gavindiaz/NexQuant
1
0
Fork 0
mirror of https://github.com/NicolasBohn/NexQuant.git synced 2026-07-29 00:17:44 +00:00
Code Issues Packages Projects Releases Wiki Activity

chore: more optional parameters for running benchmark analysis (#431)

Browse Source 
* set title and round

* decision from multiple types

* check if decision is true

* reformat

* remove unused file
This commit is contained in:
Tim
2024-10-15 12:41:32 +08:00
committed by GitHub
parent 5ad3619492
commit b9a36e1b25
2 changed files with 12 additions and 19 deletions
Download Patch File Download Diff File Expand all files Collapse all files
rdagent/components/coder/factor_coder/CoSTEER/evaluators.py
+3 -14
View File
@@ -195,14 +195,7 @@ class FactorOutputFormatEvaluator(FactorEvaluator):
user_prompt=gen_df_info_str, system_prompt=system_prompt, json_mode=True
)
resp_dict = json.loads(resp)
if isinstance(resp_dict["output_format_decision"], str) and resp_dict[
"output_format_decision"
].lower() in (
"true",
"false",
):
resp_dict["output_format_decision"] = resp_dict["output_format_decision"].lower() == "true"
resp_dict["output_format_decision"] = str(resp_dict["output_format_decision"]).lower() in ["true", "1"]
return (
resp_dict["output_format_feedback"],
@@ -243,7 +236,7 @@ class FactorDatetimeDailyEvaluator(FactorEvaluator):
False,
)
time_diff = gen_df.index.get_level_values("datetime").to_series().diff().dropna().unique()
time_diff = pd.to_datetime(gen_df.index.get_level_values("datetime")).to_series().diff().dropna().unique()
if pd.Timedelta(minutes=1) in time_diff:
return (
"The generated dataframe is not daily. The implementation is definitely wrong. Please check the implementation.",
@@ -548,11 +541,7 @@ class FactorFinalDecisionEvaluator(Evaluator):
final_decision = final_evaluation_dict["final_decision"]
final_feedback = final_evaluation_dict["final_feedback"]
if isinstance(final_decision, str) and final_decision.lower() in ("true", "false"):
final_decision = final_decision.lower() == "true"
elif isinstance(final_decision, int) and final_decision in (0, 1):
final_decision = bool(final_decision)
final_decision = str(final_decision).lower() in ["true", "1"]
return final_decision, final_feedback
except json.JSONDecodeError as e: