annotate keras_train_and_eval.py @ 39:b4ebe47701e4 draft

planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5eca9041ce0154eded5aec07195502d5eb3cdd4f
author bgruening
date Fri, 03 Nov 2023 22:59:03 +0000
parents dc17e2878dc1
children
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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 KerasGClassifier,
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14 KerasGRegressor
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15 )
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16 from galaxy_ml.model_persist import dump_model_to_h5, load_model_from_h5
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17 from galaxy_ml.model_validations import train_test_split
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18 from galaxy_ml.utils import (
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19 clean_params,
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20 gen_compute_scores,
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21 get_main_estimator,
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22 get_module,
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23 get_scoring,
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24 read_columns,
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25 SafeEval
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26 )
29
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27 from scipy.io import mmread
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28 from sklearn.metrics._scorer import _check_multimetric_scoring
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29 from sklearn.model_selection._validation import _score
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30 from sklearn.utils import _safe_indexing, indexable
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31
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32 N_JOBS = int(os.environ.get("GALAXY_SLOTS", 1))
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33 CACHE_DIR = os.path.join(os.getcwd(), "cached")
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34 NON_SEARCHABLE = (
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35 "n_jobs",
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36 "pre_dispatch",
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37 "memory",
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38 "_path",
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39 "_dir",
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40 "nthread",
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41 "callbacks",
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42 )
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43 ALLOWED_CALLBACKS = (
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44 "EarlyStopping",
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45 "TerminateOnNaN",
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46 "ReduceLROnPlateau",
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47 "CSVLogger",
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48 "None",
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49 )
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52 def _eval_swap_params(params_builder):
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53 swap_params = {}
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54
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55 for p in params_builder["param_set"]:
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56 swap_value = p["sp_value"].strip()
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57 if swap_value == "":
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58 continue
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59
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60 param_name = p["sp_name"]
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61 if param_name.lower().endswith(NON_SEARCHABLE):
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62 warnings.warn(
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63 "Warning: `%s` is not eligible for search and was "
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64 "omitted!" % param_name
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65 )
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66 continue
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67
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68 if not swap_value.startswith(":"):
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69 safe_eval = SafeEval(load_scipy=True, load_numpy=True)
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70 ev = safe_eval(swap_value)
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71 else:
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72 # Have `:` before search list, asks for estimator evaluatio
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73 safe_eval_es = SafeEval(load_estimators=True)
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74 swap_value = swap_value[1:].strip()
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75 # TODO maybe add regular express check
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76 ev = safe_eval_es(swap_value)
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78 swap_params[param_name] = ev
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80 return swap_params
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83 def train_test_split_none(*arrays, **kwargs):
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84 """extend train_test_split to take None arrays
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85 and support split by group names.
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86 """
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87 nones = []
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88 new_arrays = []
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89 for idx, arr in enumerate(arrays):
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90 if arr is None:
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91 nones.append(idx)
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92 else:
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93 new_arrays.append(arr)
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94
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95 if kwargs["shuffle"] == "None":
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96 kwargs["shuffle"] = None
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97
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98 group_names = kwargs.pop("group_names", None)
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99
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100 if group_names is not None and group_names.strip():
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101 group_names = [name.strip() for name in group_names.split(",")]
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102 new_arrays = indexable(*new_arrays)
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103 groups = kwargs["labels"]
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104 n_samples = new_arrays[0].shape[0]
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105 index_arr = np.arange(n_samples)
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106 test = index_arr[np.isin(groups, group_names)]
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107 train = index_arr[~np.isin(groups, group_names)]
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108 rval = list(
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109 chain.from_iterable(
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110 (_safe_indexing(a, train), _safe_indexing(a, test)) for a in new_arrays
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111 )
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112 )
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113 else:
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114 rval = train_test_split(*new_arrays, **kwargs)
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115
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116 for pos in nones:
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117 rval[pos * 2: 2] = [None, None]
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118
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119 return rval
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120
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121
34
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122 def _evaluate_keras_and_sklearn_scores(
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123 estimator,
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124 data_generator,
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125 X,
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126 y=None,
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127 sk_scoring=None,
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128 steps=None,
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129 batch_size=32,
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130 return_predictions=False,
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131 ):
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132 """output scores for bother keras and sklearn metrics
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133
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134 Parameters
34
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135 -----------
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136 estimator : object
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137 Fitted `galaxy_ml.keras_galaxy_models.KerasGBatchClassifier`.
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138 data_generator : object
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139 From `galaxy_ml.preprocessors.ImageDataFrameBatchGenerator`.
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140 X : 2-D array
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141 Contains indecies of images that need to be evaluated.
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142 y : None
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143 Target value.
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144 sk_scoring : dict
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145 Galaxy tool input parameters.
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146 steps : integer or None
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147 Evaluation/prediction steps before stop.
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148 batch_size : integer
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149 Number of samples in a batch
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150 return_predictions : bool, default is False
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151 Whether to return predictions and true labels.
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152 """
34
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153 scores = {}
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154
34
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155 generator = data_generator.flow(X, y=y, batch_size=batch_size)
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156 # keras metrics evaluation
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157 # handle scorer, convert to scorer dict
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158 generator.reset()
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159 score_results = estimator.model_.evaluate_generator(generator, steps=steps)
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160 metrics_names = estimator.model_.metrics_names
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161 if not isinstance(metrics_names, list):
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162 scores[metrics_names] = score_results
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163 else:
34
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164 scores = dict(zip(metrics_names, score_results))
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165
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166 if sk_scoring["primary_scoring"] == "default" and not return_predictions:
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167 return scores
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168
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169 generator.reset()
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170 predictions, y_true = _predict_generator(estimator.model_, generator, steps=steps)
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171
34
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172 # for sklearn metrics
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173 if sk_scoring["primary_scoring"] != "default":
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174 scorer = get_scoring(sk_scoring)
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175 if not isinstance(scorer, (dict, list)):
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176 scorer = [sk_scoring["primary_scoring"]]
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177 scorer = _check_multimetric_scoring(estimator, scoring=scorer)
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178 sk_scores = gen_compute_scores(y_true, predictions, scorer)
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179 scores.update(sk_scores)
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180
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181 if return_predictions:
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182 return scores, predictions, y_true
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183 else:
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184 return scores, None, None
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185
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186
28
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187 def main(
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188 inputs,
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189 infile_estimator,
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190 infile1,
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191 infile2,
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192 outfile_result,
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193 outfile_history=None,
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194 outfile_object=None,
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195 outfile_y_true=None,
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196 outfile_y_preds=None,
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197 groups=None,
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198 ref_seq=None,
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199 intervals=None,
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200 targets=None,
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201 fasta_path=None,
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202 ):
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203 """
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204 Parameter
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205 ---------
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206 inputs : str
34
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207 File path to galaxy tool parameter.
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208
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209 infile_estimator : str
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210 File path to estimator.
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211
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212 infile1 : str
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213 File path to dataset containing features.
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214
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215 infile2 : str
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216 File path to dataset containing target values.
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217
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218 outfile_result : str
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219 File path to save the results, either cv_results or test result.
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220
38
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221 outfile_history : str, optional
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222 File path to save the training history.
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223
24
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224 outfile_object : str, optional
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225 File path to save searchCV object.
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226
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227 outfile_y_true : str, optional
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228 File path to target values for prediction.
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229
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230 outfile_y_preds : str, optional
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231 File path to save predictions.
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232
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233 groups : str
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234 File path to dataset containing groups labels.
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235
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236 ref_seq : str
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237 File path to dataset containing genome sequence file.
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238
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239 intervals : str
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240 File path to dataset containing interval file.
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241
a152c1d23379 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
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242 targets : str
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243 File path to dataset compressed target bed file.
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244
a152c1d23379 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
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245 fasta_path : str
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246 File path to dataset containing fasta file.
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247 """
28
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248 warnings.simplefilter("ignore")
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249
28
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250 with open(inputs, "r") as param_handler:
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251 params = json.load(param_handler)
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252
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253 # load estimator
34
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254 estimator = load_model_from_h5(infile_estimator)
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255
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256 estimator = clean_params(estimator)
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257
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258 # swap hyperparameter
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259 swapping = params["experiment_schemes"]["hyperparams_swapping"]
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260 swap_params = _eval_swap_params(swapping)
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261 estimator.set_params(**swap_params)
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262 estimator_params = estimator.get_params()
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263 # store read dataframe object
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264 loaded_df = {}
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265
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266 input_type = params["input_options"]["selected_input"]
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267 # tabular input
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268 if input_type == "tabular":
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269 header = "infer" if params["input_options"]["header1"] else None
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270 column_option = params["input_options"]["column_selector_options_1"][
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271 "selected_column_selector_option"
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272 ]
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273 if column_option in [
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274 "by_index_number",
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275 "all_but_by_index_number",
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276 "by_header_name",
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277 "all_but_by_header_name",
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278 ]:
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279 c = params["input_options"]["column_selector_options_1"]["col1"]
24
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280 else:
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281 c = None
a152c1d23379 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
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282
a152c1d23379 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
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283 df_key = infile1 + repr(header)
28
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284 df = pd.read_csv(infile1, sep="\t", header=header, parse_dates=True)
24
a152c1d23379 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
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285 loaded_df[df_key] = df
a152c1d23379 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
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286
a152c1d23379 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
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287 X = read_columns(df, c=c, c_option=column_option).astype(float)
a152c1d23379 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
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288 # sparse input
28
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289 elif input_type == "sparse":
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290 X = mmread(open(infile1, "r"))
24
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291
a152c1d23379 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
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292 # fasta_file input
28
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293 elif input_type == "seq_fasta":
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294 pyfaidx = get_module("pyfaidx")
24
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295 sequences = pyfaidx.Fasta(fasta_path)
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296 n_seqs = len(sequences.keys())
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297 X = np.arange(n_seqs)[:, np.newaxis]
a152c1d23379 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
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298 for param in estimator_params.keys():
28
0cc5098a9bff "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
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299 if param.endswith("fasta_path"):
0cc5098a9bff "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
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300 estimator.set_params(**{param: fasta_path})
24
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301 break
a152c1d23379 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
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302 else:
a152c1d23379 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
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303 raise ValueError(
a152c1d23379 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
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304 "The selected estimator doesn't support "
a152c1d23379 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
bgruening
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diff changeset
305 "fasta file input! Please consider using "
a152c1d23379 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
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306 "KerasGBatchClassifier with "
a152c1d23379 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
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307 "FastaDNABatchGenerator/FastaProteinBatchGenerator "
a152c1d23379 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
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308 "or having GenomeOneHotEncoder/ProteinOneHotEncoder "
28
0cc5098a9bff "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
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309 "in pipeline!"
0cc5098a9bff "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
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310 )
24
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311
28
0cc5098a9bff "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
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312 elif input_type == "refseq_and_interval":
24
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313 path_params = {
28
0cc5098a9bff "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
bgruening
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diff changeset
314 "data_batch_generator__ref_genome_path": ref_seq,
0cc5098a9bff "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
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diff changeset
315 "data_batch_generator__intervals_path": intervals,
0cc5098a9bff "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
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316 "data_batch_generator__target_path": targets,
24
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bgruening
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317 }
a152c1d23379 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
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318 estimator.set_params(**path_params)
a152c1d23379 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
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319 n_intervals = sum(1 for line in open(intervals))
a152c1d23379 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
bgruening
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320 X = np.arange(n_intervals)[:, np.newaxis]
a152c1d23379 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
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321
a152c1d23379 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
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diff changeset
322 # Get target y
28
0cc5098a9bff "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
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diff changeset
323 header = "infer" if params["input_options"]["header2"] else None
30
70c5a9127f99 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ea12f973df4b97a2691d9e4ce6bf6fae59d57717"
bgruening
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diff changeset
324 column_option = params["input_options"]["column_selector_options_2"][
70c5a9127f99 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ea12f973df4b97a2691d9e4ce6bf6fae59d57717"
bgruening
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diff changeset
325 "selected_column_selector_option2"
70c5a9127f99 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ea12f973df4b97a2691d9e4ce6bf6fae59d57717"
bgruening
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326 ]
28
0cc5098a9bff "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
bgruening
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diff changeset
327 if column_option in [
0cc5098a9bff "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
bgruening
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328 "by_index_number",
0cc5098a9bff "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
bgruening
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329 "all_but_by_index_number",
0cc5098a9bff "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
bgruening
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diff changeset
330 "by_header_name",
0cc5098a9bff "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
bgruening
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diff changeset
331 "all_but_by_header_name",
0cc5098a9bff "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
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diff changeset
332 ]:
0cc5098a9bff "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
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diff changeset
333 c = params["input_options"]["column_selector_options_2"]["col2"]
24
a152c1d23379 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
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parents:
diff changeset
334 else:
a152c1d23379 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
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diff changeset
335 c = None
a152c1d23379 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
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diff changeset
336
a152c1d23379 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
bgruening
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diff changeset
337 df_key = infile2 + repr(header)
a152c1d23379 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
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diff changeset
338 if df_key in loaded_df:
a152c1d23379 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
bgruening
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diff changeset
339 infile2 = loaded_df[df_key]
a152c1d23379 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
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diff changeset
340 else:
28
0cc5098a9bff "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
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diff changeset
341 infile2 = pd.read_csv(infile2, sep="\t", header=header, parse_dates=True)
24
a152c1d23379 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
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diff changeset
342 loaded_df[df_key] = infile2
a152c1d23379 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
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343
30
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diff changeset
344 y = read_columns(
34
642452aeed0d planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 9981e25b00de29ed881b2229a173a8c812ded9bb
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diff changeset
345 infile2,
642452aeed0d planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 9981e25b00de29ed881b2229a173a8c812ded9bb
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diff changeset
346 c=c,
642452aeed0d planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 9981e25b00de29ed881b2229a173a8c812ded9bb
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diff changeset
347 c_option=column_option,
642452aeed0d planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 9981e25b00de29ed881b2229a173a8c812ded9bb
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diff changeset
348 sep="\t",
642452aeed0d planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 9981e25b00de29ed881b2229a173a8c812ded9bb
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diff changeset
349 header=header,
642452aeed0d planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 9981e25b00de29ed881b2229a173a8c812ded9bb
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diff changeset
350 parse_dates=True,
30
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bgruening
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diff changeset
351 )
24
a152c1d23379 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
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parents:
diff changeset
352 if len(y.shape) == 2 and y.shape[1] == 1:
a152c1d23379 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
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353 y = y.ravel()
28
0cc5098a9bff "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
bgruening
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diff changeset
354 if input_type == "refseq_and_interval":
0cc5098a9bff "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
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diff changeset
355 estimator.set_params(data_batch_generator__features=y.ravel().tolist())
24
a152c1d23379 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
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356 y = None
a152c1d23379 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
bgruening
parents:
diff changeset
357 # end y
a152c1d23379 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
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358
a152c1d23379 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
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diff changeset
359 # load groups
a152c1d23379 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
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diff changeset
360 if groups:
30
70c5a9127f99 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ea12f973df4b97a2691d9e4ce6bf6fae59d57717"
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diff changeset
361 groups_selector = (
70c5a9127f99 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ea12f973df4b97a2691d9e4ce6bf6fae59d57717"
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diff changeset
362 params["experiment_schemes"]["test_split"]["split_algos"]
70c5a9127f99 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ea12f973df4b97a2691d9e4ce6bf6fae59d57717"
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diff changeset
363 ).pop("groups_selector")
24
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diff changeset
364
28
0cc5098a9bff "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
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diff changeset
365 header = "infer" if groups_selector["header_g"] else None
30
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bgruening
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diff changeset
366 column_option = groups_selector["column_selector_options_g"][
70c5a9127f99 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ea12f973df4b97a2691d9e4ce6bf6fae59d57717"
bgruening
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diff changeset
367 "selected_column_selector_option_g"
70c5a9127f99 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ea12f973df4b97a2691d9e4ce6bf6fae59d57717"
bgruening
parents: 29
diff changeset
368 ]
28
0cc5098a9bff "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
bgruening
parents: 24
diff changeset
369 if column_option in [
0cc5098a9bff "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
bgruening
parents: 24
diff changeset
370 "by_index_number",
0cc5098a9bff "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
bgruening
parents: 24
diff changeset
371 "all_but_by_index_number",
0cc5098a9bff "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
bgruening
parents: 24
diff changeset
372 "by_header_name",
0cc5098a9bff "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
bgruening
parents: 24
diff changeset
373 "all_but_by_header_name",
0cc5098a9bff "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
bgruening
parents: 24
diff changeset
374 ]:
0cc5098a9bff "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
bgruening
parents: 24
diff changeset
375 c = groups_selector["column_selector_options_g"]["col_g"]
24
a152c1d23379 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
bgruening
parents:
diff changeset
376 else:
a152c1d23379 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
bgruening
parents:
diff changeset
377 c = None
a152c1d23379 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
bgruening
parents:
diff changeset
378
a152c1d23379 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
bgruening
parents:
diff changeset
379 df_key = groups + repr(header)
a152c1d23379 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
bgruening
parents:
diff changeset
380 if df_key in loaded_df:
a152c1d23379 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
bgruening
parents:
diff changeset
381 groups = loaded_df[df_key]
a152c1d23379 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
bgruening
parents:
diff changeset
382
30
70c5a9127f99 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ea12f973df4b97a2691d9e4ce6bf6fae59d57717"
bgruening
parents: 29
diff changeset
383 groups = read_columns(
70c5a9127f99 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ea12f973df4b97a2691d9e4ce6bf6fae59d57717"
bgruening
parents: 29
diff changeset
384 groups,
70c5a9127f99 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ea12f973df4b97a2691d9e4ce6bf6fae59d57717"
bgruening
parents: 29
diff changeset
385 c=c,
70c5a9127f99 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ea12f973df4b97a2691d9e4ce6bf6fae59d57717"
bgruening
parents: 29
diff changeset
386 c_option=column_option,
70c5a9127f99 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ea12f973df4b97a2691d9e4ce6bf6fae59d57717"
bgruening
parents: 29
diff changeset
387 sep="\t",
70c5a9127f99 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ea12f973df4b97a2691d9e4ce6bf6fae59d57717"
bgruening
parents: 29
diff changeset
388 header=header,
70c5a9127f99 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ea12f973df4b97a2691d9e4ce6bf6fae59d57717"
bgruening
parents: 29
diff changeset
389 parse_dates=True,
70c5a9127f99 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ea12f973df4b97a2691d9e4ce6bf6fae59d57717"
bgruening
parents: 29
diff changeset
390 )
24
a152c1d23379 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
bgruening
parents:
diff changeset
391 groups = groups.ravel()
a152c1d23379 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
bgruening
parents:
diff changeset
392
a152c1d23379 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
bgruening
parents:
diff changeset
393 # del loaded_df
a152c1d23379 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
bgruening
parents:
diff changeset
394 del loaded_df
a152c1d23379 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
bgruening
parents:
diff changeset
395
a152c1d23379 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
bgruening
parents:
diff changeset
396 # cache iraps_core fits could increase search speed significantly
a152c1d23379 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
bgruening
parents:
diff changeset
397 memory = joblib.Memory(location=CACHE_DIR, verbose=0)
a152c1d23379 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
bgruening
parents:
diff changeset
398 main_est = get_main_estimator(estimator)
28
0cc5098a9bff "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
bgruening
parents: 24
diff changeset
399 if main_est.__class__.__name__ == "IRAPSClassifier":
24
a152c1d23379 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
bgruening
parents:
diff changeset
400 main_est.set_params(memory=memory)
a152c1d23379 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
bgruening
parents:
diff changeset
401
a152c1d23379 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
bgruening
parents:
diff changeset
402 # handle scorer, convert to scorer dict
30
70c5a9127f99 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ea12f973df4b97a2691d9e4ce6bf6fae59d57717"
bgruening
parents: 29
diff changeset
403 scoring = params["experiment_schemes"]["metrics"]["scoring"]
24
a152c1d23379 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
bgruening
parents:
diff changeset
404 scorer = get_scoring(scoring)
39
b4ebe47701e4 planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5eca9041ce0154eded5aec07195502d5eb3cdd4f
bgruening
parents: 38
diff changeset
405
b4ebe47701e4 planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5eca9041ce0154eded5aec07195502d5eb3cdd4f
bgruening
parents: 38
diff changeset
406 # We get 'None' back from the call to 'get_scoring()' if
b4ebe47701e4 planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5eca9041ce0154eded5aec07195502d5eb3cdd4f
bgruening
parents: 38
diff changeset
407 # the primary scoring is 'default'. Replace 'default' with
b4ebe47701e4 planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5eca9041ce0154eded5aec07195502d5eb3cdd4f
bgruening
parents: 38
diff changeset
408 # the default scoring for classification/regression (accuracy/r2)
b4ebe47701e4 planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5eca9041ce0154eded5aec07195502d5eb3cdd4f
bgruening
parents: 38
diff changeset
409 if scorer is None:
b4ebe47701e4 planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5eca9041ce0154eded5aec07195502d5eb3cdd4f
bgruening
parents: 38
diff changeset
410 if isinstance(estimator, KerasGClassifier):
b4ebe47701e4 planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5eca9041ce0154eded5aec07195502d5eb3cdd4f
bgruening
parents: 38
diff changeset
411 scorer = ['accuracy']
b4ebe47701e4 planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5eca9041ce0154eded5aec07195502d5eb3cdd4f
bgruening
parents: 38
diff changeset
412 if isinstance(estimator, KerasGRegressor):
b4ebe47701e4 planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5eca9041ce0154eded5aec07195502d5eb3cdd4f
bgruening
parents: 38
diff changeset
413 scorer = ['r2']
b4ebe47701e4 planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5eca9041ce0154eded5aec07195502d5eb3cdd4f
bgruening
parents: 38
diff changeset
414
34
642452aeed0d planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 9981e25b00de29ed881b2229a173a8c812ded9bb
bgruening
parents: 30
diff changeset
415 scorer = _check_multimetric_scoring(estimator, scoring=scorer)
24
a152c1d23379 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
bgruening
parents:
diff changeset
416
a152c1d23379 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
bgruening
parents:
diff changeset
417 # handle test (first) split
28
0cc5098a9bff "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
bgruening
parents: 24
diff changeset
418 test_split_options = params["experiment_schemes"]["test_split"]["split_algos"]
24
a152c1d23379 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
bgruening
parents:
diff changeset
419
28
0cc5098a9bff "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
bgruening
parents: 24
diff changeset
420 if test_split_options["shuffle"] == "group":
0cc5098a9bff "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
bgruening
parents: 24
diff changeset
421 test_split_options["labels"] = groups
0cc5098a9bff "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
bgruening
parents: 24
diff changeset
422 if test_split_options["shuffle"] == "stratified":
24
a152c1d23379 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
bgruening
parents:
diff changeset
423 if y is not None:
28
0cc5098a9bff "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
bgruening
parents: 24
diff changeset
424 test_split_options["labels"] = y
24
a152c1d23379 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
bgruening
parents:
diff changeset
425 else:
30
70c5a9127f99 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ea12f973df4b97a2691d9e4ce6bf6fae59d57717"
bgruening
parents: 29
diff changeset
426 raise ValueError(
70c5a9127f99 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ea12f973df4b97a2691d9e4ce6bf6fae59d57717"
bgruening
parents: 29
diff changeset
427 "Stratified shuffle split is not " "applicable on empty target values!"
70c5a9127f99 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ea12f973df4b97a2691d9e4ce6bf6fae59d57717"
bgruening
parents: 29
diff changeset
428 )
24
a152c1d23379 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
bgruening
parents:
diff changeset
429
34
642452aeed0d planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 9981e25b00de29ed881b2229a173a8c812ded9bb
bgruening
parents: 30
diff changeset
430 X_train, X_test, y_train, y_test, groups_train, groups_test = train_test_split_none(
642452aeed0d planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 9981e25b00de29ed881b2229a173a8c812ded9bb
bgruening
parents: 30
diff changeset
431 X, y, groups, **test_split_options
642452aeed0d planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 9981e25b00de29ed881b2229a173a8c812ded9bb
bgruening
parents: 30
diff changeset
432 )
24
a152c1d23379 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
bgruening
parents:
diff changeset
433
28
0cc5098a9bff "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
bgruening
parents: 24
diff changeset
434 exp_scheme = params["experiment_schemes"]["selected_exp_scheme"]
24
a152c1d23379 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
bgruening
parents:
diff changeset
435
a152c1d23379 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
bgruening
parents:
diff changeset
436 # handle validation (second) split
28
0cc5098a9bff "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
bgruening
parents: 24
diff changeset
437 if exp_scheme == "train_val_test":
0cc5098a9bff "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
bgruening
parents: 24
diff changeset
438 val_split_options = params["experiment_schemes"]["val_split"]["split_algos"]
24
a152c1d23379 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
bgruening
parents:
diff changeset
439
28
0cc5098a9bff "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
bgruening
parents: 24
diff changeset
440 if val_split_options["shuffle"] == "group":
0cc5098a9bff "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
bgruening
parents: 24
diff changeset
441 val_split_options["labels"] = groups_train
0cc5098a9bff "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
bgruening
parents: 24
diff changeset
442 if val_split_options["shuffle"] == "stratified":
24
a152c1d23379 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
bgruening
parents:
diff changeset
443 if y_train is not None:
28
0cc5098a9bff "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
bgruening
parents: 24
diff changeset
444 val_split_options["labels"] = y_train
24
a152c1d23379 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
bgruening
parents:
diff changeset
445 else:
30
70c5a9127f99 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ea12f973df4b97a2691d9e4ce6bf6fae59d57717"
bgruening
parents: 29
diff changeset
446 raise ValueError(
70c5a9127f99 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ea12f973df4b97a2691d9e4ce6bf6fae59d57717"
bgruening
parents: 29
diff changeset
447 "Stratified shuffle split is not "
70c5a9127f99 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ea12f973df4b97a2691d9e4ce6bf6fae59d57717"
bgruening
parents: 29
diff changeset
448 "applicable on empty target values!"
70c5a9127f99 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ea12f973df4b97a2691d9e4ce6bf6fae59d57717"
bgruening
parents: 29
diff changeset
449 )
24
a152c1d23379 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
bgruening
parents:
diff changeset
450
28
0cc5098a9bff "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
bgruening
parents: 24
diff changeset
451 (
0cc5098a9bff "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
bgruening
parents: 24
diff changeset
452 X_train,
0cc5098a9bff "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
bgruening
parents: 24
diff changeset
453 X_val,
0cc5098a9bff "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
bgruening
parents: 24
diff changeset
454 y_train,
0cc5098a9bff "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
bgruening
parents: 24
diff changeset
455 y_val,
0cc5098a9bff "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
bgruening
parents: 24
diff changeset
456 groups_train,
34
642452aeed0d planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 9981e25b00de29ed881b2229a173a8c812ded9bb
bgruening
parents: 30
diff changeset
457 groups_val,
28
0cc5098a9bff "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
bgruening
parents: 24
diff changeset
458 ) = train_test_split_none(X_train, y_train, groups_train, **val_split_options)
24
a152c1d23379 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
bgruening
parents:
diff changeset
459
a152c1d23379 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
bgruening
parents:
diff changeset
460 # train and eval
34
642452aeed0d planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 9981e25b00de29ed881b2229a173a8c812ded9bb
bgruening
parents: 30
diff changeset
461 if hasattr(estimator, "config") and hasattr(estimator, "model_type"):
28
0cc5098a9bff "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
bgruening
parents: 24
diff changeset
462 if exp_scheme == "train_val_test":
38
dc17e2878dc1 planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 80417bf0158a9b596e485dd66408f738f405145a
bgruening
parents: 34
diff changeset
463 history = estimator.fit(X_train, y_train, validation_data=(X_val, y_val))
24
a152c1d23379 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
bgruening
parents:
diff changeset
464 else:
38
dc17e2878dc1 planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 80417bf0158a9b596e485dd66408f738f405145a
bgruening
parents: 34
diff changeset
465 history = estimator.fit(X_train, y_train, validation_data=(X_test, y_test))
24
a152c1d23379 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
bgruening
parents:
diff changeset
466 else:
38
dc17e2878dc1 planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 80417bf0158a9b596e485dd66408f738f405145a
bgruening
parents: 34
diff changeset
467 history = estimator.fit(X_train, y_train)
dc17e2878dc1 planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 80417bf0158a9b596e485dd66408f738f405145a
bgruening
parents: 34
diff changeset
468 if "callbacks" in estimator_params:
dc17e2878dc1 planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 80417bf0158a9b596e485dd66408f738f405145a
bgruening
parents: 34
diff changeset
469 for cb in estimator_params["callbacks"]:
dc17e2878dc1 planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 80417bf0158a9b596e485dd66408f738f405145a
bgruening
parents: 34
diff changeset
470 if cb["callback_selection"]["callback_type"] == "CSVLogger":
dc17e2878dc1 planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 80417bf0158a9b596e485dd66408f738f405145a
bgruening
parents: 34
diff changeset
471 hist_df = pd.DataFrame(history.history)
dc17e2878dc1 planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 80417bf0158a9b596e485dd66408f738f405145a
bgruening
parents: 34
diff changeset
472 hist_df["epoch"] = np.arange(1, estimator_params["epochs"] + 1)
dc17e2878dc1 planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 80417bf0158a9b596e485dd66408f738f405145a
bgruening
parents: 34
diff changeset
473 epo_col = hist_df.pop('epoch')
dc17e2878dc1 planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 80417bf0158a9b596e485dd66408f738f405145a
bgruening
parents: 34
diff changeset
474 hist_df.insert(0, 'epoch', epo_col)
dc17e2878dc1 planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 80417bf0158a9b596e485dd66408f738f405145a
bgruening
parents: 34
diff changeset
475 hist_df.to_csv(path_or_buf=outfile_history, sep="\t", header=True, index=False)
dc17e2878dc1 planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 80417bf0158a9b596e485dd66408f738f405145a
bgruening
parents: 34
diff changeset
476 break
34
642452aeed0d planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 9981e25b00de29ed881b2229a173a8c812ded9bb
bgruening
parents: 30
diff changeset
477 if isinstance(estimator, KerasGBatchClassifier):
642452aeed0d planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 9981e25b00de29ed881b2229a173a8c812ded9bb
bgruening
parents: 30
diff changeset
478 scores = {}
24
a152c1d23379 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
bgruening
parents:
diff changeset
479 steps = estimator.prediction_steps
a152c1d23379 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
bgruening
parents:
diff changeset
480 batch_size = estimator.batch_size
34
642452aeed0d planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 9981e25b00de29ed881b2229a173a8c812ded9bb
bgruening
parents: 30
diff changeset
481 data_generator = estimator.data_generator_
642452aeed0d planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 9981e25b00de29ed881b2229a173a8c812ded9bb
bgruening
parents: 30
diff changeset
482
642452aeed0d planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 9981e25b00de29ed881b2229a173a8c812ded9bb
bgruening
parents: 30
diff changeset
483 scores, predictions, y_true = _evaluate_keras_and_sklearn_scores(
642452aeed0d planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 9981e25b00de29ed881b2229a173a8c812ded9bb
bgruening
parents: 30
diff changeset
484 estimator,
642452aeed0d planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 9981e25b00de29ed881b2229a173a8c812ded9bb
bgruening
parents: 30
diff changeset
485 data_generator,
642452aeed0d planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 9981e25b00de29ed881b2229a173a8c812ded9bb
bgruening
parents: 30
diff changeset
486 X_test,
642452aeed0d planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 9981e25b00de29ed881b2229a173a8c812ded9bb
bgruening
parents: 30
diff changeset
487 y=y_test,
642452aeed0d planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 9981e25b00de29ed881b2229a173a8c812ded9bb
bgruening
parents: 30
diff changeset
488 sk_scoring=scoring,
642452aeed0d planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 9981e25b00de29ed881b2229a173a8c812ded9bb
bgruening
parents: 30
diff changeset
489 steps=steps,
642452aeed0d planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 9981e25b00de29ed881b2229a173a8c812ded9bb
bgruening
parents: 30
diff changeset
490 batch_size=batch_size,
642452aeed0d planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 9981e25b00de29ed881b2229a173a8c812ded9bb
bgruening
parents: 30
diff changeset
491 return_predictions=bool(outfile_y_true),
30
70c5a9127f99 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ea12f973df4b97a2691d9e4ce6bf6fae59d57717"
bgruening
parents: 29
diff changeset
492 )
24
a152c1d23379 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
bgruening
parents:
diff changeset
493
a152c1d23379 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
bgruening
parents:
diff changeset
494 else:
34
642452aeed0d planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 9981e25b00de29ed881b2229a173a8c812ded9bb
bgruening
parents: 30
diff changeset
495 scores = {}
642452aeed0d planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 9981e25b00de29ed881b2229a173a8c812ded9bb
bgruening
parents: 30
diff changeset
496 if hasattr(estimator, "model_") and hasattr(estimator.model_, "metrics_names"):
642452aeed0d planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 9981e25b00de29ed881b2229a173a8c812ded9bb
bgruening
parents: 30
diff changeset
497 batch_size = estimator.batch_size
642452aeed0d planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 9981e25b00de29ed881b2229a173a8c812ded9bb
bgruening
parents: 30
diff changeset
498 score_results = estimator.model_.evaluate(
642452aeed0d planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 9981e25b00de29ed881b2229a173a8c812ded9bb
bgruening
parents: 30
diff changeset
499 X_test, y=y_test, batch_size=batch_size, verbose=0
642452aeed0d planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 9981e25b00de29ed881b2229a173a8c812ded9bb
bgruening
parents: 30
diff changeset
500 )
642452aeed0d planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 9981e25b00de29ed881b2229a173a8c812ded9bb
bgruening
parents: 30
diff changeset
501 metrics_names = estimator.model_.metrics_names
642452aeed0d planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 9981e25b00de29ed881b2229a173a8c812ded9bb
bgruening
parents: 30
diff changeset
502 if not isinstance(metrics_names, list):
642452aeed0d planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 9981e25b00de29ed881b2229a173a8c812ded9bb
bgruening
parents: 30
diff changeset
503 scores[metrics_names] = score_results
642452aeed0d planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 9981e25b00de29ed881b2229a173a8c812ded9bb
bgruening
parents: 30
diff changeset
504 else:
642452aeed0d planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 9981e25b00de29ed881b2229a173a8c812ded9bb
bgruening
parents: 30
diff changeset
505 scores = dict(zip(metrics_names, score_results))
642452aeed0d planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 9981e25b00de29ed881b2229a173a8c812ded9bb
bgruening
parents: 30
diff changeset
506
28
0cc5098a9bff "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
bgruening
parents: 24
diff changeset
507 if hasattr(estimator, "predict_proba"):
24
a152c1d23379 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
bgruening
parents:
diff changeset
508 predictions = estimator.predict_proba(X_test)
a152c1d23379 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
bgruening
parents:
diff changeset
509 else:
a152c1d23379 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
bgruening
parents:
diff changeset
510 predictions = estimator.predict(X_test)
a152c1d23379 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
bgruening
parents:
diff changeset
511
39
b4ebe47701e4 planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5eca9041ce0154eded5aec07195502d5eb3cdd4f
bgruening
parents: 38
diff changeset
512 # Un-do OHE of the validation labels
b4ebe47701e4 planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5eca9041ce0154eded5aec07195502d5eb3cdd4f
bgruening
parents: 38
diff changeset
513 if len(y_test.shape) == 2:
b4ebe47701e4 planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5eca9041ce0154eded5aec07195502d5eb3cdd4f
bgruening
parents: 38
diff changeset
514 rounded_test_labels = np.argmax(y_test, axis=1)
b4ebe47701e4 planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5eca9041ce0154eded5aec07195502d5eb3cdd4f
bgruening
parents: 38
diff changeset
515 y_true = rounded_test_labels
b4ebe47701e4 planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5eca9041ce0154eded5aec07195502d5eb3cdd4f
bgruening
parents: 38
diff changeset
516 sk_scores = _score(estimator, X_test, rounded_test_labels, scorer)
b4ebe47701e4 planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5eca9041ce0154eded5aec07195502d5eb3cdd4f
bgruening
parents: 38
diff changeset
517 else:
b4ebe47701e4 planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5eca9041ce0154eded5aec07195502d5eb3cdd4f
bgruening
parents: 38
diff changeset
518 y_true = y_test
b4ebe47701e4 planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5eca9041ce0154eded5aec07195502d5eb3cdd4f
bgruening
parents: 38
diff changeset
519 sk_scores = _score(estimator, X_test, y_true, scorer)
b4ebe47701e4 planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5eca9041ce0154eded5aec07195502d5eb3cdd4f
bgruening
parents: 38
diff changeset
520
34
642452aeed0d planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 9981e25b00de29ed881b2229a173a8c812ded9bb
bgruening
parents: 30
diff changeset
521 scores.update(sk_scores)
642452aeed0d planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 9981e25b00de29ed881b2229a173a8c812ded9bb
bgruening
parents: 30
diff changeset
522
642452aeed0d planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 9981e25b00de29ed881b2229a173a8c812ded9bb
bgruening
parents: 30
diff changeset
523 # handle output
24
a152c1d23379 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
bgruening
parents:
diff changeset
524 if outfile_y_true:
a152c1d23379 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
bgruening
parents:
diff changeset
525 try:
28
0cc5098a9bff "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
bgruening
parents: 24
diff changeset
526 pd.DataFrame(y_true).to_csv(outfile_y_true, sep="\t", index=False)
24
a152c1d23379 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
bgruening
parents:
diff changeset
527 pd.DataFrame(predictions).astype(np.float32).to_csv(
28
0cc5098a9bff "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
bgruening
parents: 24
diff changeset
528 outfile_y_preds,
0cc5098a9bff "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
bgruening
parents: 24
diff changeset
529 sep="\t",
0cc5098a9bff "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
bgruening
parents: 24
diff changeset
530 index=False,
0cc5098a9bff "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
bgruening
parents: 24
diff changeset
531 float_format="%g",
0cc5098a9bff "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
bgruening
parents: 24
diff changeset
532 chunksize=10000,
0cc5098a9bff "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
bgruening
parents: 24
diff changeset
533 )
24
a152c1d23379 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
bgruening
parents:
diff changeset
534 except Exception as e:
a152c1d23379 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
bgruening
parents:
diff changeset
535 print("Error in saving predictions: %s" % e)
a152c1d23379 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
bgruening
parents:
diff changeset
536 # handle output
a152c1d23379 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
bgruening
parents:
diff changeset
537 for name, score in scores.items():
a152c1d23379 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
bgruening
parents:
diff changeset
538 scores[name] = [score]
a152c1d23379 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
bgruening
parents:
diff changeset
539 df = pd.DataFrame(scores)
a152c1d23379 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
bgruening
parents:
diff changeset
540 df = df[sorted(df.columns)]
28
0cc5098a9bff "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
bgruening
parents: 24
diff changeset
541 df.to_csv(path_or_buf=outfile_result, sep="\t", header=True, index=False)
24
a152c1d23379 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
bgruening
parents:
diff changeset
542
a152c1d23379 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
bgruening
parents:
diff changeset
543 memory.clear(warn=False)
a152c1d23379 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
bgruening
parents:
diff changeset
544
a152c1d23379 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
bgruening
parents:
diff changeset
545 if outfile_object:
34
642452aeed0d planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 9981e25b00de29ed881b2229a173a8c812ded9bb
bgruening
parents: 30
diff changeset
546 dump_model_to_h5(estimator, outfile_object)
24
a152c1d23379 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
bgruening
parents:
diff changeset
547
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548
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549 if __name__ == "__main__":
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a152c1d23379 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
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550 aparser = argparse.ArgumentParser()
a152c1d23379 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
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551 aparser.add_argument("-i", "--inputs", dest="inputs", required=True)
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552 aparser.add_argument("-e", "--estimator", dest="infile_estimator")
a152c1d23379 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
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553 aparser.add_argument("-X", "--infile1", dest="infile1")
a152c1d23379 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
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554 aparser.add_argument("-y", "--infile2", dest="infile2")
a152c1d23379 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
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555 aparser.add_argument("-O", "--outfile_result", dest="outfile_result")
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dc17e2878dc1 planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 80417bf0158a9b596e485dd66408f738f405145a
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556 aparser.add_argument("-hi", "--outfile_history", dest="outfile_history")
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557 aparser.add_argument("-o", "--outfile_object", dest="outfile_object")
a152c1d23379 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
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558 aparser.add_argument("-l", "--outfile_y_true", dest="outfile_y_true")
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559 aparser.add_argument("-p", "--outfile_y_preds", dest="outfile_y_preds")
a152c1d23379 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
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560 aparser.add_argument("-g", "--groups", dest="groups")
a152c1d23379 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
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561 aparser.add_argument("-r", "--ref_seq", dest="ref_seq")
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562 aparser.add_argument("-b", "--intervals", dest="intervals")
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563 aparser.add_argument("-t", "--targets", dest="targets")
a152c1d23379 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
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564 aparser.add_argument("-f", "--fasta_path", dest="fasta_path")
a152c1d23379 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
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565 args = aparser.parse_args()
a152c1d23379 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
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566
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567 main(
0cc5098a9bff "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
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568 args.inputs,
0cc5098a9bff "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
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569 args.infile_estimator,
0cc5098a9bff "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
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570 args.infile1,
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571 args.infile2,
0cc5098a9bff "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
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572 args.outfile_result,
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dc17e2878dc1 planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 80417bf0158a9b596e485dd66408f738f405145a
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573 outfile_history=args.outfile_history,
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574 outfile_object=args.outfile_object,
0cc5098a9bff "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
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575 outfile_y_true=args.outfile_y_true,
0cc5098a9bff "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
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576 outfile_y_preds=args.outfile_y_preds,
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577 groups=args.groups,
0cc5098a9bff "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
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578 ref_seq=args.ref_seq,
0cc5098a9bff "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
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579 intervals=args.intervals,
0cc5098a9bff "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
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580 targets=args.targets,
0cc5098a9bff "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
bgruening
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581 fasta_path=args.fasta_path,
0cc5098a9bff "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
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582 )