Rename method to be public
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@ -1,7 +1,7 @@
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import logging
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from datetime import timedelta
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from pathlib import Path
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from typing import Dict, Tuple, List, Any
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from typing import Dict, List, Any
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from pandas import DataFrame
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from tabulate import tabulate
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@ -59,7 +59,7 @@ def _generate_result_line(result: DataFrame, max_open_trades: int, first_column:
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'trades': len(result.index),
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'profit_mean': result.profit_percent.mean(),
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'profit_mean_pct': result.profit_percent.mean() * 100.0,
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'profit_sum': result.profit_percent.sum() * 100.0,
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'profit_sum': result.profit_percent.sum(),
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'profit_sum_pct': result.profit_percent.sum() * 100.0,
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'profit_total_abs': result.profit_abs.sum(),
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'profit_total_pct': result.profit_percent.sum() * 100.0 / max_open_trades,
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@ -78,8 +78,8 @@ def _generate_result_line(result: DataFrame, max_open_trades: int, first_column:
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}
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def _generate_pair_results(data: Dict[str, Dict], stake_currency: str, max_open_trades: int,
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results: DataFrame, skip_nan: bool = False) -> List[Dict]:
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def generate_pair_results(data: Dict[str, Dict], stake_currency: str, max_open_trades: int,
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results: DataFrame, skip_nan: bool = False) -> List[Dict]:
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"""
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Generates and returns a list for the given backtest data and the results dataframe
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:param data: Dict of <pair: dataframe> containing data that was used during backtesting.
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@ -161,7 +161,8 @@ def generate_sell_reason_stats(max_open_trades: int,
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return tabular_data
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def generate_text_table_sell_reason(sell_reason_stats: List[Dict[str, Any]], stake_currency: str) -> str:
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def generate_text_table_sell_reason(sell_reason_stats: List[Dict[str, Any]],
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stake_currency: str) -> str:
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"""
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Generate small table outlining Backtest results
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:param stake_currency: Stakecurrency used
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@ -257,9 +258,9 @@ def show_backtest_results(config: Dict, btdata: Dict[str, DataFrame],
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for strategy, results in all_results.items():
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print(f"Result for strategy {strategy}")
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pair_results = _generate_pair_results(btdata, stake_currency=config['stake_currency'],
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max_open_trades=config['max_open_trades'],
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results=results, skip_nan=False)
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pair_results = generate_pair_results(btdata, stake_currency=config['stake_currency'],
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max_open_trades=config['max_open_trades'],
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results=results, skip_nan=False)
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table = generate_text_table(pair_results, stake_currency=config['stake_currency'])
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if isinstance(table, str):
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print(' BACKTESTING REPORT '.center(len(table.splitlines()[0]), '='))
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@ -274,10 +275,10 @@ def show_backtest_results(config: Dict, btdata: Dict[str, DataFrame],
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print(' SELL REASON STATS '.center(len(table.splitlines()[0]), '='))
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print(table)
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left_open_results = _generate_pair_results(btdata, stake_currency=config['stake_currency'],
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max_open_trades=config['max_open_trades'],
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results=results.loc[results['open_at_end']],
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skip_nan=True)
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left_open_results = generate_pair_results(btdata, stake_currency=config['stake_currency'],
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max_open_trades=config['max_open_trades'],
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results=results.loc[results['open_at_end']],
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skip_nan=True)
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table = generate_text_table(left_open_results, stake_currency=config['stake_currency'])
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if isinstance(table, str):
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print(' LEFT OPEN TRADES REPORT '.center(len(table.splitlines()[0]), '='))
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@ -6,7 +6,7 @@ from arrow import Arrow
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from freqtrade.edge import PairInfo
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from freqtrade.optimize.optimize_reports import (
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_generate_pair_results, generate_edge_table, generate_sell_reason_stats,
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generate_pair_results, generate_edge_table, generate_sell_reason_stats,
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generate_text_table, generate_text_table_sell_reason,
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generate_text_table_strategy, store_backtest_result)
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from freqtrade.strategy.interface import SellType
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@ -38,13 +38,37 @@ def test_generate_text_table(default_conf, mocker):
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' 15.00 | 0:20:00 | 2 | 0 | 0 |'
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)
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pair_results = _generate_pair_results(data={'ETH/BTC': {}}, stake_currency='BTC',
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max_open_trades=2,
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results=results)
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pair_results = generate_pair_results(data={'ETH/BTC': {}}, stake_currency='BTC',
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max_open_trades=2, results=results)
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assert generate_text_table(pair_results,
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stake_currency='BTC') == result_str
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def test_generate_pair_results(default_conf, mocker):
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results = pd.DataFrame(
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{
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'pair': ['ETH/BTC', 'ETH/BTC'],
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'profit_percent': [0.1, 0.2],
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'profit_abs': [0.2, 0.4],
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'trade_duration': [10, 30],
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'wins': [2, 0],
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'draws': [0, 0],
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'losses': [0, 0]
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}
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)
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pair_results = generate_pair_results(data={'ETH/BTC': {}}, stake_currency='BTC',
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max_open_trades=2, results=results)
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assert isinstance(pair_results, list)
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assert len(pair_results) == 2
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assert pair_results[-1]['key'] == 'TOTAL'
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assert (
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pytest.approx(pair_results[-1]['profit_mean_pct']) == pair_results[-1]['profit_mean'] * 100)
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assert (
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pytest.approx(pair_results[-1]['profit_sum_pct']) == pair_results[-1]['profit_sum'] * 100)
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def test_generate_text_table_sell_reason(default_conf):
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results = pd.DataFrame(
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