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Adapt tests to new loss-function method
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@ -18,6 +18,7 @@ from pandas import DataFrame
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from skopt import Optimizer
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from skopt.space import Dimension
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from freqtrade import OperationalException
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from freqtrade.configuration import Arguments
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from freqtrade.data.history import load_data, get_timeframe
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from freqtrade.optimize.backtesting import Backtesting
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@ -71,18 +72,17 @@ class Hyperopt(Backtesting):
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self.trials: List = []
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# Assign loss function
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if self.config['loss_function'] == 'legacy':
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if self.config.get('loss_function', 'legacy') == 'legacy':
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self.calculate_loss = hyperopt_loss_legacy
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elif (self.config['loss_function'] == 'custom' and
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hasattr(self.custom_hyperopt, 'hyperopt_loss_custom')):
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self.calculate_loss = self.custom_hyperopt.hyperopt_loss_custom # type: ignore
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# Implement fallback to avoid odd crashes when custom-hyperopt fails to load.
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# TODO: Maybe this should just stop hyperopt completely?
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if not hasattr(self.custom_hyperopt, 'hyperopt_loss_custom'):
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logger.warning("Could not load hyperopt configuration. "
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"Falling back to legacy configuration.")
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self.calculate_loss = hyperopt_loss_legacy
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raise OperationalException("Could not load hyperopt loss function.")
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# Populate functions here (hasattr is slow so should not be run during "regular" operations)
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if hasattr(self.custom_hyperopt, 'populate_buy_trend'):
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@ -2,20 +2,24 @@
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import os
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from datetime import datetime
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from unittest.mock import MagicMock
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from filelock import Timeout
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import pandas as pd
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import pytest
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from arrow import Arrow
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from filelock import Timeout
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from freqtrade import DependencyException
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from freqtrade.data.converter import parse_ticker_dataframe
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from freqtrade.data.history import load_tickerdata_file
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from freqtrade.optimize.default_hyperopt import DefaultHyperOpts
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from freqtrade.optimize.hyperopt import Hyperopt, HYPEROPT_LOCKFILE, TICKERDATA_PICKLE
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from freqtrade.optimize import setup_configuration, start_hyperopt
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from freqtrade.optimize.default_hyperopt import DefaultHyperOpts
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from freqtrade.optimize.hyperopt import (HYPEROPT_LOCKFILE, TICKERDATA_PICKLE,
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Hyperopt)
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from freqtrade.resolvers.hyperopt_resolver import HyperOptResolver
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from freqtrade.state import RunMode
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from freqtrade.tests.conftest import (get_args, log_has, log_has_re, patch_exchange,
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from freqtrade.strategy.interface import SellType
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from freqtrade.tests.conftest import (get_args, log_has, log_has_re,
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patch_exchange,
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patched_configuration_load_config_file)
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@ -25,6 +29,21 @@ def hyperopt(default_conf, mocker):
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return Hyperopt(default_conf)
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@pytest.fixture(scope='function')
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def hyperopt_results():
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return pd.DataFrame(
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{
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'pair': ['ETH/BTC', 'ETH/BTC', 'ETH/BTC'],
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'profit_percent': [0.1, 0.2, 0.3],
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'profit_abs': [0.2, 0.4, 0.5],
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'trade_duration': [10, 30, 10],
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'profit': [2, 0, 0],
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'loss': [0, 0, 1],
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'sell_reason': [SellType.ROI, SellType.ROI, SellType.STOP_LOSS]
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}
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)
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# Functions for recurrent object patching
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def create_trials(mocker, hyperopt) -> None:
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"""
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@ -254,26 +273,33 @@ def test_start_filelock(mocker, default_conf, caplog) -> None:
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)
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def test_loss_calculation_prefer_correct_trade_count(hyperopt) -> None:
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correct = hyperopt.calculate_loss(1, hyperopt.target_trades, 20)
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over = hyperopt.calculate_loss(1, hyperopt.target_trades + 100, 20)
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under = hyperopt.calculate_loss(1, hyperopt.target_trades - 100, 20)
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def test_loss_calculation_prefer_correct_trade_count(hyperopt, hyperopt_results) -> None:
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correct = hyperopt.calculate_loss(hyperopt_results, hyperopt.target_trades)
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over = hyperopt.calculate_loss(hyperopt_results, hyperopt.target_trades + 100)
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under = hyperopt.calculate_loss(hyperopt_results, hyperopt.target_trades - 100)
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assert over > correct
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assert under > correct
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def test_loss_calculation_prefer_shorter_trades(hyperopt) -> None:
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shorter = hyperopt.calculate_loss(1, 100, 20)
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longer = hyperopt.calculate_loss(1, 100, 30)
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def test_loss_calculation_prefer_shorter_trades(hyperopt, hyperopt_results) -> None:
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resultsb = hyperopt_results.copy()
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resultsb['trade_duration'][1] = 20
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longer = hyperopt.calculate_loss(hyperopt_results, 100)
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shorter = hyperopt.calculate_loss(resultsb, 100)
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assert shorter < longer
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def test_loss_calculation_has_limited_profit(hyperopt) -> None:
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correct = hyperopt.calculate_loss(hyperopt.expected_max_profit, hyperopt.target_trades, 20)
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over = hyperopt.calculate_loss(hyperopt.expected_max_profit * 2, hyperopt.target_trades, 20)
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under = hyperopt.calculate_loss(hyperopt.expected_max_profit / 2, hyperopt.target_trades, 20)
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assert over == correct
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def test_loss_calculation_has_limited_profit(hyperopt, hyperopt_results) -> None:
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results_over = hyperopt_results.copy()
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results_over['profit_percent'] = hyperopt_results['profit_percent'] * 2
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results_under = hyperopt_results.copy()
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results_under['profit_percent'] = hyperopt_results['profit_percent'] / 2
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correct = hyperopt.calculate_loss(hyperopt_results, hyperopt.target_trades)
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over = hyperopt.calculate_loss(results_over, hyperopt.target_trades)
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under = hyperopt.calculate_loss(results_under, hyperopt.target_trades)
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assert over < correct
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assert under > correct
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@ -472,7 +498,7 @@ def test_generate_optimizer(mocker, default_conf) -> None:
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)
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mocker.patch(
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'freqtrade.optimize.hyperopt.get_timeframe',
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MagicMock(return_value=(datetime(2017, 12, 10), datetime(2017, 12, 13)))
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MagicMock(return_value=(Arrow(2017, 12, 10), Arrow(2017, 12, 13)))
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)
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patch_exchange(mocker)
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mocker.patch('freqtrade.optimize.hyperopt.load', MagicMock())
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