Mercurial > repos > galaxy-australia > alphafold2

annotate gen_extra_outputs.py @ 0:7ae9d78b06f5 draft

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"planemo upload for repository https://github.com/usegalaxy-au/galaxy-local-tools commit 7b79778448363aa8c9b14604337e81009e461bd2-dirty"
author galaxy-australia
date Fri, 28 Jan 2022 04:56:29 +0000
parents
children 3bd420ec162d
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3 import json
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4 import pickle
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5 import argparse
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6 from typing import Any, Dict, List
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9 class Settings:
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10 """parses then keeps track of program settings"""
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11 def __init__(self):
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12 self.workdir = None
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13 self.output_confidence_scores = True
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14 self.output_residue_scores = False
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16 def parse_settings(self) -> None:
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17 parser = argparse.ArgumentParser()
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18 parser.add_argument(
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19 "workdir",
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20 help="alphafold output directory",
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21 type=str
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22 )
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23 parser.add_argument(
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24 "-p",
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25 "--plddts",
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26 help="output per-residue confidence scores (pLDDTs)",
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27 action="store_true"
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28 )
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29 args = parser.parse_args()
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30 self.workdir = args.workdir.rstrip('/')
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31 self.output_residue_scores = args.plddts
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32
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34 class ExecutionContext:
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35 """uses program settings to get paths to files etc"""
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36 def __init__(self, settings: Settings):
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37 self.settings = settings
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38
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39 @property
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40 def ranking_debug(self) -> str:
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41 return f'{self.settings.workdir}/ranking_debug.json'
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42
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43 @property
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44 def model_pkls(self) -> List[str]:
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45 return [f'{self.settings.workdir}/result_model_{i}.pkl'
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46 for i in range(1, 6)]
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47
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48 @property
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49 def model_conf_score_output(self) -> str:
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50 return f'{self.settings.workdir}/model_confidence_scores.tsv'
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51
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52 @property
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53 def plddt_output(self) -> str:
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54 return f'{self.settings.workdir}/plddts.tsv'
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55
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56
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57 class FileLoader:
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58 """loads file data for use by other classes"""
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59 def __init__(self, context: ExecutionContext):
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60 self.context = context
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61
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62 def get_model_mapping(self) -> Dict[str, int]:
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63 data = self.load_ranking_debug()
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64 return {name: int(rank) + 1
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65 for (rank, name) in enumerate(data['order'])}
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66
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67 def get_conf_scores(self) -> Dict[str, float]:
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68 data = self.load_ranking_debug()
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69 return {name: float(f'{score:.2f}')
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70 for name, score in data['plddts'].items()}
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72 def load_ranking_debug(self) -> Dict[str, Any]:
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73 with open(self.context.ranking_debug, 'r') as fp:
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74 return json.load(fp)
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75
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76 def get_model_plddts(self) -> Dict[str, List[float]]:
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77 plddts: Dict[str, List[float]] = {}
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78 model_pkls = self.context.model_pkls
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79 for i in range(5):
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80 pklfile = model_pkls[i]
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81 with open(pklfile, 'rb') as fp:
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82 data = pickle.load(fp)
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83 plddts[f'model_{i+1}'] = [float(f'{x:.2f}') for x in data['plddt']]
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84 return plddts
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85
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86
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87 class OutputGenerator:
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88 """generates the output data we are interested in creating"""
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89 def __init__(self, loader: FileLoader):
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90 self.loader = loader
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91
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92 def gen_conf_scores(self):
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93 mapping = self.loader.get_model_mapping()
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94 scores = self.loader.get_conf_scores()
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95 ranked = list(scores.items())
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96 ranked.sort(key=lambda x: x[1], reverse=True)
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97 return {f'model_{mapping[name]}': score
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98 for name, score in ranked}
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99
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100 def gen_residue_scores(self) -> Dict[str, List[float]]:
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101 mapping = self.loader.get_model_mapping()
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102 model_plddts = self.loader.get_model_plddts()
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103 return {f'model_{mapping[name]}': plddts
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104 for name, plddts in model_plddts.items()}
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105
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106
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107 class OutputWriter:
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108 """writes generated data to files"""
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109 def __init__(self, context: ExecutionContext):
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110 self.context = context
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111
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112 def write_conf_scores(self, data: Dict[str, float]) -> None:
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113 outfile = self.context.model_conf_score_output
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114 with open(outfile, 'w') as fp:
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115 for model, score in data.items():
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116 fp.write(f'{model}\t{score}\n')
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117
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118 def write_residue_scores(self, data: Dict[str, List[float]]) -> None:
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119 outfile = self.context.plddt_output
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120 model_plddts = list(data.items())
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121 model_plddts.sort()
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122
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123 with open(outfile, 'w') as fp:
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124 for model, plddts in model_plddts:
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125 plddt_str_list = [str(x) for x in plddts]
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126 plddt_str = ','.join(plddt_str_list)
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127 fp.write(f'{model}\t{plddt_str}\n')
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128
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129
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130 def main():
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131 # setup
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132 settings = Settings()
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133 settings.parse_settings()
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134 context = ExecutionContext(settings)
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135 loader = FileLoader(context)
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136
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137 # generate & write outputs
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138 generator = OutputGenerator(loader)
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139 writer = OutputWriter(context)
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140
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141 # confidence scores
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142 conf_scores = generator.gen_conf_scores()
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143 writer.write_conf_scores(conf_scores)
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144
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145 # per-residue plddts
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146 if settings.output_residue_scores:
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147 residue_scores = generator.gen_residue_scores()
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148 writer.write_residue_scores(residue_scores)
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149
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150
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151 if __name__ == '__main__':
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152 main()
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153
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154
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155