updating gitignore and markets map

.gitignore

@@ -22,6 +22,8 @@ parts/
 sdist/
 var/
 wheels/
+json_data/
+tmp/
 share/python-wheels/
 *.egg-info/
 .installed.cfg

scripts/markets.py

@@ -59,6 +59,7 @@ DEFAULT_FILENAME = "fpmms.parquet"
 SCRIPTS_DIR = Path(__file__).parent
 ROOT_DIR = SCRIPTS_DIR.parent
 DATA_DIR = ROOT_DIR / "data"
+market_creators_map = {"quickstart": CREATOR, "pearl": PEARL_CREATOR}
 
 
 class RetriesExceeded(Exception):

scripts/utils.py

@@ -3,7 +3,7 @@ import json
 import os
 import time
 from tqdm import tqdm
-from typing import List, Any, Optional, Union
+from typing import List, Any, Optional, Union, Tuple
 import numpy as np
 import pandas as pd
 import gc
@@ -222,6 +222,18 @@ EVENT_TO_MECH_STRUCT = {
 }
 
 
+def measure_execution_time(func):
+    def wrapper(*args, **kwargs):
+        start_time = time.time()
+        result = func(*args, **kwargs)
+        end_time = time.time()
+        execution_time = end_time - start_time
+        print(f"Execution time: {execution_time:.6f} seconds")
+        return result
+
+    return wrapper
+
+
 def parse_args() -> str:
     """Parse the arguments and return the RPC."""
     if len(sys.argv) != 2:
@@ -364,6 +376,48 @@ def measure_execution_time(func):
     return wrapper
 
 
+def get_vote(p_yes, p_no) -> Optional[str]:
+    """Return the vote."""
+    if p_no == p_yes:
+        return None
+    if p_no > p_yes:
+        return "No"
+    return "Yes"
+
+
+def get_win_probability(p_yes, p_no) -> Optional[float]:
+    """Return the probability estimation for winning with vote."""
+    return max(p_no, p_yes)
+
+
+def get_result_values(result: str) -> Tuple:
+    if result == "Invalid response":
+        return 1, "Invalid response from tool", None
+    error_message = None
+    params = None
+    try:
+        if isinstance(result, str):
+            params = json.loads(result)
+            error_value = 0
+
+    except JSONDecodeError:
+        error_message = "Response parsing error"
+        error_value = 1
+
+    except Exception as e:
+        error_message = str(e)
+        error_value = 1
+    return error_value, error_message, params
+
+
+def get_prediction_values(params: dict) -> Tuple:
+    p_yes = float(params.pop("p_yes"))
+    p_no = float(params.pop("p_no"))
+    confidence = float(params.pop("confidence"))
+    info_utility = float(params.pop("info_utility"))
+    return p_yes, p_no, confidence, info_utility
+
+
 def _to_content(q: str) -> dict[str, Any]:
     """Convert the given query string to payload content, i.e., add it under a `queries` key and convert it to bytes."""
     finalized_query = {

tabs/metrics.py

@@ -243,9 +243,9 @@ def get_trade_metrics_text() -> gr.Markdown:
     metric_text = """ 
         ## Description of the graph
         These metrics are computed weekly. The statistical measures are:
-        * min, max values, 25th(q1), 50th(median), 75th(q2) percentiles
+        * min, max, 25th(q1), 50th(median) and 75th(q2) percentiles
         * the upper and lower fences to delimit possible outliers
-        * the average values as the dotten lines
+        * the average values as the dotted lines
         """
 
     return gr.Markdown(metric_text)