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freqtrade_origin/tests/edge/test_edge.py

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# pragma pylint: disable=missing-docstring, C0103, C0330
# pragma pylint: disable=protected-access, too-many-lines, invalid-name, too-many-arguments
import logging
import math
from unittest.mock import MagicMock
import arrow
import numpy as np
import pytest
from pandas import DataFrame, to_datetime
from freqtrade.data.converter import ohlcv_to_dataframe
from freqtrade.edge import Edge, PairInfo
from freqtrade.exceptions import OperationalException
from freqtrade.strategy.interface import SellType
from tests.conftest import get_patched_freqtradebot, log_has
from tests.optimize import (BTContainer, BTrade, _build_backtest_dataframe,
_get_frame_time_from_offset)
# Cases to be tested:
# 1) Open trade should be removed from the end
# 2) Two complete trades within dataframe (with sell hit for all)
# 3) Entered, sl 1%, candle drops 8% => Trade closed, 1% loss
# 4) Entered, sl 3%, candle drops 4%, recovers to 1% => Trade closed, 3% loss
# 5) Stoploss and sell are hit. should sell on stoploss
####################################################################
tests_start_time = arrow.get(2018, 10, 3)
timeframe_in_minute = 60
_ohlc = {'date': 0, 'buy': 1, 'open': 2, 'high': 3, 'low': 4, 'close': 5, 'sell': 6, 'volume': 7}
# Helpers for this test file
def _validate_ohlc(buy_ohlc_sell_matrice):
for index, ohlc in enumerate(buy_ohlc_sell_matrice):
# if not high < open < low or not high < close < low
if not ohlc[3] >= ohlc[2] >= ohlc[4] or not ohlc[3] >= ohlc[5] >= ohlc[4]:
raise Exception('Line ' + str(index + 1) + ' of ohlc has invalid values!')
return True
def _build_dataframe(buy_ohlc_sell_matrice):
_validate_ohlc(buy_ohlc_sell_matrice)
data = []
for ohlc in buy_ohlc_sell_matrice:
d = {
'date': tests_start_time.shift(
minutes=(
ohlc[0] *
timeframe_in_minute)).int_timestamp *
1000,
'buy': ohlc[1],
'open': ohlc[2],
'high': ohlc[3],
'low': ohlc[4],
'close': ohlc[5],
'sell': ohlc[6]}
data.append(d)
frame = DataFrame(data)
frame['date'] = to_datetime(frame['date'],
unit='ms',
utc=True,
infer_datetime_format=True)
return frame
def _time_on_candle(number):
return np.datetime64(tests_start_time.shift(
minutes=(number * timeframe_in_minute)).int_timestamp * 1000, 'ms')
# End helper functions
# Open trade should be removed from the end
tc0 = BTContainer(data=[
# D O H L C V B S
[0, 5000, 5025, 4975, 4987, 6172, 1, 0],
[1, 5000, 5025, 4975, 4987, 6172, 0, 1]], # enter trade (signal on last candle)
stop_loss=-0.99, roi={"0": float('inf')}, profit_perc=0.00,
trades=[]
)
# Two complete trades within dataframe(with sell hit for all)
tc1 = BTContainer(data=[
# D O H L C V B S
[0, 5000, 5025, 4975, 4987, 6172, 1, 0],
[1, 5000, 5025, 4975, 4987, 6172, 0, 1], # enter trade (signal on last candle)
[2, 5000, 5025, 4975, 4987, 6172, 0, 0], # exit at open
[3, 5000, 5025, 4975, 4987, 6172, 1, 0], # no action
[4, 5000, 5025, 4975, 4987, 6172, 0, 0], # should enter the trade
[5, 5000, 5025, 4975, 4987, 6172, 0, 1], # no action
[6, 5000, 5025, 4975, 4987, 6172, 0, 0], # should sell
],
stop_loss=-0.99, roi={"0": float('inf')}, profit_perc=0.00,
trades=[BTrade(sell_reason=SellType.SELL_SIGNAL, open_tick=1, close_tick=2),
BTrade(sell_reason=SellType.SELL_SIGNAL, open_tick=4, close_tick=6)]
)
# 3) Entered, sl 1%, candle drops 8% => Trade closed, 1% loss
tc2 = BTContainer(data=[
# D O H L C V B S
[0, 5000, 5025, 4975, 4987, 6172, 1, 0],
[1, 5000, 5025, 4600, 4987, 6172, 0, 0], # enter trade, stoploss hit
[2, 5000, 5025, 4975, 4987, 6172, 0, 0],
],
stop_loss=-0.01, roi={"0": float('inf')}, profit_perc=-0.01,
trades=[BTrade(sell_reason=SellType.STOP_LOSS, open_tick=1, close_tick=1)]
)
# 4) Entered, sl 3 %, candle drops 4%, recovers to 1 % = > Trade closed, 3 % loss
tc3 = BTContainer(data=[
# D O H L C V B S
[0, 5000, 5025, 4975, 4987, 6172, 1, 0],
[1, 5000, 5025, 4800, 4987, 6172, 0, 0], # enter trade, stoploss hit
[2, 5000, 5025, 4975, 4987, 6172, 0, 0],
],
stop_loss=-0.03, roi={"0": float('inf')}, profit_perc=-0.03,
trades=[BTrade(sell_reason=SellType.STOP_LOSS, open_tick=1, close_tick=1)]
)
# 5) Stoploss and sell are hit. should sell on stoploss
tc4 = BTContainer(data=[
# D O H L C V B S
[0, 5000, 5025, 4975, 4987, 6172, 1, 0],
[1, 5000, 5025, 4800, 4987, 6172, 0, 1], # enter trade, stoploss hit, sell signal
[2, 5000, 5025, 4975, 4987, 6172, 0, 0],
],
stop_loss=-0.03, roi={"0": float('inf')}, profit_perc=-0.03,
trades=[BTrade(sell_reason=SellType.STOP_LOSS, open_tick=1, close_tick=1)]
)
TESTS = [
tc0,
tc1,
tc2,
tc3,
tc4
]
@pytest.mark.parametrize("data", TESTS)
def test_edge_results(edge_conf, mocker, caplog, data) -> None:
"""
run functional tests
"""
freqtrade = get_patched_freqtradebot(mocker, edge_conf)
edge = Edge(edge_conf, freqtrade.exchange, freqtrade.strategy)
frame = _build_backtest_dataframe(data.data)
caplog.set_level(logging.DEBUG)
edge.fee = 0
trades = edge._find_trades_for_stoploss_range(frame, 'TEST/BTC', [data.stop_loss])
results = edge._fill_calculable_fields(DataFrame(trades)) if trades else DataFrame()
assert len(trades) == len(data.trades)
if not results.empty:
assert round(results["profit_ratio"].sum(), 3) == round(data.profit_perc, 3)
for c, trade in enumerate(data.trades):
res = results.iloc[c]
assert res.exit_type == trade.sell_reason
assert res.open_date == _get_frame_time_from_offset(trade.open_tick).replace(tzinfo=None)
assert res.close_date == _get_frame_time_from_offset(trade.close_tick).replace(tzinfo=None)
def test_adjust(mocker, edge_conf):
freqtrade = get_patched_freqtradebot(mocker, edge_conf)
edge = Edge(edge_conf, freqtrade.exchange, freqtrade.strategy)
mocker.patch('freqtrade.edge.Edge._cached_pairs', mocker.PropertyMock(
return_value={
'E/F': PairInfo(-0.01, 0.66, 3.71, 0.50, 1.71, 10, 60),
'C/D': PairInfo(-0.01, 0.66, 3.71, 0.50, 1.71, 10, 60),
'N/O': PairInfo(-0.01, 0.66, 3.71, 0.50, 1.71, 10, 60)
}
))
pairs = ['A/B', 'C/D', 'E/F', 'G/H']
assert(edge.adjust(pairs) == ['E/F', 'C/D'])
def test_stoploss(mocker, edge_conf):
freqtrade = get_patched_freqtradebot(mocker, edge_conf)
edge = Edge(edge_conf, freqtrade.exchange, freqtrade.strategy)
mocker.patch('freqtrade.edge.Edge._cached_pairs', mocker.PropertyMock(
return_value={
'E/F': PairInfo(-0.01, 0.66, 3.71, 0.50, 1.71, 10, 60),
'C/D': PairInfo(-0.01, 0.66, 3.71, 0.50, 1.71, 10, 60),
'N/O': PairInfo(-0.01, 0.66, 3.71, 0.50, 1.71, 10, 60)
}
))
assert edge.stoploss('E/F') == -0.01
def test_nonexisting_stoploss(mocker, edge_conf):
freqtrade = get_patched_freqtradebot(mocker, edge_conf)
edge = Edge(edge_conf, freqtrade.exchange, freqtrade.strategy)
mocker.patch('freqtrade.edge.Edge._cached_pairs', mocker.PropertyMock(
return_value={
'E/F': PairInfo(-0.01, 0.66, 3.71, 0.50, 1.71, 10, 60),
}
))
assert edge.stoploss('N/O') == -0.1
def test_stake_amount(mocker, edge_conf):
freqtrade = get_patched_freqtradebot(mocker, edge_conf)
edge = Edge(edge_conf, freqtrade.exchange, freqtrade.strategy)
mocker.patch('freqtrade.edge.Edge._cached_pairs', mocker.PropertyMock(
return_value={
'E/F': PairInfo(-0.02, 0.66, 3.71, 0.50, 1.71, 10, 60),
}
))
free = 100
total = 100
in_trade = 25
assert edge.stake_amount('E/F', free, total, in_trade) == 31.25
free = 20
total = 100
in_trade = 25
assert edge.stake_amount('E/F', free, total, in_trade) == 20
free = 0
total = 100
in_trade = 25
assert edge.stake_amount('E/F', free, total, in_trade) == 0
def test_nonexisting_stake_amount(mocker, edge_conf):
freqtrade = get_patched_freqtradebot(mocker, edge_conf)
edge = Edge(edge_conf, freqtrade.exchange, freqtrade.strategy)
mocker.patch('freqtrade.edge.Edge._cached_pairs', mocker.PropertyMock(
return_value={
'E/F': PairInfo(-0.11, 0.66, 3.71, 0.50, 1.71, 10, 60),
}
))
# should use strategy stoploss
assert edge.stake_amount('N/O', 1, 2, 1) == 0.15
def test_edge_heartbeat_calculate(mocker, edge_conf):
freqtrade = get_patched_freqtradebot(mocker, edge_conf)
edge = Edge(edge_conf, freqtrade.exchange, freqtrade.strategy)
heartbeat = edge_conf['edge']['process_throttle_secs']
# should not recalculate if heartbeat not reached
edge._last_updated = arrow.utcnow().int_timestamp - heartbeat + 1
assert edge.calculate() is False
def mocked_load_data(datadir, pairs=[], timeframe='0m',
timerange=None, *args, **kwargs):
hz = 0.1
base = 0.001
NEOBTC = [
[
tests_start_time.shift(minutes=(x * timeframe_in_minute)).int_timestamp * 1000,
math.sin(x * hz) / 1000 + base,
math.sin(x * hz) / 1000 + base + 0.0001,
math.sin(x * hz) / 1000 + base - 0.0001,
math.sin(x * hz) / 1000 + base,
123.45
] for x in range(0, 500)]
hz = 0.2
base = 0.002
LTCBTC = [
[
tests_start_time.shift(minutes=(x * timeframe_in_minute)).int_timestamp * 1000,
math.sin(x * hz) / 1000 + base,
math.sin(x * hz) / 1000 + base + 0.0001,
math.sin(x * hz) / 1000 + base - 0.0001,
math.sin(x * hz) / 1000 + base,
123.45
] for x in range(0, 500)]
pairdata = {'NEO/BTC': ohlcv_to_dataframe(NEOBTC, '1h', pair="NEO/BTC",
fill_missing=True),
'LTC/BTC': ohlcv_to_dataframe(LTCBTC, '1h', pair="LTC/BTC",
fill_missing=True)}
return pairdata
def test_edge_process_downloaded_data(mocker, edge_conf):
freqtrade = get_patched_freqtradebot(mocker, edge_conf)
mocker.patch('freqtrade.exchange.Exchange.get_fee', MagicMock(return_value=0.001))
mocker.patch('freqtrade.edge.edge_positioning.refresh_data', MagicMock())
mocker.patch('freqtrade.edge.edge_positioning.load_data', mocked_load_data)
edge = Edge(edge_conf, freqtrade.exchange, freqtrade.strategy)
assert edge.calculate()
assert len(edge._cached_pairs) == 2
assert edge._last_updated <= arrow.utcnow().int_timestamp + 2
def test_edge_process_no_data(mocker, edge_conf, caplog):
freqtrade = get_patched_freqtradebot(mocker, edge_conf)
mocker.patch('freqtrade.exchange.Exchange.get_fee', MagicMock(return_value=0.001))
mocker.patch('freqtrade.edge.edge_positioning.refresh_data', MagicMock())
mocker.patch('freqtrade.edge.edge_positioning.load_data', MagicMock(return_value={}))
edge = Edge(edge_conf, freqtrade.exchange, freqtrade.strategy)
assert not edge.calculate()
assert len(edge._cached_pairs) == 0
assert log_has("No data found. Edge is stopped ...", caplog)
assert edge._last_updated == 0
def test_edge_process_no_trades(mocker, edge_conf, caplog):
freqtrade = get_patched_freqtradebot(mocker, edge_conf)
mocker.patch('freqtrade.exchange.Exchange.get_fee', MagicMock(return_value=0.001))
mocker.patch('freqtrade.edge.edge_positioning.refresh_data', MagicMock())
mocker.patch('freqtrade.edge.edge_positioning.load_data', mocked_load_data)
# Return empty
mocker.patch('freqtrade.edge.Edge._find_trades_for_stoploss_range', MagicMock(return_value=[]))
edge = Edge(edge_conf, freqtrade.exchange, freqtrade.strategy)
assert not edge.calculate()
assert len(edge._cached_pairs) == 0
assert log_has("No trades found.", caplog)
def test_edge_init_error(mocker, edge_conf,):
edge_conf['stake_amount'] = 0.5
mocker.patch('freqtrade.exchange.Exchange.get_fee', MagicMock(return_value=0.001))
with pytest.raises(OperationalException, match='Edge works only with unlimited stake amount'):
get_patched_freqtradebot(mocker, edge_conf)
@pytest.mark.parametrize("fee,risk_reward_ratio,expectancy", [
(0.0005, 306.5384615384, 101.5128205128),
(0.001, 152.6923076923, 50.2307692308),
])
def test_process_expectancy(mocker, edge_conf, fee, risk_reward_ratio, expectancy):
edge_conf['edge']['min_trade_number'] = 2
freqtrade = get_patched_freqtradebot(mocker, edge_conf)
def get_fee(*args, **kwargs):
return fee
freqtrade.exchange.get_fee = get_fee
edge = Edge(edge_conf, freqtrade.exchange, freqtrade.strategy)
trades = [
{'pair': 'TEST/BTC',
'stoploss': -0.9,
'profit_percent': '',
'profit_abs': '',
'open_date': np.datetime64('2018-10-03T00:05:00.000000000'),
'close_date': np.datetime64('2018-10-03T00:10:00.000000000'),
'trade_duration': '',
'open_rate': 17,
'close_rate': 17,
'exit_type': 'sell_signal'},
{'pair': 'TEST/BTC',
'stoploss': -0.9,
'profit_percent': '',
'profit_abs': '',
'open_date': np.datetime64('2018-10-03T00:20:00.000000000'),
'close_date': np.datetime64('2018-10-03T00:25:00.000000000'),
'trade_duration': '',
'open_rate': 20,
'close_rate': 20,
'exit_type': 'sell_signal'},
{'pair': 'TEST/BTC',
'stoploss': -0.9,
'profit_percent': '',
'profit_abs': '',
'open_date': np.datetime64('2018-10-03T00:30:00.000000000'),
'close_date': np.datetime64('2018-10-03T00:40:00.000000000'),
'trade_duration': '',
'open_rate': 26,
'close_rate': 34,
'exit_type': 'sell_signal'}
]
trades_df = DataFrame(trades)
trades_df = edge._fill_calculable_fields(trades_df)
final = edge._process_expectancy(trades_df)
assert len(final) == 1
assert 'TEST/BTC' in final
assert final['TEST/BTC'].stoploss == -0.9
assert round(final['TEST/BTC'].winrate, 10) == 0.3333333333
assert round(final['TEST/BTC'].risk_reward_ratio, 10) == risk_reward_ratio
assert round(final['TEST/BTC'].required_risk_reward, 10) == 2.0
assert round(final['TEST/BTC'].expectancy, 10) == expectancy
# Pop last item so no trade is profitable
trades.pop()
trades_df = DataFrame(trades)
trades_df = edge._fill_calculable_fields(trades_df)
final = edge._process_expectancy(trades_df)
assert len(final) == 0
assert isinstance(final, dict)
def test_process_expectancy_remove_pumps(mocker, edge_conf, fee,):
edge_conf['edge']['min_trade_number'] = 2
edge_conf['edge']['remove_pumps'] = True
freqtrade = get_patched_freqtradebot(mocker, edge_conf)
freqtrade.exchange.get_fee = fee
edge = Edge(edge_conf, freqtrade.exchange, freqtrade.strategy)
trades = [
{'pair': 'TEST/BTC',
'stoploss': -0.9,
'profit_percent': '',
'profit_abs': '',
'open_date': np.datetime64('2018-10-03T00:05:00.000000000'),
'close_date': np.datetime64('2018-10-03T00:10:00.000000000'),
'open_index': 1,
'close_index': 1,
'trade_duration': '',
'open_rate': 17,
'close_rate': 15,
'exit_type': 'sell_signal'},
{'pair': 'TEST/BTC',
'stoploss': -0.9,
'profit_percent': '',
'profit_abs': '',
'open_date': np.datetime64('2018-10-03T00:20:00.000000000'),
'close_date': np.datetime64('2018-10-03T00:25:00.000000000'),
'open_index': 4,
'close_index': 4,
'trade_duration': '',
'open_rate': 20,
'close_rate': 10,
'exit_type': 'sell_signal'},
{'pair': 'TEST/BTC',
'stoploss': -0.9,
'profit_percent': '',
'profit_abs': '',
'open_date': np.datetime64('2018-10-03T00:20:00.000000000'),
'close_date': np.datetime64('2018-10-03T00:25:00.000000000'),
'open_index': 4,
'close_index': 4,
'trade_duration': '',
'open_rate': 20,
'close_rate': 10,
'exit_type': 'sell_signal'},
{'pair': 'TEST/BTC',
'stoploss': -0.9,
'profit_percent': '',
'profit_abs': '',
'open_date': np.datetime64('2018-10-03T00:20:00.000000000'),
'close_date': np.datetime64('2018-10-03T00:25:00.000000000'),
'open_index': 4,
'close_index': 4,
'trade_duration': '',
'open_rate': 20,
'close_rate': 10,
'exit_type': 'sell_signal'},
{'pair': 'TEST/BTC',
'stoploss': -0.9,
'profit_percent': '',
'profit_abs': '',
'open_date': np.datetime64('2018-10-03T00:20:00.000000000'),
'close_date': np.datetime64('2018-10-03T00:25:00.000000000'),
'open_index': 4,
'close_index': 4,
'trade_duration': '',
'open_rate': 20,
'close_rate': 10,
'exit_type': 'sell_signal'},
{'pair': 'TEST/BTC',
'stoploss': -0.9,
'profit_percent': '',
'profit_abs': '',
'open_date': np.datetime64('2018-10-03T00:30:00.000000000'),
'close_date': np.datetime64('2018-10-03T00:40:00.000000000'),
'open_index': 6,
'close_index': 7,
'trade_duration': '',
'open_rate': 26,
'close_rate': 134,
'exit_type': 'sell_signal'}
]
trades_df = DataFrame(trades)
trades_df = edge._fill_calculable_fields(trades_df)
final = edge._process_expectancy(trades_df)
assert 'TEST/BTC' in final
assert final['TEST/BTC'].stoploss == -0.9
assert final['TEST/BTC'].nb_trades == len(trades_df) - 1
assert round(final['TEST/BTC'].winrate, 10) == 0.0
def test_process_expectancy_only_wins(mocker, edge_conf, fee,):
edge_conf['edge']['min_trade_number'] = 2
freqtrade = get_patched_freqtradebot(mocker, edge_conf)
freqtrade.exchange.get_fee = fee
edge = Edge(edge_conf, freqtrade.exchange, freqtrade.strategy)
trades = [
{'pair': 'TEST/BTC',
'stoploss': -0.9,
'profit_percent': '',
'profit_abs': '',
'open_date': np.datetime64('2018-10-03T00:05:00.000000000'),
'close_date': np.datetime64('2018-10-03T00:10:00.000000000'),
'open_index': 1,
'close_index': 1,
'trade_duration': '',
'open_rate': 15,
'close_rate': 17,
'exit_type': 'sell_signal'},
{'pair': 'TEST/BTC',
'stoploss': -0.9,
'profit_percent': '',
'profit_abs': '',
'open_date': np.datetime64('2018-10-03T00:20:00.000000000'),
'close_date': np.datetime64('2018-10-03T00:25:00.000000000'),
'open_index': 4,
'close_index': 4,
'trade_duration': '',
'open_rate': 10,
'close_rate': 20,
'exit_type': 'sell_signal'},
{'pair': 'TEST/BTC',
'stoploss': -0.9,
'profit_percent': '',
'profit_abs': '',
'open_date': np.datetime64('2018-10-03T00:30:00.000000000'),
'close_date': np.datetime64('2018-10-03T00:40:00.000000000'),
'open_index': 6,
'close_index': 7,
'trade_duration': '',
'open_rate': 26,
'close_rate': 134,
'exit_type': 'sell_signal'}
]
trades_df = DataFrame(trades)
trades_df = edge._fill_calculable_fields(trades_df)
final = edge._process_expectancy(trades_df)
assert 'TEST/BTC' in final
assert final['TEST/BTC'].stoploss == -0.9
assert final['TEST/BTC'].nb_trades == len(trades_df)
assert round(final['TEST/BTC'].winrate, 10) == 1.0
assert round(final['TEST/BTC'].risk_reward_ratio, 10) == float('inf')
assert round(final['TEST/BTC'].expectancy, 10) == float('inf')
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