Mercurial > repos > bgruening > sklearn_numeric_clustering
annotate keras_train_and_eval.py @ 38:4bbaf77573ef draft
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 8850f42c2c3763e614f7454c9c006f3d2ff572c0
author | bgruening |
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date | Fri, 27 May 2022 11:51:48 +0000 |
parents | 73e7f1c76ece |
children | 06d772036a62 |
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"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
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1 import argparse |
83938131dd46
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
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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 |
83938131dd46
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
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4 import pickle |
83938131dd46
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
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5 import warnings |
83938131dd46
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
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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 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
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7 |
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8 import joblib |
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9 import numpy as np |
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"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 208a8d348e7c7a182cfbe1b6f17868146428a7e2"
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10 import pandas as pd |
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11 from galaxy_ml.externals.selene_sdk.utils import compute_score |
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"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
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12 from galaxy_ml.keras_galaxy_models import _predict_generator |
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13 from galaxy_ml.model_validations import train_test_split |
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14 from galaxy_ml.utils import (clean_params, get_main_estimator, |
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15 get_module, get_scoring, load_model, read_columns, |
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"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ea12f973df4b97a2691d9e4ce6bf6fae59d57717"
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16 SafeEval, try_get_attr) |
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17 from scipy.io import mmread |
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18 from sklearn.metrics.scorer import _check_multimetric_scoring |
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19 from sklearn.model_selection import _search, _validation |
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20 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 208a8d348e7c7a182cfbe1b6f17868146428a7e2"
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21 from sklearn.pipeline import Pipeline |
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22 from sklearn.utils import indexable, safe_indexing |
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23 |
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24 _fit_and_score = try_get_attr("galaxy_ml.model_validations", "_fit_and_score") |
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25 setattr(_search, "_fit_and_score", _fit_and_score) |
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26 setattr(_validation, "_fit_and_score", _fit_and_score) |
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27 |
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28 N_JOBS = int(os.environ.get("GALAXY_SLOTS", 1)) |
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29 CACHE_DIR = os.path.join(os.getcwd(), "cached") |
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30 del os |
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31 NON_SEARCHABLE = ("n_jobs", "pre_dispatch", "memory", "_path", "nthread", "callbacks") |
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32 ALLOWED_CALLBACKS = ( |
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33 "EarlyStopping", |
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34 "TerminateOnNaN", |
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35 "ReduceLROnPlateau", |
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36 "CSVLogger", |
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37 "None", |
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38 ) |
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39 |
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40 |
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41 def _eval_swap_params(params_builder): |
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42 swap_params = {} |
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43 |
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44 for p in params_builder["param_set"]: |
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45 swap_value = p["sp_value"].strip() |
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46 if swap_value == "": |
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47 continue |
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48 |
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49 param_name = p["sp_name"] |
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50 if param_name.lower().endswith(NON_SEARCHABLE): |
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51 warnings.warn( |
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52 "Warning: `%s` is not eligible for search and was " |
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53 "omitted!" % param_name |
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54 ) |
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55 continue |
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56 |
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57 if not swap_value.startswith(":"): |
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58 safe_eval = SafeEval(load_scipy=True, load_numpy=True) |
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59 ev = safe_eval(swap_value) |
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60 else: |
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61 # Have `:` before search list, asks for estimator evaluatio |
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62 safe_eval_es = SafeEval(load_estimators=True) |
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63 swap_value = swap_value[1:].strip() |
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64 # TODO maybe add regular express check |
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65 ev = safe_eval_es(swap_value) |
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66 |
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67 swap_params[param_name] = ev |
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68 |
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69 return swap_params |
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70 |
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71 |
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72 def train_test_split_none(*arrays, **kwargs): |
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73 """extend train_test_split to take None arrays |
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74 and support split by group names. |
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75 """ |
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76 nones = [] |
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77 new_arrays = [] |
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78 for idx, arr in enumerate(arrays): |
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79 if arr is None: |
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80 nones.append(idx) |
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81 else: |
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"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
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82 new_arrays.append(arr) |
83938131dd46
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83 |
34
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84 if kwargs["shuffle"] == "None": |
816b65d52c33
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
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85 kwargs["shuffle"] = None |
31
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86 |
34
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"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
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87 group_names = kwargs.pop("group_names", None) |
31
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"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
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88 |
83938131dd46
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
bgruening
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89 if group_names is not None and group_names.strip(): |
34
816b65d52c33
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
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90 group_names = [name.strip() for name in group_names.split(",")] |
31
83938131dd46
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
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91 new_arrays = indexable(*new_arrays) |
34
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"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
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92 groups = kwargs["labels"] |
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"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
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93 n_samples = new_arrays[0].shape[0] |
83938131dd46
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
bgruening
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94 index_arr = np.arange(n_samples) |
83938131dd46
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
bgruening
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95 test = index_arr[np.isin(groups, group_names)] |
83938131dd46
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
bgruening
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96 train = index_arr[~np.isin(groups, group_names)] |
36
73e7f1c76ece
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ea12f973df4b97a2691d9e4ce6bf6fae59d57717"
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97 rval = list( |
73e7f1c76ece
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ea12f973df4b97a2691d9e4ce6bf6fae59d57717"
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98 chain.from_iterable( |
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"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ea12f973df4b97a2691d9e4ce6bf6fae59d57717"
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99 (safe_indexing(a, train), safe_indexing(a, test)) for a in new_arrays |
73e7f1c76ece
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ea12f973df4b97a2691d9e4ce6bf6fae59d57717"
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100 ) |
73e7f1c76ece
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ea12f973df4b97a2691d9e4ce6bf6fae59d57717"
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101 ) |
31
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102 else: |
83938131dd46
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
bgruening
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103 rval = train_test_split(*new_arrays, **kwargs) |
83938131dd46
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
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104 |
83938131dd46
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
bgruening
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105 for pos in nones: |
35
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"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 208a8d348e7c7a182cfbe1b6f17868146428a7e2"
bgruening
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106 rval[pos * 2: 2] = [None, None] |
31
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"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
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107 |
83938131dd46
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
bgruening
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108 return rval |
83938131dd46
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
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109 |
83938131dd46
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
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110 |
83938131dd46
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
bgruening
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111 def _evaluate(y_true, pred_probas, scorer, is_multimetric=True): |
34
816b65d52c33
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
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112 """output scores based on input scorer |
31
83938131dd46
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113 |
83938131dd46
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
bgruening
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114 Parameters |
83938131dd46
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
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115 ---------- |
83938131dd46
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
bgruening
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116 y_true : array |
83938131dd46
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
bgruening
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117 True label or target values |
83938131dd46
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
bgruening
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118 pred_probas : array |
83938131dd46
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
bgruening
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119 Prediction values, probability for classification problem |
83938131dd46
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
bgruening
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120 scorer : dict |
83938131dd46
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
bgruening
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121 dict of `sklearn.metrics.scorer.SCORER` |
83938131dd46
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
bgruening
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122 is_multimetric : bool, default is True |
83938131dd46
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
bgruening
parents:
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|
123 """ |
83938131dd46
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
bgruening
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124 if y_true.ndim == 1 or y_true.shape[-1] == 1: |
83938131dd46
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
bgruening
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125 pred_probas = pred_probas.ravel() |
34
816b65d52c33
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
bgruening
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126 pred_labels = (pred_probas > 0.5).astype("int32") |
816b65d52c33
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
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127 targets = y_true.ravel().astype("int32") |
31
83938131dd46
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
bgruening
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128 if not is_multimetric: |
36
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"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ea12f973df4b97a2691d9e4ce6bf6fae59d57717"
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129 preds = ( |
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130 pred_labels |
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"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ea12f973df4b97a2691d9e4ce6bf6fae59d57717"
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131 if scorer.__class__.__name__ == "_PredictScorer" |
73e7f1c76ece
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ea12f973df4b97a2691d9e4ce6bf6fae59d57717"
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132 else pred_probas |
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"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ea12f973df4b97a2691d9e4ce6bf6fae59d57717"
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|
133 ) |
31
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bgruening
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134 score = scorer._score_func(targets, preds, **scorer._kwargs) |
83938131dd46
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
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135 |
83938131dd46
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
bgruening
parents:
diff
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|
136 return score |
83938131dd46
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
bgruening
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137 else: |
83938131dd46
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
bgruening
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138 scores = {} |
83938131dd46
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
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139 for name, one_scorer in scorer.items(): |
36
73e7f1c76ece
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ea12f973df4b97a2691d9e4ce6bf6fae59d57717"
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140 preds = ( |
73e7f1c76ece
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ea12f973df4b97a2691d9e4ce6bf6fae59d57717"
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141 pred_labels |
73e7f1c76ece
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ea12f973df4b97a2691d9e4ce6bf6fae59d57717"
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142 if one_scorer.__class__.__name__ == "_PredictScorer" |
73e7f1c76ece
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ea12f973df4b97a2691d9e4ce6bf6fae59d57717"
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143 else pred_probas |
73e7f1c76ece
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ea12f973df4b97a2691d9e4ce6bf6fae59d57717"
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|
144 ) |
34
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"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
bgruening
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145 score = one_scorer._score_func(targets, preds, **one_scorer._kwargs) |
31
83938131dd46
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
bgruening
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146 scores[name] = score |
83938131dd46
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
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147 |
83938131dd46
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
bgruening
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|
148 # TODO: multi-class metrics |
83938131dd46
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
bgruening
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149 # multi-label |
83938131dd46
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
bgruening
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|
150 else: |
34
816b65d52c33
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
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151 pred_labels = (pred_probas > 0.5).astype("int32") |
816b65d52c33
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
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152 targets = y_true.astype("int32") |
31
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153 if not is_multimetric: |
36
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"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ea12f973df4b97a2691d9e4ce6bf6fae59d57717"
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154 preds = ( |
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155 pred_labels |
73e7f1c76ece
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ea12f973df4b97a2691d9e4ce6bf6fae59d57717"
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156 if scorer.__class__.__name__ == "_PredictScorer" |
73e7f1c76ece
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ea12f973df4b97a2691d9e4ce6bf6fae59d57717"
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157 else pred_probas |
73e7f1c76ece
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ea12f973df4b97a2691d9e4ce6bf6fae59d57717"
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|
158 ) |
34
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"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
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159 score, _ = compute_score(preds, targets, scorer._score_func) |
31
83938131dd46
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
bgruening
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|
160 return score |
83938131dd46
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
bgruening
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|
161 else: |
83938131dd46
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
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162 scores = {} |
83938131dd46
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
bgruening
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|
163 for name, one_scorer in scorer.items(): |
36
73e7f1c76ece
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ea12f973df4b97a2691d9e4ce6bf6fae59d57717"
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164 preds = ( |
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165 pred_labels |
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166 if one_scorer.__class__.__name__ == "_PredictScorer" |
73e7f1c76ece
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ea12f973df4b97a2691d9e4ce6bf6fae59d57717"
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167 else pred_probas |
73e7f1c76ece
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168 ) |
34
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169 score, _ = compute_score(preds, targets, one_scorer._score_func) |
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170 scores[name] = score |
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171 |
83938131dd46
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172 return scores |
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173 |
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174 |
34
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175 def main( |
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176 inputs, |
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177 infile_estimator, |
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178 infile1, |
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179 infile2, |
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180 outfile_result, |
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181 outfile_object=None, |
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182 outfile_weights=None, |
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183 outfile_y_true=None, |
816b65d52c33
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
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184 outfile_y_preds=None, |
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185 groups=None, |
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186 ref_seq=None, |
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187 intervals=None, |
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188 targets=None, |
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189 fasta_path=None, |
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190 ): |
31
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191 """ |
83938131dd46
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192 Parameter |
83938131dd46
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193 --------- |
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194 inputs : str |
83938131dd46
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195 File path to galaxy tool parameter |
83938131dd46
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196 |
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197 infile_estimator : str |
83938131dd46
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198 File path to estimator |
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199 |
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200 infile1 : str |
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201 File path to dataset containing features |
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202 |
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203 infile2 : str |
83938131dd46
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204 File path to dataset containing target values |
83938131dd46
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205 |
83938131dd46
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206 outfile_result : str |
83938131dd46
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207 File path to save the results, either cv_results or test result |
83938131dd46
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
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208 |
83938131dd46
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209 outfile_object : str, optional |
83938131dd46
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
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210 File path to save searchCV object |
83938131dd46
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
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211 |
83938131dd46
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212 outfile_weights : str, optional |
83938131dd46
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
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213 File path to save deep learning model weights |
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214 |
83938131dd46
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215 outfile_y_true : str, optional |
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"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
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216 File path to target values for prediction |
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217 |
83938131dd46
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218 outfile_y_preds : str, optional |
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219 File path to save deep learning model weights |
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220 |
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221 groups : str |
83938131dd46
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222 File path to dataset containing groups labels |
83938131dd46
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223 |
83938131dd46
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224 ref_seq : str |
83938131dd46
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
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225 File path to dataset containing genome sequence file |
83938131dd46
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
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226 |
83938131dd46
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227 intervals : str |
83938131dd46
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
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228 File path to dataset containing interval file |
83938131dd46
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229 |
83938131dd46
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230 targets : str |
83938131dd46
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
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231 File path to dataset compressed target bed file |
83938131dd46
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
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232 |
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233 fasta_path : str |
83938131dd46
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234 File path to dataset containing fasta file |
83938131dd46
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
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235 """ |
34
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236 warnings.simplefilter("ignore") |
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237 |
34
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238 with open(inputs, "r") as param_handler: |
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239 params = json.load(param_handler) |
83938131dd46
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
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240 |
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241 # load estimator |
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242 with open(infile_estimator, "rb") as estimator_handler: |
31
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243 estimator = load_model(estimator_handler) |
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244 |
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245 estimator = clean_params(estimator) |
83938131dd46
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
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246 |
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247 # swap hyperparameter |
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248 swapping = params["experiment_schemes"]["hyperparams_swapping"] |
31
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249 swap_params = _eval_swap_params(swapping) |
83938131dd46
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
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250 estimator.set_params(**swap_params) |
83938131dd46
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
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251 |
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252 estimator_params = estimator.get_params() |
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253 |
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254 # store read dataframe object |
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255 loaded_df = {} |
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256 |
34
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257 input_type = params["input_options"]["selected_input"] |
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258 # tabular input |
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259 if input_type == "tabular": |
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260 header = "infer" if params["input_options"]["header1"] else None |
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261 column_option = params["input_options"]["column_selector_options_1"][ |
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262 "selected_column_selector_option" |
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263 ] |
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264 if column_option in [ |
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265 "by_index_number", |
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266 "all_but_by_index_number", |
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267 "by_header_name", |
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268 "all_but_by_header_name", |
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269 ]: |
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270 c = params["input_options"]["column_selector_options_1"]["col1"] |
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271 else: |
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272 c = None |
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273 |
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274 df_key = infile1 + repr(header) |
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275 df = pd.read_csv(infile1, sep="\t", header=header, parse_dates=True) |
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276 loaded_df[df_key] = df |
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277 |
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278 X = read_columns(df, c=c, c_option=column_option).astype(float) |
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279 # sparse input |
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280 elif input_type == "sparse": |
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281 X = mmread(open(infile1, "r")) |
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282 |
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283 # fasta_file input |
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284 elif input_type == "seq_fasta": |
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285 pyfaidx = get_module("pyfaidx") |
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286 sequences = pyfaidx.Fasta(fasta_path) |
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287 n_seqs = len(sequences.keys()) |
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288 X = np.arange(n_seqs)[:, np.newaxis] |
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289 for param in estimator_params.keys(): |
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290 if param.endswith("fasta_path"): |
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291 estimator.set_params(**{param: fasta_path}) |
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292 break |
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293 else: |
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294 raise ValueError( |
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295 "The selected estimator doesn't support " |
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296 "fasta file input! Please consider using " |
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297 "KerasGBatchClassifier with " |
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298 "FastaDNABatchGenerator/FastaProteinBatchGenerator " |
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299 "or having GenomeOneHotEncoder/ProteinOneHotEncoder " |
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300 "in pipeline!" |
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301 ) |
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302 |
34
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303 elif input_type == "refseq_and_interval": |
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304 path_params = { |
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305 "data_batch_generator__ref_genome_path": ref_seq, |
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306 "data_batch_generator__intervals_path": intervals, |
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307 "data_batch_generator__target_path": targets, |
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308 } |
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309 estimator.set_params(**path_params) |
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310 n_intervals = sum(1 for line in open(intervals)) |
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311 X = np.arange(n_intervals)[:, np.newaxis] |
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312 |
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313 # Get target y |
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314 header = "infer" if params["input_options"]["header2"] else None |
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315 column_option = params["input_options"]["column_selector_options_2"][ |
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316 "selected_column_selector_option2" |
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317 ] |
34
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318 if column_option in [ |
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319 "by_index_number", |
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320 "all_but_by_index_number", |
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321 "by_header_name", |
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322 "all_but_by_header_name", |
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323 ]: |
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324 c = params["input_options"]["column_selector_options_2"]["col2"] |
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325 else: |
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326 c = None |
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327 |
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328 df_key = infile2 + repr(header) |
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329 if df_key in loaded_df: |
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330 infile2 = loaded_df[df_key] |
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331 else: |
34
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332 infile2 = pd.read_csv(infile2, sep="\t", header=header, parse_dates=True) |
31
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333 loaded_df[df_key] = infile2 |
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334 |
36
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335 y = read_columns( |
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336 infile2, c=c, c_option=column_option, sep="\t", header=header, parse_dates=True |
73e7f1c76ece
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337 ) |
31
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338 if len(y.shape) == 2 and y.shape[1] == 1: |
83938131dd46
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
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339 y = y.ravel() |
34
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340 if input_type == "refseq_and_interval": |
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341 estimator.set_params(data_batch_generator__features=y.ravel().tolist()) |
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342 y = None |
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343 # end y |
83938131dd46
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344 |
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345 # load groups |
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346 if groups: |
36
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347 groups_selector = ( |
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348 params["experiment_schemes"]["test_split"]["split_algos"] |
73e7f1c76ece
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ea12f973df4b97a2691d9e4ce6bf6fae59d57717"
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349 ).pop("groups_selector") |
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350 |
34
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351 header = "infer" if groups_selector["header_g"] else None |
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352 column_option = groups_selector["column_selector_options_g"][ |
73e7f1c76ece
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ea12f973df4b97a2691d9e4ce6bf6fae59d57717"
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353 "selected_column_selector_option_g" |
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"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ea12f973df4b97a2691d9e4ce6bf6fae59d57717"
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354 ] |
34
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355 if column_option in [ |
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356 "by_index_number", |
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357 "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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358 "by_header_name", |
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359 "all_but_by_header_name", |
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360 ]: |
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361 c = groups_selector["column_selector_options_g"]["col_g"] |
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362 else: |
83938131dd46
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363 c = None |
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364 |
83938131dd46
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365 df_key = groups + repr(header) |
83938131dd46
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
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366 if df_key in loaded_df: |
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"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
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367 groups = loaded_df[df_key] |
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368 |
36
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369 groups = read_columns( |
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370 groups, |
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371 c=c, |
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372 c_option=column_option, |
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"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ea12f973df4b97a2691d9e4ce6bf6fae59d57717"
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373 sep="\t", |
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374 header=header, |
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375 parse_dates=True, |
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"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ea12f973df4b97a2691d9e4ce6bf6fae59d57717"
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376 ) |
31
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377 groups = groups.ravel() |
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378 |
83938131dd46
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379 # del loaded_df |
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380 del loaded_df |
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381 |
83938131dd46
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
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382 # cache iraps_core fits could increase search speed significantly |
83938131dd46
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
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383 memory = joblib.Memory(location=CACHE_DIR, verbose=0) |
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384 main_est = get_main_estimator(estimator) |
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385 if main_est.__class__.__name__ == "IRAPSClassifier": |
31
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386 main_est.set_params(memory=memory) |
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"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
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387 |
83938131dd46
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
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388 # handle scorer, convert to scorer dict |
36
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389 scoring = params["experiment_schemes"]["metrics"]["scoring"] |
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390 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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391 # 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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392 # Check if secondary_scoring is specified |
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"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
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393 secondary_scoring = scoring.get("secondary_scoring", None) |
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"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
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394 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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395 # 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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396 scoring["secondary_scoring"] = ",".join(scoring["secondary_scoring"]) |
816b65d52c33
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
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397 |
31
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398 scorer = get_scoring(scoring) |
83938131dd46
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
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399 scorer, _ = _check_multimetric_scoring(estimator, scoring=scorer) |
83938131dd46
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
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|
400 |
83938131dd46
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
bgruening
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|
401 # handle test (first) split |
34
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402 test_split_options = params["experiment_schemes"]["test_split"]["split_algos"] |
31
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403 |
34
816b65d52c33
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
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404 if test_split_options["shuffle"] == "group": |
816b65d52c33
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
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405 test_split_options["labels"] = groups |
816b65d52c33
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
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406 if test_split_options["shuffle"] == "stratified": |
31
83938131dd46
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407 if y is not None: |
34
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408 test_split_options["labels"] = y |
31
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409 else: |
36
73e7f1c76ece
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ea12f973df4b97a2691d9e4ce6bf6fae59d57717"
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410 raise ValueError( |
73e7f1c76ece
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ea12f973df4b97a2691d9e4ce6bf6fae59d57717"
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411 "Stratified shuffle split is not " "applicable on empty target values!" |
73e7f1c76ece
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ea12f973df4b97a2691d9e4ce6bf6fae59d57717"
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412 ) |
31
83938131dd46
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
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413 |
34
816b65d52c33
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
bgruening
parents:
31
diff
changeset
|
414 ( |
816b65d52c33
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
bgruening
parents:
31
diff
changeset
|
415 X_train, |
816b65d52c33
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
bgruening
parents:
31
diff
changeset
|
416 X_test, |
816b65d52c33
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
bgruening
parents:
31
diff
changeset
|
417 y_train, |
816b65d52c33
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
bgruening
parents:
31
diff
changeset
|
418 y_test, |
816b65d52c33
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
bgruening
parents:
31
diff
changeset
|
419 groups_train, |
816b65d52c33
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
bgruening
parents:
31
diff
changeset
|
420 _groups_test, |
816b65d52c33
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
bgruening
parents:
31
diff
changeset
|
421 ) = train_test_split_none(X, y, groups, **test_split_options) |
31
83938131dd46
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
bgruening
parents:
diff
changeset
|
422 |
34
816b65d52c33
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
bgruening
parents:
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diff
changeset
|
423 exp_scheme = params["experiment_schemes"]["selected_exp_scheme"] |
31
83938131dd46
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
bgruening
parents:
diff
changeset
|
424 |
83938131dd46
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
bgruening
parents:
diff
changeset
|
425 # handle validation (second) split |
34
816b65d52c33
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
bgruening
parents:
31
diff
changeset
|
426 if exp_scheme == "train_val_test": |
816b65d52c33
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
bgruening
parents:
31
diff
changeset
|
427 val_split_options = params["experiment_schemes"]["val_split"]["split_algos"] |
31
83938131dd46
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
bgruening
parents:
diff
changeset
|
428 |
34
816b65d52c33
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
bgruening
parents:
31
diff
changeset
|
429 if val_split_options["shuffle"] == "group": |
816b65d52c33
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
bgruening
parents:
31
diff
changeset
|
430 val_split_options["labels"] = groups_train |
816b65d52c33
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
bgruening
parents:
31
diff
changeset
|
431 if val_split_options["shuffle"] == "stratified": |
31
83938131dd46
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
bgruening
parents:
diff
changeset
|
432 if y_train is not None: |
34
816b65d52c33
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
bgruening
parents:
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|
433 val_split_options["labels"] = y_train |
31
83938131dd46
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
bgruening
parents:
diff
changeset
|
434 else: |
36
73e7f1c76ece
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ea12f973df4b97a2691d9e4ce6bf6fae59d57717"
bgruening
parents:
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diff
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435 raise ValueError( |
73e7f1c76ece
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ea12f973df4b97a2691d9e4ce6bf6fae59d57717"
bgruening
parents:
35
diff
changeset
|
436 "Stratified shuffle split is not " |
73e7f1c76ece
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ea12f973df4b97a2691d9e4ce6bf6fae59d57717"
bgruening
parents:
35
diff
changeset
|
437 "applicable on empty target values!" |
73e7f1c76ece
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ea12f973df4b97a2691d9e4ce6bf6fae59d57717"
bgruening
parents:
35
diff
changeset
|
438 ) |
31
83938131dd46
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
bgruening
parents:
diff
changeset
|
439 |
34
816b65d52c33
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
bgruening
parents:
31
diff
changeset
|
440 ( |
816b65d52c33
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
bgruening
parents:
31
diff
changeset
|
441 X_train, |
816b65d52c33
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
bgruening
parents:
31
diff
changeset
|
442 X_val, |
816b65d52c33
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
bgruening
parents:
31
diff
changeset
|
443 y_train, |
816b65d52c33
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
bgruening
parents:
31
diff
changeset
|
444 y_val, |
816b65d52c33
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
bgruening
parents:
31
diff
changeset
|
445 groups_train, |
816b65d52c33
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
bgruening
parents:
31
diff
changeset
|
446 _groups_val, |
816b65d52c33
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
bgruening
parents:
31
diff
changeset
|
447 ) = train_test_split_none(X_train, y_train, groups_train, **val_split_options) |
31
83938131dd46
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
bgruening
parents:
diff
changeset
|
448 |
83938131dd46
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
bgruening
parents:
diff
changeset
|
449 # train and eval |
34
816b65d52c33
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
bgruening
parents:
31
diff
changeset
|
450 if hasattr(estimator, "validation_data"): |
816b65d52c33
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
bgruening
parents:
31
diff
changeset
|
451 if exp_scheme == "train_val_test": |
816b65d52c33
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
bgruening
parents:
31
diff
changeset
|
452 estimator.fit(X_train, y_train, validation_data=(X_val, y_val)) |
31
83938131dd46
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
bgruening
parents:
diff
changeset
|
453 else: |
34
816b65d52c33
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
bgruening
parents:
31
diff
changeset
|
454 estimator.fit(X_train, y_train, validation_data=(X_test, y_test)) |
31
83938131dd46
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
bgruening
parents:
diff
changeset
|
455 else: |
83938131dd46
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
bgruening
parents:
diff
changeset
|
456 estimator.fit(X_train, y_train) |
83938131dd46
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
bgruening
parents:
diff
changeset
|
457 |
34
816b65d52c33
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
bgruening
parents:
31
diff
changeset
|
458 if hasattr(estimator, "evaluate"): |
31
83938131dd46
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
bgruening
parents:
diff
changeset
|
459 steps = estimator.prediction_steps |
83938131dd46
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
bgruening
parents:
diff
changeset
|
460 batch_size = estimator.batch_size |
36
73e7f1c76ece
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ea12f973df4b97a2691d9e4ce6bf6fae59d57717"
bgruening
parents:
35
diff
changeset
|
461 generator = estimator.data_generator_.flow( |
73e7f1c76ece
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ea12f973df4b97a2691d9e4ce6bf6fae59d57717"
bgruening
parents:
35
diff
changeset
|
462 X_test, y=y_test, batch_size=batch_size |
73e7f1c76ece
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ea12f973df4b97a2691d9e4ce6bf6fae59d57717"
bgruening
parents:
35
diff
changeset
|
463 ) |
73e7f1c76ece
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ea12f973df4b97a2691d9e4ce6bf6fae59d57717"
bgruening
parents:
35
diff
changeset
|
464 predictions, y_true = _predict_generator( |
73e7f1c76ece
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ea12f973df4b97a2691d9e4ce6bf6fae59d57717"
bgruening
parents:
35
diff
changeset
|
465 estimator.model_, generator, steps=steps |
73e7f1c76ece
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ea12f973df4b97a2691d9e4ce6bf6fae59d57717"
bgruening
parents:
35
diff
changeset
|
466 ) |
31
83938131dd46
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
bgruening
parents:
diff
changeset
|
467 scores = _evaluate(y_true, predictions, scorer, is_multimetric=True) |
83938131dd46
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
bgruening
parents:
diff
changeset
|
468 |
83938131dd46
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
bgruening
parents:
diff
changeset
|
469 else: |
34
816b65d52c33
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
bgruening
parents:
31
diff
changeset
|
470 if hasattr(estimator, "predict_proba"): |
31
83938131dd46
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
bgruening
parents:
diff
changeset
|
471 predictions = estimator.predict_proba(X_test) |
83938131dd46
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
bgruening
parents:
diff
changeset
|
472 else: |
83938131dd46
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
bgruening
parents:
diff
changeset
|
473 predictions = estimator.predict(X_test) |
83938131dd46
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
bgruening
parents:
diff
changeset
|
474 |
83938131dd46
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
bgruening
parents:
diff
changeset
|
475 y_true = y_test |
34
816b65d52c33
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
bgruening
parents:
31
diff
changeset
|
476 scores = _score(estimator, X_test, y_test, scorer, is_multimetric=True) |
31
83938131dd46
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
bgruening
parents:
diff
changeset
|
477 if outfile_y_true: |
83938131dd46
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
bgruening
parents:
diff
changeset
|
478 try: |
34
816b65d52c33
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
bgruening
parents:
31
diff
changeset
|
479 pd.DataFrame(y_true).to_csv(outfile_y_true, sep="\t", index=False) |
31
83938131dd46
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
bgruening
parents:
diff
changeset
|
480 pd.DataFrame(predictions).astype(np.float32).to_csv( |
34
816b65d52c33
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
bgruening
parents:
31
diff
changeset
|
481 outfile_y_preds, |
816b65d52c33
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
bgruening
parents:
31
diff
changeset
|
482 sep="\t", |
816b65d52c33
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
bgruening
parents:
31
diff
changeset
|
483 index=False, |
816b65d52c33
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
bgruening
parents:
31
diff
changeset
|
484 float_format="%g", |
816b65d52c33
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
bgruening
parents:
31
diff
changeset
|
485 chunksize=10000, |
816b65d52c33
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
bgruening
parents:
31
diff
changeset
|
486 ) |
31
83938131dd46
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
bgruening
parents:
diff
changeset
|
487 except Exception as e: |
83938131dd46
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
bgruening
parents:
diff
changeset
|
488 print("Error in saving predictions: %s" % e) |
83938131dd46
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
bgruening
parents:
diff
changeset
|
489 |
83938131dd46
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
bgruening
parents:
diff
changeset
|
490 # handle output |
83938131dd46
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
bgruening
parents:
diff
changeset
|
491 for name, score in scores.items(): |
83938131dd46
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
bgruening
parents:
diff
changeset
|
492 scores[name] = [score] |
83938131dd46
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
bgruening
parents:
diff
changeset
|
493 df = pd.DataFrame(scores) |
83938131dd46
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
bgruening
parents:
diff
changeset
|
494 df = df[sorted(df.columns)] |
34
816b65d52c33
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
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495 df.to_csv(path_or_buf=outfile_result, sep="\t", header=True, index=False) |
31
83938131dd46
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
bgruening
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496 |
83938131dd46
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
bgruening
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497 memory.clear(warn=False) |
83938131dd46
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
bgruening
parents:
diff
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498 |
83938131dd46
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
bgruening
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diff
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499 if outfile_object: |
83938131dd46
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
bgruening
parents:
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500 main_est = estimator |
83938131dd46
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
bgruening
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501 if isinstance(estimator, Pipeline): |
83938131dd46
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
bgruening
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502 main_est = estimator.steps[-1][-1] |
83938131dd46
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
bgruening
parents:
diff
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503 |
34
816b65d52c33
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
bgruening
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504 if hasattr(main_est, "model_") and hasattr(main_est, "save_weights"): |
31
83938131dd46
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
bgruening
parents:
diff
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505 if outfile_weights: |
83938131dd46
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
bgruening
parents:
diff
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506 main_est.save_weights(outfile_weights) |
83938131dd46
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
bgruening
parents:
diff
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507 del main_est.model_ |
83938131dd46
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
bgruening
parents:
diff
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508 del main_est.fit_params |
83938131dd46
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
bgruening
parents:
diff
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509 del main_est.model_class_ |
34
816b65d52c33
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
bgruening
parents:
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510 if getattr(main_est, "validation_data", None): |
816b65d52c33
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
bgruening
parents:
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511 del main_est.validation_data |
816b65d52c33
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
bgruening
parents:
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512 if getattr(main_est, "data_generator_", None): |
31
83938131dd46
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
bgruening
parents:
diff
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|
513 del main_est.data_generator_ |
83938131dd46
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
bgruening
parents:
diff
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514 |
34
816b65d52c33
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
bgruening
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515 with open(outfile_object, "wb") as output_handler: |
816b65d52c33
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
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516 pickle.dump(estimator, output_handler, pickle.HIGHEST_PROTOCOL) |
31
83938131dd46
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
bgruening
parents:
diff
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|
517 |
83938131dd46
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
bgruening
parents:
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|
518 |
34
816b65d52c33
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
bgruening
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519 if __name__ == "__main__": |
31
83938131dd46
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
bgruening
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520 aparser = argparse.ArgumentParser() |
83938131dd46
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
bgruening
parents:
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521 aparser.add_argument("-i", "--inputs", dest="inputs", required=True) |
83938131dd46
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
bgruening
parents:
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522 aparser.add_argument("-e", "--estimator", dest="infile_estimator") |
83938131dd46
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
bgruening
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523 aparser.add_argument("-X", "--infile1", dest="infile1") |
83938131dd46
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
bgruening
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524 aparser.add_argument("-y", "--infile2", dest="infile2") |
83938131dd46
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
bgruening
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525 aparser.add_argument("-O", "--outfile_result", dest="outfile_result") |
83938131dd46
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
bgruening
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526 aparser.add_argument("-o", "--outfile_object", dest="outfile_object") |
83938131dd46
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
bgruening
parents:
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527 aparser.add_argument("-w", "--outfile_weights", dest="outfile_weights") |
83938131dd46
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
bgruening
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528 aparser.add_argument("-l", "--outfile_y_true", dest="outfile_y_true") |
83938131dd46
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
bgruening
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529 aparser.add_argument("-p", "--outfile_y_preds", dest="outfile_y_preds") |
83938131dd46
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
bgruening
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530 aparser.add_argument("-g", "--groups", dest="groups") |
83938131dd46
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
bgruening
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531 aparser.add_argument("-r", "--ref_seq", dest="ref_seq") |
83938131dd46
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
bgruening
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532 aparser.add_argument("-b", "--intervals", dest="intervals") |
83938131dd46
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
bgruening
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533 aparser.add_argument("-t", "--targets", dest="targets") |
83938131dd46
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
bgruening
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534 aparser.add_argument("-f", "--fasta_path", dest="fasta_path") |
83938131dd46
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
bgruening
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535 args = aparser.parse_args() |
83938131dd46
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
bgruening
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536 |
34
816b65d52c33
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
bgruening
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537 main( |
816b65d52c33
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
bgruening
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538 args.inputs, |
816b65d52c33
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
bgruening
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539 args.infile_estimator, |
816b65d52c33
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
bgruening
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540 args.infile1, |
816b65d52c33
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
bgruening
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541 args.infile2, |
816b65d52c33
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
bgruening
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542 args.outfile_result, |
816b65d52c33
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
bgruening
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543 outfile_object=args.outfile_object, |
816b65d52c33
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
bgruening
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544 outfile_weights=args.outfile_weights, |
816b65d52c33
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
bgruening
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545 outfile_y_true=args.outfile_y_true, |
816b65d52c33
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
bgruening
parents:
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546 outfile_y_preds=args.outfile_y_preds, |
816b65d52c33
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
bgruening
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547 groups=args.groups, |
816b65d52c33
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
bgruening
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548 ref_seq=args.ref_seq, |
816b65d52c33
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
bgruening
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549 intervals=args.intervals, |
816b65d52c33
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
bgruening
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550 targets=args.targets, |
816b65d52c33
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
bgruening
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551 fasta_path=args.fasta_path, |
816b65d52c33
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
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552 ) |