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annotate dashboard.py @ 0:1bc26b9636d2 draft default tip

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planemo upload for repository https://github.com/goeckslab/Galaxy-Pycaret commit 5089a5dffc154c8202624cfbd5f1be0f36a9f0cc
author goeckslab
date Wed, 11 Dec 2024 03:29:00 +0000
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1bc26b9636d2 planemo upload for repository https://github.com/goeckslab/Galaxy-Pycaret commit 5089a5dffc154c8202624cfbd5f1be0f36a9f0cc
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1 import logging
1bc26b9636d2 planemo upload for repository https://github.com/goeckslab/Galaxy-Pycaret commit 5089a5dffc154c8202624cfbd5f1be0f36a9f0cc
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2 from typing import Any, Dict, Optional
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4 from pycaret.utils.generic import get_label_encoder
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6 logging.basicConfig(level=logging.DEBUG)
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7 LOG = logging.getLogger(__name__)
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10 def generate_classifier_explainer_dashboard(
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11 exp,
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12 estimator,
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13 display_format: str = "dash",
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14 dashboard_kwargs: Optional[Dict[str, Any]] = None,
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15 run_kwargs: Optional[Dict[str, Any]] = None,
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16 **kwargs,):
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18 """
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19 This function is changed from pycaret.classification.oop.dashboard()
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21 This function generates the interactive dashboard for a trained model.
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22 The dashboard is implemented using
1bc26b9636d2 planemo upload for repository https://github.com/goeckslab/Galaxy-Pycaret commit 5089a5dffc154c8202624cfbd5f1be0f36a9f0cc
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23 ExplainerDashboard (explainerdashboard.readthedocs.io)
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26 estimator: scikit-learn compatible object
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27 Trained model object
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30 display_format: str, default = 'dash'
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31 Render mode for the dashboard. The default is set to ``dash``
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32 which will
1bc26b9636d2 planemo upload for repository https://github.com/goeckslab/Galaxy-Pycaret commit 5089a5dffc154c8202624cfbd5f1be0f36a9f0cc
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33 render a dashboard in browser. There are four possible options:
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35 - 'dash' - displays the dashboard in browser
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36 - 'inline' - displays the dashboard in the jupyter notebook cell.
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37 - 'jupyterlab' - displays the dashboard in jupyterlab pane.
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38 - 'external' - displays the dashboard in a separate tab.
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39 (use in Colab)
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42 dashboard_kwargs: dict, default = {} (empty dict)
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43 Dictionary of arguments passed to the ``ExplainerDashboard`` class.
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46 run_kwargs: dict, default = {} (empty dict)
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47 Dictionary of arguments passed to the ``run``
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48 method of ``ExplainerDashboard``.
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50
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51 **kwargs:
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52 Additional keyword arguments to pass to the ``ClassifierExplainer``
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53 or ``RegressionExplainer`` class.
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54
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55
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56 Returns:
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57 ExplainerDashboard
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58 """
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60 dashboard_kwargs = dashboard_kwargs or {}
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61 run_kwargs = run_kwargs or {}
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63 from explainerdashboard import ClassifierExplainer, ExplainerDashboard
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64
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65 le = get_label_encoder(exp.pipeline)
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66 if le:
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67 labels_ = list(le.classes_)
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68 else:
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69 labels_ = None
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71 # Replaceing chars which dash doesnt accept for column name `.` , `{`, `}`
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73 X_test_df = exp.X_test_transformed.copy()
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74 LOG.info(X_test_df)
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75 X_test_df.columns = [
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76 col.replace(".", "__").replace("{", "__").replace("}", "__")
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77 for col in X_test_df.columns
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78 ]
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79
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80 explainer = ClassifierExplainer(
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81 estimator, X_test_df, exp.y_test_transformed, labels=labels_, **kwargs
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82 )
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83 return ExplainerDashboard(
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84 explainer, mode=display_format,
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85 contributions=False, whatif=False,
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86 **dashboard_kwargs
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87 )
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88
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89
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90 def generate_regression_explainer_dashboard(
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91 exp,
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92 estimator,
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93 display_format: str = "dash",
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94 dashboard_kwargs: Optional[Dict[str, Any]] = None,
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95 run_kwargs: Optional[Dict[str, Any]] = None,
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96 **kwargs,):
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97
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98 """
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99 This function is changed from pycaret.regression.oop.dashboard()
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100
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101 This function generates the interactive dashboard for a trained model.
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102 The dashboard is implemented using ExplainerDashboard
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103 (explainerdashboard.readthedocs.io)
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104
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105
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106 estimator: scikit-learn compatible object
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107 Trained model object
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108
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109
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110 display_format: str, default = 'dash'
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111 Render mode for the dashboard. The default is set to ``dash``
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112 which will
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113 render a dashboard in browser. There are four possible options:
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114
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115 - 'dash' - displays the dashboard in browser
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116 - 'inline' - displays the dashboard in the jupyter notebook cell.
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117 - 'jupyterlab' - displays the dashboard in jupyterlab pane.
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118 - 'external' - displays the dashboard in a separate tab.
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119 (use in Colab)
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120
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121
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122 dashboard_kwargs: dict, default = {} (empty dict)
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123 Dictionary of arguments passed to the ``ExplainerDashboard`` class.
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124
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125
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126 run_kwargs: dict, default = {} (empty dict)
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127 Dictionary of arguments passed to the ``run`` method
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128 of ``ExplainerDashboard``.
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129
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130
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131 **kwargs:
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132 Additional keyword arguments to pass to the
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133 ``ClassifierExplainer`` or
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134 ``RegressionExplainer`` class.
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135
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136
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137 Returns:
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138 ExplainerDashboard
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139 """
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140
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141 dashboard_kwargs = dashboard_kwargs or {}
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142 run_kwargs = run_kwargs or {}
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143
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144 from explainerdashboard import ExplainerDashboard, RegressionExplainer
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145
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146 # Replaceing chars which dash doesnt accept for column name `.` , `{`, `}`
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147 X_test_df = exp.X_test_transformed.copy()
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148 X_test_df.columns = [
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149 col.replace(".", "__").replace("{", "__").replace("}", "__")
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150 for col in X_test_df.columns
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151 ]
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152 explainer = RegressionExplainer(
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153 estimator, X_test_df, exp.y_test_transformed, **kwargs
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154 )
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155 return ExplainerDashboard(
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156 explainer, mode=display_format, contributions=False,
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157 whatif=False, shap_interaction=False, decision_trees=False,
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158 **dashboard_kwargs
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159 )