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Update app.py
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app.py
CHANGED
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@@ -97,29 +97,8 @@ def update_leaderboard(selected_methods, selected_metrics):
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# ------- Visualisation helpers ---------------------------------------------
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def get_plot_explanation(benchmark_type, x_metric, y_metric, aspect, dataset, single_metric):
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if benchmark_type == "similarity":
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return (
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f"Scatter plot compares models on **{x_metric}** (x‑axis) and **{y_metric}** (y‑axis). "
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"Upper‑right points indicate jointly strong performance."
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)
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if benchmark_type == "function":
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return (
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f"Heat‑map shows model scores for **{aspect.upper()}** terms with **{single_metric}**. "
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"Darker squares → better predictions."
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)
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if benchmark_type == "family":
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return (
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f"Box‑plots summarise cross‑fold MCC on **{dataset}**; higher medians are better."
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)
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if benchmark_type == "affinity":
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return (
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f"Box‑plots display distribution of **{single_metric}** scores for affinity prediction; higher values are better."
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)
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return ""
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def
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plot_path = benchmark_plot(
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benchmark_type,
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methods_selected,
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@@ -129,8 +108,7 @@ def generate_plot_and_explanation(benchmark_type, methods_selected, x_metric, y_
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dataset,
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single_metric,
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)
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return explanation, plot_path
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# ---------------------------------------------------------------------------
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# Custom CSS for frozen first column and clearer table styles
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@@ -258,7 +236,7 @@ with block:
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# ------------------------------------------------------------------
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# 2️⃣ Visualisation tab
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# ------------------------------------------------------------------
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with gr.TabItem("📊
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gr.Markdown(
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"""## **Interactive Visualizations**
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Choose a benchmark type; context‑specific options will appear. Click **Plot** and an explanation will follow the figure.""",
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@@ -298,7 +276,7 @@ with block:
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],
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)
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plot_button.click(
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inputs=[
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vis_benchmark_type_selector,
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vis_method_selector,
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@@ -308,7 +286,7 @@ with block:
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vis_dataset_selector,
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vis_single_metric_selector,
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],
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outputs=[
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)
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# ------------------------------------------------------------------
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# ------- Visualisation helpers ---------------------------------------------
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def generate_plot(benchmark_type, methods_selected, x_metric, y_metric, aspect, dataset, single_metric):
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plot_path = benchmark_plot(
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benchmark_type,
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methods_selected,
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dataset,
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single_metric,
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)
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return plot_path
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# ---------------------------------------------------------------------------
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# Custom CSS for frozen first column and clearer table styles
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# ------------------------------------------------------------------
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# 2️⃣ Visualisation tab
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# ------------------------------------------------------------------
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with gr.TabItem("📊 Visualization", elem_id="probe-benchmark-tab-visualization", id=2):
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gr.Markdown(
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"""## **Interactive Visualizations**
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Choose a benchmark type; context‑specific options will appear. Click **Plot** and an explanation will follow the figure.""",
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],
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)
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plot_button.click(
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generate_plot,
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inputs=[
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vis_benchmark_type_selector,
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vis_method_selector,
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vis_dataset_selector,
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vis_single_metric_selector,
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],
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outputs=[plot_output],
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)
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# ------------------------------------------------------------------
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