Mercurial > repos > recetox > spec2vec_similarity

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planemo upload for repository https://github.com/RECETOX/galaxytools/tree/master/tools/spec2vec commit f79a5b51599254817727bc9028b9797ea994cb4e
author recetox
date Tue, 27 Jun 2023 14:23:58 +0000
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881742fff7ff planemo upload for repository https://github.com/RECETOX/galaxytools/tree/master/tools/spec2vec commit f79a5b51599254817727bc9028b9797ea994cb4e
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1 <tool id="spec2vec_similarity" name="spec2vec similarity" version="@TOOL_VERSION@+galaxy0" profile="21.09">
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2 <macros>
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3 <import>macros.xml</import>
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4 </macros>
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5 <expand macro="creator"/>
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6 <expand macro="edam" />
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8 <requirements>
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9 <requirement type="package" version="@TOOL_VERSION@">spec2vec</requirement>
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10 </requirements>
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12 <command detect_errors="aggressive"><![CDATA[
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13 python3 ${python_wrapper}
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14 ]]></command>
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15 <configfiles>
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16 <configfile name="python_wrapper">
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17 @init_logger@
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18 @init_model@
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20 import numpy as np
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21 from spec2vec import Spec2Vec
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23 similarity = Spec2Vec(
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24 model,
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25 intensity_weighting_power=${intensity_power},
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26 allowed_missing_percentage=${allow_missing_percentage} * 100
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27 )
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28 name="Spec2Vec_${intensity_power}_${allow_missing_percentage}"
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30 @init_scores@
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32 from matchms.filtering import normalize_intensities
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34 layer = similarity.sparse_array(
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35 references=np.asarray(list(map(normalize_intensities, scores.references))),
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36 queries=np.asarray(list(map(normalize_intensities, scores.queries))),
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37 idx_row = scores._scores.row,
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38 idx_col = scores._scores.col,
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39 is_symmetric=False)
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41 scores._scores.add_sparse_data(scores._scores.row, scores._scores.col, layer, name)
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43 scores.filter_by_range(inplace=True, name=name, low=0)
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44 scores.to_json("$similarity_scores")
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45 </configfile>
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46 </configfiles>
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48 <inputs>
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49 <expand macro="input_param" />
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50 <param label="Model JSON file" name="model_metadata" type="data" format="json"
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51 help="Model JSON file to use for Spec2Vec similarity computing."/>
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52 <param label="Model NPY file" name="model_weights" type="data" format="binary"
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53 help="Model NPY file to use for Spec2Vec similarity computing."/>
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54 <param label="intensity_power" name="intensity_power" type="float" value="0.0"
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55 help="Spectrum vectors are a weighted sum of the word vectors. The given word intensities will be raised to the given power.
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56 The default is 0, which means that no weighing will be done."/>
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57 <param label="Maximum share of new peaks" name="allow_missing_percentage" type="float" value="0.1" max="1.0" min="0.0"
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58 help="Maximum allowed share of the peaks that are new to the model in relation to the whole peak corpus."/>
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59 </inputs>
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60 <outputs>
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61 <data label="Spec2Vec scores of ${on_string}" name="similarity_scores" format="json"/>
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62 </outputs>
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63
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64 <tests>
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65 <test> <!-- TEST #1: Test Spec2Vec. -->
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66 <param name="references" value="inp_filtered_library.msp" ftype="msp"/>
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67 <param name="queries" value="inp_filtered_spectra.msp" ftype="msp"/>
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68 <param name="model_metadata" value="model_100.json" ftype="json"/>
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69 <param name="model_weights" value="weights_100.binary" ftype="auto"/>
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70 <param name="allow_missing_percentage" value="1.0"/>
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71 <output name="similarity_scores" file="s2v_scores_test1_out.json" ftype="json"/>
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72 </test>
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73 <test>
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74 <param name="use_scores" value="True"/>
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75 <param name="scores_in" value="ri_match_60.json" ftype="json"/>
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76 <param name="model_metadata" value="model_100.json" ftype="json"/>
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77 <param name="model_weights" value="weights_100.binary" ftype="auto"/>
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78 <param name="allow_missing_percentage" value="1.0"/>
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79 <output name="similarity_scores" value="s2v_scores_test2_out.json" ftype="json" />
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80 </test>
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81 </tests>
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82
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83 <expand macro="citations"/>
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84 </tool>