mirror of
https://github.com/freqtrade/freqtrade.git
synced 2024-09-20 09:31:12 +00:00
Split Lookahead helper to separate file
This commit is contained in:
Matthias
parent
7b9f82c71a
commit
1c4a7c7a05
|
|
@ -141,7 +141,7 @@ def start_lookahead_analysis(args: Dict[str, Any]) -> None:
|
|||
:param args: Cli args from Arguments()
|
||||
:return: None
|
||||
"""
|
||||
from freqtrade.optimize.lookahead_analysis import LookaheadAnalysisSubFunctions
|
||||
from freqtrade.optimize.lookahead_analysis_helpers import LookaheadAnalysisSubFunctions
|
||||
|
||||
config = setup_utils_configuration(args, RunMode.UTIL_NO_EXCHANGE)
|
||||
|
||||
|
|
|
|||
|
|
@ -2,10 +2,8 @@ import copy
|
|||
import logging
|
||||
import pathlib
|
||||
import shutil
|
||||
import time
|
||||
from copy import deepcopy
|
||||
from datetime import datetime, timedelta, timezone
|
||||
from pathlib import Path
|
||||
from typing import Any, Dict, List
|
||||
|
||||
import pandas as pd
|
||||
|
|
@ -263,89 +261,4 @@ class LookaheadAnalysis:
|
|||
self.failed_bias_check = False
|
||||
|
||||
|
||||
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
|
||||
|
|
|
|||
95
freqtrade/optimize/lookahead_analysis_helpers.py
Normal file
95
freqtrade/optimize/lookahead_analysis_helpers.py
Normal file
|
|
@ -0,0 +1,95 @@
|
|||
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
|
||||
Loading…
Reference in New Issue
Block a user