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Merge branch 'develop' into feat/short

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This commit is contained in:
Matthias
2022-01-07 10:09:17 +01:00
parent 173524ea5b 7f20f6834b
commit 46809f08fe
27 changed files with 211 additions and 216 deletions
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4
freqtrade/optimize/backtesting.py
View File

@@ -448,8 +448,10 @@ class Backtesting:
detail_data.loc[:, 'exit_long'] = sell_row[ELONG_IDX]
detail_data.loc[:, 'enter_long'] = sell_row[LONG_IDX]
detail_data.loc[:, 'exit_long'] = sell_row[ELONG_IDX]
detail_data.loc[:, 'enter_tag'] = sell_row[ENTER_TAG_IDX]
detail_data.loc[:, 'exit_tag'] = sell_row[EXIT_TAG_IDX]
headers = ['date', 'open', 'high', 'low', 'close', 'enter_long', 'exit_long',
'enter_short', 'exit_short']
'enter_short', 'exit_short', 'enter_tag', 'exit_tag']
for det_row in detail_data[headers].values.tolist():
res = self._get_sell_trade_entry_for_candle(trade, det_row)
if res:

3
freqtrade/optimize/hyperopt.py
View File

@@ -76,6 +76,7 @@ class Hyperopt:
self.config = config
self.backtesting = Backtesting(self.config)
self.pairlist = self.backtesting.pairlists.whitelist
if not self.config.get('hyperopt'):
self.custom_hyperopt = HyperOptAuto(self.config)
@@ -332,7 +333,7 @@ class Hyperopt:
params_details = self._get_params_details(params_dict)
strat_stats = generate_strategy_stats(
processed, self.backtesting.strategy.get_strategy_name(),
self.pairlist, self.backtesting.strategy.get_strategy_name(),
backtesting_results, min_date, max_date, market_change=0
)
results_explanation = HyperoptTools.format_results_explanation_string(

3
freqtrade/optimize/hyperopt_loss_calmar.py
View File

@@ -47,10 +47,9 @@ class CalmarHyperOptLoss(IHyperOptLoss):
# calculate max drawdown
try:
_, _, _, high_val, low_val = calculate_max_drawdown(
_, _, _, _, _, max_drawdown = calculate_max_drawdown(
results, value_col="profit_abs"
)
max_drawdown = (high_val - low_val) / high_val
except ValueError:
max_drawdown = 0

43
freqtrade/optimize/hyperopt_tools.py
View File

@@ -308,8 +308,7 @@ class HyperoptTools():
if not has_drawdown:
# Ensure compatibility with older versions of hyperopt results
trials['results_metrics.max_drawdown_abs'] = None
trials['results_metrics.max_drawdown'] = None
trials['results_metrics.max_drawdown_account'] = None
# New mode, using backtest result for metrics
trials['results_metrics.winsdrawslosses'] = trials.apply(
@@ -320,12 +319,15 @@ class HyperoptTools():
'results_metrics.winsdrawslosses',
'results_metrics.profit_mean', 'results_metrics.profit_total_abs',
'results_metrics.profit_total', 'results_metrics.holding_avg',
'results_metrics.max_drawdown', 'results_metrics.max_drawdown_abs',
'results_metrics.max_drawdown',
'results_metrics.max_drawdown_account', 'results_metrics.max_drawdown_abs',
'loss', 'is_initial_point', 'is_best']]
trials.columns = ['Best', 'Epoch', 'Trades', ' Win Draw Loss', 'Avg profit',
'Total profit', 'Profit', 'Avg duration', 'Max Drawdown',
'max_drawdown_abs', 'Objective', 'is_initial_point', 'is_best']
trials.columns = [
'Best', 'Epoch', 'Trades', ' Win Draw Loss', 'Avg profit',
'Total profit', 'Profit', 'Avg duration', 'max_drawdown', 'max_drawdown_account',
'max_drawdown_abs', 'Objective', 'is_initial_point', 'is_best'
]
return trials
@@ -341,9 +343,9 @@ class HyperoptTools():
tabulate.PRESERVE_WHITESPACE = True
trials = json_normalize(results, max_level=1)
has_drawdown = 'results_metrics.max_drawdown_abs' in trials.columns
has_account_drawdown = 'results_metrics.max_drawdown_account' in trials.columns
trials = HyperoptTools.prepare_trials_columns(trials, has_drawdown)
trials = HyperoptTools.prepare_trials_columns(trials, has_account_drawdown)
trials['is_profit'] = False
trials.loc[trials['is_initial_point'], 'Best'] = '* '
@@ -368,19 +370,20 @@ class HyperoptTools():
stake_currency = config['stake_currency']
if has_drawdown:
trials['Max Drawdown'] = trials.apply(
lambda x: '{} {}'.format(
round_coin_value(x['max_drawdown_abs'], stake_currency),
f"({x['Max Drawdown']:,.2%})".rjust(10, ' ')
).rjust(25 + len(stake_currency))
if x['Max Drawdown'] != 0.0 else '--'.rjust(25 + len(stake_currency)),
axis=1
)
else:
trials = trials.drop(columns=['Max Drawdown'])
trials[f"Max Drawdown{' (Acct)' if has_account_drawdown else ''}"] = trials.apply(
lambda x: "{} {}".format(
round_coin_value(x['max_drawdown_abs'], stake_currency),
(f"({x['max_drawdown_account']:,.2%})"
if has_account_drawdown
else f"({x['max_drawdown']:,.2%})"
).rjust(10, ' ')
).rjust(25 + len(stake_currency))
if x['max_drawdown'] != 0.0 or x['max_drawdown_account'] != 0.0
else '--'.rjust(25 + len(stake_currency)),
axis=1
)
trials = trials.drop(columns=['max_drawdown_abs'])
trials = trials.drop(columns=['max_drawdown_abs', 'max_drawdown', 'max_drawdown_account'])
trials['Profit'] = trials.apply(
lambda x: '{} {}'.format(

69
freqtrade/optimize/optimize_reports.py
View File

@@ -1,4 +1,5 @@
import logging
from copy import deepcopy
from datetime import datetime, timedelta, timezone
from pathlib import Path
from typing import Any, Dict, List, Union
@@ -98,11 +99,11 @@ def _generate_result_line(result: DataFrame, starting_balance: int, first_column
}
def generate_pair_metrics(data: Dict[str, Dict], stake_currency: str, starting_balance: int,
def generate_pair_metrics(pairlist: List[str], stake_currency: str, starting_balance: int,
results: DataFrame, skip_nan: bool = False) -> List[Dict]:
"""
Generates and returns a list for the given backtest data and the results dataframe
:param data: Dict of <pair: dataframe> containing data that was used during backtesting.
:param pairlist: Pairlist used
:param stake_currency: stake-currency - used to correctly name headers
:param starting_balance: Starting balance
:param results: Dataframe containing the backtest results
@@ -112,7 +113,7 @@ def generate_pair_metrics(data: Dict[str, Dict], stake_currency: str, starting_b
tabular_data = []
for pair in data:
for pair in pairlist:
result = results[results['pair'] == pair]
if skip_nan and result['profit_abs'].isnull().all():
continue
@@ -194,29 +195,21 @@ def generate_sell_reason_stats(max_open_trades: int, results: DataFrame) -> List
return tabular_data
def generate_strategy_comparison(all_results: Dict) -> List[Dict]:
def generate_strategy_comparison(bt_stats: Dict) -> List[Dict]:
"""
Generate summary per strategy
:param all_results: Dict of <Strategyname: DataFrame> containing results for all strategies
:param bt_stats: Dict of <Strategyname: DataFrame> containing results for all strategies
:return: List of Dicts containing the metrics per Strategy
"""
tabular_data = []
for strategy, results in all_results.items():
tabular_data.append(_generate_result_line(
results['results'], results['config']['dry_run_wallet'], strategy)
)
try:
max_drawdown_per, _, _, _, _ = calculate_max_drawdown(results['results'],
value_col='profit_ratio')
max_drawdown_abs, _, _, _, _ = calculate_max_drawdown(results['results'],
value_col='profit_abs')
except ValueError:
max_drawdown_per = 0
max_drawdown_abs = 0
tabular_data[-1]['max_drawdown_per'] = round(max_drawdown_per * 100, 2)
tabular_data[-1]['max_drawdown_abs'] = \
round_coin_value(max_drawdown_abs, results['config']['stake_currency'], False)
for strategy, result in bt_stats.items():
tabular_data.append(deepcopy(result['results_per_pair'][-1]))
# Update "key" to strategy (results_per_pair has it as "Total").
tabular_data[-1]['key'] = strategy
tabular_data[-1]['max_drawdown_account'] = result['max_drawdown_account']
tabular_data[-1]['max_drawdown_abs'] = round_coin_value(
result['max_drawdown_abs'], result['stake_currency'], False)
return tabular_data
@@ -352,14 +345,14 @@ def generate_daily_stats(results: DataFrame) -> Dict[str, Any]:
}
def generate_strategy_stats(btdata: Dict[str, DataFrame],
def generate_strategy_stats(pairlist: List[str],
strategy: str,
content: Dict[str, Any],
min_date: datetime, max_date: datetime,
market_change: float
) -> Dict[str, Any]:
"""
:param btdata: Backtest data
:param pairlist: List of pairs to backtest
:param strategy: Strategy name
:param content: Backtest result data in the format:
{'results: results, 'config: config}}.
@@ -372,11 +365,11 @@ def generate_strategy_stats(btdata: Dict[str, DataFrame],
if not isinstance(results, DataFrame):
return {}
config = content['config']
max_open_trades = min(config['max_open_trades'], len(btdata.keys()))
max_open_trades = min(config['max_open_trades'], len(pairlist))
start_balance = config['dry_run_wallet']
stake_currency = config['stake_currency']
pair_results = generate_pair_metrics(btdata, stake_currency=stake_currency,
pair_results = generate_pair_metrics(pairlist, stake_currency=stake_currency,
starting_balance=start_balance,
results=results, skip_nan=False)
@@ -385,7 +378,7 @@ def generate_strategy_stats(btdata: Dict[str, DataFrame],
sell_reason_stats = generate_sell_reason_stats(max_open_trades=max_open_trades,
results=results)
left_open_results = generate_pair_metrics(btdata, stake_currency=stake_currency,
left_open_results = generate_pair_metrics(pairlist, stake_currency=stake_currency,
starting_balance=start_balance,
results=results.loc[results['is_open']],
skip_nan=True)
@@ -435,7 +428,7 @@ def generate_strategy_stats(btdata: Dict[str, DataFrame],
'trades_per_day': round(len(results) / backtest_days, 2),
'market_change': market_change,
'pairlist': list(btdata.keys()),
'pairlist': pairlist,
'stake_amount': config['stake_amount'],
'stake_currency': config['stake_currency'],
'stake_currency_decimals': decimals_per_coin(config['stake_currency']),
@@ -468,12 +461,14 @@ def generate_strategy_stats(btdata: Dict[str, DataFrame],
}
try:
max_drawdown, _, _, _, _ = calculate_max_drawdown(
max_drawdown_legacy, _, _, _, _, _ = calculate_max_drawdown(
results, value_col='profit_ratio')
drawdown_abs, drawdown_start, drawdown_end, high_val, low_val = calculate_max_drawdown(
results, value_col='profit_abs')
(drawdown_abs, drawdown_start, drawdown_end, high_val, low_val,
max_drawdown) = calculate_max_drawdown(
results, value_col='profit_abs', starting_balance=start_balance)
strat_stats.update({
'max_drawdown': max_drawdown,
'max_drawdown': max_drawdown_legacy, # Deprecated - do not use
'max_drawdown_account': max_drawdown,
'max_drawdown_abs': drawdown_abs,
'drawdown_start': drawdown_start.strftime(DATETIME_PRINT_FORMAT),
'drawdown_start_ts': drawdown_start.timestamp() * 1000,
@@ -493,6 +488,7 @@ def generate_strategy_stats(btdata: Dict[str, DataFrame],
except ValueError:
strat_stats.update({
'max_drawdown': 0.0,
'max_drawdown_account': 0.0,
'max_drawdown_abs': 0.0,
'max_drawdown_low': 0.0,
'max_drawdown_high': 0.0,
@@ -521,13 +517,13 @@ def generate_backtest_stats(btdata: Dict[str, DataFrame],
"""
result: Dict[str, Any] = {'strategy': {}}
market_change = calculate_market_change(btdata, 'close')
pairlist = list(btdata.keys())
for strategy, content in all_results.items():
strat_stats = generate_strategy_stats(btdata, strategy, content,
strat_stats = generate_strategy_stats(pairlist, strategy, content,
min_date, max_date, market_change=market_change)
result['strategy'][strategy] = strat_stats
strategy_results = generate_strategy_comparison(all_results=all_results)
strategy_results = generate_strategy_comparison(bt_stats=result['strategy'])
result['strategy_comparison'] = strategy_results
@@ -652,7 +648,7 @@ def text_table_strategy(strategy_results, stake_currency: str) -> str:
headers.append('Drawdown')
# Align drawdown string on the center two space separator.
drawdown = [f'{t["max_drawdown_per"]:.2f}' for t in strategy_results]
drawdown = [f'{t["max_drawdown_account"] * 100:.2f}' for t in strategy_results]
dd_pad_abs = max([len(t['max_drawdown_abs']) for t in strategy_results])
dd_pad_per = max([len(dd) for dd in drawdown])
drawdown = [f'{t["max_drawdown_abs"]:>{dd_pad_abs}} {stake_currency} {dd:>{dd_pad_per}}%'
@@ -737,7 +733,10 @@ def text_table_add_metrics(strat_results: Dict) -> str:
('Max balance', round_coin_value(strat_results['csum_max'],
strat_results['stake_currency'])),
('Drawdown', f"{strat_results['max_drawdown']:.2%}"),
# Compatibility to show old hyperopt results
('Drawdown (Account)', f"{strat_results['max_drawdown_account']:.2%}")
if 'max_drawdown_account' in strat_results else (
'Drawdown', f"{strat_results['max_drawdown']:.2%}"),
('Drawdown', round_coin_value(strat_results['max_drawdown_abs'],
strat_results['stake_currency'])),
('Drawdown high', round_coin_value(strat_results['max_drawdown_high'],