Update app.py

app.py

@@ -4,7 +4,12 @@ import pandas as pd
 from constants import *
 
 
-def get_data(verified, dataset, ipc, label_type):
+def get_data(verified, dataset, ipc, label_type, metric_weights=None):
+    if metric_weights is None:
+        metric_weights = [1.0 / len(METRICS) for _ in METRICS]
+    if not isinstance(label_type, list):
+        label_type = [label_type]
+
     data = pd.read_csv("data.csv")
     data["verified"] = data["verified"].apply(lambda x: bool(x))
     data["dataset"] = data["dataset"].apply(lambda x: DATASET_LIST[x])
@@ -14,17 +19,24 @@ def get_data(verified, dataset, ipc, label_type):
         data = data[data["verified"] == verified]
     data = data[data["dataset"] == dataset]
     data = data[data["ipc"] == ipc]
-    data = data[data["label_type"] == label_type]
+    data = data[data["label_type"].apply(lambda x: x in label_type)]
+
+    # create a new column for the score
+    data["score"] = data[METRICS[0].lower()] * 0.0
+    for i, metric in enumerate(METRICS):
+        data["score"] += data[metric.lower()] * metric_weights[i]
     data = data.sort_values(by="score", ascending=False)
+    data["ranking"] = range(1, len(data) + 1)
 
     # formatting
     data["method"] = "[" + data["method"] + "](" + data["method_reference"] + ")"
     data["verified"] = data["verified"].apply(lambda x: "✅" if x else "")
-    data = data.drop(columns=["method_reference", "dataset", "ipc", "label_type"])
+    data = data.drop(columns=["method_reference", "dataset", "ipc"])
+    data = data[['ranking', 'method', 'verified', 'date', 'label_type', 'hlr', 'ior', 'score']]
     if label_type == "Hard Label":
-        data = data.rename(columns={"method": "Method", "date": "Date", "recovery": "Hard Recovery", "improvement": "Hard Improvement", "score": "Score", "verified": "Verified"})
+        data = data.rename(columns={"ranking": "Ranking", "method": "Method", "date": "Date", "label_type": "Label Type", "hlr": "HLR↓", "ior": "IOR↑", "score": "Score", "verified": "Verified"})
     else:
-        data = data.rename(columns={"method": "Method", "date": "Date", "recovery": "Hard Recovery", "improvement": "Soft Improvement", "score": "Score", "verified": "Verified"})
+        data = data.rename(columns={"ranking": "Ranking", "method": "Method", "date": "Date", "label_type": "Label Type", "hlr": "HLR↓", "ior": "IOR↑", "score": "Score", "verified": "Verified"})
     return data
 
 
@@ -50,16 +62,30 @@ with gr.Blocks() as leaderboard:
         interactive=True,
         info=IPC_INFO
     )
-    label = gr.Radio(
+    label = gr.CheckboxGroup(
         label="Label Type",
         choices=LABEL_TYPE_LIST,
-        value=LABEL_TYPE_LIST[0],
+        value=LABEL_TYPE_LIST,
+        info=LABEL_TYPE_INFO,
         interactive=True,
-        info=LABEL_TYPE_INFO
     )
 
+    with gr.Accordion("Adjust Score Weights", open=False):
+        gr.Markdown(WEIGHT_ADJUSTMENT_INTRODUCTION, latex_delimiters=[
+              {'left': '$$', 'right': '$$', 'display': True},
+              {'left': '$', 'right': '$', 'display': False},
+              {'left': '\\(', 'right': '\\)', 'display': False},
+              {'left': '\\[', 'right': '\\]', 'display': True}
+          ])
+        metric_sliders = []
+        for metric in METRICS:
+            metric_sliders.append(gr.Slider(label=f"Weight for {metric}", minimum=0.0, maximum=1.0, value=0.5, interactive=True))
+        adjust_btn = gr.Button("Adjust Weights")
+
+
+    metric_weights = [s.value for s in metric_sliders]
     board = gr.components.Dataframe(
-        value=get_data(verified.value, dataset.value, ipc.value, label.value),
+        value=get_data(verified.value, dataset.value, ipc.value, label.value, metric_weights),
         headers=COLUMN_NAMES,
         type="pandas",
         datatype=DATA_TITLE_TYPE,
@@ -69,15 +95,25 @@ with gr.Blocks() as leaderboard:
     )
 
     for component in [verified, dataset, ipc, label]:
-        component.change(fn=lambda v, d, i, l: gr.components.Dataframe(
-            value=get_data(v, d, i, l),
+        component.change(lambda v, d, i, l, *m: gr.components.Dataframe(
+            value=get_data(v, d, i, l, [s for s in m]),
+            headers=COLUMN_NAMES,
+            type="pandas",
+            datatype=DATA_TITLE_TYPE,
+            interactive=False,
+            visible=True,
+            max_height=500,
+        ), inputs=[verified, dataset, ipc, label] + metric_sliders, outputs=board)
+
+    adjust_btn.click(fn=lambda v, d, i, l, *m: gr.components.Dataframe(
+            value=get_data(v, d, i, l, [s for s in m]),
             headers=COLUMN_NAMES,
             type="pandas",
             datatype=DATA_TITLE_TYPE,
             interactive=False,
             visible=True,
             max_height=500,
-        ), inputs=[verified, dataset, ipc, label], outputs=board)
+        ), inputs=[verified, dataset, ipc, label] + metric_sliders, outputs=board)
 
     citation_button = gr.Textbox(
         value=CITATION_BUTTON_TEXT,