Mercurial > repos > bgruening > sklearn_feature_selection
annotate ml_visualization_ex.py @ 24:4170e2bda73d draft
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit d6333e7294e67be5968a41f404b66699cad4ae53"
author | bgruening |
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date | Thu, 07 Nov 2019 05:37:06 -0500 |
parents | c2cd3219543a |
children | 41b109e70a7f |
rev | line source |
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21
fe47a06943fb
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ba6a47bdf76bbf4cb276206ac1a8cbf61332fd16"
bgruening
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1 import argparse |
fe47a06943fb
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ba6a47bdf76bbf4cb276206ac1a8cbf61332fd16"
bgruening
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2 import json |
fe47a06943fb
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ba6a47bdf76bbf4cb276206ac1a8cbf61332fd16"
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3 import numpy as np |
fe47a06943fb
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ba6a47bdf76bbf4cb276206ac1a8cbf61332fd16"
bgruening
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4 import pandas as pd |
fe47a06943fb
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ba6a47bdf76bbf4cb276206ac1a8cbf61332fd16"
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5 import plotly |
fe47a06943fb
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ba6a47bdf76bbf4cb276206ac1a8cbf61332fd16"
bgruening
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6 import plotly.graph_objs as go |
fe47a06943fb
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ba6a47bdf76bbf4cb276206ac1a8cbf61332fd16"
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7 import warnings |
fe47a06943fb
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ba6a47bdf76bbf4cb276206ac1a8cbf61332fd16"
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8 |
fe47a06943fb
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ba6a47bdf76bbf4cb276206ac1a8cbf61332fd16"
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9 from keras.models import model_from_json |
fe47a06943fb
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ba6a47bdf76bbf4cb276206ac1a8cbf61332fd16"
bgruening
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10 from keras.utils import plot_model |
fe47a06943fb
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ba6a47bdf76bbf4cb276206ac1a8cbf61332fd16"
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11 from sklearn.feature_selection.base import SelectorMixin |
fe47a06943fb
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ba6a47bdf76bbf4cb276206ac1a8cbf61332fd16"
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12 from sklearn.metrics import precision_recall_curve, average_precision_score |
fe47a06943fb
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ba6a47bdf76bbf4cb276206ac1a8cbf61332fd16"
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13 from sklearn.metrics import roc_curve, auc |
fe47a06943fb
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ba6a47bdf76bbf4cb276206ac1a8cbf61332fd16"
bgruening
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14 from sklearn.pipeline import Pipeline |
fe47a06943fb
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ba6a47bdf76bbf4cb276206ac1a8cbf61332fd16"
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15 from galaxy_ml.utils import load_model, read_columns, SafeEval |
fe47a06943fb
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ba6a47bdf76bbf4cb276206ac1a8cbf61332fd16"
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16 |
fe47a06943fb
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ba6a47bdf76bbf4cb276206ac1a8cbf61332fd16"
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17 |
fe47a06943fb
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ba6a47bdf76bbf4cb276206ac1a8cbf61332fd16"
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18 safe_eval = SafeEval() |
fe47a06943fb
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ba6a47bdf76bbf4cb276206ac1a8cbf61332fd16"
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19 |
fe47a06943fb
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ba6a47bdf76bbf4cb276206ac1a8cbf61332fd16"
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20 |
fe47a06943fb
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ba6a47bdf76bbf4cb276206ac1a8cbf61332fd16"
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21 def main(inputs, infile_estimator=None, infile1=None, |
fe47a06943fb
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ba6a47bdf76bbf4cb276206ac1a8cbf61332fd16"
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22 infile2=None, outfile_result=None, |
fe47a06943fb
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ba6a47bdf76bbf4cb276206ac1a8cbf61332fd16"
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23 outfile_object=None, groups=None, |
fe47a06943fb
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ba6a47bdf76bbf4cb276206ac1a8cbf61332fd16"
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24 ref_seq=None, intervals=None, |
fe47a06943fb
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ba6a47bdf76bbf4cb276206ac1a8cbf61332fd16"
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25 targets=None, fasta_path=None, |
fe47a06943fb
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ba6a47bdf76bbf4cb276206ac1a8cbf61332fd16"
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26 model_config=None): |
fe47a06943fb
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ba6a47bdf76bbf4cb276206ac1a8cbf61332fd16"
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27 """ |
fe47a06943fb
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ba6a47bdf76bbf4cb276206ac1a8cbf61332fd16"
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28 Parameter |
fe47a06943fb
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ba6a47bdf76bbf4cb276206ac1a8cbf61332fd16"
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29 --------- |
fe47a06943fb
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ba6a47bdf76bbf4cb276206ac1a8cbf61332fd16"
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30 inputs : str |
fe47a06943fb
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ba6a47bdf76bbf4cb276206ac1a8cbf61332fd16"
bgruening
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31 File path to galaxy tool parameter |
fe47a06943fb
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ba6a47bdf76bbf4cb276206ac1a8cbf61332fd16"
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32 |
fe47a06943fb
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ba6a47bdf76bbf4cb276206ac1a8cbf61332fd16"
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33 infile_estimator : str, default is None |
fe47a06943fb
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ba6a47bdf76bbf4cb276206ac1a8cbf61332fd16"
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34 File path to estimator |
fe47a06943fb
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ba6a47bdf76bbf4cb276206ac1a8cbf61332fd16"
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35 |
fe47a06943fb
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ba6a47bdf76bbf4cb276206ac1a8cbf61332fd16"
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36 infile1 : str, default is None |
fe47a06943fb
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ba6a47bdf76bbf4cb276206ac1a8cbf61332fd16"
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37 File path to dataset containing features or true labels. |
fe47a06943fb
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ba6a47bdf76bbf4cb276206ac1a8cbf61332fd16"
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38 |
fe47a06943fb
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ba6a47bdf76bbf4cb276206ac1a8cbf61332fd16"
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39 infile2 : str, default is None |
fe47a06943fb
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ba6a47bdf76bbf4cb276206ac1a8cbf61332fd16"
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40 File path to dataset containing target values or predicted |
fe47a06943fb
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ba6a47bdf76bbf4cb276206ac1a8cbf61332fd16"
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41 probabilities. |
fe47a06943fb
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ba6a47bdf76bbf4cb276206ac1a8cbf61332fd16"
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42 |
fe47a06943fb
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ba6a47bdf76bbf4cb276206ac1a8cbf61332fd16"
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43 outfile_result : str, default is None |
fe47a06943fb
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ba6a47bdf76bbf4cb276206ac1a8cbf61332fd16"
bgruening
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44 File path to save the results, either cv_results or test result |
fe47a06943fb
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ba6a47bdf76bbf4cb276206ac1a8cbf61332fd16"
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45 |
fe47a06943fb
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ba6a47bdf76bbf4cb276206ac1a8cbf61332fd16"
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46 outfile_object : str, default is None |
fe47a06943fb
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ba6a47bdf76bbf4cb276206ac1a8cbf61332fd16"
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47 File path to save searchCV object |
fe47a06943fb
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ba6a47bdf76bbf4cb276206ac1a8cbf61332fd16"
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48 |
fe47a06943fb
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ba6a47bdf76bbf4cb276206ac1a8cbf61332fd16"
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49 groups : str, default is None |
fe47a06943fb
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ba6a47bdf76bbf4cb276206ac1a8cbf61332fd16"
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50 File path to dataset containing groups labels |
fe47a06943fb
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ba6a47bdf76bbf4cb276206ac1a8cbf61332fd16"
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51 |
fe47a06943fb
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ba6a47bdf76bbf4cb276206ac1a8cbf61332fd16"
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52 ref_seq : str, default is None |
fe47a06943fb
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ba6a47bdf76bbf4cb276206ac1a8cbf61332fd16"
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53 File path to dataset containing genome sequence file |
fe47a06943fb
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ba6a47bdf76bbf4cb276206ac1a8cbf61332fd16"
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54 |
fe47a06943fb
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ba6a47bdf76bbf4cb276206ac1a8cbf61332fd16"
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55 intervals : str, default is None |
fe47a06943fb
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ba6a47bdf76bbf4cb276206ac1a8cbf61332fd16"
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56 File path to dataset containing interval file |
fe47a06943fb
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ba6a47bdf76bbf4cb276206ac1a8cbf61332fd16"
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57 |
fe47a06943fb
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ba6a47bdf76bbf4cb276206ac1a8cbf61332fd16"
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58 targets : str, default is None |
fe47a06943fb
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ba6a47bdf76bbf4cb276206ac1a8cbf61332fd16"
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59 File path to dataset compressed target bed file |
fe47a06943fb
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ba6a47bdf76bbf4cb276206ac1a8cbf61332fd16"
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60 |
fe47a06943fb
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ba6a47bdf76bbf4cb276206ac1a8cbf61332fd16"
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61 fasta_path : str, default is None |
fe47a06943fb
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ba6a47bdf76bbf4cb276206ac1a8cbf61332fd16"
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62 File path to dataset containing fasta file |
fe47a06943fb
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ba6a47bdf76bbf4cb276206ac1a8cbf61332fd16"
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63 |
fe47a06943fb
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ba6a47bdf76bbf4cb276206ac1a8cbf61332fd16"
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64 model_config : str, default is None |
fe47a06943fb
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ba6a47bdf76bbf4cb276206ac1a8cbf61332fd16"
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65 File path to dataset containing JSON config for neural networks |
fe47a06943fb
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ba6a47bdf76bbf4cb276206ac1a8cbf61332fd16"
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66 """ |
fe47a06943fb
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ba6a47bdf76bbf4cb276206ac1a8cbf61332fd16"
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67 warnings.simplefilter('ignore') |
fe47a06943fb
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ba6a47bdf76bbf4cb276206ac1a8cbf61332fd16"
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68 |
fe47a06943fb
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69 with open(inputs, 'r') as param_handler: |
fe47a06943fb
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ba6a47bdf76bbf4cb276206ac1a8cbf61332fd16"
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70 params = json.load(param_handler) |
fe47a06943fb
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71 |
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72 title = params['plotting_selection']['title'].strip() |
fe47a06943fb
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ba6a47bdf76bbf4cb276206ac1a8cbf61332fd16"
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73 plot_type = params['plotting_selection']['plot_type'] |
fe47a06943fb
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ba6a47bdf76bbf4cb276206ac1a8cbf61332fd16"
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74 if plot_type == 'feature_importances': |
fe47a06943fb
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ba6a47bdf76bbf4cb276206ac1a8cbf61332fd16"
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75 with open(infile_estimator, 'rb') as estimator_handler: |
fe47a06943fb
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ba6a47bdf76bbf4cb276206ac1a8cbf61332fd16"
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76 estimator = load_model(estimator_handler) |
fe47a06943fb
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ba6a47bdf76bbf4cb276206ac1a8cbf61332fd16"
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77 |
fe47a06943fb
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78 column_option = (params['plotting_selection'] |
fe47a06943fb
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ba6a47bdf76bbf4cb276206ac1a8cbf61332fd16"
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79 ['column_selector_options'] |
fe47a06943fb
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ba6a47bdf76bbf4cb276206ac1a8cbf61332fd16"
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80 ['selected_column_selector_option']) |
fe47a06943fb
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ba6a47bdf76bbf4cb276206ac1a8cbf61332fd16"
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81 if column_option in ['by_index_number', 'all_but_by_index_number', |
fe47a06943fb
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ba6a47bdf76bbf4cb276206ac1a8cbf61332fd16"
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82 'by_header_name', 'all_but_by_header_name']: |
fe47a06943fb
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ba6a47bdf76bbf4cb276206ac1a8cbf61332fd16"
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83 c = (params['plotting_selection'] |
fe47a06943fb
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ba6a47bdf76bbf4cb276206ac1a8cbf61332fd16"
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84 ['column_selector_options']['col1']) |
fe47a06943fb
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ba6a47bdf76bbf4cb276206ac1a8cbf61332fd16"
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85 else: |
fe47a06943fb
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ba6a47bdf76bbf4cb276206ac1a8cbf61332fd16"
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86 c = None |
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87 |
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88 _, input_df = read_columns(infile1, c=c, |
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89 c_option=column_option, |
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90 return_df=True, |
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91 sep='\t', header='infer', |
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92 parse_dates=True) |
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93 |
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94 feature_names = input_df.columns.values |
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95 |
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96 if isinstance(estimator, Pipeline): |
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97 for st in estimator.steps[:-1]: |
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98 if isinstance(st[-1], SelectorMixin): |
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99 mask = st[-1].get_support() |
fe47a06943fb
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100 feature_names = feature_names[mask] |
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101 estimator = estimator.steps[-1][-1] |
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102 |
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103 if hasattr(estimator, 'coef_'): |
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104 coefs = estimator.coef_ |
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105 else: |
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106 coefs = getattr(estimator, 'feature_importances_', None) |
fe47a06943fb
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107 if coefs is None: |
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108 raise RuntimeError('The classifier does not expose ' |
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109 '"coef_" or "feature_importances_" ' |
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110 'attributes') |
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111 |
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112 threshold = params['plotting_selection']['threshold'] |
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113 if threshold is not None: |
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114 mask = (coefs > threshold) | (coefs < -threshold) |
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115 coefs = coefs[mask] |
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116 feature_names = feature_names[mask] |
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117 |
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118 # sort |
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119 indices = np.argsort(coefs)[::-1] |
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120 |
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121 trace = go.Bar(x=feature_names[indices], |
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122 y=coefs[indices]) |
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123 layout = go.Layout(title=title or "Feature Importances") |
fe47a06943fb
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ba6a47bdf76bbf4cb276206ac1a8cbf61332fd16"
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124 fig = go.Figure(data=[trace], layout=layout) |
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125 |
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126 elif plot_type == 'pr_curve': |
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127 df1 = pd.read_csv(infile1, sep='\t', header=None) |
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"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ba6a47bdf76bbf4cb276206ac1a8cbf61332fd16"
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128 df2 = pd.read_csv(infile2, sep='\t', header=None) |
fe47a06943fb
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ba6a47bdf76bbf4cb276206ac1a8cbf61332fd16"
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129 |
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130 precision = {} |
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131 recall = {} |
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132 ap = {} |
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133 |
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134 pos_label = params['plotting_selection']['pos_label'].strip() \ |
fe47a06943fb
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ba6a47bdf76bbf4cb276206ac1a8cbf61332fd16"
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135 or None |
fe47a06943fb
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ba6a47bdf76bbf4cb276206ac1a8cbf61332fd16"
bgruening
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136 for col in df1.columns: |
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137 y_true = df1[col].values |
fe47a06943fb
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ba6a47bdf76bbf4cb276206ac1a8cbf61332fd16"
bgruening
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138 y_score = df2[col].values |
fe47a06943fb
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ba6a47bdf76bbf4cb276206ac1a8cbf61332fd16"
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139 |
fe47a06943fb
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bgruening
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140 precision[col], recall[col], _ = precision_recall_curve( |
fe47a06943fb
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ba6a47bdf76bbf4cb276206ac1a8cbf61332fd16"
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141 y_true, y_score, pos_label=pos_label) |
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"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ba6a47bdf76bbf4cb276206ac1a8cbf61332fd16"
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142 ap[col] = average_precision_score( |
fe47a06943fb
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ba6a47bdf76bbf4cb276206ac1a8cbf61332fd16"
bgruening
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143 y_true, y_score, pos_label=pos_label or 1) |
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"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ba6a47bdf76bbf4cb276206ac1a8cbf61332fd16"
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144 |
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145 if len(df1.columns) > 1: |
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"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ba6a47bdf76bbf4cb276206ac1a8cbf61332fd16"
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146 precision["micro"], recall["micro"], _ = precision_recall_curve( |
fe47a06943fb
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ba6a47bdf76bbf4cb276206ac1a8cbf61332fd16"
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147 df1.values.ravel(), df2.values.ravel(), pos_label=pos_label) |
fe47a06943fb
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ba6a47bdf76bbf4cb276206ac1a8cbf61332fd16"
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148 ap['micro'] = average_precision_score( |
22
c2cd3219543a
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 02087ce2966cf8b4aac9197a41171e7f986c11d1-dirty"
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149 df1.values, df2.values, average='micro', |
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"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 02087ce2966cf8b4aac9197a41171e7f986c11d1-dirty"
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150 pos_label=pos_label or 1) |
21
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151 |
fe47a06943fb
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152 data = [] |
fe47a06943fb
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153 for key in precision.keys(): |
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154 trace = go.Scatter( |
fe47a06943fb
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ba6a47bdf76bbf4cb276206ac1a8cbf61332fd16"
bgruening
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155 x=recall[key], |
fe47a06943fb
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156 y=precision[key], |
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157 mode='lines', |
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158 name='%s (area = %.2f)' % (key, ap[key]) if key == 'micro' |
fe47a06943fb
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ba6a47bdf76bbf4cb276206ac1a8cbf61332fd16"
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159 else 'column %s (area = %.2f)' % (key, ap[key]) |
fe47a06943fb
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ba6a47bdf76bbf4cb276206ac1a8cbf61332fd16"
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160 ) |
fe47a06943fb
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ba6a47bdf76bbf4cb276206ac1a8cbf61332fd16"
bgruening
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161 data.append(trace) |
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162 |
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"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ba6a47bdf76bbf4cb276206ac1a8cbf61332fd16"
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163 layout = go.Layout( |
fe47a06943fb
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164 title=title or "Precision-Recall curve", |
fe47a06943fb
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ba6a47bdf76bbf4cb276206ac1a8cbf61332fd16"
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165 xaxis=dict(title='Recall'), |
fe47a06943fb
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ba6a47bdf76bbf4cb276206ac1a8cbf61332fd16"
bgruening
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166 yaxis=dict(title='Precision') |
fe47a06943fb
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ba6a47bdf76bbf4cb276206ac1a8cbf61332fd16"
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167 ) |
fe47a06943fb
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ba6a47bdf76bbf4cb276206ac1a8cbf61332fd16"
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168 |
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169 fig = go.Figure(data=data, layout=layout) |
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170 |
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171 elif plot_type == 'roc_curve': |
fe47a06943fb
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ba6a47bdf76bbf4cb276206ac1a8cbf61332fd16"
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172 df1 = pd.read_csv(infile1, sep='\t', header=None) |
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173 df2 = pd.read_csv(infile2, sep='\t', header=None) |
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174 |
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175 fpr = {} |
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176 tpr = {} |
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177 roc_auc = {} |
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178 |
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179 pos_label = params['plotting_selection']['pos_label'].strip() \ |
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180 or None |
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181 for col in df1.columns: |
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182 y_true = df1[col].values |
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183 y_score = df2[col].values |
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184 |
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185 fpr[col], tpr[col], _ = roc_curve( |
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186 y_true, y_score, pos_label=pos_label) |
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187 roc_auc[col] = auc(fpr[col], tpr[col]) |
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188 |
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189 if len(df1.columns) > 1: |
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190 fpr["micro"], tpr["micro"], _ = roc_curve( |
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191 df1.values.ravel(), df2.values.ravel(), pos_label=pos_label) |
fe47a06943fb
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192 roc_auc['micro'] = auc(fpr["micro"], tpr["micro"]) |
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193 |
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194 data = [] |
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195 for key in fpr.keys(): |
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196 trace = go.Scatter( |
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197 x=fpr[key], |
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198 y=tpr[key], |
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199 mode='lines', |
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200 name='%s (area = %.2f)' % (key, roc_auc[key]) if key == 'micro' |
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201 else 'column %s (area = %.2f)' % (key, roc_auc[key]) |
fe47a06943fb
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202 ) |
fe47a06943fb
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203 data.append(trace) |
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204 |
22
c2cd3219543a
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 02087ce2966cf8b4aac9197a41171e7f986c11d1-dirty"
bgruening
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21
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205 trace = go.Scatter(x=[0, 1], y=[0, 1], |
21
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206 mode='lines', |
fe47a06943fb
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207 line=dict(color='black', dash='dash'), |
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208 showlegend=False) |
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209 data.append(trace) |
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210 |
fe47a06943fb
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211 layout = go.Layout( |
fe47a06943fb
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212 title=title or "Receiver operating characteristic curve", |
fe47a06943fb
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213 xaxis=dict(title='False Positive Rate'), |
fe47a06943fb
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214 yaxis=dict(title='True Positive Rate') |
fe47a06943fb
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215 ) |
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216 |
fe47a06943fb
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217 fig = go.Figure(data=data, layout=layout) |
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218 |
fe47a06943fb
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219 elif plot_type == 'rfecv_gridscores': |
fe47a06943fb
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220 input_df = pd.read_csv(infile1, sep='\t', header='infer') |
fe47a06943fb
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ba6a47bdf76bbf4cb276206ac1a8cbf61332fd16"
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221 scores = input_df.iloc[:, 0] |
fe47a06943fb
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ba6a47bdf76bbf4cb276206ac1a8cbf61332fd16"
bgruening
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222 steps = params['plotting_selection']['steps'].strip() |
fe47a06943fb
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ba6a47bdf76bbf4cb276206ac1a8cbf61332fd16"
bgruening
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223 steps = safe_eval(steps) |
fe47a06943fb
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224 |
fe47a06943fb
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225 data = go.Scatter( |
fe47a06943fb
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226 x=list(range(len(scores))), |
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227 y=scores, |
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228 text=[str(_) for _ in steps] if steps else None, |
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"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ba6a47bdf76bbf4cb276206ac1a8cbf61332fd16"
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229 mode='lines' |
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230 ) |
fe47a06943fb
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ba6a47bdf76bbf4cb276206ac1a8cbf61332fd16"
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231 layout = go.Layout( |
fe47a06943fb
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232 xaxis=dict(title="Number of features selected"), |
fe47a06943fb
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233 yaxis=dict(title="Cross validation score"), |
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234 title=title or None |
fe47a06943fb
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235 ) |
fe47a06943fb
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236 |
fe47a06943fb
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237 fig = go.Figure(data=[data], layout=layout) |
fe47a06943fb
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238 |
fe47a06943fb
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239 elif plot_type == 'learning_curve': |
fe47a06943fb
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ba6a47bdf76bbf4cb276206ac1a8cbf61332fd16"
bgruening
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240 input_df = pd.read_csv(infile1, sep='\t', header='infer') |
fe47a06943fb
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ba6a47bdf76bbf4cb276206ac1a8cbf61332fd16"
bgruening
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241 plot_std_err = params['plotting_selection']['plot_std_err'] |
fe47a06943fb
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ba6a47bdf76bbf4cb276206ac1a8cbf61332fd16"
bgruening
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242 data1 = go.Scatter( |
fe47a06943fb
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ba6a47bdf76bbf4cb276206ac1a8cbf61332fd16"
bgruening
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243 x=input_df['train_sizes_abs'], |
fe47a06943fb
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ba6a47bdf76bbf4cb276206ac1a8cbf61332fd16"
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244 y=input_df['mean_train_scores'], |
fe47a06943fb
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ba6a47bdf76bbf4cb276206ac1a8cbf61332fd16"
bgruening
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245 error_y=dict( |
fe47a06943fb
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246 array=input_df['std_train_scores'] |
fe47a06943fb
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ba6a47bdf76bbf4cb276206ac1a8cbf61332fd16"
bgruening
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247 ) if plot_std_err else None, |
fe47a06943fb
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ba6a47bdf76bbf4cb276206ac1a8cbf61332fd16"
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248 mode='lines', |
fe47a06943fb
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bgruening
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249 name="Train Scores", |
fe47a06943fb
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bgruening
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250 ) |
fe47a06943fb
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ba6a47bdf76bbf4cb276206ac1a8cbf61332fd16"
bgruening
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251 data2 = go.Scatter( |
fe47a06943fb
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ba6a47bdf76bbf4cb276206ac1a8cbf61332fd16"
bgruening
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252 x=input_df['train_sizes_abs'], |
fe47a06943fb
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ba6a47bdf76bbf4cb276206ac1a8cbf61332fd16"
bgruening
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253 y=input_df['mean_test_scores'], |
fe47a06943fb
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ba6a47bdf76bbf4cb276206ac1a8cbf61332fd16"
bgruening
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254 error_y=dict( |
fe47a06943fb
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ba6a47bdf76bbf4cb276206ac1a8cbf61332fd16"
bgruening
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255 array=input_df['std_test_scores'] |
fe47a06943fb
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ba6a47bdf76bbf4cb276206ac1a8cbf61332fd16"
bgruening
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256 ) if plot_std_err else None, |
fe47a06943fb
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ba6a47bdf76bbf4cb276206ac1a8cbf61332fd16"
bgruening
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257 mode='lines', |
fe47a06943fb
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ba6a47bdf76bbf4cb276206ac1a8cbf61332fd16"
bgruening
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258 name="Test Scores", |
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259 ) |
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260 layout = dict( |
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261 xaxis=dict( |
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262 title='No. of samples' |
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263 ), |
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264 yaxis=dict( |
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265 title='Performance Score' |
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266 ), |
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267 title=title or 'Learning Curve' |
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268 ) |
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269 fig = go.Figure(data=[data1, data2], layout=layout) |
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270 |
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271 elif plot_type == 'keras_plot_model': |
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272 with open(model_config, 'r') as f: |
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273 model_str = f.read() |
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274 model = model_from_json(model_str) |
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275 plot_model(model, to_file="output.png") |
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276 __import__('os').rename('output.png', 'output') |
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277 |
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278 return 0 |
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279 |
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280 plotly.offline.plot(fig, filename="output.html", |
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281 auto_open=False) |
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282 # to be discovered by `from_work_dir` |
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283 __import__('os').rename('output.html', 'output') |
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284 |
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285 |
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286 if __name__ == '__main__': |
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287 aparser = argparse.ArgumentParser() |
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288 aparser.add_argument("-i", "--inputs", dest="inputs", required=True) |
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289 aparser.add_argument("-e", "--estimator", dest="infile_estimator") |
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290 aparser.add_argument("-X", "--infile1", dest="infile1") |
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291 aparser.add_argument("-y", "--infile2", dest="infile2") |
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292 aparser.add_argument("-O", "--outfile_result", dest="outfile_result") |
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293 aparser.add_argument("-o", "--outfile_object", dest="outfile_object") |
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294 aparser.add_argument("-g", "--groups", dest="groups") |
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295 aparser.add_argument("-r", "--ref_seq", dest="ref_seq") |
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296 aparser.add_argument("-b", "--intervals", dest="intervals") |
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297 aparser.add_argument("-t", "--targets", dest="targets") |
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298 aparser.add_argument("-f", "--fasta_path", dest="fasta_path") |
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299 aparser.add_argument("-c", "--model_config", dest="model_config") |
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300 args = aparser.parse_args() |
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301 |
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302 main(args.inputs, args.infile_estimator, args.infile1, args.infile2, |
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303 args.outfile_result, outfile_object=args.outfile_object, |
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304 groups=args.groups, ref_seq=args.ref_seq, intervals=args.intervals, |
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305 targets=args.targets, fasta_path=args.fasta_path, |
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306 model_config=args.model_config) |