Mercurial > repos > bgruening > sklearn_clf_metrics

annotate keras_train_and_eval.py @ 42:9fdff01a34b0 draft

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planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 9981e25b00de29ed881b2229a173a8c812ded9bb
author bgruening
date Wed, 09 Aug 2023 12:37:34 +0000
parents ed7d6d7c6e93
children 21d05f8abca6
Ignore whitespace changes - Everywhere: Within whitespace: At end of lines:
rev   line source
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1 import argparse
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2 import json
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3 import os
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4 import warnings
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5 from itertools import chain
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6
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7 import joblib
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8 import numpy as np
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9 import pandas as pd
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10 from galaxy_ml.keras_galaxy_models import (
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11 _predict_generator,
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12 KerasGBatchClassifier,
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13 )
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14 from galaxy_ml.model_persist import dump_model_to_h5, load_model_from_h5
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15 from galaxy_ml.model_validations import train_test_split
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16 from galaxy_ml.utils import (
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17 clean_params,
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18 gen_compute_scores,
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19 get_main_estimator,
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20 get_module,
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21 get_scoring,
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22 read_columns,
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23 SafeEval
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24 )
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25 from scipy.io import mmread
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26 from sklearn.metrics._scorer import _check_multimetric_scoring
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27 from sklearn.model_selection._validation import _score
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28 from sklearn.utils import _safe_indexing, indexable
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29
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30 N_JOBS = int(os.environ.get("GALAXY_SLOTS", 1))
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31 CACHE_DIR = os.path.join(os.getcwd(), "cached")
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32 NON_SEARCHABLE = (
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33 "n_jobs",
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34 "pre_dispatch",
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35 "memory",
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36 "_path",
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37 "_dir",
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38 "nthread",
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39 "callbacks",
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40 )
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41 ALLOWED_CALLBACKS = (
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42 "EarlyStopping",
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43 "TerminateOnNaN",
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44 "ReduceLROnPlateau",
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45 "CSVLogger",
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46 "None",
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47 )
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50 def _eval_swap_params(params_builder):
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51 swap_params = {}
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52
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53 for p in params_builder["param_set"]:
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54 swap_value = p["sp_value"].strip()
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55 if swap_value == "":
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56 continue
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57
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58 param_name = p["sp_name"]
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59 if param_name.lower().endswith(NON_SEARCHABLE):
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60 warnings.warn(
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61 "Warning: `%s` is not eligible for search and was "
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62 "omitted!" % param_name
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63 )
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64 continue
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65
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66 if not swap_value.startswith(":"):
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67 safe_eval = SafeEval(load_scipy=True, load_numpy=True)
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68 ev = safe_eval(swap_value)
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69 else:
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70 # Have `:` before search list, asks for estimator evaluatio
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71 safe_eval_es = SafeEval(load_estimators=True)
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72 swap_value = swap_value[1:].strip()
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73 # TODO maybe add regular express check
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74 ev = safe_eval_es(swap_value)
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76 swap_params[param_name] = ev
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78 return swap_params
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81 def train_test_split_none(*arrays, **kwargs):
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82 """extend train_test_split to take None arrays
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83 and support split by group names.
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84 """
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85 nones = []
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86 new_arrays = []
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87 for idx, arr in enumerate(arrays):
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88 if arr is None:
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89 nones.append(idx)
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90 else:
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91 new_arrays.append(arr)
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92
35
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93 if kwargs["shuffle"] == "None":
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94 kwargs["shuffle"] = None
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95
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96 group_names = kwargs.pop("group_names", None)
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97
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98 if group_names is not None and group_names.strip():
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99 group_names = [name.strip() for name in group_names.split(",")]
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100 new_arrays = indexable(*new_arrays)
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101 groups = kwargs["labels"]
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102 n_samples = new_arrays[0].shape[0]
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103 index_arr = np.arange(n_samples)
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104 test = index_arr[np.isin(groups, group_names)]
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105 train = index_arr[~np.isin(groups, group_names)]
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106 rval = list(
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107 chain.from_iterable(
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108 (_safe_indexing(a, train), _safe_indexing(a, test)) for a in new_arrays
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109 )
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110 )
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111 else:
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112 rval = train_test_split(*new_arrays, **kwargs)
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113
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114 for pos in nones:
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115 rval[pos * 2: 2] = [None, None]
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116
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117 return rval
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118
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119
41
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120 def _evaluate_keras_and_sklearn_scores(
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121 estimator,
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122 data_generator,
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123 X,
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124 y=None,
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125 sk_scoring=None,
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126 steps=None,
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127 batch_size=32,
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128 return_predictions=False,
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129 ):
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130 """output scores for bother keras and sklearn metrics
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131
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132 Parameters
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133 -----------
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134 estimator : object
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135 Fitted `galaxy_ml.keras_galaxy_models.KerasGBatchClassifier`.
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136 data_generator : object
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137 From `galaxy_ml.preprocessors.ImageDataFrameBatchGenerator`.
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138 X : 2-D array
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139 Contains indecies of images that need to be evaluated.
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140 y : None
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141 Target value.
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142 sk_scoring : dict
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143 Galaxy tool input parameters.
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144 steps : integer or None
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145 Evaluation/prediction steps before stop.
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146 batch_size : integer
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147 Number of samples in a batch
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148 return_predictions : bool, default is False
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149 Whether to return predictions and true labels.
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150 """
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151 scores = {}
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152
41
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153 generator = data_generator.flow(X, y=y, batch_size=batch_size)
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154 # keras metrics evaluation
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155 # handle scorer, convert to scorer dict
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156 generator.reset()
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157 score_results = estimator.model_.evaluate_generator(generator, steps=steps)
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158 metrics_names = estimator.model_.metrics_names
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159 if not isinstance(metrics_names, list):
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160 scores[metrics_names] = score_results
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161 else:
41
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162 scores = dict(zip(metrics_names, score_results))
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163
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164 if sk_scoring["primary_scoring"] == "default" and not return_predictions:
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165 return scores
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166
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167 generator.reset()
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168 predictions, y_true = _predict_generator(estimator.model_, generator, steps=steps)
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169
41
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170 # for sklearn metrics
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171 if sk_scoring["primary_scoring"] != "default":
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172 scorer = get_scoring(sk_scoring)
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173 if not isinstance(scorer, (dict, list)):
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174 scorer = [sk_scoring["primary_scoring"]]
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175 scorer = _check_multimetric_scoring(estimator, scoring=scorer)
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176 sk_scores = gen_compute_scores(y_true, predictions, scorer)
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177 scores.update(sk_scores)
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178
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179 if return_predictions:
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180 return scores, predictions, y_true
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181 else:
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182 return scores, None, None
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183
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184
35
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185 def main(
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186 inputs,
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187 infile_estimator,
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188 infile1,
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189 infile2,
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190 outfile_result,
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191 outfile_object=None,
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192 outfile_y_true=None,
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193 outfile_y_preds=None,
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194 groups=None,
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195 ref_seq=None,
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196 intervals=None,
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197 targets=None,
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198 fasta_path=None,
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199 ):
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200 """
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201 Parameter
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202 ---------
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203 inputs : str
41
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204 File path to galaxy tool parameter.
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205
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206 infile_estimator : str
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207 File path to estimator.
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208
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209 infile1 : str
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210 File path to dataset containing features.
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211
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212 infile2 : str
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213 File path to dataset containing target values.
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214
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215 outfile_result : str
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216 File path to save the results, either cv_results or test result.
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217
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218 outfile_object : str, optional
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219 File path to save searchCV object.
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220
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221 outfile_y_true : str, optional
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222 File path to target values for prediction.
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223
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224 outfile_y_preds : str, optional
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225 File path to save predictions.
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226
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227 groups : str
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228 File path to dataset containing groups labels.
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229
e801d2034575 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
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230 ref_seq : str
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231 File path to dataset containing genome sequence file.
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232
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233 intervals : str
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234 File path to dataset containing interval file.
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235
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236 targets : str
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237 File path to dataset compressed target bed file.
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238
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239 fasta_path : str
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240 File path to dataset containing fasta file.
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241 """
35
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242 warnings.simplefilter("ignore")
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243
35
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244 with open(inputs, "r") as param_handler:
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245 params = json.load(param_handler)
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246
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247 # load estimator
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248 estimator = load_model_from_h5(infile_estimator)
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249
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250 estimator = clean_params(estimator)
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251
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252 # swap hyperparameter
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253 swapping = params["experiment_schemes"]["hyperparams_swapping"]
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254 swap_params = _eval_swap_params(swapping)
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255 estimator.set_params(**swap_params)
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256
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257 estimator_params = estimator.get_params()
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258
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259 # store read dataframe object
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260 loaded_df = {}
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261
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262 input_type = params["input_options"]["selected_input"]
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263 # tabular input
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264 if input_type == "tabular":
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265 header = "infer" if params["input_options"]["header1"] else None
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266 column_option = params["input_options"]["column_selector_options_1"][
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267 "selected_column_selector_option"
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268 ]
35
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269 if column_option in [
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270 "by_index_number",
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271 "all_but_by_index_number",
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272 "by_header_name",
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273 "all_but_by_header_name",
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274 ]:
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275 c = params["input_options"]["column_selector_options_1"]["col1"]
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276 else:
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277 c = None
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278
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279 df_key = infile1 + repr(header)
35
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280 df = pd.read_csv(infile1, sep="\t", header=header, parse_dates=True)
32
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281 loaded_df[df_key] = df
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282
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283 X = read_columns(df, c=c, c_option=column_option).astype(float)
e801d2034575 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
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284 # sparse input
35
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285 elif input_type == "sparse":
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286 X = mmread(open(infile1, "r"))
32
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287
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288 # fasta_file input
35
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289 elif input_type == "seq_fasta":
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290 pyfaidx = get_module("pyfaidx")
32
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291 sequences = pyfaidx.Fasta(fasta_path)
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292 n_seqs = len(sequences.keys())
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293 X = np.arange(n_seqs)[:, np.newaxis]
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294 for param in estimator_params.keys():
35
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295 if param.endswith("fasta_path"):
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296 estimator.set_params(**{param: fasta_path})
32
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297 break
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298 else:
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299 raise ValueError(
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300 "The selected estimator doesn't support "
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301 "fasta file input! Please consider using "
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302 "KerasGBatchClassifier with "
e801d2034575 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
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303 "FastaDNABatchGenerator/FastaProteinBatchGenerator "
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304 "or having GenomeOneHotEncoder/ProteinOneHotEncoder "
35
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305 "in pipeline!"
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306 )
32
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307
35
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308 elif input_type == "refseq_and_interval":
32
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309 path_params = {
35
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310 "data_batch_generator__ref_genome_path": ref_seq,
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311 "data_batch_generator__intervals_path": intervals,
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312 "data_batch_generator__target_path": targets,
32
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313 }
e801d2034575 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
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314 estimator.set_params(**path_params)
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315 n_intervals = sum(1 for line in open(intervals))
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316 X = np.arange(n_intervals)[:, np.newaxis]
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317
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318 # Get target y
35
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319 header = "infer" if params["input_options"]["header2"] else None
36
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320 column_option = params["input_options"]["column_selector_options_2"][
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321 "selected_column_selector_option2"
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322 ]
35
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323 if column_option in [
3c5034b0d775 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 208a8d348e7c7a182cfbe1b6f17868146428a7e2"
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324 "by_index_number",
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325 "all_but_by_index_number",
3c5034b0d775 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 208a8d348e7c7a182cfbe1b6f17868146428a7e2"
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326 "by_header_name",
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327 "all_but_by_header_name",
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328 ]:
3c5034b0d775 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 208a8d348e7c7a182cfbe1b6f17868146428a7e2"
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329 c = params["input_options"]["column_selector_options_2"]["col2"]
32
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330 else:
e801d2034575 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
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331 c = None
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332
e801d2034575 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
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333 df_key = infile2 + repr(header)
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334 if df_key in loaded_df:
e801d2034575 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
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335 infile2 = loaded_df[df_key]
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336 else:
35
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diff changeset
337 infile2 = pd.read_csv(infile2, sep="\t", header=header, parse_dates=True)
32
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338 loaded_df[df_key] = infile2
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339
36
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340 y = read_columns(
41
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341 infile2,
ed7d6d7c6e93 planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 9981e25b00de29ed881b2229a173a8c812ded9bb
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342 c=c,
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343 c_option=column_option,
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344 sep="\t",
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345 header=header,
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346 parse_dates=True,
36
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347 )
32
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348 if len(y.shape) == 2 and y.shape[1] == 1:
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349 y = y.ravel()
35
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350 if input_type == "refseq_and_interval":
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diff changeset
351 estimator.set_params(data_batch_generator__features=y.ravel().tolist())
32
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352 y = None
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353 # end y
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354
e801d2034575 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
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355 # load groups
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356 if groups:
36
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357 groups_selector = (
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diff changeset
358 params["experiment_schemes"]["test_split"]["split_algos"]
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diff changeset
359 ).pop("groups_selector")
32
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360
35
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diff changeset
361 header = "infer" if groups_selector["header_g"] else None
36
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diff changeset
362 column_option = groups_selector["column_selector_options_g"][
fc0801adfba1 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ca87db9c038a6fcf96aa39da50f384865fd932ff"
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363 "selected_column_selector_option_g"
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364 ]
35
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diff changeset
365 if column_option in [
3c5034b0d775 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 208a8d348e7c7a182cfbe1b6f17868146428a7e2"
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366 "by_index_number",
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parents: 32
diff changeset
367 "all_but_by_index_number",
3c5034b0d775 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 208a8d348e7c7a182cfbe1b6f17868146428a7e2"
bgruening
parents: 32
diff changeset
368 "by_header_name",
3c5034b0d775 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 208a8d348e7c7a182cfbe1b6f17868146428a7e2"
bgruening
parents: 32
diff changeset
369 "all_but_by_header_name",
3c5034b0d775 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 208a8d348e7c7a182cfbe1b6f17868146428a7e2"
bgruening
parents: 32
diff changeset
370 ]:
3c5034b0d775 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 208a8d348e7c7a182cfbe1b6f17868146428a7e2"
bgruening
parents: 32
diff changeset
371 c = groups_selector["column_selector_options_g"]["col_g"]
32
e801d2034575 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
bgruening
parents:
diff changeset
372 else:
e801d2034575 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
bgruening
parents:
diff changeset
373 c = None
e801d2034575 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
bgruening
parents:
diff changeset
374
e801d2034575 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
bgruening
parents:
diff changeset
375 df_key = groups + repr(header)
e801d2034575 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
bgruening
parents:
diff changeset
376 if df_key in loaded_df:
e801d2034575 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
bgruening
parents:
diff changeset
377 groups = loaded_df[df_key]
e801d2034575 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
bgruening
parents:
diff changeset
378
36
fc0801adfba1 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ca87db9c038a6fcf96aa39da50f384865fd932ff"
bgruening
parents: 35
diff changeset
379 groups = read_columns(
fc0801adfba1 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ca87db9c038a6fcf96aa39da50f384865fd932ff"
bgruening
parents: 35
diff changeset
380 groups,
fc0801adfba1 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ca87db9c038a6fcf96aa39da50f384865fd932ff"
bgruening
parents: 35
diff changeset
381 c=c,
fc0801adfba1 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ca87db9c038a6fcf96aa39da50f384865fd932ff"
bgruening
parents: 35
diff changeset
382 c_option=column_option,
fc0801adfba1 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ca87db9c038a6fcf96aa39da50f384865fd932ff"
bgruening
parents: 35
diff changeset
383 sep="\t",
fc0801adfba1 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ca87db9c038a6fcf96aa39da50f384865fd932ff"
bgruening
parents: 35
diff changeset
384 header=header,
fc0801adfba1 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ca87db9c038a6fcf96aa39da50f384865fd932ff"
bgruening
parents: 35
diff changeset
385 parse_dates=True,
fc0801adfba1 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ca87db9c038a6fcf96aa39da50f384865fd932ff"
bgruening
parents: 35
diff changeset
386 )
32
e801d2034575 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
bgruening
parents:
diff changeset
387 groups = groups.ravel()
e801d2034575 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
bgruening
parents:
diff changeset
388
e801d2034575 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
bgruening
parents:
diff changeset
389 # del loaded_df
e801d2034575 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
bgruening
parents:
diff changeset
390 del loaded_df
e801d2034575 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
bgruening
parents:
diff changeset
391
e801d2034575 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
bgruening
parents:
diff changeset
392 # cache iraps_core fits could increase search speed significantly
e801d2034575 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
bgruening
parents:
diff changeset
393 memory = joblib.Memory(location=CACHE_DIR, verbose=0)
e801d2034575 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
bgruening
parents:
diff changeset
394 main_est = get_main_estimator(estimator)
35
3c5034b0d775 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 208a8d348e7c7a182cfbe1b6f17868146428a7e2"
bgruening
parents: 32
diff changeset
395 if main_est.__class__.__name__ == "IRAPSClassifier":
32
e801d2034575 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
bgruening
parents:
diff changeset
396 main_est.set_params(memory=memory)
e801d2034575 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
bgruening
parents:
diff changeset
397
e801d2034575 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
bgruening
parents:
diff changeset
398 # handle scorer, convert to scorer dict
36
fc0801adfba1 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ca87db9c038a6fcf96aa39da50f384865fd932ff"
bgruening
parents: 35
diff changeset
399 scoring = params["experiment_schemes"]["metrics"]["scoring"]
32
e801d2034575 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
bgruening
parents:
diff changeset
400 scorer = get_scoring(scoring)
41
ed7d6d7c6e93 planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 9981e25b00de29ed881b2229a173a8c812ded9bb
bgruening
parents: 36
diff changeset
401 if not isinstance(scorer, (dict, list)):
ed7d6d7c6e93 planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 9981e25b00de29ed881b2229a173a8c812ded9bb
bgruening
parents: 36
diff changeset
402 scorer = [scoring["primary_scoring"]]
ed7d6d7c6e93 planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 9981e25b00de29ed881b2229a173a8c812ded9bb
bgruening
parents: 36
diff changeset
403 scorer = _check_multimetric_scoring(estimator, scoring=scorer)
32
e801d2034575 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
bgruening
parents:
diff changeset
404
e801d2034575 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
bgruening
parents:
diff changeset
405 # handle test (first) split
35
3c5034b0d775 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 208a8d348e7c7a182cfbe1b6f17868146428a7e2"
bgruening
parents: 32
diff changeset
406 test_split_options = params["experiment_schemes"]["test_split"]["split_algos"]
32
e801d2034575 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
bgruening
parents:
diff changeset
407
35
3c5034b0d775 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 208a8d348e7c7a182cfbe1b6f17868146428a7e2"
bgruening
parents: 32
diff changeset
408 if test_split_options["shuffle"] == "group":
3c5034b0d775 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 208a8d348e7c7a182cfbe1b6f17868146428a7e2"
bgruening
parents: 32
diff changeset
409 test_split_options["labels"] = groups
3c5034b0d775 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 208a8d348e7c7a182cfbe1b6f17868146428a7e2"
bgruening
parents: 32
diff changeset
410 if test_split_options["shuffle"] == "stratified":
32
e801d2034575 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
bgruening
parents:
diff changeset
411 if y is not None:
35
3c5034b0d775 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 208a8d348e7c7a182cfbe1b6f17868146428a7e2"
bgruening
parents: 32
diff changeset
412 test_split_options["labels"] = y
32
e801d2034575 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
bgruening
parents:
diff changeset
413 else:
36
fc0801adfba1 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ca87db9c038a6fcf96aa39da50f384865fd932ff"
bgruening
parents: 35
diff changeset
414 raise ValueError(
fc0801adfba1 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ca87db9c038a6fcf96aa39da50f384865fd932ff"
bgruening
parents: 35
diff changeset
415 "Stratified shuffle split is not " "applicable on empty target values!"
fc0801adfba1 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ca87db9c038a6fcf96aa39da50f384865fd932ff"
bgruening
parents: 35
diff changeset
416 )
32
e801d2034575 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
bgruening
parents:
diff changeset
417
41
ed7d6d7c6e93 planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 9981e25b00de29ed881b2229a173a8c812ded9bb
bgruening
parents: 36
diff changeset
418 X_train, X_test, y_train, y_test, groups_train, groups_test = train_test_split_none(
ed7d6d7c6e93 planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 9981e25b00de29ed881b2229a173a8c812ded9bb
bgruening
parents: 36
diff changeset
419 X, y, groups, **test_split_options
ed7d6d7c6e93 planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 9981e25b00de29ed881b2229a173a8c812ded9bb
bgruening
parents: 36
diff changeset
420 )
32
e801d2034575 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
bgruening
parents:
diff changeset
421
35
3c5034b0d775 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 208a8d348e7c7a182cfbe1b6f17868146428a7e2"
bgruening
parents: 32
diff changeset
422 exp_scheme = params["experiment_schemes"]["selected_exp_scheme"]
32
e801d2034575 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
bgruening
parents:
diff changeset
423
e801d2034575 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
bgruening
parents:
diff changeset
424 # handle validation (second) split
35
3c5034b0d775 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 208a8d348e7c7a182cfbe1b6f17868146428a7e2"
bgruening
parents: 32
diff changeset
425 if exp_scheme == "train_val_test":
3c5034b0d775 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 208a8d348e7c7a182cfbe1b6f17868146428a7e2"
bgruening
parents: 32
diff changeset
426 val_split_options = params["experiment_schemes"]["val_split"]["split_algos"]
32
e801d2034575 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
bgruening
parents:
diff changeset
427
35
3c5034b0d775 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 208a8d348e7c7a182cfbe1b6f17868146428a7e2"
bgruening
parents: 32
diff changeset
428 if val_split_options["shuffle"] == "group":
3c5034b0d775 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 208a8d348e7c7a182cfbe1b6f17868146428a7e2"
bgruening
parents: 32
diff changeset
429 val_split_options["labels"] = groups_train
3c5034b0d775 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 208a8d348e7c7a182cfbe1b6f17868146428a7e2"
bgruening
parents: 32
diff changeset
430 if val_split_options["shuffle"] == "stratified":
32
e801d2034575 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
bgruening
parents:
diff changeset
431 if y_train is not None:
35
3c5034b0d775 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 208a8d348e7c7a182cfbe1b6f17868146428a7e2"
bgruening
parents: 32
diff changeset
432 val_split_options["labels"] = y_train
32
e801d2034575 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
bgruening
parents:
diff changeset
433 else:
36
fc0801adfba1 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ca87db9c038a6fcf96aa39da50f384865fd932ff"
bgruening
parents: 35
diff changeset
434 raise ValueError(
fc0801adfba1 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ca87db9c038a6fcf96aa39da50f384865fd932ff"
bgruening
parents: 35
diff changeset
435 "Stratified shuffle split is not "
fc0801adfba1 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ca87db9c038a6fcf96aa39da50f384865fd932ff"
bgruening
parents: 35
diff changeset
436 "applicable on empty target values!"
fc0801adfba1 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ca87db9c038a6fcf96aa39da50f384865fd932ff"
bgruening
parents: 35
diff changeset
437 )
32
e801d2034575 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
bgruening
parents:
diff changeset
438
35
3c5034b0d775 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 208a8d348e7c7a182cfbe1b6f17868146428a7e2"
bgruening
parents: 32
diff changeset
439 (
3c5034b0d775 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 208a8d348e7c7a182cfbe1b6f17868146428a7e2"
bgruening
parents: 32
diff changeset
440 X_train,
3c5034b0d775 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 208a8d348e7c7a182cfbe1b6f17868146428a7e2"
bgruening
parents: 32
diff changeset
441 X_val,
3c5034b0d775 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 208a8d348e7c7a182cfbe1b6f17868146428a7e2"
bgruening
parents: 32
diff changeset
442 y_train,
3c5034b0d775 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 208a8d348e7c7a182cfbe1b6f17868146428a7e2"
bgruening
parents: 32
diff changeset
443 y_val,
3c5034b0d775 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 208a8d348e7c7a182cfbe1b6f17868146428a7e2"
bgruening
parents: 32
diff changeset
444 groups_train,
41
ed7d6d7c6e93 planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 9981e25b00de29ed881b2229a173a8c812ded9bb
bgruening
parents: 36
diff changeset
445 groups_val,
35
3c5034b0d775 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 208a8d348e7c7a182cfbe1b6f17868146428a7e2"
bgruening
parents: 32
diff changeset
446 ) = train_test_split_none(X_train, y_train, groups_train, **val_split_options)
32
e801d2034575 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
bgruening
parents:
diff changeset
447
e801d2034575 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
bgruening
parents:
diff changeset
448 # train and eval
41
ed7d6d7c6e93 planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 9981e25b00de29ed881b2229a173a8c812ded9bb
bgruening
parents: 36
diff changeset
449 if hasattr(estimator, "config") and hasattr(estimator, "model_type"):
35
3c5034b0d775 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 208a8d348e7c7a182cfbe1b6f17868146428a7e2"
bgruening
parents: 32
diff changeset
450 if exp_scheme == "train_val_test":
3c5034b0d775 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 208a8d348e7c7a182cfbe1b6f17868146428a7e2"
bgruening
parents: 32
diff changeset
451 estimator.fit(X_train, y_train, validation_data=(X_val, y_val))
32
e801d2034575 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
bgruening
parents:
diff changeset
452 else:
35
3c5034b0d775 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 208a8d348e7c7a182cfbe1b6f17868146428a7e2"
bgruening
parents: 32
diff changeset
453 estimator.fit(X_train, y_train, validation_data=(X_test, y_test))
32
e801d2034575 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
bgruening
parents:
diff changeset
454 else:
e801d2034575 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
bgruening
parents:
diff changeset
455 estimator.fit(X_train, y_train)
e801d2034575 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
bgruening
parents:
diff changeset
456
41
ed7d6d7c6e93 planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 9981e25b00de29ed881b2229a173a8c812ded9bb
bgruening
parents: 36
diff changeset
457 if isinstance(estimator, KerasGBatchClassifier):
ed7d6d7c6e93 planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 9981e25b00de29ed881b2229a173a8c812ded9bb
bgruening
parents: 36
diff changeset
458 scores = {}
32
e801d2034575 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
bgruening
parents:
diff changeset
459 steps = estimator.prediction_steps
e801d2034575 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
bgruening
parents:
diff changeset
460 batch_size = estimator.batch_size
41
ed7d6d7c6e93 planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 9981e25b00de29ed881b2229a173a8c812ded9bb
bgruening
parents: 36
diff changeset
461 data_generator = estimator.data_generator_
ed7d6d7c6e93 planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 9981e25b00de29ed881b2229a173a8c812ded9bb
bgruening
parents: 36
diff changeset
462
ed7d6d7c6e93 planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 9981e25b00de29ed881b2229a173a8c812ded9bb
bgruening
parents: 36
diff changeset
463 scores, predictions, y_true = _evaluate_keras_and_sklearn_scores(
ed7d6d7c6e93 planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 9981e25b00de29ed881b2229a173a8c812ded9bb
bgruening
parents: 36
diff changeset
464 estimator,
ed7d6d7c6e93 planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 9981e25b00de29ed881b2229a173a8c812ded9bb
bgruening
parents: 36
diff changeset
465 data_generator,
ed7d6d7c6e93 planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 9981e25b00de29ed881b2229a173a8c812ded9bb
bgruening
parents: 36
diff changeset
466 X_test,
ed7d6d7c6e93 planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 9981e25b00de29ed881b2229a173a8c812ded9bb
bgruening
parents: 36
diff changeset
467 y=y_test,
ed7d6d7c6e93 planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 9981e25b00de29ed881b2229a173a8c812ded9bb
bgruening
parents: 36
diff changeset
468 sk_scoring=scoring,
ed7d6d7c6e93 planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 9981e25b00de29ed881b2229a173a8c812ded9bb
bgruening
parents: 36
diff changeset
469 steps=steps,
ed7d6d7c6e93 planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 9981e25b00de29ed881b2229a173a8c812ded9bb
bgruening
parents: 36
diff changeset
470 batch_size=batch_size,
ed7d6d7c6e93 planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 9981e25b00de29ed881b2229a173a8c812ded9bb
bgruening
parents: 36
diff changeset
471 return_predictions=bool(outfile_y_true),
36
fc0801adfba1 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ca87db9c038a6fcf96aa39da50f384865fd932ff"
bgruening
parents: 35
diff changeset
472 )
32
e801d2034575 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
bgruening
parents:
diff changeset
473
e801d2034575 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
bgruening
parents:
diff changeset
474 else:
41
ed7d6d7c6e93 planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 9981e25b00de29ed881b2229a173a8c812ded9bb
bgruening
parents: 36
diff changeset
475 scores = {}
ed7d6d7c6e93 planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 9981e25b00de29ed881b2229a173a8c812ded9bb
bgruening
parents: 36
diff changeset
476 if hasattr(estimator, "model_") and hasattr(estimator.model_, "metrics_names"):
ed7d6d7c6e93 planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 9981e25b00de29ed881b2229a173a8c812ded9bb
bgruening
parents: 36
diff changeset
477 batch_size = estimator.batch_size
ed7d6d7c6e93 planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 9981e25b00de29ed881b2229a173a8c812ded9bb
bgruening
parents: 36
diff changeset
478 score_results = estimator.model_.evaluate(
ed7d6d7c6e93 planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 9981e25b00de29ed881b2229a173a8c812ded9bb
bgruening
parents: 36
diff changeset
479 X_test, y=y_test, batch_size=batch_size, verbose=0
ed7d6d7c6e93 planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 9981e25b00de29ed881b2229a173a8c812ded9bb
bgruening
parents: 36
diff changeset
480 )
ed7d6d7c6e93 planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 9981e25b00de29ed881b2229a173a8c812ded9bb
bgruening
parents: 36
diff changeset
481 metrics_names = estimator.model_.metrics_names
ed7d6d7c6e93 planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 9981e25b00de29ed881b2229a173a8c812ded9bb
bgruening
parents: 36
diff changeset
482 if not isinstance(metrics_names, list):
ed7d6d7c6e93 planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 9981e25b00de29ed881b2229a173a8c812ded9bb
bgruening
parents: 36
diff changeset
483 scores[metrics_names] = score_results
ed7d6d7c6e93 planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 9981e25b00de29ed881b2229a173a8c812ded9bb
bgruening
parents: 36
diff changeset
484 else:
ed7d6d7c6e93 planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 9981e25b00de29ed881b2229a173a8c812ded9bb
bgruening
parents: 36
diff changeset
485 scores = dict(zip(metrics_names, score_results))
ed7d6d7c6e93 planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 9981e25b00de29ed881b2229a173a8c812ded9bb
bgruening
parents: 36
diff changeset
486
35
3c5034b0d775 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 208a8d348e7c7a182cfbe1b6f17868146428a7e2"
bgruening
parents: 32
diff changeset
487 if hasattr(estimator, "predict_proba"):
32
e801d2034575 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
bgruening
parents:
diff changeset
488 predictions = estimator.predict_proba(X_test)
e801d2034575 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
bgruening
parents:
diff changeset
489 else:
e801d2034575 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
bgruening
parents:
diff changeset
490 predictions = estimator.predict(X_test)
e801d2034575 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
bgruening
parents:
diff changeset
491
e801d2034575 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
bgruening
parents:
diff changeset
492 y_true = y_test
41
ed7d6d7c6e93 planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 9981e25b00de29ed881b2229a173a8c812ded9bb
bgruening
parents: 36
diff changeset
493 sk_scores = _score(estimator, X_test, y_test, scorer)
ed7d6d7c6e93 planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 9981e25b00de29ed881b2229a173a8c812ded9bb
bgruening
parents: 36
diff changeset
494 scores.update(sk_scores)
ed7d6d7c6e93 planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 9981e25b00de29ed881b2229a173a8c812ded9bb
bgruening
parents: 36
diff changeset
495
ed7d6d7c6e93 planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 9981e25b00de29ed881b2229a173a8c812ded9bb
bgruening
parents: 36
diff changeset
496 # handle output
32
e801d2034575 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
bgruening
parents:
diff changeset
497 if outfile_y_true:
e801d2034575 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
bgruening
parents:
diff changeset
498 try:
35
3c5034b0d775 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 208a8d348e7c7a182cfbe1b6f17868146428a7e2"
bgruening
parents: 32
diff changeset
499 pd.DataFrame(y_true).to_csv(outfile_y_true, sep="\t", index=False)
32
e801d2034575 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
bgruening
parents:
diff changeset
500 pd.DataFrame(predictions).astype(np.float32).to_csv(
35
3c5034b0d775 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 208a8d348e7c7a182cfbe1b6f17868146428a7e2"
bgruening
parents: 32
diff changeset
501 outfile_y_preds,
3c5034b0d775 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 208a8d348e7c7a182cfbe1b6f17868146428a7e2"
bgruening
parents: 32
diff changeset
502 sep="\t",
3c5034b0d775 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 208a8d348e7c7a182cfbe1b6f17868146428a7e2"
bgruening
parents: 32
diff changeset
503 index=False,
3c5034b0d775 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 208a8d348e7c7a182cfbe1b6f17868146428a7e2"
bgruening
parents: 32
diff changeset
504 float_format="%g",
3c5034b0d775 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 208a8d348e7c7a182cfbe1b6f17868146428a7e2"
bgruening
parents: 32
diff changeset
505 chunksize=10000,
3c5034b0d775 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 208a8d348e7c7a182cfbe1b6f17868146428a7e2"
bgruening
parents: 32
diff changeset
506 )
32
e801d2034575 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
bgruening
parents:
diff changeset
507 except Exception as e:
e801d2034575 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
bgruening
parents:
diff changeset
508 print("Error in saving predictions: %s" % e)
e801d2034575 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
bgruening
parents:
diff changeset
509 # handle output
e801d2034575 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
bgruening
parents:
diff changeset
510 for name, score in scores.items():
e801d2034575 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
bgruening
parents:
diff changeset
511 scores[name] = [score]
e801d2034575 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
bgruening
parents:
diff changeset
512 df = pd.DataFrame(scores)
e801d2034575 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
bgruening
parents:
diff changeset
513 df = df[sorted(df.columns)]
35
3c5034b0d775 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 208a8d348e7c7a182cfbe1b6f17868146428a7e2"
bgruening
parents: 32
diff changeset
514 df.to_csv(path_or_buf=outfile_result, sep="\t", header=True, index=False)
32
e801d2034575 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
bgruening
parents:
diff changeset
515
e801d2034575 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
bgruening
parents:
diff changeset
516 memory.clear(warn=False)
e801d2034575 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
bgruening
parents:
diff changeset
517
e801d2034575 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
bgruening
parents:
diff changeset
518 if outfile_object:
41
ed7d6d7c6e93 planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 9981e25b00de29ed881b2229a173a8c812ded9bb
bgruening
parents: 36
diff changeset
519 dump_model_to_h5(estimator, outfile_object)
32
e801d2034575 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
bgruening
parents:
diff changeset
520
e801d2034575 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
bgruening
parents:
diff changeset
521
35
3c5034b0d775 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 208a8d348e7c7a182cfbe1b6f17868146428a7e2"
bgruening
parents: 32
diff changeset
522 if __name__ == "__main__":
32
e801d2034575 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
bgruening
parents:
diff changeset
523 aparser = argparse.ArgumentParser()
e801d2034575 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
bgruening
parents:
diff changeset
524 aparser.add_argument("-i", "--inputs", dest="inputs", required=True)
e801d2034575 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
bgruening
parents:
diff changeset
525 aparser.add_argument("-e", "--estimator", dest="infile_estimator")
e801d2034575 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
bgruening
parents:
diff changeset
526 aparser.add_argument("-X", "--infile1", dest="infile1")
e801d2034575 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
bgruening
parents:
diff changeset
527 aparser.add_argument("-y", "--infile2", dest="infile2")
e801d2034575 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
bgruening
parents:
diff changeset
528 aparser.add_argument("-O", "--outfile_result", dest="outfile_result")
e801d2034575 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
bgruening
parents:
diff changeset
529 aparser.add_argument("-o", "--outfile_object", dest="outfile_object")
e801d2034575 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
bgruening
parents:
diff changeset
530 aparser.add_argument("-l", "--outfile_y_true", dest="outfile_y_true")
e801d2034575 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
bgruening
parents:
diff changeset
531 aparser.add_argument("-p", "--outfile_y_preds", dest="outfile_y_preds")
e801d2034575 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
bgruening
parents:
diff changeset
532 aparser.add_argument("-g", "--groups", dest="groups")
e801d2034575 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
bgruening
parents:
diff changeset
533 aparser.add_argument("-r", "--ref_seq", dest="ref_seq")
e801d2034575 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
bgruening
parents:
diff changeset
534 aparser.add_argument("-b", "--intervals", dest="intervals")
e801d2034575 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
bgruening
parents:
diff changeset
535 aparser.add_argument("-t", "--targets", dest="targets")
e801d2034575 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
bgruening
parents:
diff changeset
536 aparser.add_argument("-f", "--fasta_path", dest="fasta_path")
e801d2034575 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
bgruening
parents:
diff changeset
537 args = aparser.parse_args()
e801d2034575 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
bgruening
parents:
diff changeset
538
35
3c5034b0d775 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 208a8d348e7c7a182cfbe1b6f17868146428a7e2"
bgruening
parents: 32
diff changeset
539 main(
3c5034b0d775 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 208a8d348e7c7a182cfbe1b6f17868146428a7e2"
bgruening
parents: 32
diff changeset
540 args.inputs,
3c5034b0d775 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 208a8d348e7c7a182cfbe1b6f17868146428a7e2"
bgruening
parents: 32
diff changeset
541 args.infile_estimator,
3c5034b0d775 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 208a8d348e7c7a182cfbe1b6f17868146428a7e2"
bgruening
parents: 32
diff changeset
542 args.infile1,
3c5034b0d775 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 208a8d348e7c7a182cfbe1b6f17868146428a7e2"
bgruening
parents: 32
diff changeset
543 args.infile2,
3c5034b0d775 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 208a8d348e7c7a182cfbe1b6f17868146428a7e2"
bgruening
parents: 32
diff changeset
544 args.outfile_result,
3c5034b0d775 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 208a8d348e7c7a182cfbe1b6f17868146428a7e2"
bgruening
parents: 32
diff changeset
545 outfile_object=args.outfile_object,
3c5034b0d775 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 208a8d348e7c7a182cfbe1b6f17868146428a7e2"
bgruening
parents: 32
diff changeset
546 outfile_y_true=args.outfile_y_true,
3c5034b0d775 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 208a8d348e7c7a182cfbe1b6f17868146428a7e2"
bgruening
parents: 32
diff changeset
547 outfile_y_preds=args.outfile_y_preds,
3c5034b0d775 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 208a8d348e7c7a182cfbe1b6f17868146428a7e2"
bgruening
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548 groups=args.groups,
3c5034b0d775 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 208a8d348e7c7a182cfbe1b6f17868146428a7e2"
bgruening
parents: 32
diff changeset
549 ref_seq=args.ref_seq,
3c5034b0d775 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 208a8d348e7c7a182cfbe1b6f17868146428a7e2"
bgruening
parents: 32
diff changeset
550 intervals=args.intervals,
3c5034b0d775 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 208a8d348e7c7a182cfbe1b6f17868146428a7e2"
bgruening
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551 targets=args.targets,
3c5034b0d775 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 208a8d348e7c7a182cfbe1b6f17868146428a7e2"
bgruening
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diff changeset
552 fasta_path=args.fasta_path,
3c5034b0d775 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 208a8d348e7c7a182cfbe1b6f17868146428a7e2"
bgruening
parents: 32
diff changeset
553 )