mirror of
https://github.com/freqtrade/freqtrade.git
synced 2024-11-11 02:33:55 +00:00
96 lines
4.1 KiB
Python
96 lines
4.1 KiB
Python
import time
|
|
from pathlib import Path
|
|
from typing import Any, Dict, List
|
|
|
|
import pandas as pd
|
|
|
|
from freqtrade.optimize.lookahead_analysis import LookaheadAnalysis, logger
|
|
|
|
|
|
class LookaheadAnalysisSubFunctions:
|
|
@staticmethod
|
|
def text_table_lookahead_analysis_instances(lookahead_instances: List[LookaheadAnalysis]):
|
|
headers = ['filename', 'strategy', 'has_bias', 'total_signals',
|
|
'biased_entry_signals', 'biased_exit_signals', 'biased_indicators']
|
|
data = []
|
|
for inst in lookahead_instances:
|
|
if inst.failed_bias_check:
|
|
data.append(
|
|
[
|
|
inst.strategy_obj['location'].parts[-1],
|
|
inst.strategy_obj['name'],
|
|
'error while checking'
|
|
]
|
|
)
|
|
else:
|
|
data.append(
|
|
[
|
|
inst.strategy_obj['location'].parts[-1],
|
|
inst.strategy_obj['name'],
|
|
inst.current_analysis.has_bias,
|
|
inst.current_analysis.total_signals,
|
|
inst.current_analysis.false_entry_signals,
|
|
inst.current_analysis.false_exit_signals,
|
|
", ".join(inst.current_analysis.false_indicators)
|
|
]
|
|
)
|
|
from tabulate import tabulate
|
|
table = tabulate(data, headers=headers, tablefmt="orgtbl")
|
|
print(table)
|
|
|
|
@staticmethod
|
|
def export_to_csv(config: Dict[str, Any], lookahead_analysis: List[LookaheadAnalysis]):
|
|
def add_or_update_row(df, row_data):
|
|
if (
|
|
(df['filename'] == row_data['filename']) &
|
|
(df['strategy'] == row_data['strategy'])
|
|
).any():
|
|
# Update existing row
|
|
pd_series = pd.DataFrame([row_data])
|
|
df.loc[
|
|
(df['filename'] == row_data['filename']) &
|
|
(df['strategy'] == row_data['strategy'])
|
|
] = pd_series
|
|
else:
|
|
# Add new row
|
|
df = pd.concat([df, pd.DataFrame([row_data], columns=df.columns)])
|
|
|
|
return df
|
|
|
|
if Path(config['lookahead_analysis_exportfilename']).exists():
|
|
# Read CSV file into a pandas dataframe
|
|
csv_df = pd.read_csv(config['lookahead_analysis_exportfilename'])
|
|
else:
|
|
# Create a new empty DataFrame with the desired column names and set the index
|
|
csv_df = pd.DataFrame(columns=[
|
|
'filename', 'strategy', 'has_bias', 'total_signals',
|
|
'biased_entry_signals', 'biased_exit_signals', 'biased_indicators'
|
|
],
|
|
index=None)
|
|
|
|
for inst in lookahead_analysis:
|
|
new_row_data = {'filename': inst.strategy_obj['location'].parts[-1],
|
|
'strategy': inst.strategy_obj['name'],
|
|
'has_bias': inst.current_analysis.has_bias,
|
|
'total_signals': inst.current_analysis.total_signals,
|
|
'biased_entry_signals': inst.current_analysis.false_entry_signals,
|
|
'biased_exit_signals': inst.current_analysis.false_exit_signals,
|
|
'biased_indicators': ",".join(inst.current_analysis.false_indicators)}
|
|
csv_df = add_or_update_row(csv_df, new_row_data)
|
|
|
|
logger.info(f"saving {config['lookahead_analysis_exportfilename']}")
|
|
csv_df.to_csv(config['lookahead_analysis_exportfilename'], index=False)
|
|
|
|
@staticmethod
|
|
def initialize_single_lookahead_analysis(strategy_obj: Dict[str, Any], config: Dict[str, Any]):
|
|
|
|
logger.info(f"Bias test of {Path(strategy_obj['location']).name} started.")
|
|
start = time.perf_counter()
|
|
current_instance = LookaheadAnalysis(config, strategy_obj)
|
|
current_instance.start()
|
|
elapsed = time.perf_counter() - start
|
|
logger.info(f"checking look ahead bias via backtests "
|
|
f"of {Path(strategy_obj['location']).name} "
|
|
f"took {elapsed:.0f} seconds.")
|
|
return current_instance
|