Mercurial > repos > bgruening > sklearn_stacking_ensemble_models

annotate search_model_validation.py @ 8:6430b9b00d2f draft

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"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 9e28f4466084464d38d3f8db2aff07974be4ba69"
author bgruening
date Wed, 11 Mar 2020 17:24:17 +0000
parents 00819b7f2f55
children b8c92e94ac1d
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47467890f541 planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ab963ec9498bd05d2fb2f24f75adb2fccae7958c
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1 import argparse
47467890f541 planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ab963ec9498bd05d2fb2f24f75adb2fccae7958c
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2 import collections
47467890f541 planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ab963ec9498bd05d2fb2f24f75adb2fccae7958c
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3 import imblearn
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4 import joblib
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47467890f541 planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ab963ec9498bd05d2fb2f24f75adb2fccae7958c
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5 import json
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6 import numpy as np
7
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7 import os
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8 import pandas as pd
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9 import pickle
47467890f541 planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ab963ec9498bd05d2fb2f24f75adb2fccae7958c
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10 import skrebate
47467890f541 planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ab963ec9498bd05d2fb2f24f75adb2fccae7958c
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11 import sys
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12 import warnings
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13 from scipy.io import mmread
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14 from sklearn import (cluster, decomposition, feature_selection,
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15 kernel_approximation, model_selection, preprocessing)
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16 from sklearn.exceptions import FitFailedWarning
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17 from sklearn.model_selection._validation import _score, cross_validate
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18 from sklearn.model_selection import _search, _validation
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19 from sklearn.pipeline import Pipeline
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20
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21 from galaxy_ml.utils import (SafeEval, get_cv, get_scoring, load_model,
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22 read_columns, try_get_attr, get_module,
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23 clean_params, get_main_estimator)
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24
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25
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26 _fit_and_score = try_get_attr('galaxy_ml.model_validations', '_fit_and_score')
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27 setattr(_search, '_fit_and_score', _fit_and_score)
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28 setattr(_validation, '_fit_and_score', _fit_and_score)
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29
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30 N_JOBS = int(os.environ.get('GALAXY_SLOTS', 1))
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31 # handle disk cache
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32 CACHE_DIR = os.path.join(os.getcwd(), 'cached')
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33 del os
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34 NON_SEARCHABLE = ('n_jobs', 'pre_dispatch', 'memory', '_path',
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35 'nthread', 'callbacks')
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38 def _eval_search_params(params_builder):
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39 search_params = {}
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41 for p in params_builder['param_set']:
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42 search_list = p['sp_list'].strip()
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43 if search_list == '':
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44 continue
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46 param_name = p['sp_name']
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47 if param_name.lower().endswith(NON_SEARCHABLE):
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48 print("Warning: `%s` is not eligible for search and was "
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49 "omitted!" % param_name)
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50 continue
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51
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52 if not search_list.startswith(':'):
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53 safe_eval = SafeEval(load_scipy=True, load_numpy=True)
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54 ev = safe_eval(search_list)
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55 search_params[param_name] = ev
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56 else:
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57 # Have `:` before search list, asks for estimator evaluatio
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58 safe_eval_es = SafeEval(load_estimators=True)
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59 search_list = search_list[1:].strip()
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60 # TODO maybe add regular express check
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61 ev = safe_eval_es(search_list)
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62 preprocessings = (
0
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63 preprocessing.StandardScaler(), preprocessing.Binarizer(),
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64 preprocessing.MaxAbsScaler(),
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65 preprocessing.Normalizer(), preprocessing.MinMaxScaler(),
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66 preprocessing.PolynomialFeatures(),
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67 preprocessing.RobustScaler(), feature_selection.SelectKBest(),
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68 feature_selection.GenericUnivariateSelect(),
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69 feature_selection.SelectPercentile(),
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70 feature_selection.SelectFpr(), feature_selection.SelectFdr(),
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71 feature_selection.SelectFwe(),
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72 feature_selection.VarianceThreshold(),
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73 decomposition.FactorAnalysis(random_state=0),
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74 decomposition.FastICA(random_state=0),
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75 decomposition.IncrementalPCA(),
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76 decomposition.KernelPCA(random_state=0, n_jobs=N_JOBS),
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77 decomposition.LatentDirichletAllocation(
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78 random_state=0, n_jobs=N_JOBS),
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79 decomposition.MiniBatchDictionaryLearning(
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80 random_state=0, n_jobs=N_JOBS),
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81 decomposition.MiniBatchSparsePCA(
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82 random_state=0, n_jobs=N_JOBS),
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83 decomposition.NMF(random_state=0),
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84 decomposition.PCA(random_state=0),
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85 decomposition.SparsePCA(random_state=0, n_jobs=N_JOBS),
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86 decomposition.TruncatedSVD(random_state=0),
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87 kernel_approximation.Nystroem(random_state=0),
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88 kernel_approximation.RBFSampler(random_state=0),
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89 kernel_approximation.AdditiveChi2Sampler(),
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90 kernel_approximation.SkewedChi2Sampler(random_state=0),
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91 cluster.FeatureAgglomeration(),
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92 skrebate.ReliefF(n_jobs=N_JOBS),
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93 skrebate.SURF(n_jobs=N_JOBS),
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94 skrebate.SURFstar(n_jobs=N_JOBS),
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95 skrebate.MultiSURF(n_jobs=N_JOBS),
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96 skrebate.MultiSURFstar(n_jobs=N_JOBS),
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97 imblearn.under_sampling.ClusterCentroids(
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98 random_state=0, n_jobs=N_JOBS),
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99 imblearn.under_sampling.CondensedNearestNeighbour(
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100 random_state=0, n_jobs=N_JOBS),
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101 imblearn.under_sampling.EditedNearestNeighbours(
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102 random_state=0, n_jobs=N_JOBS),
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103 imblearn.under_sampling.RepeatedEditedNearestNeighbours(
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104 random_state=0, n_jobs=N_JOBS),
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105 imblearn.under_sampling.AllKNN(random_state=0, n_jobs=N_JOBS),
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106 imblearn.under_sampling.InstanceHardnessThreshold(
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107 random_state=0, n_jobs=N_JOBS),
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108 imblearn.under_sampling.NearMiss(
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109 random_state=0, n_jobs=N_JOBS),
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110 imblearn.under_sampling.NeighbourhoodCleaningRule(
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111 random_state=0, n_jobs=N_JOBS),
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112 imblearn.under_sampling.OneSidedSelection(
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113 random_state=0, n_jobs=N_JOBS),
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114 imblearn.under_sampling.RandomUnderSampler(
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115 random_state=0),
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116 imblearn.under_sampling.TomekLinks(
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117 random_state=0, n_jobs=N_JOBS),
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118 imblearn.over_sampling.ADASYN(random_state=0, n_jobs=N_JOBS),
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119 imblearn.over_sampling.RandomOverSampler(random_state=0),
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120 imblearn.over_sampling.SMOTE(random_state=0, n_jobs=N_JOBS),
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121 imblearn.over_sampling.SVMSMOTE(random_state=0, n_jobs=N_JOBS),
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122 imblearn.over_sampling.BorderlineSMOTE(
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123 random_state=0, n_jobs=N_JOBS),
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124 imblearn.over_sampling.SMOTENC(
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125 categorical_features=[], random_state=0, n_jobs=N_JOBS),
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126 imblearn.combine.SMOTEENN(random_state=0),
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127 imblearn.combine.SMOTETomek(random_state=0))
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128 newlist = []
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129 for obj in ev:
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130 if obj is None:
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131 newlist.append(None)
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132 elif obj == 'all_0':
2
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133 newlist.extend(preprocessings[0:35])
0
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134 elif obj == 'sk_prep_all': # no KernalCenter()
2
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135 newlist.extend(preprocessings[0:7])
0
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136 elif obj == 'fs_all':
2
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137 newlist.extend(preprocessings[7:14])
0
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138 elif obj == 'decomp_all':
2
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139 newlist.extend(preprocessings[14:25])
0
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140 elif obj == 'k_appr_all':
2
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141 newlist.extend(preprocessings[25:29])
0
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142 elif obj == 'reb_all':
2
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143 newlist.extend(preprocessings[30:35])
0
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144 elif obj == 'imb_all':
2
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145 newlist.extend(preprocessings[35:54])
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146 elif type(obj) is int and -1 < obj < len(preprocessings):
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147 newlist.append(preprocessings[obj])
0
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148 elif hasattr(obj, 'get_params'): # user uploaded object
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149 if 'n_jobs' in obj.get_params():
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150 newlist.append(obj.set_params(n_jobs=N_JOBS))
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151 else:
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152 newlist.append(obj)
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153 else:
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154 sys.exit("Unsupported estimator type: %r" % (obj))
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155
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156 search_params[param_name] = newlist
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157
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158 return search_params
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159
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160
7
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161 def _handle_X_y(estimator, params, infile1, infile2, loaded_df={},
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162 ref_seq=None, intervals=None, targets=None,
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163 fasta_path=None):
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164 """read inputs
0
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165
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166 Params
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167 -------
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168 estimator : estimator object
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169 params : dict
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170 Galaxy tool parameter inputs
0
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171 infile1 : str
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172 File path to dataset containing features
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173 infile2 : str
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174 File path to dataset containing target values
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175 loaded_df : dict
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176 Contains loaded DataFrame objects with file path as keys
2
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177 ref_seq : str
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178 File path to dataset containing genome sequence file
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179 interval : str
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180 File path to dataset containing interval file
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181 targets : str
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182 File path to dataset compressed target bed file
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183 fasta_path : str
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184 File path to dataset containing fasta file
0
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185
3
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186
7
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187 Returns
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188 -------
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189 estimator : estimator object after setting new attributes
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190 X : numpy array
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191 y : numpy array
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192 """
2
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193 estimator_params = estimator.get_params()
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194
0
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195 input_type = params['input_options']['selected_input']
2
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196 # tabular input
0
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197 if input_type == 'tabular':
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198 header = 'infer' if params['input_options']['header1'] else None
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199 column_option = (params['input_options']['column_selector_options_1']
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200 ['selected_column_selector_option'])
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201 if column_option in ['by_index_number', 'all_but_by_index_number',
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202 'by_header_name', 'all_but_by_header_name']:
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203 c = params['input_options']['column_selector_options_1']['col1']
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204 else:
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205 c = None
2
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206
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207 df_key = infile1 + repr(header)
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208
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209 if df_key in loaded_df:
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210 infile1 = loaded_df[df_key]
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211
2
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212 df = pd.read_csv(infile1, sep='\t', header=header,
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213 parse_dates=True)
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214 loaded_df[df_key] = df
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215
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216 X = read_columns(df, c=c, c_option=column_option).astype(float)
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217 # sparse input
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218 elif input_type == 'sparse':
0
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219 X = mmread(open(infile1, 'r'))
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220
2
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221 # fasta_file input
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222 elif input_type == 'seq_fasta':
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223 pyfaidx = get_module('pyfaidx')
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224 sequences = pyfaidx.Fasta(fasta_path)
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225 n_seqs = len(sequences.keys())
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226 X = np.arange(n_seqs)[:, np.newaxis]
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227 for param in estimator_params.keys():
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228 if param.endswith('fasta_path'):
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229 estimator.set_params(
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230 **{param: fasta_path})
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231 break
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232 else:
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233 raise ValueError(
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234 "The selected estimator doesn't support "
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235 "fasta file input! Please consider using "
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236 "KerasGBatchClassifier with "
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237 "FastaDNABatchGenerator/FastaProteinBatchGenerator "
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238 "or having GenomeOneHotEncoder/ProteinOneHotEncoder "
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239 "in pipeline!")
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240
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241 elif input_type == 'refseq_and_interval':
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242 path_params = {
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243 'data_batch_generator__ref_genome_path': ref_seq,
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244 'data_batch_generator__intervals_path': intervals,
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245 'data_batch_generator__target_path': targets
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246 }
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247 estimator.set_params(**path_params)
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248 n_intervals = sum(1 for line in open(intervals))
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249 X = np.arange(n_intervals)[:, np.newaxis]
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250
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251 # Get target y
0
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252 header = 'infer' if params['input_options']['header2'] else None
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253 column_option = (params['input_options']['column_selector_options_2']
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254 ['selected_column_selector_option2'])
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255 if column_option in ['by_index_number', 'all_but_by_index_number',
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256 'by_header_name', 'all_but_by_header_name']:
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257 c = params['input_options']['column_selector_options_2']['col2']
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258 else:
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259 c = None
2
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260
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261 df_key = infile2 + repr(header)
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262 if df_key in loaded_df:
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263 infile2 = loaded_df[df_key]
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264 else:
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265 infile2 = pd.read_csv(infile2, sep='\t',
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266 header=header, parse_dates=True)
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267 loaded_df[df_key] = infile2
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268
0
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269 y = read_columns(
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270 infile2,
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271 c=c,
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272 c_option=column_option,
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273 sep='\t',
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274 header=header,
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275 parse_dates=True)
2
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276 if len(y.shape) == 2 and y.shape[1] == 1:
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277 y = y.ravel()
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278 if input_type == 'refseq_and_interval':
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279 estimator.set_params(
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280 data_batch_generator__features=y.ravel().tolist())
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281 y = None
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282 # end y
0
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283
7
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284 return estimator, X, y
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285
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286
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287 def _do_outer_cv(searcher, X, y, outer_cv, scoring, error_score='raise',
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288 outfile=None):
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289 """Do outer cross-validation for nested CV
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290
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291 Parameters
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292 ----------
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293 searcher : object
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294 SearchCV object
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295 X : numpy array
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296 Containing features
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297 y : numpy array
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298 Target values or labels
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299 outer_cv : int or CV splitter
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300 Control the cv splitting
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301 scoring : object
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302 Scorer
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303 error_score: str, float or numpy float
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304 Whether to raise fit error or return an value
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305 outfile : str
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306 File path to store the restuls
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307 """
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308 if error_score == 'raise':
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309 rval = cross_validate(
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310 searcher, X, y, scoring=scoring,
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311 cv=outer_cv, n_jobs=N_JOBS, verbose=0,
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312 error_score=error_score)
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313 else:
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314 warnings.simplefilter('always', FitFailedWarning)
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315 with warnings.catch_warnings(record=True) as w:
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316 try:
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317 rval = cross_validate(
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318 searcher, X, y,
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319 scoring=scoring,
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320 cv=outer_cv, n_jobs=N_JOBS,
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321 verbose=0,
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322 error_score=error_score)
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323 except ValueError:
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324 pass
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325 for warning in w:
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326 print(repr(warning.message))
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327
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328 keys = list(rval.keys())
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329 for k in keys:
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330 if k.startswith('test'):
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331 rval['mean_' + k] = np.mean(rval[k])
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332 rval['std_' + k] = np.std(rval[k])
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333 if k.endswith('time'):
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334 rval.pop(k)
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335 rval = pd.DataFrame(rval)
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336 rval = rval[sorted(rval.columns)]
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337 rval.to_csv(path_or_buf=outfile, sep='\t', header=True, index=False)
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338
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339
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340 def _do_train_test_split_val(searcher, X, y, params, error_score='raise',
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341 primary_scoring=None, groups=None,
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342 outfile=None):
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343 """ do train test split, searchCV validates on the train and then use
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344 the best_estimator_ to evaluate on the test
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345
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346 Returns
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347 --------
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348 Fitted SearchCV object
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349 """
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350 train_test_split = try_get_attr(
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351 'galaxy_ml.model_validations', 'train_test_split')
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352 split_options = params['outer_split']
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353
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354 # splits
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355 if split_options['shuffle'] == 'stratified':
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356 split_options['labels'] = y
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357 X, X_test, y, y_test = train_test_split(X, y, **split_options)
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358 elif split_options['shuffle'] == 'group':
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359 if groups is None:
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360 raise ValueError("No group based CV option was choosen for "
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361 "group shuffle!")
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362 split_options['labels'] = groups
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diff changeset
363 if y is None:
00819b7f2f55 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 756f8be9c3cd437e131e6410cd625c24fe078e8c"
bgruening
parents: 3
diff changeset
364 X, X_test, groups, _ =\
00819b7f2f55 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 756f8be9c3cd437e131e6410cd625c24fe078e8c"
bgruening
parents: 3
diff changeset
365 train_test_split(X, groups, **split_options)
00819b7f2f55 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 756f8be9c3cd437e131e6410cd625c24fe078e8c"
bgruening
parents: 3
diff changeset
366 else:
00819b7f2f55 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 756f8be9c3cd437e131e6410cd625c24fe078e8c"
bgruening
parents: 3
diff changeset
367 X, X_test, y, y_test, groups, _ =\
00819b7f2f55 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 756f8be9c3cd437e131e6410cd625c24fe078e8c"
bgruening
parents: 3
diff changeset
368 train_test_split(X, y, groups, **split_options)
00819b7f2f55 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 756f8be9c3cd437e131e6410cd625c24fe078e8c"
bgruening
parents: 3
diff changeset
369 else:
00819b7f2f55 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 756f8be9c3cd437e131e6410cd625c24fe078e8c"
bgruening
parents: 3
diff changeset
370 if split_options['shuffle'] == 'None':
00819b7f2f55 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 756f8be9c3cd437e131e6410cd625c24fe078e8c"
bgruening
parents: 3
diff changeset
371 split_options['shuffle'] = None
00819b7f2f55 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 756f8be9c3cd437e131e6410cd625c24fe078e8c"
bgruening
parents: 3
diff changeset
372 X, X_test, y, y_test =\
00819b7f2f55 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 756f8be9c3cd437e131e6410cd625c24fe078e8c"
bgruening
parents: 3
diff changeset
373 train_test_split(X, y, **split_options)
00819b7f2f55 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 756f8be9c3cd437e131e6410cd625c24fe078e8c"
bgruening
parents: 3
diff changeset
374
00819b7f2f55 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 756f8be9c3cd437e131e6410cd625c24fe078e8c"
bgruening
parents: 3
diff changeset
375 if error_score == 'raise':
00819b7f2f55 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 756f8be9c3cd437e131e6410cd625c24fe078e8c"
bgruening
parents: 3
diff changeset
376 searcher.fit(X, y, groups=groups)
00819b7f2f55 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 756f8be9c3cd437e131e6410cd625c24fe078e8c"
bgruening
parents: 3
diff changeset
377 else:
00819b7f2f55 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 756f8be9c3cd437e131e6410cd625c24fe078e8c"
bgruening
parents: 3
diff changeset
378 warnings.simplefilter('always', FitFailedWarning)
00819b7f2f55 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 756f8be9c3cd437e131e6410cd625c24fe078e8c"
bgruening
parents: 3
diff changeset
379 with warnings.catch_warnings(record=True) as w:
00819b7f2f55 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 756f8be9c3cd437e131e6410cd625c24fe078e8c"
bgruening
parents: 3
diff changeset
380 try:
00819b7f2f55 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 756f8be9c3cd437e131e6410cd625c24fe078e8c"
bgruening
parents: 3
diff changeset
381 searcher.fit(X, y, groups=groups)
00819b7f2f55 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 756f8be9c3cd437e131e6410cd625c24fe078e8c"
bgruening
parents: 3
diff changeset
382 except ValueError:
00819b7f2f55 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 756f8be9c3cd437e131e6410cd625c24fe078e8c"
bgruening
parents: 3
diff changeset
383 pass
00819b7f2f55 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 756f8be9c3cd437e131e6410cd625c24fe078e8c"
bgruening
parents: 3
diff changeset
384 for warning in w:
00819b7f2f55 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 756f8be9c3cd437e131e6410cd625c24fe078e8c"
bgruening
parents: 3
diff changeset
385 print(repr(warning.message))
00819b7f2f55 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 756f8be9c3cd437e131e6410cd625c24fe078e8c"
bgruening
parents: 3
diff changeset
386
00819b7f2f55 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 756f8be9c3cd437e131e6410cd625c24fe078e8c"
bgruening
parents: 3
diff changeset
387 scorer_ = searcher.scorer_
00819b7f2f55 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 756f8be9c3cd437e131e6410cd625c24fe078e8c"
bgruening
parents: 3
diff changeset
388 if isinstance(scorer_, collections.Mapping):
00819b7f2f55 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 756f8be9c3cd437e131e6410cd625c24fe078e8c"
bgruening
parents: 3
diff changeset
389 is_multimetric = True
00819b7f2f55 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 756f8be9c3cd437e131e6410cd625c24fe078e8c"
bgruening
parents: 3
diff changeset
390 else:
00819b7f2f55 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 756f8be9c3cd437e131e6410cd625c24fe078e8c"
bgruening
parents: 3
diff changeset
391 is_multimetric = False
00819b7f2f55 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 756f8be9c3cd437e131e6410cd625c24fe078e8c"
bgruening
parents: 3
diff changeset
392
00819b7f2f55 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 756f8be9c3cd437e131e6410cd625c24fe078e8c"
bgruening
parents: 3
diff changeset
393 best_estimator_ = getattr(searcher, 'best_estimator_')
00819b7f2f55 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 756f8be9c3cd437e131e6410cd625c24fe078e8c"
bgruening
parents: 3
diff changeset
394
00819b7f2f55 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 756f8be9c3cd437e131e6410cd625c24fe078e8c"
bgruening
parents: 3
diff changeset
395 # TODO Solve deep learning models in pipeline
00819b7f2f55 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 756f8be9c3cd437e131e6410cd625c24fe078e8c"
bgruening
parents: 3
diff changeset
396 if best_estimator_.__class__.__name__ == 'KerasGBatchClassifier':
00819b7f2f55 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 756f8be9c3cd437e131e6410cd625c24fe078e8c"
bgruening
parents: 3
diff changeset
397 test_score = best_estimator_.evaluate(
00819b7f2f55 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 756f8be9c3cd437e131e6410cd625c24fe078e8c"
bgruening
parents: 3
diff changeset
398 X_test, scorer=scorer_, is_multimetric=is_multimetric)
00819b7f2f55 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 756f8be9c3cd437e131e6410cd625c24fe078e8c"
bgruening
parents: 3
diff changeset
399 else:
00819b7f2f55 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 756f8be9c3cd437e131e6410cd625c24fe078e8c"
bgruening
parents: 3
diff changeset
400 test_score = _score(best_estimator_, X_test,
00819b7f2f55 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 756f8be9c3cd437e131e6410cd625c24fe078e8c"
bgruening
parents: 3
diff changeset
401 y_test, scorer_,
00819b7f2f55 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 756f8be9c3cd437e131e6410cd625c24fe078e8c"
bgruening
parents: 3
diff changeset
402 is_multimetric=is_multimetric)
00819b7f2f55 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 756f8be9c3cd437e131e6410cd625c24fe078e8c"
bgruening
parents: 3
diff changeset
403
00819b7f2f55 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 756f8be9c3cd437e131e6410cd625c24fe078e8c"
bgruening
parents: 3
diff changeset
404 if not is_multimetric:
00819b7f2f55 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 756f8be9c3cd437e131e6410cd625c24fe078e8c"
bgruening
parents: 3
diff changeset
405 test_score = {primary_scoring: test_score}
00819b7f2f55 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 756f8be9c3cd437e131e6410cd625c24fe078e8c"
bgruening
parents: 3
diff changeset
406 for key, value in test_score.items():
00819b7f2f55 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 756f8be9c3cd437e131e6410cd625c24fe078e8c"
bgruening
parents: 3
diff changeset
407 test_score[key] = [value]
00819b7f2f55 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 756f8be9c3cd437e131e6410cd625c24fe078e8c"
bgruening
parents: 3
diff changeset
408 result_df = pd.DataFrame(test_score)
00819b7f2f55 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 756f8be9c3cd437e131e6410cd625c24fe078e8c"
bgruening
parents: 3
diff changeset
409 result_df.to_csv(path_or_buf=outfile, sep='\t', header=True,
00819b7f2f55 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 756f8be9c3cd437e131e6410cd625c24fe078e8c"
bgruening
parents: 3
diff changeset
410 index=False)
00819b7f2f55 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 756f8be9c3cd437e131e6410cd625c24fe078e8c"
bgruening
parents: 3
diff changeset
411
00819b7f2f55 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 756f8be9c3cd437e131e6410cd625c24fe078e8c"
bgruening
parents: 3
diff changeset
412 return searcher
00819b7f2f55 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 756f8be9c3cd437e131e6410cd625c24fe078e8c"
bgruening
parents: 3
diff changeset
413
00819b7f2f55 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 756f8be9c3cd437e131e6410cd625c24fe078e8c"
bgruening
parents: 3
diff changeset
414
00819b7f2f55 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 756f8be9c3cd437e131e6410cd625c24fe078e8c"
bgruening
parents: 3
diff changeset
415 def main(inputs, infile_estimator, infile1, infile2,
00819b7f2f55 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 756f8be9c3cd437e131e6410cd625c24fe078e8c"
bgruening
parents: 3
diff changeset
416 outfile_result, outfile_object=None,
00819b7f2f55 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 756f8be9c3cd437e131e6410cd625c24fe078e8c"
bgruening
parents: 3
diff changeset
417 outfile_weights=None, groups=None,
00819b7f2f55 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 756f8be9c3cd437e131e6410cd625c24fe078e8c"
bgruening
parents: 3
diff changeset
418 ref_seq=None, intervals=None, targets=None,
00819b7f2f55 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 756f8be9c3cd437e131e6410cd625c24fe078e8c"
bgruening
parents: 3
diff changeset
419 fasta_path=None):
00819b7f2f55 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 756f8be9c3cd437e131e6410cd625c24fe078e8c"
bgruening
parents: 3
diff changeset
420 """
00819b7f2f55 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 756f8be9c3cd437e131e6410cd625c24fe078e8c"
bgruening
parents: 3
diff changeset
421 Parameter
00819b7f2f55 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 756f8be9c3cd437e131e6410cd625c24fe078e8c"
bgruening
parents: 3
diff changeset
422 ---------
00819b7f2f55 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 756f8be9c3cd437e131e6410cd625c24fe078e8c"
bgruening
parents: 3
diff changeset
423 inputs : str
00819b7f2f55 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 756f8be9c3cd437e131e6410cd625c24fe078e8c"
bgruening
parents: 3
diff changeset
424 File path to galaxy tool parameter
00819b7f2f55 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 756f8be9c3cd437e131e6410cd625c24fe078e8c"
bgruening
parents: 3
diff changeset
425
00819b7f2f55 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 756f8be9c3cd437e131e6410cd625c24fe078e8c"
bgruening
parents: 3
diff changeset
426 infile_estimator : str
00819b7f2f55 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 756f8be9c3cd437e131e6410cd625c24fe078e8c"
bgruening
parents: 3
diff changeset
427 File path to estimator
00819b7f2f55 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 756f8be9c3cd437e131e6410cd625c24fe078e8c"
bgruening
parents: 3
diff changeset
428
00819b7f2f55 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 756f8be9c3cd437e131e6410cd625c24fe078e8c"
bgruening
parents: 3
diff changeset
429 infile1 : str
00819b7f2f55 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 756f8be9c3cd437e131e6410cd625c24fe078e8c"
bgruening
parents: 3
diff changeset
430 File path to dataset containing features
00819b7f2f55 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 756f8be9c3cd437e131e6410cd625c24fe078e8c"
bgruening
parents: 3
diff changeset
431
00819b7f2f55 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 756f8be9c3cd437e131e6410cd625c24fe078e8c"
bgruening
parents: 3
diff changeset
432 infile2 : str
00819b7f2f55 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 756f8be9c3cd437e131e6410cd625c24fe078e8c"
bgruening
parents: 3
diff changeset
433 File path to dataset containing target values
00819b7f2f55 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 756f8be9c3cd437e131e6410cd625c24fe078e8c"
bgruening
parents: 3
diff changeset
434
00819b7f2f55 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 756f8be9c3cd437e131e6410cd625c24fe078e8c"
bgruening
parents: 3
diff changeset
435 outfile_result : str
00819b7f2f55 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 756f8be9c3cd437e131e6410cd625c24fe078e8c"
bgruening
parents: 3
diff changeset
436 File path to save the results, either cv_results or test result
00819b7f2f55 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 756f8be9c3cd437e131e6410cd625c24fe078e8c"
bgruening
parents: 3
diff changeset
437
00819b7f2f55 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 756f8be9c3cd437e131e6410cd625c24fe078e8c"
bgruening
parents: 3
diff changeset
438 outfile_object : str, optional
00819b7f2f55 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 756f8be9c3cd437e131e6410cd625c24fe078e8c"
bgruening
parents: 3
diff changeset
439 File path to save searchCV object
00819b7f2f55 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 756f8be9c3cd437e131e6410cd625c24fe078e8c"
bgruening
parents: 3
diff changeset
440
00819b7f2f55 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 756f8be9c3cd437e131e6410cd625c24fe078e8c"
bgruening
parents: 3
diff changeset
441 outfile_weights : str, optional
00819b7f2f55 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 756f8be9c3cd437e131e6410cd625c24fe078e8c"
bgruening
parents: 3
diff changeset
442 File path to save model weights
00819b7f2f55 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 756f8be9c3cd437e131e6410cd625c24fe078e8c"
bgruening
parents: 3
diff changeset
443
00819b7f2f55 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 756f8be9c3cd437e131e6410cd625c24fe078e8c"
bgruening
parents: 3
diff changeset
444 groups : str
00819b7f2f55 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 756f8be9c3cd437e131e6410cd625c24fe078e8c"
bgruening
parents: 3
diff changeset
445 File path to dataset containing groups labels
00819b7f2f55 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 756f8be9c3cd437e131e6410cd625c24fe078e8c"
bgruening
parents: 3
diff changeset
446
00819b7f2f55 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 756f8be9c3cd437e131e6410cd625c24fe078e8c"
bgruening
parents: 3
diff changeset
447 ref_seq : str
00819b7f2f55 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 756f8be9c3cd437e131e6410cd625c24fe078e8c"
bgruening
parents: 3
diff changeset
448 File path to dataset containing genome sequence file
00819b7f2f55 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 756f8be9c3cd437e131e6410cd625c24fe078e8c"
bgruening
parents: 3
diff changeset
449
00819b7f2f55 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 756f8be9c3cd437e131e6410cd625c24fe078e8c"
bgruening
parents: 3
diff changeset
450 intervals : str
00819b7f2f55 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 756f8be9c3cd437e131e6410cd625c24fe078e8c"
bgruening
parents: 3
diff changeset
451 File path to dataset containing interval file
00819b7f2f55 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 756f8be9c3cd437e131e6410cd625c24fe078e8c"
bgruening
parents: 3
diff changeset
452
00819b7f2f55 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 756f8be9c3cd437e131e6410cd625c24fe078e8c"
bgruening
parents: 3
diff changeset
453 targets : str
00819b7f2f55 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 756f8be9c3cd437e131e6410cd625c24fe078e8c"
bgruening
parents: 3
diff changeset
454 File path to dataset compressed target bed file
00819b7f2f55 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 756f8be9c3cd437e131e6410cd625c24fe078e8c"
bgruening
parents: 3
diff changeset
455
00819b7f2f55 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 756f8be9c3cd437e131e6410cd625c24fe078e8c"
bgruening
parents: 3
diff changeset
456 fasta_path : str
00819b7f2f55 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 756f8be9c3cd437e131e6410cd625c24fe078e8c"
bgruening
parents: 3
diff changeset
457 File path to dataset containing fasta file
00819b7f2f55 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 756f8be9c3cd437e131e6410cd625c24fe078e8c"
bgruening
parents: 3
diff changeset
458 """
00819b7f2f55 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 756f8be9c3cd437e131e6410cd625c24fe078e8c"
bgruening
parents: 3
diff changeset
459 warnings.simplefilter('ignore')
00819b7f2f55 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 756f8be9c3cd437e131e6410cd625c24fe078e8c"
bgruening
parents: 3
diff changeset
460
00819b7f2f55 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 756f8be9c3cd437e131e6410cd625c24fe078e8c"
bgruening
parents: 3
diff changeset
461 # store read dataframe object
00819b7f2f55 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 756f8be9c3cd437e131e6410cd625c24fe078e8c"
bgruening
parents: 3
diff changeset
462 loaded_df = {}
00819b7f2f55 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 756f8be9c3cd437e131e6410cd625c24fe078e8c"
bgruening
parents: 3
diff changeset
463
00819b7f2f55 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 756f8be9c3cd437e131e6410cd625c24fe078e8c"
bgruening
parents: 3
diff changeset
464 with open(inputs, 'r') as param_handler:
00819b7f2f55 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 756f8be9c3cd437e131e6410cd625c24fe078e8c"
bgruening
parents: 3
diff changeset
465 params = json.load(param_handler)
00819b7f2f55 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 756f8be9c3cd437e131e6410cd625c24fe078e8c"
bgruening
parents: 3
diff changeset
466
00819b7f2f55 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 756f8be9c3cd437e131e6410cd625c24fe078e8c"
bgruening
parents: 3
diff changeset
467 # Override the refit parameter
00819b7f2f55 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 756f8be9c3cd437e131e6410cd625c24fe078e8c"
bgruening
parents: 3
diff changeset
468 params['search_schemes']['options']['refit'] = True \
00819b7f2f55 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 756f8be9c3cd437e131e6410cd625c24fe078e8c"
bgruening
parents: 3
diff changeset
469 if params['save'] != 'nope' else False
00819b7f2f55 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 756f8be9c3cd437e131e6410cd625c24fe078e8c"
bgruening
parents: 3
diff changeset
470
00819b7f2f55 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 756f8be9c3cd437e131e6410cd625c24fe078e8c"
bgruening
parents: 3
diff changeset
471 with open(infile_estimator, 'rb') as estimator_handler:
00819b7f2f55 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 756f8be9c3cd437e131e6410cd625c24fe078e8c"
bgruening
parents: 3
diff changeset
472 estimator = load_model(estimator_handler)
00819b7f2f55 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 756f8be9c3cd437e131e6410cd625c24fe078e8c"
bgruening
parents: 3
diff changeset
473
0
47467890f541 planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ab963ec9498bd05d2fb2f24f75adb2fccae7958c
bgruening
parents:
diff changeset
474 optimizer = params['search_schemes']['selected_search_scheme']
47467890f541 planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ab963ec9498bd05d2fb2f24f75adb2fccae7958c
bgruening
parents:
diff changeset
475 optimizer = getattr(model_selection, optimizer)
47467890f541 planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ab963ec9498bd05d2fb2f24f75adb2fccae7958c
bgruening
parents:
diff changeset
476
2
e18d9b17c322 planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit c035d399196b3bef9982db4f8e47331411dbb20e
bgruening
parents: 0
diff changeset
477 # handle gridsearchcv options
0
47467890f541 planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ab963ec9498bd05d2fb2f24f75adb2fccae7958c
bgruening
parents:
diff changeset
478 options = params['search_schemes']['options']
47467890f541 planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ab963ec9498bd05d2fb2f24f75adb2fccae7958c
bgruening
parents:
diff changeset
479
2
e18d9b17c322 planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit c035d399196b3bef9982db4f8e47331411dbb20e
bgruening
parents: 0
diff changeset
480 if groups:
e18d9b17c322 planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit c035d399196b3bef9982db4f8e47331411dbb20e
bgruening
parents: 0
diff changeset
481 header = 'infer' if (options['cv_selector']['groups_selector']
e18d9b17c322 planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit c035d399196b3bef9982db4f8e47331411dbb20e
bgruening
parents: 0
diff changeset
482 ['header_g']) else None
e18d9b17c322 planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit c035d399196b3bef9982db4f8e47331411dbb20e
bgruening
parents: 0
diff changeset
483 column_option = (options['cv_selector']['groups_selector']
e18d9b17c322 planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit c035d399196b3bef9982db4f8e47331411dbb20e
bgruening
parents: 0
diff changeset
484 ['column_selector_options_g']
e18d9b17c322 planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit c035d399196b3bef9982db4f8e47331411dbb20e
bgruening
parents: 0
diff changeset
485 ['selected_column_selector_option_g'])
e18d9b17c322 planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit c035d399196b3bef9982db4f8e47331411dbb20e
bgruening
parents: 0
diff changeset
486 if column_option in ['by_index_number', 'all_but_by_index_number',
e18d9b17c322 planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit c035d399196b3bef9982db4f8e47331411dbb20e
bgruening
parents: 0
diff changeset
487 'by_header_name', 'all_but_by_header_name']:
e18d9b17c322 planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit c035d399196b3bef9982db4f8e47331411dbb20e
bgruening
parents: 0
diff changeset
488 c = (options['cv_selector']['groups_selector']
e18d9b17c322 planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit c035d399196b3bef9982db4f8e47331411dbb20e
bgruening
parents: 0
diff changeset
489 ['column_selector_options_g']['col_g'])
e18d9b17c322 planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit c035d399196b3bef9982db4f8e47331411dbb20e
bgruening
parents: 0
diff changeset
490 else:
e18d9b17c322 planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit c035d399196b3bef9982db4f8e47331411dbb20e
bgruening
parents: 0
diff changeset
491 c = None
e18d9b17c322 planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit c035d399196b3bef9982db4f8e47331411dbb20e
bgruening
parents: 0
diff changeset
492
e18d9b17c322 planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit c035d399196b3bef9982db4f8e47331411dbb20e
bgruening
parents: 0
diff changeset
493 df_key = groups + repr(header)
7
00819b7f2f55 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 756f8be9c3cd437e131e6410cd625c24fe078e8c"
bgruening
parents: 3
diff changeset
494
00819b7f2f55 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 756f8be9c3cd437e131e6410cd625c24fe078e8c"
bgruening
parents: 3
diff changeset
495 groups = pd.read_csv(groups, sep='\t', header=header,
00819b7f2f55 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 756f8be9c3cd437e131e6410cd625c24fe078e8c"
bgruening
parents: 3
diff changeset
496 parse_dates=True)
00819b7f2f55 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 756f8be9c3cd437e131e6410cd625c24fe078e8c"
bgruening
parents: 3
diff changeset
497 loaded_df[df_key] = groups
2
e18d9b17c322 planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit c035d399196b3bef9982db4f8e47331411dbb20e
bgruening
parents: 0
diff changeset
498
e18d9b17c322 planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit c035d399196b3bef9982db4f8e47331411dbb20e
bgruening
parents: 0
diff changeset
499 groups = read_columns(
e18d9b17c322 planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit c035d399196b3bef9982db4f8e47331411dbb20e
bgruening
parents: 0
diff changeset
500 groups,
e18d9b17c322 planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit c035d399196b3bef9982db4f8e47331411dbb20e
bgruening
parents: 0
diff changeset
501 c=c,
e18d9b17c322 planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit c035d399196b3bef9982db4f8e47331411dbb20e
bgruening
parents: 0
diff changeset
502 c_option=column_option,
e18d9b17c322 planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit c035d399196b3bef9982db4f8e47331411dbb20e
bgruening
parents: 0
diff changeset
503 sep='\t',
e18d9b17c322 planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit c035d399196b3bef9982db4f8e47331411dbb20e
bgruening
parents: 0
diff changeset
504 header=header,
e18d9b17c322 planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit c035d399196b3bef9982db4f8e47331411dbb20e
bgruening
parents: 0
diff changeset
505 parse_dates=True)
e18d9b17c322 planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit c035d399196b3bef9982db4f8e47331411dbb20e
bgruening
parents: 0
diff changeset
506 groups = groups.ravel()
e18d9b17c322 planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit c035d399196b3bef9982db4f8e47331411dbb20e
bgruening
parents: 0
diff changeset
507 options['cv_selector']['groups_selector'] = groups
e18d9b17c322 planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit c035d399196b3bef9982db4f8e47331411dbb20e
bgruening
parents: 0
diff changeset
508
0
47467890f541 planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ab963ec9498bd05d2fb2f24f75adb2fccae7958c
bgruening
parents:
diff changeset
509 splitter, groups = get_cv(options.pop('cv_selector'))
47467890f541 planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ab963ec9498bd05d2fb2f24f75adb2fccae7958c
bgruening
parents:
diff changeset
510 options['cv'] = splitter
47467890f541 planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ab963ec9498bd05d2fb2f24f75adb2fccae7958c
bgruening
parents:
diff changeset
511 primary_scoring = options['scoring']['primary_scoring']
47467890f541 planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ab963ec9498bd05d2fb2f24f75adb2fccae7958c
bgruening
parents:
diff changeset
512 options['scoring'] = get_scoring(options['scoring'])
47467890f541 planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ab963ec9498bd05d2fb2f24f75adb2fccae7958c
bgruening
parents:
diff changeset
513 if options['error_score']:
47467890f541 planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ab963ec9498bd05d2fb2f24f75adb2fccae7958c
bgruening
parents:
diff changeset
514 options['error_score'] = 'raise'
47467890f541 planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ab963ec9498bd05d2fb2f24f75adb2fccae7958c
bgruening
parents:
diff changeset
515 else:
47467890f541 planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ab963ec9498bd05d2fb2f24f75adb2fccae7958c
bgruening
parents:
diff changeset
516 options['error_score'] = np.NaN
47467890f541 planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ab963ec9498bd05d2fb2f24f75adb2fccae7958c
bgruening
parents:
diff changeset
517 if options['refit'] and isinstance(options['scoring'], dict):
47467890f541 planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ab963ec9498bd05d2fb2f24f75adb2fccae7958c
bgruening
parents:
diff changeset
518 options['refit'] = primary_scoring
47467890f541 planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ab963ec9498bd05d2fb2f24f75adb2fccae7958c
bgruening
parents:
diff changeset
519 if 'pre_dispatch' in options and options['pre_dispatch'] == '':
47467890f541 planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ab963ec9498bd05d2fb2f24f75adb2fccae7958c
bgruening
parents:
diff changeset
520 options['pre_dispatch'] = None
47467890f541 planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ab963ec9498bd05d2fb2f24f75adb2fccae7958c
bgruening
parents:
diff changeset
521
7
00819b7f2f55 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 756f8be9c3cd437e131e6410cd625c24fe078e8c"
bgruening
parents: 3
diff changeset
522 params_builder = params['search_schemes']['search_params_builder']
00819b7f2f55 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 756f8be9c3cd437e131e6410cd625c24fe078e8c"
bgruening
parents: 3
diff changeset
523 param_grid = _eval_search_params(params_builder)
00819b7f2f55 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 756f8be9c3cd437e131e6410cd625c24fe078e8c"
bgruening
parents: 3
diff changeset
524
00819b7f2f55 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 756f8be9c3cd437e131e6410cd625c24fe078e8c"
bgruening
parents: 3
diff changeset
525 estimator = clean_params(estimator)
0
47467890f541 planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ab963ec9498bd05d2fb2f24f75adb2fccae7958c
bgruening
parents:
diff changeset
526
7
00819b7f2f55 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 756f8be9c3cd437e131e6410cd625c24fe078e8c"
bgruening
parents: 3
diff changeset
527 # save the SearchCV object without fit
00819b7f2f55 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 756f8be9c3cd437e131e6410cd625c24fe078e8c"
bgruening
parents: 3
diff changeset
528 if params['save'] == 'save_no_fit':
00819b7f2f55 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 756f8be9c3cd437e131e6410cd625c24fe078e8c"
bgruening
parents: 3
diff changeset
529 searcher = optimizer(estimator, param_grid, **options)
00819b7f2f55 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 756f8be9c3cd437e131e6410cd625c24fe078e8c"
bgruening
parents: 3
diff changeset
530 print(searcher)
00819b7f2f55 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 756f8be9c3cd437e131e6410cd625c24fe078e8c"
bgruening
parents: 3
diff changeset
531 with open(outfile_object, 'wb') as output_handler:
00819b7f2f55 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 756f8be9c3cd437e131e6410cd625c24fe078e8c"
bgruening
parents: 3
diff changeset
532 pickle.dump(searcher, output_handler,
00819b7f2f55 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 756f8be9c3cd437e131e6410cd625c24fe078e8c"
bgruening
parents: 3
diff changeset
533 pickle.HIGHEST_PROTOCOL)
00819b7f2f55 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 756f8be9c3cd437e131e6410cd625c24fe078e8c"
bgruening
parents: 3
diff changeset
534 return 0
00819b7f2f55 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 756f8be9c3cd437e131e6410cd625c24fe078e8c"
bgruening
parents: 3
diff changeset
535
00819b7f2f55 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 756f8be9c3cd437e131e6410cd625c24fe078e8c"
bgruening
parents: 3
diff changeset
536 # read inputs and loads new attributes, like paths
00819b7f2f55 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 756f8be9c3cd437e131e6410cd625c24fe078e8c"
bgruening
parents: 3
diff changeset
537 estimator, X, y = _handle_X_y(estimator, params, infile1, infile2,
00819b7f2f55 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 756f8be9c3cd437e131e6410cd625c24fe078e8c"
bgruening
parents: 3
diff changeset
538 loaded_df=loaded_df, ref_seq=ref_seq,
00819b7f2f55 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 756f8be9c3cd437e131e6410cd625c24fe078e8c"
bgruening
parents: 3
diff changeset
539 intervals=intervals, targets=targets,
00819b7f2f55 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 756f8be9c3cd437e131e6410cd625c24fe078e8c"
bgruening
parents: 3
diff changeset
540 fasta_path=fasta_path)
00819b7f2f55 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 756f8be9c3cd437e131e6410cd625c24fe078e8c"
bgruening
parents: 3
diff changeset
541
0
47467890f541 planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ab963ec9498bd05d2fb2f24f75adb2fccae7958c
bgruening
parents:
diff changeset
542 # cache iraps_core fits could increase search speed significantly
7
00819b7f2f55 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 756f8be9c3cd437e131e6410cd625c24fe078e8c"
bgruening
parents: 3
diff changeset
543 memory = joblib.Memory(location=CACHE_DIR, verbose=0)
00819b7f2f55 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 756f8be9c3cd437e131e6410cd625c24fe078e8c"
bgruening
parents: 3
diff changeset
544 main_est = get_main_estimator(estimator)
00819b7f2f55 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 756f8be9c3cd437e131e6410cd625c24fe078e8c"
bgruening
parents: 3
diff changeset
545 if main_est.__class__.__name__ == 'IRAPSClassifier':
00819b7f2f55 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 756f8be9c3cd437e131e6410cd625c24fe078e8c"
bgruening
parents: 3
diff changeset
546 main_est.set_params(memory=memory)
0
47467890f541 planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ab963ec9498bd05d2fb2f24f75adb2fccae7958c
bgruening
parents:
diff changeset
547
47467890f541 planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ab963ec9498bd05d2fb2f24f75adb2fccae7958c
bgruening
parents:
diff changeset
548 searcher = optimizer(estimator, param_grid, **options)
47467890f541 planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ab963ec9498bd05d2fb2f24f75adb2fccae7958c
bgruening
parents:
diff changeset
549
2
e18d9b17c322 planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit c035d399196b3bef9982db4f8e47331411dbb20e
bgruening
parents: 0
diff changeset
550 split_mode = params['outer_split'].pop('split_mode')
7
00819b7f2f55 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 756f8be9c3cd437e131e6410cd625c24fe078e8c"
bgruening
parents: 3
diff changeset
551
2
e18d9b17c322 planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit c035d399196b3bef9982db4f8e47331411dbb20e
bgruening
parents: 0
diff changeset
552 if split_mode == 'nested_cv':
7
00819b7f2f55 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 756f8be9c3cd437e131e6410cd625c24fe078e8c"
bgruening
parents: 3
diff changeset
553 # make sure refit is choosen
00819b7f2f55 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 756f8be9c3cd437e131e6410cd625c24fe078e8c"
bgruening
parents: 3
diff changeset
554 # this could be True for sklearn models, but not the case for
00819b7f2f55 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 756f8be9c3cd437e131e6410cd625c24fe078e8c"
bgruening
parents: 3
diff changeset
555 # deep learning models
00819b7f2f55 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 756f8be9c3cd437e131e6410cd625c24fe078e8c"
bgruening
parents: 3
diff changeset
556 if not options['refit'] and \
00819b7f2f55 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 756f8be9c3cd437e131e6410cd625c24fe078e8c"
bgruening
parents: 3
diff changeset
557 not all(hasattr(estimator, attr)
00819b7f2f55 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 756f8be9c3cd437e131e6410cd625c24fe078e8c"
bgruening
parents: 3
diff changeset
558 for attr in ('config', 'model_type')):
00819b7f2f55 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 756f8be9c3cd437e131e6410cd625c24fe078e8c"
bgruening
parents: 3
diff changeset
559 warnings.warn("Refit is change to `True` for nested validation!")
00819b7f2f55 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 756f8be9c3cd437e131e6410cd625c24fe078e8c"
bgruening
parents: 3
diff changeset
560 setattr(searcher, 'refit', True)
00819b7f2f55 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 756f8be9c3cd437e131e6410cd625c24fe078e8c"
bgruening
parents: 3
diff changeset
561
2
e18d9b17c322 planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit c035d399196b3bef9982db4f8e47331411dbb20e
bgruening
parents: 0
diff changeset
562 outer_cv, _ = get_cv(params['outer_split']['cv_selector'])
7
00819b7f2f55 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 756f8be9c3cd437e131e6410cd625c24fe078e8c"
bgruening
parents: 3
diff changeset
563 # nested CV, outer cv using cross_validate
2
e18d9b17c322 planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit c035d399196b3bef9982db4f8e47331411dbb20e
bgruening
parents: 0
diff changeset
564 if options['error_score'] == 'raise':
e18d9b17c322 planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit c035d399196b3bef9982db4f8e47331411dbb20e
bgruening
parents: 0
diff changeset
565 rval = cross_validate(
e18d9b17c322 planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit c035d399196b3bef9982db4f8e47331411dbb20e
bgruening
parents: 0
diff changeset
566 searcher, X, y, scoring=options['scoring'],
7
00819b7f2f55 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 756f8be9c3cd437e131e6410cd625c24fe078e8c"
bgruening
parents: 3
diff changeset
567 cv=outer_cv, n_jobs=N_JOBS,
00819b7f2f55 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 756f8be9c3cd437e131e6410cd625c24fe078e8c"
bgruening
parents: 3
diff changeset
568 verbose=options['verbose'],
00819b7f2f55 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 756f8be9c3cd437e131e6410cd625c24fe078e8c"
bgruening
parents: 3
diff changeset
569 return_estimator=(params['save'] == 'save_estimator'),
00819b7f2f55 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 756f8be9c3cd437e131e6410cd625c24fe078e8c"
bgruening
parents: 3
diff changeset
570 error_score=options['error_score'],
00819b7f2f55 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 756f8be9c3cd437e131e6410cd625c24fe078e8c"
bgruening
parents: 3
diff changeset
571 return_train_score=True)
0
47467890f541 planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ab963ec9498bd05d2fb2f24f75adb2fccae7958c
bgruening
parents:
diff changeset
572 else:
2
e18d9b17c322 planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit c035d399196b3bef9982db4f8e47331411dbb20e
bgruening
parents: 0
diff changeset
573 warnings.simplefilter('always', FitFailedWarning)
e18d9b17c322 planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit c035d399196b3bef9982db4f8e47331411dbb20e
bgruening
parents: 0
diff changeset
574 with warnings.catch_warnings(record=True) as w:
e18d9b17c322 planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit c035d399196b3bef9982db4f8e47331411dbb20e
bgruening
parents: 0
diff changeset
575 try:
e18d9b17c322 planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit c035d399196b3bef9982db4f8e47331411dbb20e
bgruening
parents: 0
diff changeset
576 rval = cross_validate(
e18d9b17c322 planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit c035d399196b3bef9982db4f8e47331411dbb20e
bgruening
parents: 0
diff changeset
577 searcher, X, y,
e18d9b17c322 planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit c035d399196b3bef9982db4f8e47331411dbb20e
bgruening
parents: 0
diff changeset
578 scoring=options['scoring'],
e18d9b17c322 planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit c035d399196b3bef9982db4f8e47331411dbb20e
bgruening
parents: 0
diff changeset
579 cv=outer_cv, n_jobs=N_JOBS,
7
00819b7f2f55 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 756f8be9c3cd437e131e6410cd625c24fe078e8c"
bgruening
parents: 3
diff changeset
580 verbose=options['verbose'],
00819b7f2f55 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 756f8be9c3cd437e131e6410cd625c24fe078e8c"
bgruening
parents: 3
diff changeset
581 return_estimator=(params['save'] == 'save_estimator'),
00819b7f2f55 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 756f8be9c3cd437e131e6410cd625c24fe078e8c"
bgruening
parents: 3
diff changeset
582 error_score=options['error_score'],
00819b7f2f55 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 756f8be9c3cd437e131e6410cd625c24fe078e8c"
bgruening
parents: 3
diff changeset
583 return_train_score=True)
2
e18d9b17c322 planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit c035d399196b3bef9982db4f8e47331411dbb20e
bgruening
parents: 0
diff changeset
584 except ValueError:
e18d9b17c322 planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit c035d399196b3bef9982db4f8e47331411dbb20e
bgruening
parents: 0
diff changeset
585 pass
e18d9b17c322 planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit c035d399196b3bef9982db4f8e47331411dbb20e
bgruening
parents: 0
diff changeset
586 for warning in w:
e18d9b17c322 planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit c035d399196b3bef9982db4f8e47331411dbb20e
bgruening
parents: 0
diff changeset
587 print(repr(warning.message))
0
47467890f541 planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ab963ec9498bd05d2fb2f24f75adb2fccae7958c
bgruening
parents:
diff changeset
588
7
00819b7f2f55 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 756f8be9c3cd437e131e6410cd625c24fe078e8c"
bgruening
parents: 3
diff changeset
589 fitted_searchers = rval.pop('estimator', [])
00819b7f2f55 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 756f8be9c3cd437e131e6410cd625c24fe078e8c"
bgruening
parents: 3
diff changeset
590 if fitted_searchers:
00819b7f2f55 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 756f8be9c3cd437e131e6410cd625c24fe078e8c"
bgruening
parents: 3
diff changeset
591 import os
00819b7f2f55 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 756f8be9c3cd437e131e6410cd625c24fe078e8c"
bgruening
parents: 3
diff changeset
592 pwd = os.getcwd()
00819b7f2f55 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 756f8be9c3cd437e131e6410cd625c24fe078e8c"
bgruening
parents: 3
diff changeset
593 save_dir = os.path.join(pwd, 'cv_results_in_folds')
00819b7f2f55 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 756f8be9c3cd437e131e6410cd625c24fe078e8c"
bgruening
parents: 3
diff changeset
594 try:
00819b7f2f55 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 756f8be9c3cd437e131e6410cd625c24fe078e8c"
bgruening
parents: 3
diff changeset
595 os.mkdir(save_dir)
00819b7f2f55 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 756f8be9c3cd437e131e6410cd625c24fe078e8c"
bgruening
parents: 3
diff changeset
596 for idx, obj in enumerate(fitted_searchers):
00819b7f2f55 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 756f8be9c3cd437e131e6410cd625c24fe078e8c"
bgruening
parents: 3
diff changeset
597 target_name = 'cv_results_' + '_' + 'split%d' % idx
00819b7f2f55 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 756f8be9c3cd437e131e6410cd625c24fe078e8c"
bgruening
parents: 3
diff changeset
598 target_path = os.path.join(pwd, save_dir, target_name)
00819b7f2f55 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 756f8be9c3cd437e131e6410cd625c24fe078e8c"
bgruening
parents: 3
diff changeset
599 cv_results_ = getattr(obj, 'cv_results_', None)
00819b7f2f55 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 756f8be9c3cd437e131e6410cd625c24fe078e8c"
bgruening
parents: 3
diff changeset
600 if not cv_results_:
00819b7f2f55 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 756f8be9c3cd437e131e6410cd625c24fe078e8c"
bgruening
parents: 3
diff changeset
601 print("%s is not available" % target_name)
00819b7f2f55 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 756f8be9c3cd437e131e6410cd625c24fe078e8c"
bgruening
parents: 3
diff changeset
602 continue
00819b7f2f55 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 756f8be9c3cd437e131e6410cd625c24fe078e8c"
bgruening
parents: 3
diff changeset
603 cv_results_ = pd.DataFrame(cv_results_)
00819b7f2f55 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 756f8be9c3cd437e131e6410cd625c24fe078e8c"
bgruening
parents: 3
diff changeset
604 cv_results_ = cv_results_[sorted(cv_results_.columns)]
00819b7f2f55 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 756f8be9c3cd437e131e6410cd625c24fe078e8c"
bgruening
parents: 3
diff changeset
605 cv_results_.to_csv(target_path, sep='\t', header=True,
00819b7f2f55 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 756f8be9c3cd437e131e6410cd625c24fe078e8c"
bgruening
parents: 3
diff changeset
606 index=False)
00819b7f2f55 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 756f8be9c3cd437e131e6410cd625c24fe078e8c"
bgruening
parents: 3
diff changeset
607 except Exception as e:
00819b7f2f55 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 756f8be9c3cd437e131e6410cd625c24fe078e8c"
bgruening
parents: 3
diff changeset
608 print(e)
00819b7f2f55 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 756f8be9c3cd437e131e6410cd625c24fe078e8c"
bgruening
parents: 3
diff changeset
609 finally:
00819b7f2f55 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 756f8be9c3cd437e131e6410cd625c24fe078e8c"
bgruening
parents: 3
diff changeset
610 del os
00819b7f2f55 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 756f8be9c3cd437e131e6410cd625c24fe078e8c"
bgruening
parents: 3
diff changeset
611
2
e18d9b17c322 planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit c035d399196b3bef9982db4f8e47331411dbb20e
bgruening
parents: 0
diff changeset
612 keys = list(rval.keys())
e18d9b17c322 planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit c035d399196b3bef9982db4f8e47331411dbb20e
bgruening
parents: 0
diff changeset
613 for k in keys:
e18d9b17c322 planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit c035d399196b3bef9982db4f8e47331411dbb20e
bgruening
parents: 0
diff changeset
614 if k.startswith('test'):
e18d9b17c322 planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit c035d399196b3bef9982db4f8e47331411dbb20e
bgruening
parents: 0
diff changeset
615 rval['mean_' + k] = np.mean(rval[k])
e18d9b17c322 planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit c035d399196b3bef9982db4f8e47331411dbb20e
bgruening
parents: 0
diff changeset
616 rval['std_' + k] = np.std(rval[k])
e18d9b17c322 planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit c035d399196b3bef9982db4f8e47331411dbb20e
bgruening
parents: 0
diff changeset
617 if k.endswith('time'):
e18d9b17c322 planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit c035d399196b3bef9982db4f8e47331411dbb20e
bgruening
parents: 0
diff changeset
618 rval.pop(k)
e18d9b17c322 planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit c035d399196b3bef9982db4f8e47331411dbb20e
bgruening
parents: 0
diff changeset
619 rval = pd.DataFrame(rval)
e18d9b17c322 planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit c035d399196b3bef9982db4f8e47331411dbb20e
bgruening
parents: 0
diff changeset
620 rval = rval[sorted(rval.columns)]
7
00819b7f2f55 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 756f8be9c3cd437e131e6410cd625c24fe078e8c"
bgruening
parents: 3
diff changeset
621 rval.to_csv(path_or_buf=outfile_result, sep='\t', header=True,
00819b7f2f55 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 756f8be9c3cd437e131e6410cd625c24fe078e8c"
bgruening
parents: 3
diff changeset
622 index=False)
00819b7f2f55 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 756f8be9c3cd437e131e6410cd625c24fe078e8c"
bgruening
parents: 3
diff changeset
623
00819b7f2f55 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 756f8be9c3cd437e131e6410cd625c24fe078e8c"
bgruening
parents: 3
diff changeset
624 return 0
0
47467890f541 planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ab963ec9498bd05d2fb2f24f75adb2fccae7958c
bgruening
parents:
diff changeset
625
7
00819b7f2f55 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 756f8be9c3cd437e131e6410cd625c24fe078e8c"
bgruening
parents: 3
diff changeset
626 # deprecate train test split mode
00819b7f2f55 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 756f8be9c3cd437e131e6410cd625c24fe078e8c"
bgruening
parents: 3
diff changeset
627 """searcher = _do_train_test_split_val(
00819b7f2f55 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 756f8be9c3cd437e131e6410cd625c24fe078e8c"
bgruening
parents: 3
diff changeset
628 searcher, X, y, params,
00819b7f2f55 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 756f8be9c3cd437e131e6410cd625c24fe078e8c"
bgruening
parents: 3
diff changeset
629 primary_scoring=primary_scoring,
00819b7f2f55 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 756f8be9c3cd437e131e6410cd625c24fe078e8c"
bgruening
parents: 3
diff changeset
630 error_score=options['error_score'],
00819b7f2f55 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 756f8be9c3cd437e131e6410cd625c24fe078e8c"
bgruening
parents: 3
diff changeset
631 groups=groups,
00819b7f2f55 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 756f8be9c3cd437e131e6410cd625c24fe078e8c"
bgruening
parents: 3
diff changeset
632 outfile=outfile_result)"""
0
47467890f541 planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ab963ec9498bd05d2fb2f24f75adb2fccae7958c
bgruening
parents:
diff changeset
633
7
00819b7f2f55 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 756f8be9c3cd437e131e6410cd625c24fe078e8c"
bgruening
parents: 3
diff changeset
634 # no outer split
00819b7f2f55 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 756f8be9c3cd437e131e6410cd625c24fe078e8c"
bgruening
parents: 3
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635 else:
00819b7f2f55 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 756f8be9c3cd437e131e6410cd625c24fe078e8c"
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636 searcher.set_params(n_jobs=N_JOBS)
2
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parents: 0
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637 if options['error_score'] == 'raise':
e18d9b17c322 planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit c035d399196b3bef9982db4f8e47331411dbb20e
bgruening
parents: 0
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638 searcher.fit(X, y, groups=groups)
0
47467890f541 planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ab963ec9498bd05d2fb2f24f75adb2fccae7958c
bgruening
parents:
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639 else:
2
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bgruening
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640 warnings.simplefilter('always', FitFailedWarning)
e18d9b17c322 planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit c035d399196b3bef9982db4f8e47331411dbb20e
bgruening
parents: 0
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641 with warnings.catch_warnings(record=True) as w:
e18d9b17c322 planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit c035d399196b3bef9982db4f8e47331411dbb20e
bgruening
parents: 0
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642 try:
e18d9b17c322 planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit c035d399196b3bef9982db4f8e47331411dbb20e
bgruening
parents: 0
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643 searcher.fit(X, y, groups=groups)
e18d9b17c322 planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit c035d399196b3bef9982db4f8e47331411dbb20e
bgruening
parents: 0
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644 except ValueError:
e18d9b17c322 planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit c035d399196b3bef9982db4f8e47331411dbb20e
bgruening
parents: 0
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645 pass
e18d9b17c322 planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit c035d399196b3bef9982db4f8e47331411dbb20e
bgruening
parents: 0
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646 for warning in w:
e18d9b17c322 planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit c035d399196b3bef9982db4f8e47331411dbb20e
bgruening
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647 print(repr(warning.message))
e18d9b17c322 planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit c035d399196b3bef9982db4f8e47331411dbb20e
bgruening
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648
7
00819b7f2f55 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 756f8be9c3cd437e131e6410cd625c24fe078e8c"
bgruening
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649 cv_results = pd.DataFrame(searcher.cv_results_)
00819b7f2f55 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 756f8be9c3cd437e131e6410cd625c24fe078e8c"
bgruening
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650 cv_results = cv_results[sorted(cv_results.columns)]
00819b7f2f55 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 756f8be9c3cd437e131e6410cd625c24fe078e8c"
bgruening
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651 cv_results.to_csv(path_or_buf=outfile_result, sep='\t',
00819b7f2f55 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 756f8be9c3cd437e131e6410cd625c24fe078e8c"
bgruening
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652 header=True, index=False)
0
47467890f541 planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ab963ec9498bd05d2fb2f24f75adb2fccae7958c
bgruening
parents:
diff changeset
653
47467890f541 planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ab963ec9498bd05d2fb2f24f75adb2fccae7958c
bgruening
parents:
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654 memory.clear(warn=False)
47467890f541 planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ab963ec9498bd05d2fb2f24f75adb2fccae7958c
bgruening
parents:
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655
7
00819b7f2f55 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 756f8be9c3cd437e131e6410cd625c24fe078e8c"
bgruening
parents: 3
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656 # output best estimator, and weights if applicable
0
47467890f541 planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ab963ec9498bd05d2fb2f24f75adb2fccae7958c
bgruening
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657 if outfile_object:
2
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bgruening
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658 best_estimator_ = getattr(searcher, 'best_estimator_', None)
e18d9b17c322 planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit c035d399196b3bef9982db4f8e47331411dbb20e
bgruening
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659 if not best_estimator_:
e18d9b17c322 planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit c035d399196b3bef9982db4f8e47331411dbb20e
bgruening
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660 warnings.warn("GridSearchCV object has no attribute "
e18d9b17c322 planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit c035d399196b3bef9982db4f8e47331411dbb20e
bgruening
parents: 0
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661 "'best_estimator_', because either it's "
e18d9b17c322 planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit c035d399196b3bef9982db4f8e47331411dbb20e
bgruening
parents: 0
diff changeset
662 "nested gridsearch or `refit` is False!")
e18d9b17c322 planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit c035d399196b3bef9982db4f8e47331411dbb20e
bgruening
parents: 0
diff changeset
663 return
e18d9b17c322 planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit c035d399196b3bef9982db4f8e47331411dbb20e
bgruening
parents: 0
diff changeset
664
7
00819b7f2f55 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 756f8be9c3cd437e131e6410cd625c24fe078e8c"
bgruening
parents: 3
diff changeset
665 # clean prams
00819b7f2f55 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 756f8be9c3cd437e131e6410cd625c24fe078e8c"
bgruening
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666 best_estimator_ = clean_params(best_estimator_)
00819b7f2f55 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 756f8be9c3cd437e131e6410cd625c24fe078e8c"
bgruening
parents: 3
diff changeset
667
00819b7f2f55 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 756f8be9c3cd437e131e6410cd625c24fe078e8c"
bgruening
parents: 3
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668 main_est = get_main_estimator(best_estimator_)
2
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bgruening
parents: 0
diff changeset
669
e18d9b17c322 planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit c035d399196b3bef9982db4f8e47331411dbb20e
bgruening
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670 if hasattr(main_est, 'model_') \
e18d9b17c322 planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit c035d399196b3bef9982db4f8e47331411dbb20e
bgruening
parents: 0
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671 and hasattr(main_est, 'save_weights'):
e18d9b17c322 planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit c035d399196b3bef9982db4f8e47331411dbb20e
bgruening
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672 if outfile_weights:
e18d9b17c322 planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit c035d399196b3bef9982db4f8e47331411dbb20e
bgruening
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673 main_est.save_weights(outfile_weights)
e18d9b17c322 planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit c035d399196b3bef9982db4f8e47331411dbb20e
bgruening
parents: 0
diff changeset
674 del main_est.model_
e18d9b17c322 planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit c035d399196b3bef9982db4f8e47331411dbb20e
bgruening
parents: 0
diff changeset
675 del main_est.fit_params
e18d9b17c322 planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit c035d399196b3bef9982db4f8e47331411dbb20e
bgruening
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676 del main_est.model_class_
e18d9b17c322 planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit c035d399196b3bef9982db4f8e47331411dbb20e
bgruening
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677 del main_est.validation_data
e18d9b17c322 planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit c035d399196b3bef9982db4f8e47331411dbb20e
bgruening
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678 if getattr(main_est, 'data_generator_', None):
e18d9b17c322 planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit c035d399196b3bef9982db4f8e47331411dbb20e
bgruening
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diff changeset
679 del main_est.data_generator_
e18d9b17c322 planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit c035d399196b3bef9982db4f8e47331411dbb20e
bgruening
parents: 0
diff changeset
680
0
47467890f541 planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ab963ec9498bd05d2fb2f24f75adb2fccae7958c
bgruening
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681 with open(outfile_object, 'wb') as output_handler:
7
00819b7f2f55 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 756f8be9c3cd437e131e6410cd625c24fe078e8c"
bgruening
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682 print("Best estimator is saved: %s " % repr(best_estimator_))
2
e18d9b17c322 planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit c035d399196b3bef9982db4f8e47331411dbb20e
bgruening
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683 pickle.dump(best_estimator_, output_handler,
e18d9b17c322 planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit c035d399196b3bef9982db4f8e47331411dbb20e
bgruening
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684 pickle.HIGHEST_PROTOCOL)
0
47467890f541 planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ab963ec9498bd05d2fb2f24f75adb2fccae7958c
bgruening
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diff changeset
685
47467890f541 planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ab963ec9498bd05d2fb2f24f75adb2fccae7958c
bgruening
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686
47467890f541 planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ab963ec9498bd05d2fb2f24f75adb2fccae7958c
bgruening
parents:
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687 if __name__ == '__main__':
47467890f541 planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ab963ec9498bd05d2fb2f24f75adb2fccae7958c
bgruening
parents:
diff changeset
688 aparser = argparse.ArgumentParser()
47467890f541 planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ab963ec9498bd05d2fb2f24f75adb2fccae7958c
bgruening
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diff changeset
689 aparser.add_argument("-i", "--inputs", dest="inputs", required=True)
47467890f541 planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ab963ec9498bd05d2fb2f24f75adb2fccae7958c
bgruening
parents:
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690 aparser.add_argument("-e", "--estimator", dest="infile_estimator")
47467890f541 planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ab963ec9498bd05d2fb2f24f75adb2fccae7958c
bgruening
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691 aparser.add_argument("-X", "--infile1", dest="infile1")
47467890f541 planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ab963ec9498bd05d2fb2f24f75adb2fccae7958c
bgruening
parents:
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692 aparser.add_argument("-y", "--infile2", dest="infile2")
2
e18d9b17c322 planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit c035d399196b3bef9982db4f8e47331411dbb20e
bgruening
parents: 0
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693 aparser.add_argument("-O", "--outfile_result", dest="outfile_result")
0
47467890f541 planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ab963ec9498bd05d2fb2f24f75adb2fccae7958c
bgruening
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694 aparser.add_argument("-o", "--outfile_object", dest="outfile_object")
2
e18d9b17c322 planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit c035d399196b3bef9982db4f8e47331411dbb20e
bgruening
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695 aparser.add_argument("-w", "--outfile_weights", dest="outfile_weights")
0
47467890f541 planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ab963ec9498bd05d2fb2f24f75adb2fccae7958c
bgruening
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696 aparser.add_argument("-g", "--groups", dest="groups")
2
e18d9b17c322 planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit c035d399196b3bef9982db4f8e47331411dbb20e
bgruening
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697 aparser.add_argument("-r", "--ref_seq", dest="ref_seq")
e18d9b17c322 planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit c035d399196b3bef9982db4f8e47331411dbb20e
bgruening
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698 aparser.add_argument("-b", "--intervals", dest="intervals")
e18d9b17c322 planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit c035d399196b3bef9982db4f8e47331411dbb20e
bgruening
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699 aparser.add_argument("-t", "--targets", dest="targets")
e18d9b17c322 planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit c035d399196b3bef9982db4f8e47331411dbb20e
bgruening
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700 aparser.add_argument("-f", "--fasta_path", dest="fasta_path")
0
47467890f541 planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ab963ec9498bd05d2fb2f24f75adb2fccae7958c
bgruening
parents:
diff changeset
701 args = aparser.parse_args()
47467890f541 planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ab963ec9498bd05d2fb2f24f75adb2fccae7958c
bgruening
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diff changeset
702
47467890f541 planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ab963ec9498bd05d2fb2f24f75adb2fccae7958c
bgruening
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703 main(args.inputs, args.infile_estimator, args.infile1, args.infile2,
47467890f541 planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ab963ec9498bd05d2fb2f24f75adb2fccae7958c
bgruening
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704 args.outfile_result, outfile_object=args.outfile_object,
2
e18d9b17c322 planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit c035d399196b3bef9982db4f8e47331411dbb20e
bgruening
parents: 0
diff changeset
705 outfile_weights=args.outfile_weights, groups=args.groups,
e18d9b17c322 planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit c035d399196b3bef9982db4f8e47331411dbb20e
bgruening
parents: 0
diff changeset
706 ref_seq=args.ref_seq, intervals=args.intervals,
e18d9b17c322 planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit c035d399196b3bef9982db4f8e47331411dbb20e
bgruening
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707 targets=args.targets, fasta_path=args.fasta_path)