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Merge branch 'develop' into sortino_hyperopt_loss

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This commit is contained in:
Yazeed Al Oyoun
2020-02-19 02:37:25 +01:00
committed by GitHub
parent df26c357d2 16cbd441ce
commit 3fb6818bd8
80 changed files with 2005 additions and 491 deletions
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6
tests/optimize/__init__.py
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@@ -1,4 +1,4 @@
from typing import Dict, List, NamedTuple
from typing import Dict, List, NamedTuple, Optional
import arrow
from pandas import DataFrame
@@ -23,14 +23,14 @@ class BTContainer(NamedTuple):
"""
Minimal BacktestContainer defining Backtest inputs and results.
"""
data: List[float]
data: List[List[float]]
stop_loss: float
roi: Dict[str, float]
trades: List[BTrade]
profit_perc: float
trailing_stop: bool = False
trailing_only_offset_is_reached: bool = False
trailing_stop_positive: float = None
trailing_stop_positive: Optional[float] = None
trailing_stop_positive_offset: float = 0.0
use_sell_signal: bool = False

2
tests/optimize/test_backtest_detail.py
View File

@@ -364,7 +364,7 @@ def test_backtest_results(default_conf, fee, mocker, caplog, data) -> None:
default_conf["trailing_stop"] = data.trailing_stop
default_conf["trailing_only_offset_is_reached"] = data.trailing_only_offset_is_reached
# Only add this to configuration If it's necessary
if data.trailing_stop_positive:
if data.trailing_stop_positive is not None:
default_conf["trailing_stop_positive"] = data.trailing_stop_positive
default_conf["trailing_stop_positive_offset"] = data.trailing_stop_positive_offset
default_conf["ask_strategy"] = {"use_sell_signal": data.use_sell_signal}

10
tests/optimize/test_backtesting.py
View File

@@ -20,8 +20,8 @@ from freqtrade.data.dataprovider import DataProvider
from freqtrade.data.history import get_timerange
from freqtrade.exceptions import DependencyException, OperationalException
from freqtrade.optimize.backtesting import Backtesting
from freqtrade.resolvers import StrategyResolver
from freqtrade.state import RunMode
from freqtrade.strategy.default_strategy import DefaultStrategy
from freqtrade.strategy.interface import SellType
from tests.conftest import (get_args, log_has, log_has_re, patch_exchange,
patched_configuration_load_config_file)
@@ -287,8 +287,8 @@ def test_start(mocker, fee, default_conf, caplog) -> None:
'--config', 'config.json',
'--strategy', 'DefaultStrategy',
]
args = get_args(args)
start_backtesting(args)
pargs = get_args(args)
start_backtesting(pargs)
assert log_has('Starting freqtrade in Backtesting mode', caplog)
assert start_mock.call_count == 1
@@ -350,7 +350,9 @@ def test_tickerdata_to_dataframe_bt(default_conf, mocker, testdatadir) -> None:
assert len(data['UNITTEST/BTC']) == 102
# Load strategy to compare the result between Backtesting function and strategy are the same
strategy = DefaultStrategy(default_conf)
default_conf.update({'strategy': 'DefaultStrategy'})
strategy = StrategyResolver.load_strategy(default_conf)
data2 = strategy.tickerdata_to_dataframe(tickerlist)
assert data['UNITTEST/BTC'].equals(data2['UNITTEST/BTC'])

4
tests/optimize/test_edge_cli.py
View File

@@ -82,8 +82,8 @@ def test_start(mocker, fee, edge_conf, caplog) -> None:
'--config', 'config.json',
'--strategy', 'DefaultStrategy',
]
args = get_args(args)
start_edge(args)
pargs = get_args(args)
start_edge(pargs)
assert log_has('Starting freqtrade in Edge mode', caplog)
assert start_mock.call_count == 1

46
tests/optimize/test_hyperopt.py
View File

@@ -2,6 +2,7 @@
import locale
from datetime import datetime
from pathlib import Path
from typing import Dict, List
from unittest.mock import MagicMock, PropertyMock
import pandas as pd
@@ -9,7 +10,8 @@ import pytest
from arrow import Arrow
from filelock import Timeout
from freqtrade.commands.optimize_commands import setup_optimize_configuration, start_hyperopt
from freqtrade.commands.optimize_commands import (setup_optimize_configuration,
start_hyperopt)
from freqtrade.data.converter import parse_ticker_dataframe
from freqtrade.data.history import load_tickerdata_file
from freqtrade.exceptions import OperationalException
@@ -54,7 +56,7 @@ def hyperopt_results():
# Functions for recurrent object patching
def create_trials(mocker, hyperopt, testdatadir) -> None:
def create_trials(mocker, hyperopt, testdatadir) -> List[Dict]:
"""
When creating trials, mock the hyperopt Trials so that *by default*
- we don't create any pickle'd files in the filesystem
@@ -228,10 +230,10 @@ def test_start_not_installed(mocker, default_conf, caplog, import_fails) -> None
'--hyperopt', 'DefaultHyperOpt',
'--epochs', '5'
]
args = get_args(args)
pargs = get_args(args)
with pytest.raises(OperationalException, match=r"Please ensure that the hyperopt dependencies"):
start_hyperopt(args)
start_hyperopt(pargs)
def test_start(mocker, default_conf, caplog) -> None:
@@ -246,8 +248,8 @@ def test_start(mocker, default_conf, caplog) -> None:
'--hyperopt', 'DefaultHyperOpt',
'--epochs', '5'
]
args = get_args(args)
start_hyperopt(args)
pargs = get_args(args)
start_hyperopt(pargs)
assert log_has('Starting freqtrade in Hyperopt mode', caplog)
assert start_mock.call_count == 1
@@ -269,9 +271,9 @@ def test_start_no_data(mocker, default_conf, caplog) -> None:
'--hyperopt', 'DefaultHyperOpt',
'--epochs', '5'
]
args = get_args(args)
pargs = get_args(args)
with pytest.raises(OperationalException, match='No data found. Terminating.'):
start_hyperopt(args)
start_hyperopt(pargs)
def test_start_filelock(mocker, default_conf, caplog) -> None:
@@ -286,16 +288,19 @@ def test_start_filelock(mocker, default_conf, caplog) -> None:
'--hyperopt', 'DefaultHyperOpt',
'--epochs', '5'
]
args = get_args(args)
start_hyperopt(args)
pargs = get_args(args)
start_hyperopt(pargs)
assert log_has("Another running instance of freqtrade Hyperopt detected.", caplog)
def test_loss_calculation_prefer_correct_trade_count(default_conf, hyperopt_results) -> None:
hl = HyperOptLossResolver.load_hyperoptloss(default_conf)
correct = hl.hyperopt_loss_function(hyperopt_results, 600)
over = hl.hyperopt_loss_function(hyperopt_results, 600 + 100)
under = hl.hyperopt_loss_function(hyperopt_results, 600 - 100)
correct = hl.hyperopt_loss_function(hyperopt_results, 600,
datetime(2019, 1, 1), datetime(2019, 5, 1))
over = hl.hyperopt_loss_function(hyperopt_results, 600 + 100,
datetime(2019, 1, 1), datetime(2019, 5, 1))
under = hl.hyperopt_loss_function(hyperopt_results, 600 - 100,
datetime(2019, 1, 1), datetime(2019, 5, 1))
assert over > correct
assert under > correct
@@ -305,8 +310,10 @@ def test_loss_calculation_prefer_shorter_trades(default_conf, hyperopt_results)
resultsb.loc[1, 'trade_duration'] = 20
hl = HyperOptLossResolver.load_hyperoptloss(default_conf)
longer = hl.hyperopt_loss_function(hyperopt_results, 100)
shorter = hl.hyperopt_loss_function(resultsb, 100)
longer = hl.hyperopt_loss_function(hyperopt_results, 100,
datetime(2019, 1, 1), datetime(2019, 5, 1))
shorter = hl.hyperopt_loss_function(resultsb, 100,
datetime(2019, 1, 1), datetime(2019, 5, 1))
assert shorter < longer
@@ -317,9 +324,12 @@ def test_loss_calculation_has_limited_profit(default_conf, hyperopt_results) ->
results_under['profit_percent'] = hyperopt_results['profit_percent'] / 2
hl = HyperOptLossResolver.load_hyperoptloss(default_conf)
correct = hl.hyperopt_loss_function(hyperopt_results, 600)
over = hl.hyperopt_loss_function(results_over, 600)
under = hl.hyperopt_loss_function(results_under, 600)
correct = hl.hyperopt_loss_function(hyperopt_results, 600,
datetime(2019, 1, 1), datetime(2019, 5, 1))
over = hl.hyperopt_loss_function(results_over, 600,
datetime(2019, 1, 1), datetime(2019, 5, 1))
under = hl.hyperopt_loss_function(results_under, 600,
datetime(2019, 1, 1), datetime(2019, 5, 1))
assert over < correct
assert under > correct

74
tests/optimize/test_optimize_reports.py
View File

@@ -15,20 +15,21 @@ def test_generate_text_table(default_conf, mocker):
'profit_percent': [0.1, 0.2],
'profit_abs': [0.2, 0.4],
'trade_duration': [10, 30],
'profit': [2, 0],
'loss': [0, 0]
'wins': [2, 0],
'draws': [0, 0],
'losses': [0, 0]
}
)
result_str = (
'| Pair | Buy Count | Avg Profit % | Cum Profit % | Tot Profit BTC '
'| Tot Profit % | Avg Duration | Wins | Losses |\n'
'|:--------|------------:|---------------:|---------------:|-----------------:'
'|---------------:|:---------------|-------:|---------:|\n'
'| ETH/BTC | 2 | 15.00 | 30.00 | 0.60000000 '
'| 15.00 | 0:20:00 | 2 | 0 |\n'
'| TOTAL | 2 | 15.00 | 30.00 | 0.60000000 '
'| 15.00 | 0:20:00 | 2 | 0 |'
'| Pair | Buys | Avg Profit % | Cum Profit % | Tot Profit BTC |'
' Tot Profit % | Avg Duration | Wins | Draws | Losses |\n'
'|:--------|-------:|---------------:|---------------:|-----------------:|'
'---------------:|:---------------|-------:|--------:|---------:|\n'
'| ETH/BTC | 2 | 15.00 | 30.00 | 0.60000000 |'
' 15.00 | 0:20:00 | 2 | 0 | 0 |\n'
'| TOTAL | 2 | 15.00 | 30.00 | 0.60000000 |'
' 15.00 | 0:20:00 | 2 | 0 | 0 |'
)
assert generate_text_table(data={'ETH/BTC': {}},
stake_currency='BTC', max_open_trades=2,
@@ -43,21 +44,22 @@ def test_generate_text_table_sell_reason(default_conf, mocker):
'profit_percent': [0.1, 0.2, -0.1],
'profit_abs': [0.2, 0.4, -0.2],
'trade_duration': [10, 30, 10],
'profit': [2, 0, 0],
'loss': [0, 0, 1],
'wins': [2, 0, 0],
'draws': [0, 0, 0],
'losses': [0, 0, 1],
'sell_reason': [SellType.ROI, SellType.ROI, SellType.STOP_LOSS]
}
)
result_str = (
'| Sell Reason | Sell Count | Wins | Losses | Avg Profit % |'
' Cum Profit % | Tot Profit BTC | Tot Profit % |\n'
'|:--------------|-------------:|-------:|---------:|---------------:|'
'---------------:|-----------------:|---------------:|\n'
'| roi | 2 | 2 | 0 | 15 |'
' 30 | 0.6 | 15 |\n'
'| stop_loss | 1 | 0 | 1 | -10 |'
' -10 | -0.2 | -5 |'
'| Sell Reason | Sells | Wins | Draws | Losses |'
' Avg Profit % | Cum Profit % | Tot Profit BTC | Tot Profit % |\n'
'|:--------------|--------:|-------:|--------:|---------:|'
'---------------:|---------------:|-----------------:|---------------:|\n'
'| roi | 2 | 2 | 0 | 0 |'
' 15 | 30 | 0.6 | 15 |\n'
'| stop_loss | 1 | 0 | 0 | 1 |'
' -10 | -10 | -0.2 | -5 |'
)
assert generate_text_table_sell_reason(
data={'ETH/BTC': {}},
@@ -67,38 +69,40 @@ def test_generate_text_table_sell_reason(default_conf, mocker):
def test_generate_text_table_strategy(default_conf, mocker):
results = {}
results['ETH/BTC'] = pd.DataFrame(
results['TestStrategy1'] = pd.DataFrame(
{
'pair': ['ETH/BTC', 'ETH/BTC', 'ETH/BTC'],
'profit_percent': [0.1, 0.2, 0.3],
'profit_abs': [0.2, 0.4, 0.5],
'trade_duration': [10, 30, 10],
'profit': [2, 0, 0],
'loss': [0, 0, 1],
'wins': [2, 0, 0],
'draws': [0, 0, 0],
'losses': [0, 0, 1],
'sell_reason': [SellType.ROI, SellType.ROI, SellType.STOP_LOSS]
}
)
results['LTC/BTC'] = pd.DataFrame(
results['TestStrategy2'] = pd.DataFrame(
{
'pair': ['LTC/BTC', 'LTC/BTC', 'LTC/BTC'],
'profit_percent': [0.4, 0.2, 0.3],
'profit_abs': [0.4, 0.4, 0.5],
'trade_duration': [15, 30, 15],
'profit': [4, 1, 0],
'loss': [0, 0, 1],
'wins': [4, 1, 0],
'draws': [0, 0, 0],
'losses': [0, 0, 1],
'sell_reason': [SellType.ROI, SellType.ROI, SellType.STOP_LOSS]
}
)
result_str = (
'| Strategy | Buy Count | Avg Profit % | Cum Profit % | Tot Profit BTC '
'| Tot Profit % | Avg Duration | Wins | Losses |\n'
'|:-----------|------------:|---------------:|---------------:|-----------------:'
'|---------------:|:---------------|-------:|---------:|\n'
'| ETH/BTC | 3 | 20.00 | 60.00 '
'| 1.10000000 | 30.00 | 0:17:00 | 3 | 0 |\n'
'| LTC/BTC | 3 | 30.00 | 90.00 '
'| 1.30000000 | 45.00 | 0:20:00 | 3 | 0 |'
'| Strategy | Buys | Avg Profit % | Cum Profit % | Tot'
' Profit BTC | Tot Profit % | Avg Duration | Wins | Draws | Losses |\n'
'|:--------------|-------:|---------------:|---------------:|------'
'-----------:|---------------:|:---------------|-------:|--------:|---------:|\n'
'| TestStrategy1 | 3 | 20.00 | 60.00 | '
' 1.10000000 | 30.00 | 0:17:00 | 3 | 0 | 0 |\n'
'| TestStrategy2 | 3 | 30.00 | 90.00 | '
' 1.30000000 | 45.00 | 0:20:00 | 3 | 0 | 0 |'
)
assert generate_text_table_strategy('BTC', 2, all_results=results) == result_str
@@ -111,4 +115,4 @@ def test_generate_edge_table(edge_conf, mocker):
assert generate_edge_table(results).count(':|') == 7
assert generate_edge_table(results).count('| ETH/BTC |') == 1
assert generate_edge_table(results).count(
'| risk reward ratio | required risk reward | expectancy |') == 1
'| Risk Reward Ratio | Required Risk Reward | Expectancy |') == 1