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		Runtime error
		
	
		Corey Morris
		
	commited on
		
		
					Commit 
							
							·
						
						e79bcf3
	
1
								Parent(s):
							
							d506f10
								
Fixed type error
Browse files- app.py +1 -1
- result_data_processor.py +6 -5
    	
        app.py
    CHANGED
    
    | @@ -105,7 +105,7 @@ def create_line_chart(df, model_names, metrics): | |
| 105 | 
             
                fig.update_layout(showlegend=True)
         | 
| 106 | 
             
                return fig
         | 
| 107 |  | 
| 108 | 
            -
            def find_top_differences_table(df, target_model, closest_models, num_differences=10, exclude_columns=['Parameters']):
         | 
| 109 | 
             
                # Calculate the absolute differences for each task between the target model and the closest models
         | 
| 110 | 
             
                new_df = df.drop(columns=exclude_columns)
         | 
| 111 | 
             
                differences = new_df.loc[closest_models].sub(new_df.loc[target_model]).abs()
         | 
|  | |
| 105 | 
             
                fig.update_layout(showlegend=True)
         | 
| 106 | 
             
                return fig
         | 
| 107 |  | 
| 108 | 
            +
            def find_top_differences_table(df, target_model, closest_models, num_differences=10, exclude_columns=['Parameters', 'organization']):
         | 
| 109 | 
             
                # Calculate the absolute differences for each task between the target model and the closest models
         | 
| 110 | 
             
                new_df = df.drop(columns=exclude_columns)
         | 
| 111 | 
             
                differences = new_df.loc[closest_models].sub(new_df.loc[target_model]).abs()
         | 
    	
        result_data_processor.py
    CHANGED
    
    | @@ -89,6 +89,7 @@ class ResultDataProcessor: | |
| 89 | 
             
                def process_data(self):
         | 
| 90 |  | 
| 91 | 
             
                    dataframes = []
         | 
|  | |
| 92 | 
             
                    for filename in self._find_files(self.directory, self.pattern):
         | 
| 93 | 
             
                        raw_data = self._read_and_transform_data(filename)
         | 
| 94 | 
             
                        split_path = filename.split('/')
         | 
| @@ -99,13 +100,15 @@ class ResultDataProcessor: | |
| 99 | 
             
                        mc2 = self._extract_mc2(raw_data, model_name)
         | 
| 100 | 
             
                        cleaned_data = pd.concat([cleaned_data, mc1])
         | 
| 101 | 
             
                        cleaned_data = pd.concat([cleaned_data, mc2])
         | 
| 102 | 
            -
                         | 
| 103 | 
            -
                        cleaned_data.loc['organization'] = organization_name
         | 
| 104 | 
             
                        dataframes.append(cleaned_data)
         | 
| 105 |  | 
| 106 |  | 
| 107 | 
             
                    data = pd.concat(dataframes, axis=1).transpose()
         | 
| 108 | 
            -
             | 
|  | |
|  | |
|  | |
| 109 | 
             
                    # Add Model Name and rearrange columns
         | 
| 110 | 
             
                    data['Model Name'] = data.index
         | 
| 111 | 
             
                    cols = data.columns.tolist()
         | 
| @@ -137,8 +140,6 @@ class ResultDataProcessor: | |
| 137 | 
             
                    # remove extreme outliers from column harness|truthfulqa:mc1
         | 
| 138 | 
             
                    data = self._remove_mc1_outliers(data)
         | 
| 139 |  | 
| 140 | 
            -
                    data = data.drop(columns=['organization'])
         | 
| 141 | 
            -
             | 
| 142 | 
             
                    return data
         | 
| 143 |  | 
| 144 | 
             
                def rank_data(self):
         | 
|  | |
| 89 | 
             
                def process_data(self):
         | 
| 90 |  | 
| 91 | 
             
                    dataframes = []
         | 
| 92 | 
            +
                    organization_names = []
         | 
| 93 | 
             
                    for filename in self._find_files(self.directory, self.pattern):
         | 
| 94 | 
             
                        raw_data = self._read_and_transform_data(filename)
         | 
| 95 | 
             
                        split_path = filename.split('/')
         | 
|  | |
| 100 | 
             
                        mc2 = self._extract_mc2(raw_data, model_name)
         | 
| 101 | 
             
                        cleaned_data = pd.concat([cleaned_data, mc1])
         | 
| 102 | 
             
                        cleaned_data = pd.concat([cleaned_data, mc2])
         | 
| 103 | 
            +
                        organization_names.append(organization_name)
         | 
|  | |
| 104 | 
             
                        dataframes.append(cleaned_data)
         | 
| 105 |  | 
| 106 |  | 
| 107 | 
             
                    data = pd.concat(dataframes, axis=1).transpose()
         | 
| 108 | 
            +
             | 
| 109 | 
            +
                    # Add organization column
         | 
| 110 | 
            +
                    data['organization'] = organization_names
         | 
| 111 | 
            +
             | 
| 112 | 
             
                    # Add Model Name and rearrange columns
         | 
| 113 | 
             
                    data['Model Name'] = data.index
         | 
| 114 | 
             
                    cols = data.columns.tolist()
         | 
|  | |
| 140 | 
             
                    # remove extreme outliers from column harness|truthfulqa:mc1
         | 
| 141 | 
             
                    data = self._remove_mc1_outliers(data)
         | 
| 142 |  | 
|  | |
|  | |
| 143 | 
             
                    return data
         | 
| 144 |  | 
| 145 | 
             
                def rank_data(self):
         | 
