Mercurial > repos > recetox > matchms

annotate matchms_wrapper.py @ 9:f06923bdd2f2 draft

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"planemo upload for repository https://github.com/RECETOX/galaxytools/tree/master/tools/matchms commit 5bd7d3aa1063b0a5a90577dd6c79504fdd93f73c"
author recetox
date Mon, 10 Jan 2022 12:21:43 +0000
parents 4571641de47a
children
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1 import argparse
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2 import sys
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4 from matchms import calculate_scores
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5 from matchms.filtering import add_precursor_mz, default_filters, normalize_intensities
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6 from matchms.importing import load_from_mgf, load_from_msp
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7 from matchms.similarity import (
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8 CosineGreedy,
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9 CosineHungarian,
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10 ModifiedCosine,
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11 )
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12 from pandas import DataFrame
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15 def main(argv):
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16 parser = argparse.ArgumentParser(description="Compute MSP similarity scores")
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17 parser.add_argument("-f", dest="default_filters", action='store_true', help="Apply default filters")
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18 parser.add_argument("-n", dest="normalize_intensities", action='store_true', help="Normalize intensities.")
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19 parser.add_argument("-s", dest="symmetric", action='store_true', help="Computation is symmetric.")
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20 parser.add_argument("--ref", dest="references_filename", type=str, help="Path to reference spectra library.")
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21 parser.add_argument("--ref_format", dest="references_format", type=str, help="Reference spectra library file format.")
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22 parser.add_argument("queries_filename", type=str, help="Path to query spectra.")
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23 parser.add_argument("queries_format", type=str, help="Query spectra file format.")
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24 parser.add_argument("similarity_metric", type=str, help='Metric to use for matching.')
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25 parser.add_argument("tolerance", type=float, help="Tolerance to use for peak matching.")
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26 parser.add_argument("mz_power", type=float, help="The power to raise mz to in the cosine function.")
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27 parser.add_argument("intensity_power", type=float, help="The power to raise intensity to in the cosine function.")
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28 parser.add_argument("output_filename_scores", type=str, help="Path where to store the output .tsv scores.")
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29 parser.add_argument("output_filename_matches", type=str, help="Path where to store the output .tsv matches.")
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30 args = parser.parse_args()
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32 if args.queries_format == 'msp':
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33 queries_spectra = list(load_from_msp(args.queries_filename))
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34 elif args.queries_format == 'mgf':
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35 queries_spectra = list(load_from_mgf(args.queries_filename))
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36 else:
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37 raise ValueError(f'File format {args.queries_format} not supported for query spectra.')
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39 if args.symmetric:
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40 reference_spectra = []
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41 else:
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42 if args.references_format == 'msp':
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43 reference_spectra = list(load_from_msp(args.references_filename))
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44 elif args.references_format == 'mgf':
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45 reference_spectra = list(load_from_mgf(args.references_filename))
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46 else:
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47 raise ValueError(f'File format {args.references_format} not supported for reference spectra library.')
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49 if args.default_filters is True:
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50 print("Applying default filters...")
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51 queries_spectra = list(map(default_filters, queries_spectra))
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52 reference_spectra = list(map(default_filters, reference_spectra))
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54 if args.normalize_intensities is True:
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55 print("Normalizing intensities...")
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56 queries_spectra = list(map(normalize_intensities, queries_spectra))
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57 reference_spectra = list(map(normalize_intensities, reference_spectra))
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58
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59 if args.similarity_metric == 'CosineGreedy':
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60 similarity_metric = CosineGreedy(args.tolerance, args.mz_power, args.intensity_power)
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61 elif args.similarity_metric == 'CosineHungarian':
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62 similarity_metric = CosineHungarian(args.tolerance, args.mz_power, args.intensity_power)
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63 elif args.similarity_metric == 'ModifiedCosine':
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64 similarity_metric = ModifiedCosine(args.tolerance, args.mz_power, args.intensity_power)
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65 reference_spectra = list(map(add_precursor_mz, reference_spectra))
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66 queries_spectra = list(map(add_precursor_mz, queries_spectra))
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67 else:
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68 return -1
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69
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70 print("Calculating scores...")
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71 scores = calculate_scores(
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72 references=queries_spectra if args.symmetric else reference_spectra,
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73 queries=queries_spectra,
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74 similarity_function=similarity_metric,
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75 is_symmetric=args.symmetric
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76 )
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77
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78 write_outputs(args, scores)
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79 return 0
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82 def write_outputs(args, scores):
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83 print("Storing outputs...")
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84 query_names = [spectra.metadata['name'] for spectra in scores.queries]
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85 reference_names = [spectra.metadata['name'] for spectra in scores.references]
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87 # Write scores to dataframe
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88 dataframe_scores = DataFrame(data=[entry["score"] for entry in scores.scores], index=reference_names, columns=query_names)
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89 dataframe_scores.to_csv(args.output_filename_scores, sep='\t')
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91 # Write number of matches to dataframe
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92 dataframe_matches = DataFrame(data=[entry["matches"] for entry in scores.scores], index=reference_names, columns=query_names)
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93 dataframe_matches.to_csv(args.output_filename_matches, sep='\t')
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94
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96 if __name__ == "__main__":
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97 main(argv=sys.argv[1:])
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98 pass