Update src/populate.py
Browse files- src/populate.py +13 -0
src/populate.py
CHANGED
@@ -1,6 +1,7 @@
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import json
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import os
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import pandas as pd
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from src.display.formatting import has_no_nan_values, make_clickable_model
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@@ -16,6 +17,18 @@ def get_leaderboard_df(results_path: str, requests_path: str, cols: list, benchm
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# df = df.sort_values(by=[AutoEvalColumn.average.name], ascending=False)
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# df = df.sort_values(by=[AutoEvalColumn.task5.name], ascending=True)
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mos_rank = df[AutoEvalColumn.task2.name].rank(method="max", numeric_only=True, ascending=True)
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bitrate_rank = df[AutoEvalColumn.task3.name].rank(method="min", numeric_only=True, ascending=True)
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df["Ranking"] = pd.Series((mos_rank + bitrate_rank)/2)
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import json
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import os
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import numpy as np
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import pandas as pd
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from src.display.formatting import has_no_nan_values, make_clickable_model
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# df = df.sort_values(by=[AutoEvalColumn.average.name], ascending=False)
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# df = df.sort_values(by=[AutoEvalColumn.task5.name], ascending=True)
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df[AutoEvalColumn.task0.name] = pd.Series(
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np.stack(
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np.array(df[AutoEvalColumn.task2.name].values)
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).squeeze()
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)
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df[AutoEvalColumn.task1.name] = pd.Series(
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np.stack(
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np.array(df[AutoEvalColumn.task3.name].values)
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).squeeze()
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)
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mos_rank = df[AutoEvalColumn.task2.name].rank(method="max", numeric_only=True, ascending=True)
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bitrate_rank = df[AutoEvalColumn.task3.name].rank(method="min", numeric_only=True, ascending=True)
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df["Ranking"] = pd.Series((mos_rank + bitrate_rank)/2)
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