Mercurial > repos > recetox > table_pandas_rename_column

annotate table_scipy_interpolate.py @ 0:3f54cd56a65e draft default tip

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planemo upload for repository https://github.com/RECETOX/galaxytools/tree/master/tools/tables commit d0ff40eb2b536fec6c973c3a9ea8e7f31cd9a0d6
author recetox
date Wed, 29 Jan 2025 15:35:31 +0000
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3f54cd56a65e planemo upload for repository https://github.com/RECETOX/galaxytools/tree/master/tools/tables commit d0ff40eb2b536fec6c973c3a9ea8e7f31cd9a0d6
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1 import argparse
3f54cd56a65e planemo upload for repository https://github.com/RECETOX/galaxytools/tree/master/tools/tables commit d0ff40eb2b536fec6c973c3a9ea8e7f31cd9a0d6
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2 import logging
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3 from typing import Callable, Tuple
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6 import numpy as np
3f54cd56a65e planemo upload for repository https://github.com/RECETOX/galaxytools/tree/master/tools/tables commit d0ff40eb2b536fec6c973c3a9ea8e7f31cd9a0d6
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7 import pandas as pd
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8 from scipy.interpolate import Akima1DInterpolator, CubicSpline, PchipInterpolator
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9 from utils import LoadDataAction, StoreOutputAction
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12 class InterpolationModelAction(argparse.Action):
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13 def __call__(
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14 self,
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15 parser: argparse.ArgumentParser,
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16 namespace: argparse.Namespace,
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17 values: str,
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18 option_string: str = None,
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19 ) -> None:
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20 """
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21 Custom argparse action to map interpolation method names to their corresponding functions.
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22
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23 Parameters:
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24 parser (argparse.ArgumentParser): The argument parser instance.
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25 namespace (argparse.Namespace): The namespace to hold the parsed values.
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26 values (str): The interpolation method name.
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27 option_string (str): The option string.
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28 """
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29 interpolators = {
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30 "linear": np.interp,
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31 "cubic": CubicSpline,
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32 "pchip": PchipInterpolator,
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33 "akima": Akima1DInterpolator,
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34 }
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35 if values not in interpolators:
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36 raise ValueError(f"Unknown interpolation method: {values}")
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37 setattr(namespace, self.dest, interpolators[values])
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38
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39
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40 def interpolate_data(
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41 reference: pd.DataFrame,
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42 query: pd.DataFrame,
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43 x_col: int,
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44 y_col: int,
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45 xnew_col: int,
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46 model: Callable,
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47 output_dataset: Tuple[Callable[[pd.DataFrame, str], None], str],
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48 ) -> None:
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49 """
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50 Interpolate data using the specified model.
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51
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52 Parameters:
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53 reference (pd.DataFrame): The reference dataset.
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54 query (pd.DataFrame): The query dataset.
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55 x_col (int): The 1-based index of the x column in the reference dataset.
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56 y_col (int): The 1-based index of the y column in the reference dataset.
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57 xnew_col (int): The 1-based index of the x column in the query dataset.
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58 model (Callable): The interpolation model to use.
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59 output_dataset (Tuple[Callable[[pd.DataFrame, str], None], str]): The output dataset and its file extension.
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60 """
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61 try:
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62 # Convert 1-based indices to 0-based indices
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63 x_col_name = reference.columns[x_col - 1]
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64 y_col_name = reference.columns[y_col - 1]
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65 xnew_col_name = query.columns[xnew_col - 1]
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66
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67 # Check if y_col already exists in the query dataset
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68 if y_col_name in query.columns:
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69 raise ValueError(
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70 f"Column '{y_col_name}' already exists in the query dataset."
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71 )
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72
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73 if model == np.interp:
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74 query[y_col_name] = model(
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75 query[xnew_col_name], reference[x_col_name], reference[y_col_name]
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76 )
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77 else:
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78 model_instance = model(reference[x_col_name], reference[y_col_name])
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79 query[y_col_name] = model_instance(query[xnew_col_name]).astype(float)
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80
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81 write_func, file_path = output_dataset
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82 write_func(query, file_path)
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83 except Exception as e:
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84 logging.error(f"Error in interpolate_data function: {e}")
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85 raise
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86
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87
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88 def main(
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89 reference_dataset: pd.DataFrame,
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90 query_dataset: pd.DataFrame,
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91 x_col: int,
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92 y_col: int,
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93 xnew_col: int,
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94 model: Callable,
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95 output_dataset: Tuple[Callable[[pd.DataFrame, str], None], str],
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96 ) -> None:
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97 """
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98 Main function to load the datasets, perform interpolation, and save the result.
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99
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100 Parameters:
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101 reference_dataset (Tuple[pd.DataFrame, str]): The reference dataset and its file extension.
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102 query_dataset (Tuple[pd.DataFrame, str]): The query dataset and its file extension.
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103 x_col (int): The 1-based index of the x column in the reference dataset.
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104 y_col (int): The 1-based index of the y column in the reference dataset.
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105 xnew_col (int): The 1-based index of the x column in the query dataset.
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106 model (Callable): The interpolation model to use.
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107 output_dataset (Tuple[Callable[[pd.DataFrame, str], None], str]): The output dataset and its file extension.
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108 """
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109 try:
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110 interpolate_data(reference_dataset, query_dataset, x_col, y_col, xnew_col, model, output_dataset)
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111 except Exception as e:
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112 logging.error(f"Error in main function: {e}")
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113 raise
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114
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115
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116 if __name__ == "__main__":
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117 logging.basicConfig(level=logging.INFO)
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118 parser = argparse.ArgumentParser(
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119 description="Interpolate data using various methods."
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120 )
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121 parser.add_argument(
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122 "--reference_dataset",
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123 nargs=2,
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124 action=LoadDataAction,
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125 required=True,
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126 help="Path to the reference dataset and its file extension (csv, tsv, parquet)",
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127 )
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128 parser.add_argument(
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129 "--query_dataset",
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130 nargs=2,
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131 action=LoadDataAction,
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132 required=True,
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133 help="Path to the query dataset and its file extension (csv, tsv, parquet)",
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134 )
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135 parser.add_argument(
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136 "--x_col",
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137 type=int,
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138 required=True,
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139 help="1-based index of the x column in the reference dataset",
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140 )
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141 parser.add_argument(
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142 "--y_col",
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143 type=int,
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144 required=True,
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145 help="1-based index of the y column in the reference dataset",
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146 )
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147 parser.add_argument(
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148 "--xnew_col",
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149 type=int,
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150 required=True,
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151 help="1-based index of the x column in the query dataset",
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152 )
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153 parser.add_argument(
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154 "--model",
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155 type=str,
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156 action=InterpolationModelAction,
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157 required=True,
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158 help="Interpolation model to use (linear, cubic, pchip, akima)",
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159 )
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160 parser.add_argument(
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161 "--output_dataset",
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162 nargs=2,
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163 action=StoreOutputAction,
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164 required=True,
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165 help="Path to the output dataset and its file extension (csv, tsv, parquet)",
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166 )
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167
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168 args = parser.parse_args()
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169 main(
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170 args.reference_dataset,
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171 args.query_dataset,
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172 args.x_col,
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173 args.y_col,
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174 args.xnew_col,
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175 args.model,
3f54cd56a65e planemo upload for repository https://github.com/RECETOX/galaxytools/tree/master/tools/tables commit d0ff40eb2b536fec6c973c3a9ea8e7f31cd9a0d6
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parents:
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176 args.output_dataset,
3f54cd56a65e planemo upload for repository https://github.com/RECETOX/galaxytools/tree/master/tools/tables commit d0ff40eb2b536fec6c973c3a9ea8e7f31cd9a0d6
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parents:
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177 )