Mercurial > repos > bgruening > sklearn_numeric_clustering

annotate keras_train_and_eval.py @ 34:816b65d52c33 draft

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"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
author bgruening
date Tue, 13 Apr 2021 18:05:02 +0000
parents 83938131dd46
children e7f047a9dca9
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1 import argparse
83938131dd46 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
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2 import joblib
83938131dd46 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
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3 import json
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4 import numpy as np
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5 import os
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6 import pandas as pd
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7 import pickle
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8 import warnings
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9 from itertools import chain
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10 from scipy.io import mmread
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11 from sklearn.pipeline import Pipeline
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12 from sklearn.metrics.scorer import _check_multimetric_scoring
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13 from sklearn.model_selection._validation import _score
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14 from sklearn.model_selection import _search, _validation
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15 from sklearn.utils import indexable, safe_indexing
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17 from galaxy_ml.externals.selene_sdk.utils import compute_score
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18 from galaxy_ml.model_validations import train_test_split
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19 from galaxy_ml.keras_galaxy_models import _predict_generator
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20 from galaxy_ml.utils import (
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21 SafeEval,
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22 get_scoring,
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23 load_model,
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24 read_columns,
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25 try_get_attr,
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26 get_module,
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27 clean_params,
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28 get_main_estimator,
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29 )
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32 _fit_and_score = try_get_attr("galaxy_ml.model_validations", "_fit_and_score")
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33 setattr(_search, "_fit_and_score", _fit_and_score)
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34 setattr(_validation, "_fit_and_score", _fit_and_score)
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35
34
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36 N_JOBS = int(os.environ.get("GALAXY_SLOTS", 1))
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37 CACHE_DIR = os.path.join(os.getcwd(), "cached")
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38 del os
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39 NON_SEARCHABLE = ("n_jobs", "pre_dispatch", "memory", "_path", "nthread", "callbacks")
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40 ALLOWED_CALLBACKS = (
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41 "EarlyStopping",
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42 "TerminateOnNaN",
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43 "ReduceLROnPlateau",
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44 "CSVLogger",
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45 "None",
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46 )
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48
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49 def _eval_swap_params(params_builder):
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50 swap_params = {}
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51
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52 for p in params_builder["param_set"]:
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53 swap_value = p["sp_value"].strip()
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54 if swap_value == "":
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55 continue
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57 param_name = p["sp_name"]
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58 if param_name.lower().endswith(NON_SEARCHABLE):
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59 warnings.warn("Warning: `%s` is not eligible for search and was " "omitted!" % param_name)
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60 continue
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61
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62 if not swap_value.startswith(":"):
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63 safe_eval = SafeEval(load_scipy=True, load_numpy=True)
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64 ev = safe_eval(swap_value)
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65 else:
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66 # Have `:` before search list, asks for estimator evaluatio
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67 safe_eval_es = SafeEval(load_estimators=True)
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68 swap_value = swap_value[1:].strip()
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69 # TODO maybe add regular express check
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70 ev = safe_eval_es(swap_value)
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72 swap_params[param_name] = ev
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74 return swap_params
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77 def train_test_split_none(*arrays, **kwargs):
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78 """extend train_test_split to take None arrays
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79 and support split by group names.
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80 """
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81 nones = []
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82 new_arrays = []
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83 for idx, arr in enumerate(arrays):
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84 if arr is None:
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85 nones.append(idx)
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86 else:
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87 new_arrays.append(arr)
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88
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89 if kwargs["shuffle"] == "None":
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90 kwargs["shuffle"] = None
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91
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92 group_names = kwargs.pop("group_names", None)
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93
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94 if group_names is not None and group_names.strip():
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95 group_names = [name.strip() for name in group_names.split(",")]
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96 new_arrays = indexable(*new_arrays)
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97 groups = kwargs["labels"]
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98 n_samples = new_arrays[0].shape[0]
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99 index_arr = np.arange(n_samples)
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100 test = index_arr[np.isin(groups, group_names)]
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101 train = index_arr[~np.isin(groups, group_names)]
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102 rval = list(chain.from_iterable((safe_indexing(a, train), safe_indexing(a, test)) for a in new_arrays))
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103 else:
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104 rval = train_test_split(*new_arrays, **kwargs)
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105
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106 for pos in nones:
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107 rval[pos * 2 : 2] = [None, None]
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108
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109 return rval
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110
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111
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112 def _evaluate(y_true, pred_probas, scorer, is_multimetric=True):
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113 """output scores based on input scorer
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114
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115 Parameters
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116 ----------
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117 y_true : array
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118 True label or target values
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119 pred_probas : array
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120 Prediction values, probability for classification problem
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121 scorer : dict
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122 dict of `sklearn.metrics.scorer.SCORER`
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123 is_multimetric : bool, default is True
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124 """
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125 if y_true.ndim == 1 or y_true.shape[-1] == 1:
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126 pred_probas = pred_probas.ravel()
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127 pred_labels = (pred_probas > 0.5).astype("int32")
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128 targets = y_true.ravel().astype("int32")
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129 if not is_multimetric:
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130 preds = pred_labels if scorer.__class__.__name__ == "_PredictScorer" else pred_probas
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131 score = scorer._score_func(targets, preds, **scorer._kwargs)
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132
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133 return score
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134 else:
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135 scores = {}
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136 for name, one_scorer in scorer.items():
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137 preds = pred_labels if one_scorer.__class__.__name__ == "_PredictScorer" else pred_probas
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138 score = one_scorer._score_func(targets, preds, **one_scorer._kwargs)
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139 scores[name] = score
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140
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141 # TODO: multi-class metrics
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142 # multi-label
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143 else:
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144 pred_labels = (pred_probas > 0.5).astype("int32")
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145 targets = y_true.astype("int32")
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146 if not is_multimetric:
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147 preds = pred_labels if scorer.__class__.__name__ == "_PredictScorer" else pred_probas
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148 score, _ = compute_score(preds, targets, scorer._score_func)
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149 return score
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150 else:
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151 scores = {}
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152 for name, one_scorer in scorer.items():
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153 preds = pred_labels if one_scorer.__class__.__name__ == "_PredictScorer" else pred_probas
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154 score, _ = compute_score(preds, targets, one_scorer._score_func)
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155 scores[name] = score
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156
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157 return scores
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158
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159
34
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160 def main(
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161 inputs,
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162 infile_estimator,
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163 infile1,
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164 infile2,
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165 outfile_result,
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166 outfile_object=None,
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167 outfile_weights=None,
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168 outfile_y_true=None,
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169 outfile_y_preds=None,
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170 groups=None,
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171 ref_seq=None,
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172 intervals=None,
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173 targets=None,
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174 fasta_path=None,
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175 ):
31
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176 """
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177 Parameter
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178 ---------
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179 inputs : str
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180 File path to galaxy tool parameter
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181
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182 infile_estimator : str
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183 File path to estimator
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184
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185 infile1 : str
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186 File path to dataset containing features
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187
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188 infile2 : str
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189 File path to dataset containing target values
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190
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191 outfile_result : str
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192 File path to save the results, either cv_results or test result
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193
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194 outfile_object : str, optional
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195 File path to save searchCV object
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196
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197 outfile_weights : str, optional
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198 File path to save deep learning model weights
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199
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200 outfile_y_true : str, optional
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201 File path to target values for prediction
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202
83938131dd46 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
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203 outfile_y_preds : str, optional
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204 File path to save deep learning model weights
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205
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206 groups : str
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207 File path to dataset containing groups labels
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208
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209 ref_seq : str
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210 File path to dataset containing genome sequence file
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211
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212 intervals : str
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213 File path to dataset containing interval file
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214
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215 targets : str
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216 File path to dataset compressed target bed file
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217
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218 fasta_path : str
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219 File path to dataset containing fasta file
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220 """
34
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221 warnings.simplefilter("ignore")
31
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222
34
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223 with open(inputs, "r") as param_handler:
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224 params = json.load(param_handler)
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225
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226 # load estimator
34
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227 with open(infile_estimator, "rb") as estimator_handler:
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228 estimator = load_model(estimator_handler)
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229
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230 estimator = clean_params(estimator)
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231
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232 # swap hyperparameter
34
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233 swapping = params["experiment_schemes"]["hyperparams_swapping"]
31
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234 swap_params = _eval_swap_params(swapping)
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235 estimator.set_params(**swap_params)
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236
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237 estimator_params = estimator.get_params()
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238
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239 # store read dataframe object
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240 loaded_df = {}
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241
34
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242 input_type = params["input_options"]["selected_input"]
31
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243 # tabular input
34
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244 if input_type == "tabular":
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245 header = "infer" if params["input_options"]["header1"] else None
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246 column_option = params["input_options"]["column_selector_options_1"]["selected_column_selector_option"]
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247 if column_option in [
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248 "by_index_number",
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249 "all_but_by_index_number",
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250 "by_header_name",
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251 "all_but_by_header_name",
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252 ]:
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253 c = params["input_options"]["column_selector_options_1"]["col1"]
31
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254 else:
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255 c = None
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256
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257 df_key = infile1 + repr(header)
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258 df = pd.read_csv(infile1, sep="\t", header=header, parse_dates=True)
31
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259 loaded_df[df_key] = df
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260
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261 X = read_columns(df, c=c, c_option=column_option).astype(float)
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262 # sparse input
34
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263 elif input_type == "sparse":
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264 X = mmread(open(infile1, "r"))
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265
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266 # fasta_file input
34
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267 elif input_type == "seq_fasta":
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268 pyfaidx = get_module("pyfaidx")
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269 sequences = pyfaidx.Fasta(fasta_path)
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270 n_seqs = len(sequences.keys())
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271 X = np.arange(n_seqs)[:, np.newaxis]
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272 for param in estimator_params.keys():
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273 if param.endswith("fasta_path"):
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274 estimator.set_params(**{param: fasta_path})
31
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275 break
83938131dd46 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
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276 else:
83938131dd46 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
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277 raise ValueError(
83938131dd46 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
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278 "The selected estimator doesn't support "
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279 "fasta file input! Please consider using "
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280 "KerasGBatchClassifier with "
83938131dd46 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
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281 "FastaDNABatchGenerator/FastaProteinBatchGenerator "
83938131dd46 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
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282 "or having GenomeOneHotEncoder/ProteinOneHotEncoder "
34
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283 "in pipeline!"
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284 )
31
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285
34
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286 elif input_type == "refseq_and_interval":
31
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287 path_params = {
34
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288 "data_batch_generator__ref_genome_path": ref_seq,
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289 "data_batch_generator__intervals_path": intervals,
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290 "data_batch_generator__target_path": targets,
31
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291 }
83938131dd46 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
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292 estimator.set_params(**path_params)
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293 n_intervals = sum(1 for line in open(intervals))
83938131dd46 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
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294 X = np.arange(n_intervals)[:, np.newaxis]
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295
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296 # Get target y
34
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297 header = "infer" if params["input_options"]["header2"] else None
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298 column_option = params["input_options"]["column_selector_options_2"]["selected_column_selector_option2"]
816b65d52c33 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
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299 if column_option in [
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300 "by_index_number",
816b65d52c33 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
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301 "all_but_by_index_number",
816b65d52c33 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
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302 "by_header_name",
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303 "all_but_by_header_name",
816b65d52c33 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
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304 ]:
816b65d52c33 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
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305 c = params["input_options"]["column_selector_options_2"]["col2"]
31
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306 else:
83938131dd46 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
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307 c = None
83938131dd46 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
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308
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309 df_key = infile2 + repr(header)
83938131dd46 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
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310 if df_key in loaded_df:
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311 infile2 = loaded_df[df_key]
83938131dd46 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
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312 else:
34
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diff changeset
313 infile2 = pd.read_csv(infile2, sep="\t", header=header, parse_dates=True)
31
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314 loaded_df[df_key] = infile2
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315
34
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316 y = read_columns(infile2,
816b65d52c33 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
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317 c=c,
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318 c_option=column_option,
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diff changeset
319 sep='\t',
816b65d52c33 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
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320 header=header,
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321 parse_dates=True)
31
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322 if len(y.shape) == 2 and y.shape[1] == 1:
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323 y = y.ravel()
34
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diff changeset
324 if input_type == "refseq_and_interval":
816b65d52c33 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
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diff changeset
325 estimator.set_params(data_batch_generator__features=y.ravel().tolist())
31
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326 y = None
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327 # end y
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diff changeset
328
83938131dd46 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
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329 # load groups
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330 if groups:
34
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diff changeset
331 groups_selector = (params["experiment_schemes"]["test_split"]["split_algos"]).pop("groups_selector")
31
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diff changeset
332
34
816b65d52c33 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
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diff changeset
333 header = "infer" if groups_selector["header_g"] else None
816b65d52c33 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
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diff changeset
334 column_option = groups_selector["column_selector_options_g"]["selected_column_selector_option_g"]
816b65d52c33 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
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parents: 31
diff changeset
335 if column_option in [
816b65d52c33 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
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parents: 31
diff changeset
336 "by_index_number",
816b65d52c33 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
bgruening
parents: 31
diff changeset
337 "all_but_by_index_number",
816b65d52c33 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
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parents: 31
diff changeset
338 "by_header_name",
816b65d52c33 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
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diff changeset
339 "all_but_by_header_name",
816b65d52c33 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
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parents: 31
diff changeset
340 ]:
816b65d52c33 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
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diff changeset
341 c = groups_selector["column_selector_options_g"]["col_g"]
31
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342 else:
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343 c = None
83938131dd46 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
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344
83938131dd46 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
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345 df_key = groups + repr(header)
83938131dd46 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
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346 if df_key in loaded_df:
83938131dd46 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
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347 groups = loaded_df[df_key]
83938131dd46 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
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diff changeset
348
34
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diff changeset
349 groups = read_columns(groups,
816b65d52c33 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
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diff changeset
350 c=c,
816b65d52c33 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
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diff changeset
351 c_option=column_option,
816b65d52c33 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
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diff changeset
352 sep='\t',
816b65d52c33 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
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diff changeset
353 header=header,
816b65d52c33 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
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diff changeset
354 parse_dates=True)
31
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diff changeset
355 groups = groups.ravel()
83938131dd46 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
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diff changeset
356
83938131dd46 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
bgruening
parents:
diff changeset
357 # del loaded_df
83938131dd46 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
bgruening
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diff changeset
358 del loaded_df
83938131dd46 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
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359
83938131dd46 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
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360 # cache iraps_core fits could increase search speed significantly
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361 memory = joblib.Memory(location=CACHE_DIR, verbose=0)
83938131dd46 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
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362 main_est = get_main_estimator(estimator)
34
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diff changeset
363 if main_est.__class__.__name__ == "IRAPSClassifier":
31
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diff changeset
364 main_est.set_params(memory=memory)
83938131dd46 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
bgruening
parents:
diff changeset
365
83938131dd46 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
bgruening
parents:
diff changeset
366 # handle scorer, convert to scorer dict
83938131dd46 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
bgruening
parents:
diff changeset
367 scoring = params['experiment_schemes']['metrics']['scoring']
34
816b65d52c33 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
bgruening
parents: 31
diff changeset
368 if scoring is not None:
816b65d52c33 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
bgruening
parents: 31
diff changeset
369 # get_scoring() expects secondary_scoring to be a comma separated string (not a list)
816b65d52c33 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
bgruening
parents: 31
diff changeset
370 # Check if secondary_scoring is specified
816b65d52c33 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
bgruening
parents: 31
diff changeset
371 secondary_scoring = scoring.get("secondary_scoring", None)
816b65d52c33 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
bgruening
parents: 31
diff changeset
372 if secondary_scoring is not None:
816b65d52c33 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
bgruening
parents: 31
diff changeset
373 # If secondary_scoring is specified, convert the list into comman separated string
816b65d52c33 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
bgruening
parents: 31
diff changeset
374 scoring["secondary_scoring"] = ",".join(scoring["secondary_scoring"])
816b65d52c33 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
bgruening
parents: 31
diff changeset
375
31
83938131dd46 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
bgruening
parents:
diff changeset
376 scorer = get_scoring(scoring)
83938131dd46 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
bgruening
parents:
diff changeset
377 scorer, _ = _check_multimetric_scoring(estimator, scoring=scorer)
83938131dd46 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
bgruening
parents:
diff changeset
378
83938131dd46 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
bgruening
parents:
diff changeset
379 # handle test (first) split
34
816b65d52c33 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
bgruening
parents: 31
diff changeset
380 test_split_options = params["experiment_schemes"]["test_split"]["split_algos"]
31
83938131dd46 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
bgruening
parents:
diff changeset
381
34
816b65d52c33 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
bgruening
parents: 31
diff changeset
382 if test_split_options["shuffle"] == "group":
816b65d52c33 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
bgruening
parents: 31
diff changeset
383 test_split_options["labels"] = groups
816b65d52c33 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
bgruening
parents: 31
diff changeset
384 if test_split_options["shuffle"] == "stratified":
31
83938131dd46 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
bgruening
parents:
diff changeset
385 if y is not None:
34
816b65d52c33 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
bgruening
parents: 31
diff changeset
386 test_split_options["labels"] = y
31
83938131dd46 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
bgruening
parents:
diff changeset
387 else:
34
816b65d52c33 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
bgruening
parents: 31
diff changeset
388 raise ValueError("Stratified shuffle split is not " "applicable on empty target values!")
31
83938131dd46 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
bgruening
parents:
diff changeset
389
34
816b65d52c33 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
bgruening
parents: 31
diff changeset
390 (
816b65d52c33 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
bgruening
parents: 31
diff changeset
391 X_train,
816b65d52c33 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
bgruening
parents: 31
diff changeset
392 X_test,
816b65d52c33 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
bgruening
parents: 31
diff changeset
393 y_train,
816b65d52c33 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
bgruening
parents: 31
diff changeset
394 y_test,
816b65d52c33 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
bgruening
parents: 31
diff changeset
395 groups_train,
816b65d52c33 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
bgruening
parents: 31
diff changeset
396 _groups_test,
816b65d52c33 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
bgruening
parents: 31
diff changeset
397 ) = train_test_split_none(X, y, groups, **test_split_options)
31
83938131dd46 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
bgruening
parents:
diff changeset
398
34
816b65d52c33 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
bgruening
parents: 31
diff changeset
399 exp_scheme = params["experiment_schemes"]["selected_exp_scheme"]
31
83938131dd46 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
bgruening
parents:
diff changeset
400
83938131dd46 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
bgruening
parents:
diff changeset
401 # handle validation (second) split
34
816b65d52c33 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
bgruening
parents: 31
diff changeset
402 if exp_scheme == "train_val_test":
816b65d52c33 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
bgruening
parents: 31
diff changeset
403 val_split_options = params["experiment_schemes"]["val_split"]["split_algos"]
31
83938131dd46 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
bgruening
parents:
diff changeset
404
34
816b65d52c33 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
bgruening
parents: 31
diff changeset
405 if val_split_options["shuffle"] == "group":
816b65d52c33 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
bgruening
parents: 31
diff changeset
406 val_split_options["labels"] = groups_train
816b65d52c33 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
bgruening
parents: 31
diff changeset
407 if val_split_options["shuffle"] == "stratified":
31
83938131dd46 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
bgruening
parents:
diff changeset
408 if y_train is not None:
34
816b65d52c33 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
bgruening
parents: 31
diff changeset
409 val_split_options["labels"] = y_train
31
83938131dd46 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
bgruening
parents:
diff changeset
410 else:
34
816b65d52c33 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
bgruening
parents: 31
diff changeset
411 raise ValueError("Stratified shuffle split is not " "applicable on empty target values!")
31
83938131dd46 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
bgruening
parents:
diff changeset
412
34
816b65d52c33 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
bgruening
parents: 31
diff changeset
413 (
816b65d52c33 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
bgruening
parents: 31
diff changeset
414 X_train,
816b65d52c33 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
bgruening
parents: 31
diff changeset
415 X_val,
816b65d52c33 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
bgruening
parents: 31
diff changeset
416 y_train,
816b65d52c33 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
bgruening
parents: 31
diff changeset
417 y_val,
816b65d52c33 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
bgruening
parents: 31
diff changeset
418 groups_train,
816b65d52c33 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
bgruening
parents: 31
diff changeset
419 _groups_val,
816b65d52c33 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
bgruening
parents: 31
diff changeset
420 ) = train_test_split_none(X_train, y_train, groups_train, **val_split_options)
31
83938131dd46 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
bgruening
parents:
diff changeset
421
83938131dd46 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
bgruening
parents:
diff changeset
422 # train and eval
34
816b65d52c33 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
bgruening
parents: 31
diff changeset
423 if hasattr(estimator, "validation_data"):
816b65d52c33 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
bgruening
parents: 31
diff changeset
424 if exp_scheme == "train_val_test":
816b65d52c33 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
bgruening
parents: 31
diff changeset
425 estimator.fit(X_train, y_train, validation_data=(X_val, y_val))
31
83938131dd46 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
bgruening
parents:
diff changeset
426 else:
34
816b65d52c33 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
bgruening
parents: 31
diff changeset
427 estimator.fit(X_train, y_train, validation_data=(X_test, y_test))
31
83938131dd46 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
bgruening
parents:
diff changeset
428 else:
83938131dd46 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
bgruening
parents:
diff changeset
429 estimator.fit(X_train, y_train)
83938131dd46 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
bgruening
parents:
diff changeset
430
34
816b65d52c33 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
bgruening
parents: 31
diff changeset
431 if hasattr(estimator, "evaluate"):
31
83938131dd46 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
bgruening
parents:
diff changeset
432 steps = estimator.prediction_steps
83938131dd46 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
bgruening
parents:
diff changeset
433 batch_size = estimator.batch_size
34
816b65d52c33 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
bgruening
parents: 31
diff changeset
434 generator = estimator.data_generator_.flow(X_test, y=y_test, batch_size=batch_size)
816b65d52c33 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
bgruening
parents: 31
diff changeset
435 predictions, y_true = _predict_generator(estimator.model_, generator, steps=steps)
31
83938131dd46 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
bgruening
parents:
diff changeset
436 scores = _evaluate(y_true, predictions, scorer, is_multimetric=True)
83938131dd46 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
bgruening
parents:
diff changeset
437
83938131dd46 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
bgruening
parents:
diff changeset
438 else:
34
816b65d52c33 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
bgruening
parents: 31
diff changeset
439 if hasattr(estimator, "predict_proba"):
31
83938131dd46 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
bgruening
parents:
diff changeset
440 predictions = estimator.predict_proba(X_test)
83938131dd46 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
bgruening
parents:
diff changeset
441 else:
83938131dd46 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
bgruening
parents:
diff changeset
442 predictions = estimator.predict(X_test)
83938131dd46 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
bgruening
parents:
diff changeset
443
83938131dd46 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
bgruening
parents:
diff changeset
444 y_true = y_test
34
816b65d52c33 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
bgruening
parents: 31
diff changeset
445 scores = _score(estimator, X_test, y_test, scorer, is_multimetric=True)
31
83938131dd46 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
bgruening
parents:
diff changeset
446 if outfile_y_true:
83938131dd46 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
bgruening
parents:
diff changeset
447 try:
34
816b65d52c33 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
bgruening
parents: 31
diff changeset
448 pd.DataFrame(y_true).to_csv(outfile_y_true, sep="\t", index=False)
31
83938131dd46 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
bgruening
parents:
diff changeset
449 pd.DataFrame(predictions).astype(np.float32).to_csv(
34
816b65d52c33 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
bgruening
parents: 31
diff changeset
450 outfile_y_preds,
816b65d52c33 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
bgruening
parents: 31
diff changeset
451 sep="\t",
816b65d52c33 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
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452 index=False,
816b65d52c33 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
bgruening
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diff changeset
453 float_format="%g",
816b65d52c33 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
bgruening
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diff changeset
454 chunksize=10000,
816b65d52c33 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
bgruening
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diff changeset
455 )
31
83938131dd46 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
bgruening
parents:
diff changeset
456 except Exception as e:
83938131dd46 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
bgruening
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457 print("Error in saving predictions: %s" % e)
83938131dd46 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
bgruening
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458
83938131dd46 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
bgruening
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459 # handle output
83938131dd46 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
bgruening
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460 for name, score in scores.items():
83938131dd46 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
bgruening
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461 scores[name] = [score]
83938131dd46 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
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462 df = pd.DataFrame(scores)
83938131dd46 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
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463 df = df[sorted(df.columns)]
34
816b65d52c33 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
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464 df.to_csv(path_or_buf=outfile_result, sep="\t", header=True, index=False)
31
83938131dd46 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
bgruening
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diff changeset
465
83938131dd46 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
bgruening
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466 memory.clear(warn=False)
83938131dd46 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
bgruening
parents:
diff changeset
467
83938131dd46 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
bgruening
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diff changeset
468 if outfile_object:
83938131dd46 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
bgruening
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diff changeset
469 main_est = estimator
83938131dd46 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
bgruening
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diff changeset
470 if isinstance(estimator, Pipeline):
83938131dd46 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
bgruening
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diff changeset
471 main_est = estimator.steps[-1][-1]
83938131dd46 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
bgruening
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diff changeset
472
34
816b65d52c33 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
bgruening
parents: 31
diff changeset
473 if hasattr(main_est, "model_") and hasattr(main_est, "save_weights"):
31
83938131dd46 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
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474 if outfile_weights:
83938131dd46 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
bgruening
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diff changeset
475 main_est.save_weights(outfile_weights)
83938131dd46 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
bgruening
parents:
diff changeset
476 del main_est.model_
83938131dd46 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
bgruening
parents:
diff changeset
477 del main_est.fit_params
83938131dd46 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
bgruening
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478 del main_est.model_class_
34
816b65d52c33 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
bgruening
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diff changeset
479 if getattr(main_est, "validation_data", None):
816b65d52c33 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
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diff changeset
480 del main_est.validation_data
816b65d52c33 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
bgruening
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diff changeset
481 if getattr(main_est, "data_generator_", None):
31
83938131dd46 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
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parents:
diff changeset
482 del main_est.data_generator_
83938131dd46 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
bgruening
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diff changeset
483
34
816b65d52c33 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
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diff changeset
484 with open(outfile_object, "wb") as output_handler:
816b65d52c33 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
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diff changeset
485 pickle.dump(estimator, output_handler, pickle.HIGHEST_PROTOCOL)
31
83938131dd46 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
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diff changeset
486
83938131dd46 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
bgruening
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diff changeset
487
34
816b65d52c33 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
bgruening
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diff changeset
488 if __name__ == "__main__":
31
83938131dd46 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
bgruening
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diff changeset
489 aparser = argparse.ArgumentParser()
83938131dd46 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
bgruening
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diff changeset
490 aparser.add_argument("-i", "--inputs", dest="inputs", required=True)
83938131dd46 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
bgruening
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491 aparser.add_argument("-e", "--estimator", dest="infile_estimator")
83938131dd46 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
bgruening
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diff changeset
492 aparser.add_argument("-X", "--infile1", dest="infile1")
83938131dd46 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
bgruening
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493 aparser.add_argument("-y", "--infile2", dest="infile2")
83938131dd46 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
bgruening
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diff changeset
494 aparser.add_argument("-O", "--outfile_result", dest="outfile_result")
83938131dd46 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
bgruening
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diff changeset
495 aparser.add_argument("-o", "--outfile_object", dest="outfile_object")
83938131dd46 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
bgruening
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496 aparser.add_argument("-w", "--outfile_weights", dest="outfile_weights")
83938131dd46 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
bgruening
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diff changeset
497 aparser.add_argument("-l", "--outfile_y_true", dest="outfile_y_true")
83938131dd46 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
bgruening
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diff changeset
498 aparser.add_argument("-p", "--outfile_y_preds", dest="outfile_y_preds")
83938131dd46 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
bgruening
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diff changeset
499 aparser.add_argument("-g", "--groups", dest="groups")
83938131dd46 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
bgruening
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diff changeset
500 aparser.add_argument("-r", "--ref_seq", dest="ref_seq")
83938131dd46 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
bgruening
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diff changeset
501 aparser.add_argument("-b", "--intervals", dest="intervals")
83938131dd46 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
bgruening
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diff changeset
502 aparser.add_argument("-t", "--targets", dest="targets")
83938131dd46 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
bgruening
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diff changeset
503 aparser.add_argument("-f", "--fasta_path", dest="fasta_path")
83938131dd46 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
bgruening
parents:
diff changeset
504 args = aparser.parse_args()
83938131dd46 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
bgruening
parents:
diff changeset
505
34
816b65d52c33 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
bgruening
parents: 31
diff changeset
506 main(
816b65d52c33 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
bgruening
parents: 31
diff changeset
507 args.inputs,
816b65d52c33 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
bgruening
parents: 31
diff changeset
508 args.infile_estimator,
816b65d52c33 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
bgruening
parents: 31
diff changeset
509 args.infile1,
816b65d52c33 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
bgruening
parents: 31
diff changeset
510 args.infile2,
816b65d52c33 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
bgruening
parents: 31
diff changeset
511 args.outfile_result,
816b65d52c33 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
bgruening
parents: 31
diff changeset
512 outfile_object=args.outfile_object,
816b65d52c33 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
bgruening
parents: 31
diff changeset
513 outfile_weights=args.outfile_weights,
816b65d52c33 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
bgruening
parents: 31
diff changeset
514 outfile_y_true=args.outfile_y_true,
816b65d52c33 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
bgruening
parents: 31
diff changeset
515 outfile_y_preds=args.outfile_y_preds,
816b65d52c33 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
bgruening
parents: 31
diff changeset
516 groups=args.groups,
816b65d52c33 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
bgruening
parents: 31
diff changeset
517 ref_seq=args.ref_seq,
816b65d52c33 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
bgruening
parents: 31
diff changeset
518 intervals=args.intervals,
816b65d52c33 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
bgruening
parents: 31
diff changeset
519 targets=args.targets,
816b65d52c33 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
bgruening
parents: 31
diff changeset
520 fasta_path=args.fasta_path,
816b65d52c33 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
bgruening
parents: 31
diff changeset
521 )