outfile_object : str, optional |
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141 File path to save searchCV object |
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142 |
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143 outfile_weights : str, optional |
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144 File path to save deep learning model weights |
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145 |
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146 groups : str |
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147 File path to dataset containing groups labels |
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148 |
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149 ref_seq : str |
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150 File path to dataset containing genome sequence file |
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151 |
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152 intervals : str |
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153 File path to dataset containing interval file |
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154 |
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155 targets : str |
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156 File path to dataset compressed target bed file |
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157 |
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158 fasta_path : str |
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159 File path to dataset containing fasta file |
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planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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160 """ |
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161 warnings.simplefilter("ignore") |
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162 |
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163 with open(inputs, "r") as param_handler: |
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164 params = json.load(param_handler) |
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165 |
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166 # load estimator |
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167 with open(infile_estimator, "rb") as estimator_handler: |
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168 estimator = load_model(estimator_handler) |
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169 |
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170 # swap hyperparameter |
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171 swapping = params["experiment_schemes"]["hyperparams_swapping"] |
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172 swap_params = _eval_swap_params(swapping) |
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173 estimator.set_params(**swap_params) |
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174 |
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175 estimator_params = estimator.get_params() |
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176 |
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177 # store read dataframe object |
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178 loaded_df = {} |
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179 |
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180 input_type = params["input_options"]["selected_input"] |
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181 # tabular input |
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182 if input_type == "tabular": |
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183 header = "infer" if params["input_options"]["header1"] else None |
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184 column_option = params["input_options"]["column_selector_options_1"][ |
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185 "selected_column_selector_option" |
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186 ] |
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187 if column_option in [ |
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188 "by_index_number", |
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189 "all_but_by_index_number", |
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190 "by_header_name", |
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191 "all_but_by_header_name", |
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192 ]: |
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193 c = params["input_options"]["column_selector_options_1"]["col1"] |
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194 else: |
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195 c = None |
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196 |
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197 df_key = infile1 + repr(header) |
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198 df = pd.read_csv(infile1, sep="\t", header=header, parse_dates=True) |
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199 loaded_df[df_key] = df |
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200 |
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201 X = read_columns(df, c=c, c_option=column_option).astype(float) |
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202 # sparse input |
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203 elif input_type == "sparse": |
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204 X = mmread(open(infile1, "r")) |
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205 |
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206 # fasta_file input |
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207 elif input_type == "seq_fasta": |
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208 pyfaidx = get_module("pyfaidx") |
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209 sequences = pyfaidx.Fasta(fasta_path) |
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210 n_seqs = len(sequences.keys()) |
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211 X = np.arange(n_seqs)[:, np.newaxis] |
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212 for param in estimator_params.keys(): |
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213 if param.endswith("fasta_path"): |
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214 estimator.set_params(**{param: fasta_path}) |
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215 break |
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216 else: |
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217 raise ValueError( |
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218 "The selected estimator doesn't support " |
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219 "fasta file input! Please consider using " |
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220 "KerasGBatchClassifier with " |
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221 "FastaDNABatchGenerator/FastaProteinBatchGenerator " |
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222 "or having GenomeOneHotEncoder/ProteinOneHotEncoder " |
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223 "in pipeline!" |
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224 ) |
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225 |
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226 elif input_type == "refseq_and_interval": |
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227 path_params = { |
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228 "data_batch_generator__ref_genome_path": ref_seq, |
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229 "data_batch_generator__intervals_path": intervals, |
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230 "data_batch_generator__target_path": targets, |
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231 } |
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232 estimator.set_params(**path_params) |
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233 n_intervals = sum(1 for line in open(intervals)) |
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234 X = np.arange(n_intervals)[:, np.newaxis] |
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235 |
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236 # Get target y |
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237 header = "infer" if params["input_options"]["header2"] else None |
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238 column_option = params["input_options"]["column_selector_options_2"][ |
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239 "selected_column_selector_option2" |
19d6c2745d34
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
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240 ] |
19d6c2745d34
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
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241 if column_option in [ |
19d6c2745d34
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
bgruening
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242 "by_index_number", |
19d6c2745d34
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
bgruening
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243 "all_but_by_index_number", |
19d6c2745d34
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
bgruening
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244 "by_header_name", |
19d6c2745d34
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
bgruening
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245 "all_but_by_header_name", |
19d6c2745d34
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
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246 ]: |
19d6c2745d34
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
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247 c = params["input_options"]["column_selector_options_2"]["col2"] |
26
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248 else: |
dde0f1654d18
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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249 c = None |
dde0f1654d18
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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250 |
dde0f1654d18
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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251 df_key = infile2 + repr(header) |
dde0f1654d18
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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252 if df_key in loaded_df: |
dde0f1654d18
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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253 infile2 = loaded_df[df_key] |
dde0f1654d18
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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254 else: |
35
19d6c2745d34
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
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255 infile2 = pd.read_csv(infile2, sep="\t", header=header, parse_dates=True) |
26
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256 loaded_df[df_key] = infile2 |
dde0f1654d18
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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257 |
37
4ecc0ce9d0a2
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ea12f973df4b97a2691d9e4ce6bf6fae59d57717"
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258 y = read_columns( |
4ecc0ce9d0a2
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ea12f973df4b97a2691d9e4ce6bf6fae59d57717"
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259 infile2, c=c, c_option=column_option, sep="\t", header=header, parse_dates=True |
4ecc0ce9d0a2
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ea12f973df4b97a2691d9e4ce6bf6fae59d57717"
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260 ) |
26
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planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
bgruening
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261 if len(y.shape) == 2 and y.shape[1] == 1: |
dde0f1654d18
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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262 y = y.ravel() |
35
19d6c2745d34
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
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263 if input_type == "refseq_and_interval": |
19d6c2745d34
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
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264 estimator.set_params(data_batch_generator__features=y.ravel().tolist()) |
26
dde0f1654d18
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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265 y = None |
dde0f1654d18
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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266 # end y |
dde0f1654d18
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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267 |
dde0f1654d18
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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268 # load groups |
dde0f1654d18
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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269 if groups: |
35
19d6c2745d34
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
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270 groups_selector = ( |
19d6c2745d34
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
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271 params["experiment_schemes"]["test_split"]["split_algos"] |
19d6c2745d34
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
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272 ).pop("groups_selector") |
26
dde0f1654d18
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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273 |
35
19d6c2745d34
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
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274 header = "infer" if groups_selector["header_g"] else None |
19d6c2745d34
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
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275 column_option = groups_selector["column_selector_options_g"][ |
19d6c2745d34
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
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276 "selected_column_selector_option_g" |
19d6c2745d34
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
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277 ] |
19d6c2745d34
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
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278 if column_option in [ |
19d6c2745d34
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
bgruening
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279 "by_index_number", |
19d6c2745d34
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
bgruening
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280 "all_but_by_index_number", |
19d6c2745d34
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
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281 "by_header_name", |
19d6c2745d34
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
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282 "all_but_by_header_name", |
19d6c2745d34
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
bgruening
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283 ]: |
19d6c2745d34
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
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284 c = groups_selector["column_selector_options_g"]["col_g"] |
26
dde0f1654d18
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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285 else: |
dde0f1654d18
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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286 c = None |
dde0f1654d18
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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287 |
dde0f1654d18
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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288 df_key = groups + repr(header) |
dde0f1654d18
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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289 if df_key in loaded_df: |
dde0f1654d18
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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290 groups = loaded_df[df_key] |
dde0f1654d18
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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291 |
37
4ecc0ce9d0a2
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ea12f973df4b97a2691d9e4ce6bf6fae59d57717"
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292 groups = read_columns( |
4ecc0ce9d0a2
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ea12f973df4b97a2691d9e4ce6bf6fae59d57717"
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293 groups, |
4ecc0ce9d0a2
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ea12f973df4b97a2691d9e4ce6bf6fae59d57717"
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294 c=c, |
4ecc0ce9d0a2
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ea12f973df4b97a2691d9e4ce6bf6fae59d57717"
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295 c_option=column_option, |
4ecc0ce9d0a2
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ea12f973df4b97a2691d9e4ce6bf6fae59d57717"
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296 sep="\t", |
4ecc0ce9d0a2
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ea12f973df4b97a2691d9e4ce6bf6fae59d57717"
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297 header=header, |
4ecc0ce9d0a2
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ea12f973df4b97a2691d9e4ce6bf6fae59d57717"
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298 parse_dates=True, |
4ecc0ce9d0a2
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ea12f973df4b97a2691d9e4ce6bf6fae59d57717"
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299 ) |
26
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300 groups = groups.ravel() |
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planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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301 |
dde0f1654d18
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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302 # del loaded_df |
dde0f1654d18
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303 del loaded_df |
dde0f1654d18
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304 |
dde0f1654d18
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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305 # handle memory |
dde0f1654d18
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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306 memory = joblib.Memory(location=CACHE_DIR, verbose=0) |
dde0f1654d18
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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307 # cache iraps_core fits could increase search speed significantly |
35
19d6c2745d34
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
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308 if estimator.__class__.__name__ == "IRAPSClassifier": |
26
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planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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309 estimator.set_params(memory=memory) |
dde0f1654d18
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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310 else: |
dde0f1654d18
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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311 # For iraps buried in pipeline |
dde0f1654d18
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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312 new_params = {} |
dde0f1654d18
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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313 for p, v in estimator_params.items(): |
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19d6c2745d34
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
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314 if p.endswith("memory"): |
26
dde0f1654d18
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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315 # for case of `__irapsclassifier__memory` |
35
19d6c2745d34
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
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316 if len(p) > 8 and p[:-8].endswith("irapsclassifier"): |
26
dde0f1654d18
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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317 # cache iraps_core fits could increase search |
dde0f1654d18
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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318 # speed significantly |
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319 new_params[p] = memory |
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320 # security reason, we don't want memory being |
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321 # modified unexpectedly |
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322 elif v: |
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323 new_params[p] = None |
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324 # handle n_jobs |
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325 elif p.endswith("n_jobs"): |
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326 # For now, 1 CPU is suggested for iprasclassifier |
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327 if len(p) > 8 and p[:-8].endswith("irapsclassifier"): |
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328 new_params[p] = 1 |
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329 else: |
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330 new_params[p] = N_JOBS |
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331 # for security reason, types of callback are limited |
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332 elif p.endswith("callbacks"): |
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333 for cb in v: |
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334 cb_type = cb["callback_selection"]["callback_type"] |
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335 if cb_type not in ALLOWED_CALLBACKS: |
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336 raise ValueError("Prohibited callback type: %s!" % cb_type) |
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337 |
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338 estimator.set_params(**new_params) |
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339 |
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340 # handle scorer, convert to scorer dict |
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341 # Check if scoring is specified |
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342 scoring = params["experiment_schemes"]["metrics"].get("scoring", None) |
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343 if scoring is not None: |
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344 # get_scoring() expects secondary_scoring to be a comma separated string (not a list) |
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345 # Check if secondary_scoring is specified |
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346 secondary_scoring = scoring.get("secondary_scoring", None) |
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347 if secondary_scoring is not None: |
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348 # 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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349 scoring["secondary_scoring"] = ",".join(scoring["secondary_scoring"]) |
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350 scorer = get_scoring(scoring) |
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351 scorer, _ = _check_multimetric_scoring(estimator, scoring=scorer) |
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352 |
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353 # handle test (first) split |
35
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354 test_split_options = params["experiment_schemes"]["test_split"]["split_algos"] |
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355 |
35
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356 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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357 test_split_options["labels"] = groups |
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358 if test_split_options["shuffle"] == "stratified": |
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359 if y is not None: |
35
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360 test_split_options["labels"] = y |
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361 else: |
35
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362 raise ValueError( |
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363 "Stratified shuffle split is not " "applicable on empty target values!" |
19d6c2745d34
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
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364 ) |
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365 |
37
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366 ( |
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367 X_train, |
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368 X_test, |
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"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ea12f973df4b97a2691d9e4ce6bf6fae59d57717"
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369 y_train, |
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"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ea12f973df4b97a2691d9e4ce6bf6fae59d57717"
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370 y_test, |
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"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ea12f973df4b97a2691d9e4ce6bf6fae59d57717"
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371 groups_train, |
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"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ea12f973df4b97a2691d9e4ce6bf6fae59d57717"
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372 _groups_test, |
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"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ea12f973df4b97a2691d9e4ce6bf6fae59d57717"
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373 ) = train_test_split_none(X, y, groups, **test_split_options) |
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374 |
35
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375 exp_scheme = params["experiment_schemes"]["selected_exp_scheme"] |
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376 |
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377 # handle validation (second) split |
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378 if exp_scheme == "train_val_test": |
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379 val_split_options = params["experiment_schemes"]["val_split"]["split_algos"] |
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380 |
35
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381 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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382 val_split_options["labels"] = groups_train |
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383 if val_split_options["shuffle"] == "stratified": |
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384 if y_train is not None: |
35
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385 val_split_options["labels"] = y_train |
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386 else: |
35
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387 raise ValueError( |
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388 "Stratified shuffle split is not " |
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389 "applicable on empty target values!" |
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390 ) |
26
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391 |
35
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392 ( |
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"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
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393 X_train, |
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394 X_val, |
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395 y_train, |
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396 y_val, |
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"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
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397 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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398 _groups_val, |
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"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
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399 ) = train_test_split_none(X_train, y_train, groups_train, **val_split_options) |
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400 |
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planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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401 # 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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402 if hasattr(estimator, "validation_data"): |
19d6c2745d34
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
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403 if exp_scheme == "train_val_test": |
19d6c2745d34
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
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404 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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405 else: |
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"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
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406 estimator.fit(X_train, y_train, validation_data=(X_test, y_test)) |
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planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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407 else: |
dde0f1654d18
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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408 estimator.fit(X_train, y_train) |
dde0f1654d18
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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409 |
35
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"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
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410 if hasattr(estimator, "evaluate"): |
19d6c2745d34
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
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411 scores = estimator.evaluate( |
19d6c2745d34
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
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412 X_test, y_test=y_test, scorer=scorer, is_multimetric=True |
19d6c2745d34
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
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413 ) |
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414 else: |
35
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"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
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415 scores = _score(estimator, X_test, y_test, scorer, is_multimetric=True) |
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planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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416 # handle output |
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417 for name, score in scores.items(): |
dde0f1654d18
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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418 scores[name] = [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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419 df = pd.DataFrame(scores) |
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planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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420 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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421 df.to_csv(path_or_buf=outfile_result, sep="\t", header=True, index=False) |
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422 |
dde0f1654d18
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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423 memory.clear(warn=False) |
dde0f1654d18
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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424 |
dde0f1654d18
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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425 if outfile_object: |
dde0f1654d18
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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426 main_est = estimator |
dde0f1654d18
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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427 if isinstance(estimator, pipeline.Pipeline): |
dde0f1654d18
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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428 main_est = estimator.steps[-1][-1] |
dde0f1654d18
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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429 |
35
19d6c2745d34
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
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430 if hasattr(main_est, "model_") and hasattr(main_est, "save_weights"): |
26
dde0f1654d18
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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431 if outfile_weights: |
dde0f1654d18
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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432 main_est.save_weights(outfile_weights) |
35
19d6c2745d34
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
bgruening
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433 if getattr(main_est, "model_", None): |
19d6c2745d34
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
bgruening
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|
434 del main_est.model_ |
19d6c2745d34
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
bgruening
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435 if getattr(main_est, "fit_params", None): |
19d6c2745d34
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
bgruening
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|
436 del main_est.fit_params |
19d6c2745d34
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
bgruening
parents:
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437 if getattr(main_est, "model_class_", None): |
19d6c2745d34
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
bgruening
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438 del main_est.model_class_ |
19d6c2745d34
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
bgruening
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439 if getattr(main_est, "validation_data", None): |
19d6c2745d34
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
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440 del main_est.validation_data |
19d6c2745d34
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
bgruening
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441 if getattr(main_est, "data_generator_", None): |
26
dde0f1654d18
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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442 del main_est.data_generator_ |
dde0f1654d18
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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443 |
35
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"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
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444 with open(outfile_object, "wb") as output_handler: |
19d6c2745d34
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
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445 pickle.dump(estimator, output_handler, pickle.HIGHEST_PROTOCOL) |
26
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446 |
dde0f1654d18
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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447 |
35
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"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
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448 if __name__ == "__main__": |
26
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449 aparser = argparse.ArgumentParser() |
dde0f1654d18
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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450 aparser.add_argument("-i", "--inputs", dest="inputs", required=True) |
dde0f1654d18
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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451 aparser.add_argument("-e", "--estimator", dest="infile_estimator") |
dde0f1654d18
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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452 aparser.add_argument("-X", "--infile1", dest="infile1") |
dde0f1654d18
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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453 aparser.add_argument("-y", "--infile2", dest="infile2") |
dde0f1654d18
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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454 aparser.add_argument("-O", "--outfile_result", dest="outfile_result") |
dde0f1654d18
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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455 aparser.add_argument("-o", "--outfile_object", dest="outfile_object") |
dde0f1654d18
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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456 aparser.add_argument("-w", "--outfile_weights", dest="outfile_weights") |
dde0f1654d18
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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457 aparser.add_argument("-g", "--groups", dest="groups") |
dde0f1654d18
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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458 aparser.add_argument("-r", "--ref_seq", dest="ref_seq") |
dde0f1654d18
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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459 aparser.add_argument("-b", "--intervals", dest="intervals") |
dde0f1654d18
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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460 aparser.add_argument("-t", "--targets", dest="targets") |
dde0f1654d18
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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461 aparser.add_argument("-f", "--fasta_path", dest="fasta_path") |
dde0f1654d18
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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462 args = aparser.parse_args() |
dde0f1654d18
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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463 |
35
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464 main( |
19d6c2745d34
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
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465 args.inputs, |
19d6c2745d34
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
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466 args.infile_estimator, |
19d6c2745d34
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
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467 args.infile1, |
19d6c2745d34
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
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468 args.infile2, |
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"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
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469 args.outfile_result, |
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"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
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470 outfile_object=args.outfile_object, |
19d6c2745d34
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
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471 outfile_weights=args.outfile_weights, |
19d6c2745d34
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
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472 groups=args.groups, |
19d6c2745d34
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
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473 ref_seq=args.ref_seq, |
19d6c2745d34
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
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474 intervals=args.intervals, |
19d6c2745d34
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
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475 targets=args.targets, |
19d6c2745d34
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
bgruening
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476 fasta_path=args.fasta_path, |
19d6c2745d34
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
bgruening
parents:
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477 ) |