Mercurial > repos > bgruening > keras_model_config

annotate ml_visualization_ex.py @ 2:bedbda03c573 draft

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"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 02087ce2966cf8b4aac9197a41171e7f986c11d1-dirty"
author bgruening
date Wed, 02 Oct 2019 03:53:02 -0400
parents 0fd7d8e90e2a
children c3813c64d678
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1 import argparse
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2 import json
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3 import numpy as np
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4 import pandas as pd
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5 import plotly
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6 import plotly.graph_objs as go
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7 import warnings
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8
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9 from keras.models import model_from_json
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10 from keras.utils import plot_model
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11 from sklearn.feature_selection.base import SelectorMixin
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12 from sklearn.metrics import precision_recall_curve, average_precision_score
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13 from sklearn.metrics import roc_curve, auc
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14 from sklearn.pipeline import Pipeline
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15 from galaxy_ml.utils import load_model, read_columns, SafeEval
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18 safe_eval = SafeEval()
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21 def main(inputs, infile_estimator=None, infile1=None,
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22 infile2=None, outfile_result=None,
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23 outfile_object=None, groups=None,
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24 ref_seq=None, intervals=None,
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25 targets=None, fasta_path=None,
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26 model_config=None):
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27 """
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28 Parameter
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29 ---------
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30 inputs : str
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31 File path to galaxy tool parameter
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32
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33 infile_estimator : str, default is None
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34 File path to estimator
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35
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36 infile1 : str, default is None
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37 File path to dataset containing features or true labels.
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38
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39 infile2 : str, default is None
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40 File path to dataset containing target values or predicted
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41 probabilities.
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42
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43 outfile_result : str, default is None
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44 File path to save the results, either cv_results or test result
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45
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46 outfile_object : str, default is None
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47 File path to save searchCV object
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48
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49 groups : str, default is None
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50 File path to dataset containing groups labels
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51
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52 ref_seq : str, default is None
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53 File path to dataset containing genome sequence file
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54
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55 intervals : str, default is None
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56 File path to dataset containing interval file
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57
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58 targets : str, default is None
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59 File path to dataset compressed target bed file
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61 fasta_path : str, default is None
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62 File path to dataset containing fasta file
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63
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64 model_config : str, default is None
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65 File path to dataset containing JSON config for neural networks
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66 """
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67 warnings.simplefilter('ignore')
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68
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69 with open(inputs, 'r') as param_handler:
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70 params = json.load(param_handler)
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71
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72 title = params['plotting_selection']['title'].strip()
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73 plot_type = params['plotting_selection']['plot_type']
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74 if plot_type == 'feature_importances':
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75 with open(infile_estimator, 'rb') as estimator_handler:
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76 estimator = load_model(estimator_handler)
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77
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78 column_option = (params['plotting_selection']
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79 ['column_selector_options']
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80 ['selected_column_selector_option'])
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81 if column_option in ['by_index_number', 'all_but_by_index_number',
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82 'by_header_name', 'all_but_by_header_name']:
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83 c = (params['plotting_selection']
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84 ['column_selector_options']['col1'])
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85 else:
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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,
0fd7d8e90e2a "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ba6a47bdf76bbf4cb276206ac1a8cbf61332fd16"
bgruening
parents:
diff changeset
90 return_df=True,
0fd7d8e90e2a "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ba6a47bdf76bbf4cb276206ac1a8cbf61332fd16"
bgruening
parents:
diff changeset
91 sep='\t', header='infer',
0fd7d8e90e2a "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ba6a47bdf76bbf4cb276206ac1a8cbf61332fd16"
bgruening
parents:
diff changeset
92 parse_dates=True)
0fd7d8e90e2a "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ba6a47bdf76bbf4cb276206ac1a8cbf61332fd16"
bgruening
parents:
diff changeset
93
0fd7d8e90e2a "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ba6a47bdf76bbf4cb276206ac1a8cbf61332fd16"
bgruening
parents:
diff changeset
94 feature_names = input_df.columns.values
0fd7d8e90e2a "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ba6a47bdf76bbf4cb276206ac1a8cbf61332fd16"
bgruening
parents:
diff changeset
95
0fd7d8e90e2a "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ba6a47bdf76bbf4cb276206ac1a8cbf61332fd16"
bgruening
parents:
diff changeset
96 if isinstance(estimator, Pipeline):
0fd7d8e90e2a "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ba6a47bdf76bbf4cb276206ac1a8cbf61332fd16"
bgruening
parents:
diff changeset
97 for st in estimator.steps[:-1]:
0fd7d8e90e2a "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ba6a47bdf76bbf4cb276206ac1a8cbf61332fd16"
bgruening
parents:
diff changeset
98 if isinstance(st[-1], SelectorMixin):
0fd7d8e90e2a "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ba6a47bdf76bbf4cb276206ac1a8cbf61332fd16"
bgruening
parents:
diff changeset
99 mask = st[-1].get_support()
0fd7d8e90e2a "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ba6a47bdf76bbf4cb276206ac1a8cbf61332fd16"
bgruening
parents:
diff changeset
100 feature_names = feature_names[mask]
0fd7d8e90e2a "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ba6a47bdf76bbf4cb276206ac1a8cbf61332fd16"
bgruening
parents:
diff changeset
101 estimator = estimator.steps[-1][-1]
0fd7d8e90e2a "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ba6a47bdf76bbf4cb276206ac1a8cbf61332fd16"
bgruening
parents:
diff changeset
102
0fd7d8e90e2a "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ba6a47bdf76bbf4cb276206ac1a8cbf61332fd16"
bgruening
parents:
diff changeset
103 if hasattr(estimator, 'coef_'):
0fd7d8e90e2a "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ba6a47bdf76bbf4cb276206ac1a8cbf61332fd16"
bgruening
parents:
diff changeset
104 coefs = estimator.coef_
0fd7d8e90e2a "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ba6a47bdf76bbf4cb276206ac1a8cbf61332fd16"
bgruening
parents:
diff changeset
105 else:
0fd7d8e90e2a "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ba6a47bdf76bbf4cb276206ac1a8cbf61332fd16"
bgruening
parents:
diff changeset
106 coefs = getattr(estimator, 'feature_importances_', None)
0fd7d8e90e2a "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ba6a47bdf76bbf4cb276206ac1a8cbf61332fd16"
bgruening
parents:
diff changeset
107 if coefs is None:
0fd7d8e90e2a "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ba6a47bdf76bbf4cb276206ac1a8cbf61332fd16"
bgruening
parents:
diff changeset
108 raise RuntimeError('The classifier does not expose '
0fd7d8e90e2a "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ba6a47bdf76bbf4cb276206ac1a8cbf61332fd16"
bgruening
parents:
diff changeset
109 '"coef_" or "feature_importances_" '
0fd7d8e90e2a "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ba6a47bdf76bbf4cb276206ac1a8cbf61332fd16"
bgruening
parents:
diff changeset
110 'attributes')
0fd7d8e90e2a "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ba6a47bdf76bbf4cb276206ac1a8cbf61332fd16"
bgruening
parents:
diff changeset
111
0fd7d8e90e2a "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ba6a47bdf76bbf4cb276206ac1a8cbf61332fd16"
bgruening
parents:
diff changeset
112 threshold = params['plotting_selection']['threshold']
0fd7d8e90e2a "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ba6a47bdf76bbf4cb276206ac1a8cbf61332fd16"
bgruening
parents:
diff changeset
113 if threshold is not None:
0fd7d8e90e2a "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ba6a47bdf76bbf4cb276206ac1a8cbf61332fd16"
bgruening
parents:
diff changeset
114 mask = (coefs > threshold) | (coefs < -threshold)
0fd7d8e90e2a "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ba6a47bdf76bbf4cb276206ac1a8cbf61332fd16"
bgruening
parents:
diff changeset
115 coefs = coefs[mask]
0fd7d8e90e2a "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ba6a47bdf76bbf4cb276206ac1a8cbf61332fd16"
bgruening
parents:
diff changeset
116 feature_names = feature_names[mask]
0fd7d8e90e2a "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ba6a47bdf76bbf4cb276206ac1a8cbf61332fd16"
bgruening
parents:
diff changeset
117
0fd7d8e90e2a "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ba6a47bdf76bbf4cb276206ac1a8cbf61332fd16"
bgruening
parents:
diff changeset
118 # sort
0fd7d8e90e2a "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ba6a47bdf76bbf4cb276206ac1a8cbf61332fd16"
bgruening
parents:
diff changeset
119 indices = np.argsort(coefs)[::-1]
0fd7d8e90e2a "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ba6a47bdf76bbf4cb276206ac1a8cbf61332fd16"
bgruening
parents:
diff changeset
120
0fd7d8e90e2a "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ba6a47bdf76bbf4cb276206ac1a8cbf61332fd16"
bgruening
parents:
diff changeset
121 trace = go.Bar(x=feature_names[indices],
0fd7d8e90e2a "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ba6a47bdf76bbf4cb276206ac1a8cbf61332fd16"
bgruening
parents:
diff changeset
122 y=coefs[indices])
0fd7d8e90e2a "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ba6a47bdf76bbf4cb276206ac1a8cbf61332fd16"
bgruening
parents:
diff changeset
123 layout = go.Layout(title=title or "Feature Importances")
0fd7d8e90e2a "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ba6a47bdf76bbf4cb276206ac1a8cbf61332fd16"
bgruening
parents:
diff changeset
124 fig = go.Figure(data=[trace], layout=layout)
0fd7d8e90e2a "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ba6a47bdf76bbf4cb276206ac1a8cbf61332fd16"
bgruening
parents:
diff changeset
125
0fd7d8e90e2a "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ba6a47bdf76bbf4cb276206ac1a8cbf61332fd16"
bgruening
parents:
diff changeset
126 elif plot_type == 'pr_curve':
0fd7d8e90e2a "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ba6a47bdf76bbf4cb276206ac1a8cbf61332fd16"
bgruening
parents:
diff changeset
127 df1 = pd.read_csv(infile1, sep='\t', header=None)
0fd7d8e90e2a "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ba6a47bdf76bbf4cb276206ac1a8cbf61332fd16"
bgruening
parents:
diff changeset
128 df2 = pd.read_csv(infile2, sep='\t', header=None)
0fd7d8e90e2a "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ba6a47bdf76bbf4cb276206ac1a8cbf61332fd16"
bgruening
parents:
diff changeset
129
0fd7d8e90e2a "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ba6a47bdf76bbf4cb276206ac1a8cbf61332fd16"
bgruening
parents:
diff changeset
130 precision = {}
0fd7d8e90e2a "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ba6a47bdf76bbf4cb276206ac1a8cbf61332fd16"
bgruening
parents:
diff changeset
131 recall = {}
0fd7d8e90e2a "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ba6a47bdf76bbf4cb276206ac1a8cbf61332fd16"
bgruening
parents:
diff changeset
132 ap = {}
0fd7d8e90e2a "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ba6a47bdf76bbf4cb276206ac1a8cbf61332fd16"
bgruening
parents:
diff changeset
133
0fd7d8e90e2a "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ba6a47bdf76bbf4cb276206ac1a8cbf61332fd16"
bgruening
parents:
diff changeset
134 pos_label = params['plotting_selection']['pos_label'].strip() \
0fd7d8e90e2a "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ba6a47bdf76bbf4cb276206ac1a8cbf61332fd16"
bgruening
parents:
diff changeset
135 or None
0fd7d8e90e2a "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ba6a47bdf76bbf4cb276206ac1a8cbf61332fd16"
bgruening
parents:
diff changeset
136 for col in df1.columns:
0fd7d8e90e2a "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ba6a47bdf76bbf4cb276206ac1a8cbf61332fd16"
bgruening
parents:
diff changeset
137 y_true = df1[col].values
0fd7d8e90e2a "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ba6a47bdf76bbf4cb276206ac1a8cbf61332fd16"
bgruening
parents:
diff changeset
138 y_score = df2[col].values
0fd7d8e90e2a "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ba6a47bdf76bbf4cb276206ac1a8cbf61332fd16"
bgruening
parents:
diff changeset
139
0fd7d8e90e2a "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ba6a47bdf76bbf4cb276206ac1a8cbf61332fd16"
bgruening
parents:
diff changeset
140 precision[col], recall[col], _ = precision_recall_curve(
0fd7d8e90e2a "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ba6a47bdf76bbf4cb276206ac1a8cbf61332fd16"
bgruening
parents:
diff changeset
141 y_true, y_score, pos_label=pos_label)
0fd7d8e90e2a "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ba6a47bdf76bbf4cb276206ac1a8cbf61332fd16"
bgruening
parents:
diff changeset
142 ap[col] = average_precision_score(
0fd7d8e90e2a "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ba6a47bdf76bbf4cb276206ac1a8cbf61332fd16"
bgruening
parents:
diff changeset
143 y_true, y_score, pos_label=pos_label or 1)
0fd7d8e90e2a "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ba6a47bdf76bbf4cb276206ac1a8cbf61332fd16"
bgruening
parents:
diff changeset
144
0fd7d8e90e2a "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ba6a47bdf76bbf4cb276206ac1a8cbf61332fd16"
bgruening
parents:
diff changeset
145 if len(df1.columns) > 1:
0fd7d8e90e2a "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ba6a47bdf76bbf4cb276206ac1a8cbf61332fd16"
bgruening
parents:
diff changeset
146 precision["micro"], recall["micro"], _ = precision_recall_curve(
0fd7d8e90e2a "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ba6a47bdf76bbf4cb276206ac1a8cbf61332fd16"
bgruening
parents:
diff changeset
147 df1.values.ravel(), df2.values.ravel(), pos_label=pos_label)
0fd7d8e90e2a "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ba6a47bdf76bbf4cb276206ac1a8cbf61332fd16"
bgruening
parents:
diff changeset
148 ap['micro'] = average_precision_score(
2
bedbda03c573 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 02087ce2966cf8b4aac9197a41171e7f986c11d1-dirty"
bgruening
parents: 1
diff changeset
149 df1.values, df2.values, average='micro',
bedbda03c573 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 02087ce2966cf8b4aac9197a41171e7f986c11d1-dirty"
bgruening
parents: 1
diff changeset
150 pos_label=pos_label or 1)
1
0fd7d8e90e2a "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ba6a47bdf76bbf4cb276206ac1a8cbf61332fd16"
bgruening
parents:
diff changeset
151
0fd7d8e90e2a "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ba6a47bdf76bbf4cb276206ac1a8cbf61332fd16"
bgruening
parents:
diff changeset
152 data = []
0fd7d8e90e2a "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ba6a47bdf76bbf4cb276206ac1a8cbf61332fd16"
bgruening
parents:
diff changeset
153 for key in precision.keys():
0fd7d8e90e2a "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ba6a47bdf76bbf4cb276206ac1a8cbf61332fd16"
bgruening
parents:
diff changeset
154 trace = go.Scatter(
0fd7d8e90e2a "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ba6a47bdf76bbf4cb276206ac1a8cbf61332fd16"
bgruening
parents:
diff changeset
155 x=recall[key],
0fd7d8e90e2a "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ba6a47bdf76bbf4cb276206ac1a8cbf61332fd16"
bgruening
parents:
diff changeset
156 y=precision[key],
0fd7d8e90e2a "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ba6a47bdf76bbf4cb276206ac1a8cbf61332fd16"
bgruening
parents:
diff changeset
157 mode='lines',
0fd7d8e90e2a "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ba6a47bdf76bbf4cb276206ac1a8cbf61332fd16"
bgruening
parents:
diff changeset
158 name='%s (area = %.2f)' % (key, ap[key]) if key == 'micro'
0fd7d8e90e2a "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ba6a47bdf76bbf4cb276206ac1a8cbf61332fd16"
bgruening
parents:
diff changeset
159 else 'column %s (area = %.2f)' % (key, ap[key])
0fd7d8e90e2a "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ba6a47bdf76bbf4cb276206ac1a8cbf61332fd16"
bgruening
parents:
diff changeset
160 )
0fd7d8e90e2a "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ba6a47bdf76bbf4cb276206ac1a8cbf61332fd16"
bgruening
parents:
diff changeset
161 data.append(trace)
0fd7d8e90e2a "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ba6a47bdf76bbf4cb276206ac1a8cbf61332fd16"
bgruening
parents:
diff changeset
162
0fd7d8e90e2a "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ba6a47bdf76bbf4cb276206ac1a8cbf61332fd16"
bgruening
parents:
diff changeset
163 layout = go.Layout(
0fd7d8e90e2a "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ba6a47bdf76bbf4cb276206ac1a8cbf61332fd16"
bgruening
parents:
diff changeset
164 title=title or "Precision-Recall curve",
0fd7d8e90e2a "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ba6a47bdf76bbf4cb276206ac1a8cbf61332fd16"
bgruening
parents:
diff changeset
165 xaxis=dict(title='Recall'),
0fd7d8e90e2a "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ba6a47bdf76bbf4cb276206ac1a8cbf61332fd16"
bgruening
parents:
diff changeset
166 yaxis=dict(title='Precision')
0fd7d8e90e2a "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ba6a47bdf76bbf4cb276206ac1a8cbf61332fd16"
bgruening
parents:
diff changeset
167 )
0fd7d8e90e2a "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ba6a47bdf76bbf4cb276206ac1a8cbf61332fd16"
bgruening
parents:
diff changeset
168
0fd7d8e90e2a "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ba6a47bdf76bbf4cb276206ac1a8cbf61332fd16"
bgruening
parents:
diff changeset
169 fig = go.Figure(data=data, layout=layout)
0fd7d8e90e2a "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ba6a47bdf76bbf4cb276206ac1a8cbf61332fd16"
bgruening
parents:
diff changeset
170
0fd7d8e90e2a "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ba6a47bdf76bbf4cb276206ac1a8cbf61332fd16"
bgruening
parents:
diff changeset
171 elif plot_type == 'roc_curve':
0fd7d8e90e2a "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ba6a47bdf76bbf4cb276206ac1a8cbf61332fd16"
bgruening
parents:
diff changeset
172 df1 = pd.read_csv(infile1, sep='\t', header=None)
0fd7d8e90e2a "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ba6a47bdf76bbf4cb276206ac1a8cbf61332fd16"
bgruening
parents:
diff changeset
173 df2 = pd.read_csv(infile2, sep='\t', header=None)
0fd7d8e90e2a "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ba6a47bdf76bbf4cb276206ac1a8cbf61332fd16"
bgruening
parents:
diff changeset
174
0fd7d8e90e2a "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ba6a47bdf76bbf4cb276206ac1a8cbf61332fd16"
bgruening
parents:
diff changeset
175 fpr = {}
0fd7d8e90e2a "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ba6a47bdf76bbf4cb276206ac1a8cbf61332fd16"
bgruening
parents:
diff changeset
176 tpr = {}
0fd7d8e90e2a "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ba6a47bdf76bbf4cb276206ac1a8cbf61332fd16"
bgruening
parents:
diff changeset
177 roc_auc = {}
0fd7d8e90e2a "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ba6a47bdf76bbf4cb276206ac1a8cbf61332fd16"
bgruening
parents:
diff changeset
178
0fd7d8e90e2a "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ba6a47bdf76bbf4cb276206ac1a8cbf61332fd16"
bgruening
parents:
diff changeset
179 pos_label = params['plotting_selection']['pos_label'].strip() \
0fd7d8e90e2a "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ba6a47bdf76bbf4cb276206ac1a8cbf61332fd16"
bgruening
parents:
diff changeset
180 or None
0fd7d8e90e2a "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ba6a47bdf76bbf4cb276206ac1a8cbf61332fd16"
bgruening
parents:
diff changeset
181 for col in df1.columns:
0fd7d8e90e2a "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ba6a47bdf76bbf4cb276206ac1a8cbf61332fd16"
bgruening
parents:
diff changeset
182 y_true = df1[col].values
0fd7d8e90e2a "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ba6a47bdf76bbf4cb276206ac1a8cbf61332fd16"
bgruening
parents:
diff changeset
183 y_score = df2[col].values
0fd7d8e90e2a "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ba6a47bdf76bbf4cb276206ac1a8cbf61332fd16"
bgruening
parents:
diff changeset
184
0fd7d8e90e2a "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ba6a47bdf76bbf4cb276206ac1a8cbf61332fd16"
bgruening
parents:
diff changeset
185 fpr[col], tpr[col], _ = roc_curve(
0fd7d8e90e2a "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ba6a47bdf76bbf4cb276206ac1a8cbf61332fd16"
bgruening
parents:
diff changeset
186 y_true, y_score, pos_label=pos_label)
0fd7d8e90e2a "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ba6a47bdf76bbf4cb276206ac1a8cbf61332fd16"
bgruening
parents:
diff changeset
187 roc_auc[col] = auc(fpr[col], tpr[col])
0fd7d8e90e2a "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ba6a47bdf76bbf4cb276206ac1a8cbf61332fd16"
bgruening
parents:
diff changeset
188
0fd7d8e90e2a "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ba6a47bdf76bbf4cb276206ac1a8cbf61332fd16"
bgruening
parents:
diff changeset
189 if len(df1.columns) > 1:
0fd7d8e90e2a "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ba6a47bdf76bbf4cb276206ac1a8cbf61332fd16"
bgruening
parents:
diff changeset
190 fpr["micro"], tpr["micro"], _ = roc_curve(
0fd7d8e90e2a "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ba6a47bdf76bbf4cb276206ac1a8cbf61332fd16"
bgruening
parents:
diff changeset
191 df1.values.ravel(), df2.values.ravel(), pos_label=pos_label)
0fd7d8e90e2a "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ba6a47bdf76bbf4cb276206ac1a8cbf61332fd16"
bgruening
parents:
diff changeset
192 roc_auc['micro'] = auc(fpr["micro"], tpr["micro"])
0fd7d8e90e2a "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ba6a47bdf76bbf4cb276206ac1a8cbf61332fd16"
bgruening
parents:
diff changeset
193
0fd7d8e90e2a "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ba6a47bdf76bbf4cb276206ac1a8cbf61332fd16"
bgruening
parents:
diff changeset
194 data = []
0fd7d8e90e2a "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ba6a47bdf76bbf4cb276206ac1a8cbf61332fd16"
bgruening
parents:
diff changeset
195 for key in fpr.keys():
0fd7d8e90e2a "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ba6a47bdf76bbf4cb276206ac1a8cbf61332fd16"
bgruening
parents:
diff changeset
196 trace = go.Scatter(
0fd7d8e90e2a "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ba6a47bdf76bbf4cb276206ac1a8cbf61332fd16"
bgruening
parents:
diff changeset
197 x=fpr[key],
0fd7d8e90e2a "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ba6a47bdf76bbf4cb276206ac1a8cbf61332fd16"
bgruening
parents:
diff changeset
198 y=tpr[key],
0fd7d8e90e2a "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ba6a47bdf76bbf4cb276206ac1a8cbf61332fd16"
bgruening
parents:
diff changeset
199 mode='lines',
0fd7d8e90e2a "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ba6a47bdf76bbf4cb276206ac1a8cbf61332fd16"
bgruening
parents:
diff changeset
200 name='%s (area = %.2f)' % (key, roc_auc[key]) if key == 'micro'
0fd7d8e90e2a "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ba6a47bdf76bbf4cb276206ac1a8cbf61332fd16"
bgruening
parents:
diff changeset
201 else 'column %s (area = %.2f)' % (key, roc_auc[key])
0fd7d8e90e2a "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ba6a47bdf76bbf4cb276206ac1a8cbf61332fd16"
bgruening
parents:
diff changeset
202 )
0fd7d8e90e2a "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ba6a47bdf76bbf4cb276206ac1a8cbf61332fd16"
bgruening
parents:
diff changeset
203 data.append(trace)
0fd7d8e90e2a "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ba6a47bdf76bbf4cb276206ac1a8cbf61332fd16"
bgruening
parents:
diff changeset
204
2
bedbda03c573 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 02087ce2966cf8b4aac9197a41171e7f986c11d1-dirty"
bgruening
parents: 1
diff changeset
205 trace = go.Scatter(x=[0, 1], y=[0, 1],
1
0fd7d8e90e2a "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ba6a47bdf76bbf4cb276206ac1a8cbf61332fd16"
bgruening
parents:
diff changeset
206 mode='lines',
0fd7d8e90e2a "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ba6a47bdf76bbf4cb276206ac1a8cbf61332fd16"
bgruening
parents:
diff changeset
207 line=dict(color='black', dash='dash'),
0fd7d8e90e2a "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ba6a47bdf76bbf4cb276206ac1a8cbf61332fd16"
bgruening
parents:
diff changeset
208 showlegend=False)
0fd7d8e90e2a "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ba6a47bdf76bbf4cb276206ac1a8cbf61332fd16"
bgruening
parents:
diff changeset
209 data.append(trace)
0fd7d8e90e2a "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ba6a47bdf76bbf4cb276206ac1a8cbf61332fd16"
bgruening
parents:
diff changeset
210
0fd7d8e90e2a "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ba6a47bdf76bbf4cb276206ac1a8cbf61332fd16"
bgruening
parents:
diff changeset
211 layout = go.Layout(
0fd7d8e90e2a "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ba6a47bdf76bbf4cb276206ac1a8cbf61332fd16"
bgruening
parents:
diff changeset
212 title=title or "Receiver operating characteristic curve",
0fd7d8e90e2a "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ba6a47bdf76bbf4cb276206ac1a8cbf61332fd16"
bgruening
parents:
diff changeset
213 xaxis=dict(title='False Positive Rate'),
0fd7d8e90e2a "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ba6a47bdf76bbf4cb276206ac1a8cbf61332fd16"
bgruening
parents:
diff changeset
214 yaxis=dict(title='True Positive Rate')
0fd7d8e90e2a "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ba6a47bdf76bbf4cb276206ac1a8cbf61332fd16"
bgruening
parents:
diff changeset
215 )
0fd7d8e90e2a "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ba6a47bdf76bbf4cb276206ac1a8cbf61332fd16"
bgruening
parents:
diff changeset
216
0fd7d8e90e2a "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ba6a47bdf76bbf4cb276206ac1a8cbf61332fd16"
bgruening
parents:
diff changeset
217 fig = go.Figure(data=data, layout=layout)
0fd7d8e90e2a "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ba6a47bdf76bbf4cb276206ac1a8cbf61332fd16"
bgruening
parents:
diff changeset
218
0fd7d8e90e2a "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ba6a47bdf76bbf4cb276206ac1a8cbf61332fd16"
bgruening
parents:
diff changeset
219 elif plot_type == 'rfecv_gridscores':
0fd7d8e90e2a "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ba6a47bdf76bbf4cb276206ac1a8cbf61332fd16"
bgruening
parents:
diff changeset
220 input_df = pd.read_csv(infile1, sep='\t', header='infer')
0fd7d8e90e2a "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ba6a47bdf76bbf4cb276206ac1a8cbf61332fd16"
bgruening
parents:
diff changeset
221 scores = input_df.iloc[:, 0]
0fd7d8e90e2a "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ba6a47bdf76bbf4cb276206ac1a8cbf61332fd16"
bgruening
parents:
diff changeset
222 steps = params['plotting_selection']['steps'].strip()
0fd7d8e90e2a "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ba6a47bdf76bbf4cb276206ac1a8cbf61332fd16"
bgruening
parents:
diff changeset
223 steps = safe_eval(steps)
0fd7d8e90e2a "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ba6a47bdf76bbf4cb276206ac1a8cbf61332fd16"
bgruening
parents:
diff changeset
224
0fd7d8e90e2a "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ba6a47bdf76bbf4cb276206ac1a8cbf61332fd16"
bgruening
parents:
diff changeset
225 data = go.Scatter(
0fd7d8e90e2a "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ba6a47bdf76bbf4cb276206ac1a8cbf61332fd16"
bgruening
parents:
diff changeset
226 x=list(range(len(scores))),
0fd7d8e90e2a "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ba6a47bdf76bbf4cb276206ac1a8cbf61332fd16"
bgruening
parents:
diff changeset
227 y=scores,
0fd7d8e90e2a "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ba6a47bdf76bbf4cb276206ac1a8cbf61332fd16"
bgruening
parents:
diff changeset
228 text=[str(_) for _ in steps] if steps else None,
0fd7d8e90e2a "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ba6a47bdf76bbf4cb276206ac1a8cbf61332fd16"
bgruening
parents:
diff changeset
229 mode='lines'
0fd7d8e90e2a "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ba6a47bdf76bbf4cb276206ac1a8cbf61332fd16"
bgruening
parents:
diff changeset
230 )
0fd7d8e90e2a "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ba6a47bdf76bbf4cb276206ac1a8cbf61332fd16"
bgruening
parents:
diff changeset
231 layout = go.Layout(
0fd7d8e90e2a "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ba6a47bdf76bbf4cb276206ac1a8cbf61332fd16"
bgruening
parents:
diff changeset
232 xaxis=dict(title="Number of features selected"),
0fd7d8e90e2a "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ba6a47bdf76bbf4cb276206ac1a8cbf61332fd16"
bgruening
parents:
diff changeset
233 yaxis=dict(title="Cross validation score"),
0fd7d8e90e2a "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ba6a47bdf76bbf4cb276206ac1a8cbf61332fd16"
bgruening
parents:
diff changeset
234 title=title or None
0fd7d8e90e2a "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ba6a47bdf76bbf4cb276206ac1a8cbf61332fd16"
bgruening
parents:
diff changeset
235 )
0fd7d8e90e2a "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ba6a47bdf76bbf4cb276206ac1a8cbf61332fd16"
bgruening
parents:
diff changeset
236
0fd7d8e90e2a "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ba6a47bdf76bbf4cb276206ac1a8cbf61332fd16"
bgruening
parents:
diff changeset
237 fig = go.Figure(data=[data], layout=layout)
0fd7d8e90e2a "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ba6a47bdf76bbf4cb276206ac1a8cbf61332fd16"
bgruening
parents:
diff changeset
238
0fd7d8e90e2a "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ba6a47bdf76bbf4cb276206ac1a8cbf61332fd16"
bgruening
parents:
diff changeset
239 elif plot_type == 'learning_curve':
0fd7d8e90e2a "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ba6a47bdf76bbf4cb276206ac1a8cbf61332fd16"
bgruening
parents:
diff changeset
240 input_df = pd.read_csv(infile1, sep='\t', header='infer')
0fd7d8e90e2a "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ba6a47bdf76bbf4cb276206ac1a8cbf61332fd16"
bgruening
parents:
diff changeset
241 plot_std_err = params['plotting_selection']['plot_std_err']
0fd7d8e90e2a "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ba6a47bdf76bbf4cb276206ac1a8cbf61332fd16"
bgruening
parents:
diff changeset
242 data1 = go.Scatter(
0fd7d8e90e2a "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ba6a47bdf76bbf4cb276206ac1a8cbf61332fd16"
bgruening
parents:
diff changeset
243 x=input_df['train_sizes_abs'],
0fd7d8e90e2a "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ba6a47bdf76bbf4cb276206ac1a8cbf61332fd16"
bgruening
parents:
diff changeset
244 y=input_df['mean_train_scores'],
0fd7d8e90e2a "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ba6a47bdf76bbf4cb276206ac1a8cbf61332fd16"
bgruening
parents:
diff changeset
245 error_y=dict(
0fd7d8e90e2a "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ba6a47bdf76bbf4cb276206ac1a8cbf61332fd16"
bgruening
parents:
diff changeset
246 array=input_df['std_train_scores']
0fd7d8e90e2a "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ba6a47bdf76bbf4cb276206ac1a8cbf61332fd16"
bgruening
parents:
diff changeset
247 ) if plot_std_err else None,
0fd7d8e90e2a "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ba6a47bdf76bbf4cb276206ac1a8cbf61332fd16"
bgruening
parents:
diff changeset
248 mode='lines',
0fd7d8e90e2a "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ba6a47bdf76bbf4cb276206ac1a8cbf61332fd16"
bgruening
parents:
diff changeset
249 name="Train Scores",
0fd7d8e90e2a "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ba6a47bdf76bbf4cb276206ac1a8cbf61332fd16"
bgruening
parents:
diff changeset
250 )
0fd7d8e90e2a "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ba6a47bdf76bbf4cb276206ac1a8cbf61332fd16"
bgruening
parents:
diff changeset
251 data2 = go.Scatter(
0fd7d8e90e2a "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ba6a47bdf76bbf4cb276206ac1a8cbf61332fd16"
bgruening
parents:
diff changeset
252 x=input_df['train_sizes_abs'],
0fd7d8e90e2a "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ba6a47bdf76bbf4cb276206ac1a8cbf61332fd16"
bgruening
parents:
diff changeset
253 y=input_df['mean_test_scores'],
0fd7d8e90e2a "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ba6a47bdf76bbf4cb276206ac1a8cbf61332fd16"
bgruening
parents:
diff changeset
254 error_y=dict(
0fd7d8e90e2a "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ba6a47bdf76bbf4cb276206ac1a8cbf61332fd16"
bgruening
parents:
diff changeset
255 array=input_df['std_test_scores']
0fd7d8e90e2a "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ba6a47bdf76bbf4cb276206ac1a8cbf61332fd16"
bgruening
parents:
diff changeset
256 ) if plot_std_err else None,
0fd7d8e90e2a "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ba6a47bdf76bbf4cb276206ac1a8cbf61332fd16"
bgruening
parents:
diff changeset
257 mode='lines',
0fd7d8e90e2a "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ba6a47bdf76bbf4cb276206ac1a8cbf61332fd16"
bgruening
parents:
diff changeset
258 name="Test Scores",
0fd7d8e90e2a "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ba6a47bdf76bbf4cb276206ac1a8cbf61332fd16"
bgruening
parents:
diff changeset
259 )
0fd7d8e90e2a "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ba6a47bdf76bbf4cb276206ac1a8cbf61332fd16"
bgruening
parents:
diff changeset
260 layout = dict(
0fd7d8e90e2a "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ba6a47bdf76bbf4cb276206ac1a8cbf61332fd16"
bgruening
parents:
diff changeset
261 xaxis=dict(
0fd7d8e90e2a "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ba6a47bdf76bbf4cb276206ac1a8cbf61332fd16"
bgruening
parents:
diff changeset
262 title='No. of samples'
0fd7d8e90e2a "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ba6a47bdf76bbf4cb276206ac1a8cbf61332fd16"
bgruening
parents:
diff changeset
263 ),
0fd7d8e90e2a "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ba6a47bdf76bbf4cb276206ac1a8cbf61332fd16"
bgruening
parents:
diff changeset
264 yaxis=dict(
0fd7d8e90e2a "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ba6a47bdf76bbf4cb276206ac1a8cbf61332fd16"
bgruening
parents:
diff changeset
265 title='Performance Score'
0fd7d8e90e2a "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ba6a47bdf76bbf4cb276206ac1a8cbf61332fd16"
bgruening
parents:
diff changeset
266 ),
0fd7d8e90e2a "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ba6a47bdf76bbf4cb276206ac1a8cbf61332fd16"
bgruening
parents:
diff changeset
267 title=title or 'Learning Curve'
0fd7d8e90e2a "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ba6a47bdf76bbf4cb276206ac1a8cbf61332fd16"
bgruening
parents:
diff changeset
268 )
0fd7d8e90e2a "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ba6a47bdf76bbf4cb276206ac1a8cbf61332fd16"
bgruening
parents:
diff changeset
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)