DontPlanToEnd commited on
Commit
5b12447
·
verified ·
1 Parent(s): 75b45d1

Update app.py

Browse files
Files changed (1) hide show
  1. app.py +7 -7
app.py CHANGED
@@ -46,7 +46,7 @@ COLUMN_GROUPS = {
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  "world_model_group": [
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  'wm_recipe_percent_error', 'wm_geoguesser_mae', 'wm_weight_percent_error',
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  'wm_music_mae', 'wm_youtube_view_percent_error', 'Show Rec Score',
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- "Show Rec MAE", "Show Rec Pearson", "Show Rec Std Dev Error"
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  ],
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  }
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@@ -165,7 +165,7 @@ def load_leaderboard_data(csv_file_path):
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  # Replace NaN with large/small numbers for sorting, which serialize reliably to JSON
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  # Higher is better -> fill with a very small number so they sort last when descending
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  df['Show Rec Score'].fillna(-99999, inplace=True)
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- df['Show Rec Pearson'].fillna(-99999, inplace=True)
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  # Lower is better -> fill with a very large number so they sort last when ascending
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  df['Show Rec MAE'].fillna(99999, inplace=True)
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  df['Show Rec Std Dev Error'].fillna(99999, inplace=True)
@@ -799,7 +799,7 @@ MASTER_COLUMN_ORDER = [
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  'wm_recipe_percent_error', 'wm_geoguesser_mae', 'wm_weight_percent_error',
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  'wm_music_mae', 'wm_youtube_view_percent_error',
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  "Show Rec Score", # Main Score
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- "Show Rec MAE", "Show Rec Pearson", "Show Rec Std Dev Error",
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  # Writing
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  "Writing ✍️",
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  "avg_nsfw_score", "avg_dark_score",
@@ -871,9 +871,9 @@ ALL_COLUMN_DEFS = {
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  valueFormatter={"function": "params.value === 99999 ? '' : String(params.value)"},
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  cellClass="border-left-dashed"
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  ),
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- "Show Rec Pearson": create_numeric_column(
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- "Show Rec Pearson",
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- headerName="Show Rec Pearson",
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  width=120,
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  filterParams={"defaultOption": "greaterThanOrEqual"},
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  # Add this formatter to hide the placeholder
@@ -1194,7 +1194,7 @@ app.layout = html.Div([
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  html.Li([html.Strong("Show Recommendation Score:"), " A model's ability to predict what rating out of ten a person will rate a TV show based on their previous ratings."]),
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  html.Ul([
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  html.Li([html.Strong("Show Rec MAE:"), " The mean absolute error between the model's predicted ratings and the user's true ratings."]),
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- html.Li([html.Strong("Show Rec Pearson:"), " Measures how well the model's predictions trend with the user's true ratings."]),
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  html.Li([html.Strong("Show Rec Std Dev Error:"), " The absolute difference between the spread of the model's predictions and the spread of the true ratings."]),
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  ], style={'listStyleType': 'circle', 'marginLeft': '20px'}),
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  ], style={'listStyleType': 'circle', 'marginLeft': '20px'}),
 
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  "world_model_group": [
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  'wm_recipe_percent_error', 'wm_geoguesser_mae', 'wm_weight_percent_error',
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  'wm_music_mae', 'wm_youtube_view_percent_error', 'Show Rec Score',
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+ "Show Rec MAE", "Show Rec Correlation", "Show Rec Std Dev Error"
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  ],
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  }
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  # Replace NaN with large/small numbers for sorting, which serialize reliably to JSON
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  # Higher is better -> fill with a very small number so they sort last when descending
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  df['Show Rec Score'].fillna(-99999, inplace=True)
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+ df['Show Rec Correlation'].fillna(-99999, inplace=True)
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  # Lower is better -> fill with a very large number so they sort last when ascending
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  df['Show Rec MAE'].fillna(99999, inplace=True)
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  df['Show Rec Std Dev Error'].fillna(99999, inplace=True)
 
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  'wm_recipe_percent_error', 'wm_geoguesser_mae', 'wm_weight_percent_error',
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  'wm_music_mae', 'wm_youtube_view_percent_error',
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  "Show Rec Score", # Main Score
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+ "Show Rec MAE", "Show Rec Correlation", "Show Rec Std Dev Error",
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  # Writing
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  "Writing ✍️",
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  "avg_nsfw_score", "avg_dark_score",
 
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  valueFormatter={"function": "params.value === 99999 ? '' : String(params.value)"},
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  cellClass="border-left-dashed"
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  ),
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+ "Show Rec Correlation": create_numeric_column(
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+ "Show Rec Correlation",
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+ headerName="Show Rec Correlation",
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  width=120,
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  filterParams={"defaultOption": "greaterThanOrEqual"},
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  # Add this formatter to hide the placeholder
 
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  html.Li([html.Strong("Show Recommendation Score:"), " A model's ability to predict what rating out of ten a person will rate a TV show based on their previous ratings."]),
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  html.Ul([
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  html.Li([html.Strong("Show Rec MAE:"), " The mean absolute error between the model's predicted ratings and the user's true ratings."]),
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+ html.Li([html.Strong("Show Rec Correlation:"), " Measures how well the model's predictions trend with the user's true ratings."]),
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  html.Li([html.Strong("Show Rec Std Dev Error:"), " The absolute difference between the spread of the model's predictions and the spread of the true ratings."]),
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  ], style={'listStyleType': 'circle', 'marginLeft': '20px'}),
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  ], style={'listStyleType': 'circle', 'marginLeft': '20px'}),