Mercurial > repos > bgruening > sklearn_feature_selection

annotate train_test_eval.py @ 35:61edd9e5c17f 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 13:10:57 +0000
parents 5773e98921fc
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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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.model_persist import dump_model_to_h5, load_model_from_h5
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11 from galaxy_ml.model_validations import train_test_split
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12 from galaxy_ml.utils import (
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13 clean_params,
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14 get_module,
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15 get_scoring,
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16 read_columns,
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17 SafeEval,
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18 try_get_attr
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19 )
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20 from scipy.io import mmread
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21 from sklearn import pipeline
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22 from sklearn.model_selection import _search, _validation
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23 from sklearn.model_selection._validation import _score
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24 from sklearn.utils import _safe_indexing, indexable
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26 _fit_and_score = try_get_attr("galaxy_ml.model_validations", "_fit_and_score")
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27 setattr(_search, "_fit_and_score", _fit_and_score)
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28 setattr(_validation, "_fit_and_score", _fit_and_score)
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29
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30 N_JOBS = int(os.environ.get("GALAXY_SLOTS", 1))
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31 CACHE_DIR = os.path.join(os.getcwd(), "cached")
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32 del os
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33 NON_SEARCHABLE = ("n_jobs", "pre_dispatch", "memory", "_path", "nthread", "callbacks")
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34 ALLOWED_CALLBACKS = (
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35 "EarlyStopping",
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36 "TerminateOnNaN",
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37 "ReduceLROnPlateau",
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38 "CSVLogger",
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39 "None",
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40 )
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43 def _eval_swap_params(params_builder):
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44 swap_params = {}
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45
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46 for p in params_builder["param_set"]:
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47 swap_value = p["sp_value"].strip()
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48 if swap_value == "":
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49 continue
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50
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51 param_name = p["sp_name"]
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52 if param_name.lower().endswith(NON_SEARCHABLE):
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53 warnings.warn(
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54 "Warning: `%s` is not eligible for search and was "
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55 "omitted!" % param_name
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56 )
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57 continue
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58
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59 if not swap_value.startswith(":"):
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60 safe_eval = SafeEval(load_scipy=True, load_numpy=True)
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61 ev = safe_eval(swap_value)
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62 else:
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63 # Have `:` before search list, asks for estimator evaluatio
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64 safe_eval_es = SafeEval(load_estimators=True)
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65 swap_value = swap_value[1:].strip()
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66 # TODO maybe add regular express check
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67 ev = safe_eval_es(swap_value)
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69 swap_params[param_name] = ev
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71 return swap_params
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74 def train_test_split_none(*arrays, **kwargs):
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75 """extend train_test_split to take None arrays
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76 and support split by group names.
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77 """
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78 nones = []
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79 new_arrays = []
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80 for idx, arr in enumerate(arrays):
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81 if arr is None:
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82 nones.append(idx)
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83 else:
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84 new_arrays.append(arr)
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85
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86 if kwargs["shuffle"] == "None":
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87 kwargs["shuffle"] = None
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88
29
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89 group_names = kwargs.pop("group_names", None)
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90
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91 if group_names is not None and group_names.strip():
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92 group_names = [name.strip() for name in group_names.split(",")]
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93 new_arrays = indexable(*new_arrays)
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94 groups = kwargs["labels"]
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95 n_samples = new_arrays[0].shape[0]
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96 index_arr = np.arange(n_samples)
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97 test = index_arr[np.isin(groups, group_names)]
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98 train = index_arr[~np.isin(groups, group_names)]
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99 rval = list(
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100 chain.from_iterable(
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101 (_safe_indexing(a, train), _safe_indexing(a, test)) for a in new_arrays
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102 )
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103 )
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104 else:
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105 rval = train_test_split(*new_arrays, **kwargs)
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106
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107 for pos in nones:
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108 rval[pos * 2: 2] = [None, None]
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109
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110 return rval
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111
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112
29
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113 def main(
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114 inputs,
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115 infile_estimator,
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116 infile1,
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117 infile2,
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118 outfile_result,
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119 outfile_object=None,
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120 outfile_weights=None,
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121 groups=None,
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122 ref_seq=None,
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123 intervals=None,
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124 targets=None,
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125 fasta_path=None,
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126 ):
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127 """
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128 Parameter
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129 ---------
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130 inputs : str
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131 File path to galaxy tool parameter
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132
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133 infile_estimator : str
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134 File path to estimator
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135
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136 infile1 : str
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137 File path to dataset containing features
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138
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139 infile2 : str
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140 File path to dataset containing target values
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141
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142 outfile_result : str
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143 File path to save the results, either cv_results or test result
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144
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145 outfile_object : str, optional
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146 File path to save searchCV object
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147
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148 outfile_weights : str, optional
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149 File path to save deep learning model weights
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150
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151 groups : str
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152 File path to dataset containing groups labels
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153
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154 ref_seq : str
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155 File path to dataset containing genome sequence file
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156
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157 intervals : str
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158 File path to dataset containing interval file
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159
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160 targets : str
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161 File path to dataset compressed target bed file
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162
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163 fasta_path : str
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164 File path to dataset containing fasta file
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165 """
29
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166 warnings.simplefilter("ignore")
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167
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168 with open(inputs, "r") as param_handler:
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169 params = json.load(param_handler)
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170
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171 # load estimator
35
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172 estimator = load_model_from_h5(infile_estimator)
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173 estimator = clean_params(estimator)
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174
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175 # swap hyperparameter
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176 swapping = params["experiment_schemes"]["hyperparams_swapping"]
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177 swap_params = _eval_swap_params(swapping)
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178 estimator.set_params(**swap_params)
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179
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180 estimator_params = estimator.get_params()
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181
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182 # store read dataframe object
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183 loaded_df = {}
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184
29
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185 input_type = params["input_options"]["selected_input"]
20
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186 # tabular input
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187 if input_type == "tabular":
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188 header = "infer" if params["input_options"]["header1"] else None
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189 column_option = params["input_options"]["column_selector_options_1"][
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190 "selected_column_selector_option"
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191 ]
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192 if column_option in [
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193 "by_index_number",
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194 "all_but_by_index_number",
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195 "by_header_name",
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196 "all_but_by_header_name",
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197 ]:
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198 c = params["input_options"]["column_selector_options_1"]["col1"]
20
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199 else:
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200 c = None
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201
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202 df_key = infile1 + repr(header)
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203 df = pd.read_csv(infile1, sep="\t", header=header, parse_dates=True)
20
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204 loaded_df[df_key] = df
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205
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206 X = read_columns(df, c=c, c_option=column_option).astype(float)
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207 # sparse input
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208 elif input_type == "sparse":
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209 X = mmread(open(infile1, "r"))
20
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210
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211 # fasta_file input
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212 elif input_type == "seq_fasta":
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213 pyfaidx = get_module("pyfaidx")
20
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214 sequences = pyfaidx.Fasta(fasta_path)
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215 n_seqs = len(sequences.keys())
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216 X = np.arange(n_seqs)[:, np.newaxis]
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217 for param in estimator_params.keys():
29
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218 if param.endswith("fasta_path"):
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219 estimator.set_params(**{param: fasta_path})
20
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220 break
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221 else:
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222 raise ValueError(
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223 "The selected estimator doesn't support "
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224 "fasta file input! Please consider using "
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225 "KerasGBatchClassifier with "
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226 "FastaDNABatchGenerator/FastaProteinBatchGenerator "
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227 "or having GenomeOneHotEncoder/ProteinOneHotEncoder "
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228 "in pipeline!"
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229 )
20
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230
29
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231 elif input_type == "refseq_and_interval":
20
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232 path_params = {
29
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233 "data_batch_generator__ref_genome_path": ref_seq,
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234 "data_batch_generator__intervals_path": intervals,
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235 "data_batch_generator__target_path": targets,
20
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236 }
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237 estimator.set_params(**path_params)
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238 n_intervals = sum(1 for line in open(intervals))
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239 X = np.arange(n_intervals)[:, np.newaxis]
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240
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241 # Get target y
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242 header = "infer" if params["input_options"]["header2"] else None
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243 column_option = params["input_options"]["column_selector_options_2"][
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244 "selected_column_selector_option2"
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245 ]
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246 if column_option in [
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247 "by_index_number",
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248 "all_but_by_index_number",
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249 "by_header_name",
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250 "all_but_by_header_name",
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251 ]:
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252 c = params["input_options"]["column_selector_options_2"]["col2"]
20
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253 else:
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254 c = None
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255
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256 df_key = infile2 + repr(header)
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257 if df_key in loaded_df:
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258 infile2 = loaded_df[df_key]
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259 else:
29
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260 infile2 = pd.read_csv(infile2, sep="\t", header=header, parse_dates=True)
20
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261 loaded_df[df_key] = infile2
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262
31
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263 y = read_columns(
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264 infile2, c=c, c_option=column_option, sep="\t", header=header, parse_dates=True
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265 )
20
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266 if len(y.shape) == 2 and y.shape[1] == 1:
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267 y = y.ravel()
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268 if input_type == "refseq_and_interval":
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269 estimator.set_params(data_batch_generator__features=y.ravel().tolist())
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270 y = None
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271 # end y
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272
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273 # load groups
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274 if groups:
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275 groups_selector = (
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276 params["experiment_schemes"]["test_split"]["split_algos"]
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277 ).pop("groups_selector")
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278
29
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279 header = "infer" if groups_selector["header_g"] else None
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280 column_option = groups_selector["column_selector_options_g"][
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281 "selected_column_selector_option_g"
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282 ]
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283 if column_option in [
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284 "by_index_number",
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285 "all_but_by_index_number",
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286 "by_header_name",
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287 "all_but_by_header_name",
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288 ]:
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289 c = groups_selector["column_selector_options_g"]["col_g"]
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290 else:
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291 c = None
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292
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293 df_key = groups + repr(header)
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294 if df_key in loaded_df:
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295 groups = loaded_df[df_key]
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296
31
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297 groups = read_columns(
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298 groups,
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299 c=c,
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300 c_option=column_option,
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301 sep="\t",
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302 header=header,
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303 parse_dates=True,
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304 )
20
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305 groups = groups.ravel()
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306
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307 # del loaded_df
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308 del loaded_df
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309
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310 # handle memory
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311 memory = joblib.Memory(location=CACHE_DIR, verbose=0)
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312 # cache iraps_core fits could increase search speed significantly
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313 if estimator.__class__.__name__ == "IRAPSClassifier":
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314 estimator.set_params(memory=memory)
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315 else:
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316 # For iraps buried in pipeline
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317 new_params = {}
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318 for p, v in estimator_params.items():
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319 if p.endswith("memory"):
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320 # for case of `__irapsclassifier__memory`
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321 if len(p) > 8 and p[:-8].endswith("irapsclassifier"):
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322 # cache iraps_core fits could increase search
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323 # speed significantly
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324 new_params[p] = memory
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325 # security reason, we don't want memory being
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326 # modified unexpectedly
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327 elif v:
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328 new_params[p] = None
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329 # handle n_jobs
29
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330 elif p.endswith("n_jobs"):
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331 # For now, 1 CPU is suggested for iprasclassifier
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332 if len(p) > 8 and p[:-8].endswith("irapsclassifier"):
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333 new_params[p] = 1
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334 else:
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335 new_params[p] = N_JOBS
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336 # for security reason, types of callback are limited
29
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337 elif p.endswith("callbacks"):
20
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338 for cb in v:
29
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339 cb_type = cb["callback_selection"]["callback_type"]
20
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340 if cb_type not in ALLOWED_CALLBACKS:
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341 raise ValueError("Prohibited callback type: %s!" % cb_type)
20
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342
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343 estimator.set_params(**new_params)
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344
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345 # handle scorer, convert to scorer dict
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346 # Check if scoring is specified
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347 scoring = params["experiment_schemes"]["metrics"].get("scoring", None)
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348 if scoring is not None:
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349 # get_scoring() expects secondary_scoring to be a comma separated string (not a list)
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350 # Check if secondary_scoring is specified
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diff changeset
351 secondary_scoring = scoring.get("secondary_scoring", None)
93f3b307485f "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
bgruening
parents: 25
diff changeset
352 if secondary_scoring is not None:
93f3b307485f "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
bgruening
parents: 25
diff changeset
353 # If secondary_scoring is specified, convert the list into comman separated string
93f3b307485f "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
bgruening
parents: 25
diff changeset
354 scoring["secondary_scoring"] = ",".join(scoring["secondary_scoring"])
20
0b88494bdcac planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
bgruening
parents:
diff changeset
355 scorer = get_scoring(scoring)
0b88494bdcac planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
bgruening
parents:
diff changeset
356
0b88494bdcac planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
bgruening
parents:
diff changeset
357 # handle test (first) split
29
93f3b307485f "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
bgruening
parents: 25
diff changeset
358 test_split_options = params["experiment_schemes"]["test_split"]["split_algos"]
20
0b88494bdcac planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
bgruening
parents:
diff changeset
359
29
93f3b307485f "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
bgruening
parents: 25
diff changeset
360 if test_split_options["shuffle"] == "group":
93f3b307485f "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
bgruening
parents: 25
diff changeset
361 test_split_options["labels"] = groups
93f3b307485f "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
bgruening
parents: 25
diff changeset
362 if test_split_options["shuffle"] == "stratified":
20
0b88494bdcac planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
bgruening
parents:
diff changeset
363 if y is not None:
29
93f3b307485f "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
bgruening
parents: 25
diff changeset
364 test_split_options["labels"] = y
20
0b88494bdcac planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
bgruening
parents:
diff changeset
365 else:
29
93f3b307485f "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
bgruening
parents: 25
diff changeset
366 raise ValueError(
93f3b307485f "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
bgruening
parents: 25
diff changeset
367 "Stratified shuffle split is not " "applicable on empty target values!"
93f3b307485f "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
bgruening
parents: 25
diff changeset
368 )
20
0b88494bdcac planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
bgruening
parents:
diff changeset
369
31
5773e98921fc "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ea12f973df4b97a2691d9e4ce6bf6fae59d57717"
bgruening
parents: 30
diff changeset
370 (
5773e98921fc "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ea12f973df4b97a2691d9e4ce6bf6fae59d57717"
bgruening
parents: 30
diff changeset
371 X_train,
5773e98921fc "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ea12f973df4b97a2691d9e4ce6bf6fae59d57717"
bgruening
parents: 30
diff changeset
372 X_test,
5773e98921fc "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ea12f973df4b97a2691d9e4ce6bf6fae59d57717"
bgruening
parents: 30
diff changeset
373 y_train,
5773e98921fc "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ea12f973df4b97a2691d9e4ce6bf6fae59d57717"
bgruening
parents: 30
diff changeset
374 y_test,
5773e98921fc "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ea12f973df4b97a2691d9e4ce6bf6fae59d57717"
bgruening
parents: 30
diff changeset
375 groups_train,
5773e98921fc "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ea12f973df4b97a2691d9e4ce6bf6fae59d57717"
bgruening
parents: 30
diff changeset
376 _groups_test,
5773e98921fc "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ea12f973df4b97a2691d9e4ce6bf6fae59d57717"
bgruening
parents: 30
diff changeset
377 ) = train_test_split_none(X, y, groups, **test_split_options)
20
0b88494bdcac planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
bgruening
parents:
diff changeset
378
29
93f3b307485f "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
bgruening
parents: 25
diff changeset
379 exp_scheme = params["experiment_schemes"]["selected_exp_scheme"]
20
0b88494bdcac planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
bgruening
parents:
diff changeset
380
0b88494bdcac planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
bgruening
parents:
diff changeset
381 # handle validation (second) split
29
93f3b307485f "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
bgruening
parents: 25
diff changeset
382 if exp_scheme == "train_val_test":
93f3b307485f "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
bgruening
parents: 25
diff changeset
383 val_split_options = params["experiment_schemes"]["val_split"]["split_algos"]
20
0b88494bdcac planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
bgruening
parents:
diff changeset
384
29
93f3b307485f "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
bgruening
parents: 25
diff changeset
385 if val_split_options["shuffle"] == "group":
93f3b307485f "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
bgruening
parents: 25
diff changeset
386 val_split_options["labels"] = groups_train
93f3b307485f "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
bgruening
parents: 25
diff changeset
387 if val_split_options["shuffle"] == "stratified":
20
0b88494bdcac planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
bgruening
parents:
diff changeset
388 if y_train is not None:
29
93f3b307485f "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
bgruening
parents: 25
diff changeset
389 val_split_options["labels"] = y_train
20
0b88494bdcac planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
bgruening
parents:
diff changeset
390 else:
29
93f3b307485f "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
bgruening
parents: 25
diff changeset
391 raise ValueError(
93f3b307485f "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
bgruening
parents: 25
diff changeset
392 "Stratified shuffle split is not "
93f3b307485f "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
bgruening
parents: 25
diff changeset
393 "applicable on empty target values!"
93f3b307485f "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
bgruening
parents: 25
diff changeset
394 )
20
0b88494bdcac planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
bgruening
parents:
diff changeset
395
29
93f3b307485f "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
bgruening
parents: 25
diff changeset
396 (
93f3b307485f "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
bgruening
parents: 25
diff changeset
397 X_train,
93f3b307485f "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
bgruening
parents: 25
diff changeset
398 X_val,
93f3b307485f "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
bgruening
parents: 25
diff changeset
399 y_train,
93f3b307485f "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
bgruening
parents: 25
diff changeset
400 y_val,
93f3b307485f "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
bgruening
parents: 25
diff changeset
401 groups_train,
93f3b307485f "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
bgruening
parents: 25
diff changeset
402 _groups_val,
93f3b307485f "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
bgruening
parents: 25
diff changeset
403 ) = train_test_split_none(X_train, y_train, groups_train, **val_split_options)
20
0b88494bdcac planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
bgruening
parents:
diff changeset
404
0b88494bdcac planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
bgruening
parents:
diff changeset
405 # train and eval
29
93f3b307485f "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
bgruening
parents: 25
diff changeset
406 if hasattr(estimator, "validation_data"):
93f3b307485f "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
bgruening
parents: 25
diff changeset
407 if exp_scheme == "train_val_test":
93f3b307485f "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
bgruening
parents: 25
diff changeset
408 estimator.fit(X_train, y_train, validation_data=(X_val, y_val))
20
0b88494bdcac planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
bgruening
parents:
diff changeset
409 else:
29
93f3b307485f "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
bgruening
parents: 25
diff changeset
410 estimator.fit(X_train, y_train, validation_data=(X_test, y_test))
20
0b88494bdcac planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
bgruening
parents:
diff changeset
411 else:
0b88494bdcac planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
bgruening
parents:
diff changeset
412 estimator.fit(X_train, y_train)
0b88494bdcac planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
bgruening
parents:
diff changeset
413
29
93f3b307485f "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
bgruening
parents: 25
diff changeset
414 if hasattr(estimator, "evaluate"):
93f3b307485f "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
bgruening
parents: 25
diff changeset
415 scores = estimator.evaluate(
93f3b307485f "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
bgruening
parents: 25
diff changeset
416 X_test, y_test=y_test, scorer=scorer, is_multimetric=True
93f3b307485f "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
bgruening
parents: 25
diff changeset
417 )
20
0b88494bdcac planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
bgruening
parents:
diff changeset
418 else:
35
61edd9e5c17f planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 9981e25b00de29ed881b2229a173a8c812ded9bb
bgruening
parents: 31
diff changeset
419 scores = _score(estimator, X_test, y_test, scorer)
20
0b88494bdcac planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
bgruening
parents:
diff changeset
420 # handle output
0b88494bdcac planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
bgruening
parents:
diff changeset
421 for name, score in scores.items():
0b88494bdcac planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
bgruening
parents:
diff changeset
422 scores[name] = [score]
0b88494bdcac planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
bgruening
parents:
diff changeset
423 df = pd.DataFrame(scores)
0b88494bdcac planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
bgruening
parents:
diff changeset
424 df = df[sorted(df.columns)]
29
93f3b307485f "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
bgruening
parents: 25
diff changeset
425 df.to_csv(path_or_buf=outfile_result, sep="\t", header=True, index=False)
20
0b88494bdcac planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
bgruening
parents:
diff changeset
426
0b88494bdcac planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
bgruening
parents:
diff changeset
427 memory.clear(warn=False)
0b88494bdcac planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
bgruening
parents:
diff changeset
428
0b88494bdcac planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
bgruening
parents:
diff changeset
429 if outfile_object:
0b88494bdcac planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
bgruening
parents:
diff changeset
430 main_est = estimator
0b88494bdcac planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
bgruening
parents:
diff changeset
431 if isinstance(estimator, pipeline.Pipeline):
0b88494bdcac planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
bgruening
parents:
diff changeset
432 main_est = estimator.steps[-1][-1]
0b88494bdcac planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
bgruening
parents:
diff changeset
433
29
93f3b307485f "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
bgruening
parents: 25
diff changeset
434 if hasattr(main_est, "model_") and hasattr(main_est, "save_weights"):
20
0b88494bdcac planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
bgruening
parents:
diff changeset
435 if outfile_weights:
0b88494bdcac planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
bgruening
parents:
diff changeset
436 main_est.save_weights(outfile_weights)
29
93f3b307485f "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
bgruening
parents: 25
diff changeset
437 if getattr(main_est, "model_", None):
93f3b307485f "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
bgruening
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438 del main_est.model_
93f3b307485f "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
bgruening
parents: 25
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439 if getattr(main_est, "fit_params", None):
93f3b307485f "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
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parents: 25
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440 del main_est.fit_params
93f3b307485f "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
bgruening
parents: 25
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441 if getattr(main_est, "model_class_", None):
93f3b307485f "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
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parents: 25
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442 del main_est.model_class_
93f3b307485f "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
bgruening
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443 if getattr(main_est, "validation_data", None):
93f3b307485f "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
bgruening
parents: 25
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444 del main_est.validation_data
93f3b307485f "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
bgruening
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445 if getattr(main_est, "data_generator_", None):
20
0b88494bdcac planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
bgruening
parents:
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446 del main_est.data_generator_
0b88494bdcac planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
bgruening
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447
35
61edd9e5c17f planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 9981e25b00de29ed881b2229a173a8c812ded9bb
bgruening
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448 dump_model_to_h5(estimator, outfile_object)
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0b88494bdcac planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
bgruening
parents:
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449
0b88494bdcac planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
bgruening
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450
29
93f3b307485f "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
bgruening
parents: 25
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451 if __name__ == "__main__":
20
0b88494bdcac planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
bgruening
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452 aparser = argparse.ArgumentParser()
0b88494bdcac planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
bgruening
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453 aparser.add_argument("-i", "--inputs", dest="inputs", required=True)
0b88494bdcac planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
bgruening
parents:
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454 aparser.add_argument("-e", "--estimator", dest="infile_estimator")
0b88494bdcac planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
bgruening
parents:
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455 aparser.add_argument("-X", "--infile1", dest="infile1")
0b88494bdcac planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
bgruening
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456 aparser.add_argument("-y", "--infile2", dest="infile2")
0b88494bdcac planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
bgruening
parents:
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457 aparser.add_argument("-O", "--outfile_result", dest="outfile_result")
0b88494bdcac planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
bgruening
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458 aparser.add_argument("-o", "--outfile_object", dest="outfile_object")
0b88494bdcac planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
bgruening
parents:
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459 aparser.add_argument("-w", "--outfile_weights", dest="outfile_weights")
0b88494bdcac planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
bgruening
parents:
diff changeset
460 aparser.add_argument("-g", "--groups", dest="groups")
0b88494bdcac planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
bgruening
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461 aparser.add_argument("-r", "--ref_seq", dest="ref_seq")
0b88494bdcac planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
bgruening
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462 aparser.add_argument("-b", "--intervals", dest="intervals")
0b88494bdcac planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
bgruening
parents:
diff changeset
463 aparser.add_argument("-t", "--targets", dest="targets")
0b88494bdcac planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
bgruening
parents:
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464 aparser.add_argument("-f", "--fasta_path", dest="fasta_path")
0b88494bdcac planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
bgruening
parents:
diff changeset
465 args = aparser.parse_args()
0b88494bdcac planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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466
29
93f3b307485f "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
bgruening
parents: 25
diff changeset
467 main(
93f3b307485f "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
bgruening
parents: 25
diff changeset
468 args.inputs,
93f3b307485f "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
bgruening
parents: 25
diff changeset
469 args.infile_estimator,
93f3b307485f "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
bgruening
parents: 25
diff changeset
470 args.infile1,
93f3b307485f "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
bgruening
parents: 25
diff changeset
471 args.infile2,
93f3b307485f "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
bgruening
parents: 25
diff changeset
472 args.outfile_result,
93f3b307485f "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
bgruening
parents: 25
diff changeset
473 outfile_object=args.outfile_object,
93f3b307485f "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
bgruening
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diff changeset
474 outfile_weights=args.outfile_weights,
93f3b307485f "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
bgruening
parents: 25
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475 groups=args.groups,
93f3b307485f "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
bgruening
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diff changeset
476 ref_seq=args.ref_seq,
93f3b307485f "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
bgruening
parents: 25
diff changeset
477 intervals=args.intervals,
93f3b307485f "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
bgruening
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diff changeset
478 targets=args.targets,
93f3b307485f "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
bgruening
parents: 25
diff changeset
479 fasta_path=args.fasta_path,
93f3b307485f "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
bgruening
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diff changeset
480 )