Adding actions for PR (goeckslab#16)

* updates for pr actions

1. formart for planemo test and lint, and flask8 lint
2. found and fixed bugs during planemo test
3. added test-data files

* Create .shed.yml

* add details to .shed.yml

* importing order

* importing order

* updated pr.yaml and import order

1 for pr.yaml: commend checking file-size for now
2. import order again

.gitignore

@@ -1,11 +1,9 @@
 .env
 env
-*.csv
-*.tsv
 *.log
 *.png
 *.txt
 *.pkl
-*.html
 *.ipynb
-__pycache__
+__pycache__
+.DS_Store

tools/.shed.yml

@@ -0,0 +1,8 @@
+categories: 
+  - Machine Learning
+description: Tools for machine learning with pycaret in a simple, powerful and robust way 
+name: galaxy-pycaret
+owner: goeckslab
+long_description: Tools for machine learning with pycaret in a simple, powerful and robust way
+remote_repository_url: https://github.com/goeckslab/Galaxy-Pycaret
+homepage_url: https://github.com/goeckslab/Galaxy-Pycaret

tools/base_model_trainer.py

@@ -1,13 +1,15 @@
-import sys
-import pandas as pd
-import os
-import logging 
 import base64
+import logging
+import os
+
+import pandas as pd
 
 logging.basicConfig(level=logging.DEBUG)
 LOG = logging.getLogger(__name__)
 
+
 class BaseModelTrainer:
+
     def __init__(self, input_file, target_col, output_dir, **kwargs):
         self.exp = None  # This will be set in the subclass
         self.input_file = input_file
@@ -21,7 +23,7 @@ def __init__(self, input_file, target_col, output_dir, **kwargs):
         for key, value in kwargs.items():
             setattr(self, key, value)
         self.setup_params = {}
-        
+
         LOG.info(f"Model kwargs: {self.__dict__}")
 
     def load_data(self):
@@ -48,26 +50,35 @@ def setup_pycaret(self):
         if hasattr(self, 'normalize') and self.normalize is not None:
             self.setup_params['normalize'] = self.normalize
 
-        if hasattr(self, 'feature_selection') and self.feature_selection is not None:
+        if hasattr(self, 'feature_selection') and \
+                self.feature_selection is not None:
             self.setup_params['feature_selection'] = self.feature_selection
 
-        if hasattr(self, 'cross_validation') and self.cross_validation is not None and self.cross_validation == False:
+        if hasattr(self, 'cross_validation') and \
+                self.cross_validation is not None \
+                and self.cross_validation is False:
             self.setup_params['cross_validation'] = self.cross_validation
 
-        if hasattr(self, 'cross_validation') and self.cross_validation is not None:
+        if hasattr(self, 'cross_validation') and \
+                self.cross_validation is not None:
             if hasattr(self, 'cross_validation_folds'):
                 self.setup_params['fold'] = self.cross_validation_folds
 
-        if hasattr(self, 'remove_outliers') and self.remove_outliers is not None:
+        if hasattr(self, 'remove_outliers') and \
+                self.remove_outliers is not None:
             self.setup_params['remove_outliers'] = self.remove_outliers
 
-        if hasattr(self, 'remove_multicollinearity') and self.remove_multicollinearity is not None:
-            self.setup_params['remove_multicollinearity'] = self.remove_multicollinearity
+        if hasattr(self, 'remove_multicollinearity') and \
+                self.remove_multicollinearity is not None:
+            self.setup_params['remove_multicollinearity'] = \
+                self.remove_multicollinearity
 
-        if hasattr(self, 'polynomial_features') and self.polynomial_features is not None:
+        if hasattr(self, 'polynomial_features') and \
+                self.polynomial_features is not None:
             self.setup_params['polynomial_features'] = self.polynomial_features
 
-        if hasattr(self, 'fix_imbalance') and self.fix_imbalance is not None:
+        if hasattr(self, 'fix_imbalance') and \
+                self.fix_imbalance is not None:
             self.setup_params['fix_imbalance'] = self.fix_imbalance
 
         LOG.info(self.setup_params)
@@ -93,17 +104,25 @@ def save_html_report(self):
         LOG.info("Saving HTML report")
 
         model_name = type(self.best_model).__name__
-
         excluded_params = ['html', 'log_experiment', 'system_log']
-        filtered_setup_params = {k: v for k, v in self.setup_params.items() if k not in excluded_params}
-        setup_params_table = pd.DataFrame(list(filtered_setup_params.items()), columns=['Parameter', 'Value'])
-
+        filtered_setup_params = {
+            k: v
+            for k, v in self.setup_params.items() if k not in excluded_params
+        }
+        setup_params_table = pd.DataFrame(
+            list(filtered_setup_params.items()),
+            columns=['Parameter', 'Value'])
         # Save model summary
-        best_model_params = pd.DataFrame(self.best_model.get_params().items(), columns=['Parameter', 'Value'])
-        best_model_params.to_csv(os.path.join(self.output_dir, 'best_model.csv'), index=False)
+        best_model_params = pd.DataFrame(
+            self.best_model.get_params().items(),
+            columns=['Parameter', 'Value'])
+        best_model_params.to_csv(
+            os.path.join(self.output_dir, 'best_model.csv'),
+            index=False)
 
         # Save comparison results
-        self.results.to_csv(os.path.join(self.output_dir, "comparison_results.csv"))
+        self.results.to_csv(os.path.join(
+            self.output_dir, "comparison_results.csv"))
 
         # Read and encode plot images
         plots_html = ""
@@ -112,7 +131,8 @@ def save_html_report(self):
             plots_html += f"""
             <div class="plot">
                 <h3>{plot_name.capitalize()}</h3>
-                <img src="data:image/png;base64,{encoded_image}" alt="{plot_name}">
+                <img src="data:image/png;base64,
+                {encoded_image}" alt="{plot_name}">
             </div>
             """
 
@@ -122,7 +142,8 @@ def save_html_report(self):
         <html lang="en">
         <head>
             <meta charset="UTF-8">
-            <meta name="viewport" content="width=device-width, initial-scale=1.0">
+            <meta name="viewport" content="width=device-width,
+            initial-scale=1.0">
             <title>PyCaret Model Training Report</title>
             <style>
                 body {{
@@ -179,16 +200,19 @@ def save_html_report(self):
                 <h2>Setup Parameters</h2>
                 <table>
                     <tr><th>Parameter</th><th>Value</th></tr>
-                    {setup_params_table.to_html(index=False, header=False, classes='table')}
+                    {setup_params_table.to_html(index=False,
+                                            header=False, classes='table')}
                 </table>
                 <h2>Best Model: {model_name}</h2>
                 <table>
                     <tr><th>Parameter</th><th>Value</th></tr>
-                    {best_model_params.to_html(index=False, header=False, classes='table')}
+                    {best_model_params.to_html(index=False,
+                                            header=False, classes='table')}
                 </table>
                 <h2>Comparison Results</h2>
                 <table>
-                    {self.results.to_html(index=False, classes='table')}
+                    {self.results.to_html(index=False,
+                                        classes='table')}
                 </table>
                 <h2>Plots</h2>
                 {plots_html}
@@ -197,12 +221,13 @@ def save_html_report(self):
         </html>
         """
 
-        with open(os.path.join(self.output_dir, "comparison_result.html"), "w") as file:
+        with open(os.path.join(
+                self.output_dir, "comparison_result.html"), "w") as file:
             file.write(html_content)
 
     def save_dashboard(self):
         raise NotImplementedError("Subclasses should implement this method")
-        
+
     def run(self):
         self.load_data()
         self.setup_pycaret()