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Sleeping
Sleeping
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Browse files
app.py
CHANGED
@@ -130,7 +130,7 @@ def main():
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st.write("#### Select a competition to view more details and rankings.")
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# Create a header for the table
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cols = st.columns([1, 3, 2, 2,
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headers = ["Index", "Competition Name", "Date", "Miner hotkey", "Days on Top"]
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for col, header in zip(cols, headers):
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col.write(header)
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@@ -139,7 +139,7 @@ def main():
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for index, (competition, details) in enumerate(COMPETITIONS.items(), start=1):
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leader_info = st.session_state.get("leader_info", {}).get(competition, {})
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cols = st.columns([1, 3, 2, 2,
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cols[0].write(index)
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if cols[1].button(competition):
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@@ -156,7 +156,7 @@ def main():
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st.write(description)
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st.subheader("Competition Summary")
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competition_summary_df = competition_summaries.get(competition_name, pd.DataFrame())
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if not competition_summary_df.empty:
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st.dataframe(competition_summary_df, height=500)
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else:
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@@ -165,7 +165,7 @@ def main():
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st.subheader("Models Evaluation")
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models_evaluation_df = model_evaluations.get(competition_name, pd.DataFrame())
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if not models_evaluation_df.empty:
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st.dataframe(models_evaluation_df.style.apply(highlight_score_column, axis=0))
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else:
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st.warning("No models evaluation data available.")
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else:
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st.write("#### Select a competition to view more details and rankings.")
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# Create a header for the table
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cols = st.columns([1, 3, 2, 2, 2, 2])
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headers = ["Index", "Competition Name", "Date", "Miner hotkey", "Days on Top"]
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for col, header in zip(cols, headers):
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col.write(header)
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for index, (competition, details) in enumerate(COMPETITIONS.items(), start=1):
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leader_info = st.session_state.get("leader_info", {}).get(competition, {})
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cols = st.columns([1, 3, 2, 2, 2, 2])
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cols[0].write(index)
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if cols[1].button(competition):
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st.write(description)
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st.subheader("Competition Summary")
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competition_summary_df = competition_summaries.get(competition_name, pd.DataFrame(), use_container_width=True)
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if not competition_summary_df.empty:
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st.dataframe(competition_summary_df, height=500)
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else:
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st.subheader("Models Evaluation")
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models_evaluation_df = model_evaluations.get(competition_name, pd.DataFrame())
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if not models_evaluation_df.empty:
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st.dataframe(models_evaluation_df.style.apply(highlight_score_column, axis=0), use_container_width=True)
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else:
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st.warning("No models evaluation data available.")
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else:
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