2017-12-26 08:08:10 +00:00
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# pragma pylint: disable=missing-docstring,W0212,C0103
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2018-01-31 17:37:38 +00:00
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import logging
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2018-02-08 19:49:43 +00:00
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from unittest.mock import MagicMock
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import pandas as pd
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2017-12-26 08:08:10 +00:00
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from freqtrade.optimize.hyperopt import calculate_loss, TARGET_TRADES, EXPECTED_MAX_PROFIT, start, \
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2018-02-09 18:59:06 +00:00
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log_results, save_trials, read_trials, generate_roi_table, has_space
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2017-11-25 00:04:11 +00:00
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2018-02-08 19:49:43 +00:00
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import freqtrade.optimize.hyperopt as hyperopt
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2017-12-26 08:08:10 +00:00
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def test_loss_calculation_prefer_correct_trade_count():
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2018-01-07 11:54:00 +00:00
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correct = calculate_loss(1, TARGET_TRADES, 20)
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over = calculate_loss(1, TARGET_TRADES + 100, 20)
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under = calculate_loss(1, TARGET_TRADES - 100, 20)
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2017-12-26 08:08:10 +00:00
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assert over > correct
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assert under > correct
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2018-01-08 00:44:26 +00:00
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2018-01-07 11:54:00 +00:00
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def test_loss_calculation_prefer_shorter_trades():
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shorter = calculate_loss(1, 100, 20)
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longer = calculate_loss(1, 100, 30)
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assert shorter < longer
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2017-12-26 08:08:10 +00:00
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def test_loss_calculation_has_limited_profit():
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2018-01-07 11:54:00 +00:00
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correct = calculate_loss(EXPECTED_MAX_PROFIT, TARGET_TRADES, 20)
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over = calculate_loss(EXPECTED_MAX_PROFIT * 2, TARGET_TRADES, 20)
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under = calculate_loss(EXPECTED_MAX_PROFIT / 2, TARGET_TRADES, 20)
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2017-12-26 08:08:10 +00:00
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assert over == correct
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assert under > correct
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def create_trials(mocker):
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2018-01-09 09:37:27 +00:00
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"""
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When creating trials, mock the hyperopt Trials so that *by default*
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- we don't create any pickle'd files in the filesystem
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- we might have a pickle'd file so make sure that we return
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false when looking for it
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"""
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mocker.patch('freqtrade.optimize.hyperopt.TRIALS_FILE',
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return_value='freqtrade/tests/optimize/ut_trials.pickle')
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mocker.patch('freqtrade.optimize.hyperopt.os.path.exists',
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return_value=False)
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mocker.patch('freqtrade.optimize.hyperopt.save_trials',
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return_value=None)
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mocker.patch('freqtrade.optimize.hyperopt.read_trials',
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return_value=None)
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2018-01-09 10:19:44 +00:00
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mocker.patch('freqtrade.optimize.hyperopt.os.remove',
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return_value=True)
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2017-12-26 08:08:10 +00:00
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return mocker.Mock(
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results=[{
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'loss': 1,
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2018-01-09 09:37:27 +00:00
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'result': 'foo',
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'status': 'ok'
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}],
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best_trial={'misc': {'vals': {'adx': 999}}}
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2017-12-26 08:08:10 +00:00
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)
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def test_start_calls_fmin(mocker):
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2018-01-09 09:37:27 +00:00
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trials = create_trials(mocker)
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2018-01-10 22:03:05 +00:00
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mocker.patch('freqtrade.optimize.tickerdata_to_dataframe')
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2018-01-09 09:37:27 +00:00
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mocker.patch('freqtrade.optimize.hyperopt.TRIALS', return_value=trials)
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mocker.patch('freqtrade.optimize.hyperopt.sorted',
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return_value=trials.results)
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2017-12-26 08:08:10 +00:00
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mocker.patch('freqtrade.optimize.preprocess')
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mocker.patch('freqtrade.optimize.load_data')
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mock_fmin = mocker.patch('freqtrade.optimize.hyperopt.fmin', return_value={})
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2018-01-15 21:25:02 +00:00
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args = mocker.Mock(epochs=1, config='config.json.example', mongodb=False,
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2018-02-09 18:59:06 +00:00
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timerange=None, spaces='all')
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2017-12-26 08:08:10 +00:00
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start(args)
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mock_fmin.assert_called_once()
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def test_start_uses_mongotrials(mocker):
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mock_mongotrials = mocker.patch('freqtrade.optimize.hyperopt.MongoTrials',
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return_value=create_trials(mocker))
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2018-01-10 22:03:05 +00:00
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mocker.patch('freqtrade.optimize.tickerdata_to_dataframe')
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2017-12-26 08:08:10 +00:00
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mocker.patch('freqtrade.optimize.load_data')
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mocker.patch('freqtrade.optimize.hyperopt.fmin', return_value={})
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2018-01-15 21:25:02 +00:00
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args = mocker.Mock(epochs=1, config='config.json.example', mongodb=True,
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2018-02-09 18:59:06 +00:00
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timerange=None, spaces='all')
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2017-12-26 08:08:10 +00:00
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start(args)
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mock_mongotrials.assert_called_once()
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def test_log_results_if_loss_improves(mocker):
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logger = mocker.patch('freqtrade.optimize.hyperopt.logger.info')
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global CURRENT_BEST_LOSS
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CURRENT_BEST_LOSS = 2
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log_results({
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'loss': 1,
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'current_tries': 1,
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'total_tries': 2,
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'result': 'foo'
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})
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logger.assert_called_once()
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def test_no_log_if_loss_does_not_improve(mocker):
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logger = mocker.patch('freqtrade.optimize.hyperopt.logger.info')
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global CURRENT_BEST_LOSS
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CURRENT_BEST_LOSS = 2
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log_results({
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'loss': 3,
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})
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assert not logger.called
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2018-01-07 01:12:32 +00:00
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def test_fmin_best_results(mocker, caplog):
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2018-01-31 17:37:38 +00:00
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caplog.set_level(logging.INFO)
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2018-01-07 01:12:32 +00:00
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fmin_result = {
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2018-01-16 11:31:45 +00:00
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"macd_below_zero": 0,
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2018-01-08 20:00:10 +00:00
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"adx": 1,
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"adx-value": 15.0,
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"fastd": 1,
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"fastd-value": 40.0,
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"green_candle": 1,
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"mfi": 0,
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"over_sar": 0,
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"rsi": 1,
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"rsi-value": 37.0,
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"trigger": 2,
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"uptrend_long_ema": 1,
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"uptrend_short_ema": 0,
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"uptrend_sma": 0,
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"stoploss": -0.1,
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2018-01-24 15:58:44 +00:00
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"roi_t1": 1,
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"roi_t2": 2,
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"roi_t3": 3,
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"roi_p1": 1,
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"roi_p2": 2,
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"roi_p3": 3,
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2018-01-07 01:12:32 +00:00
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}
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mocker.patch('freqtrade.optimize.hyperopt.MongoTrials', return_value=create_trials(mocker))
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2018-01-10 22:03:05 +00:00
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mocker.patch('freqtrade.optimize.tickerdata_to_dataframe')
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2018-01-07 01:12:32 +00:00
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mocker.patch('freqtrade.optimize.load_data')
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mocker.patch('freqtrade.optimize.hyperopt.fmin', return_value=fmin_result)
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2018-01-15 21:25:02 +00:00
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args = mocker.Mock(epochs=1, config='config.json.example',
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2018-02-09 18:59:06 +00:00
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timerange=None, spaces='all')
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2018-01-07 01:12:32 +00:00
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start(args)
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exists = [
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'Best parameters',
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'"adx": {\n "enabled": true,\n "value": 15.0\n },',
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'"green_candle": {\n "enabled": true\n },',
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'"mfi": {\n "enabled": false\n },',
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2018-01-16 11:31:45 +00:00
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'"trigger": {\n "type": "faststoch10"\n },',
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2018-01-08 20:00:10 +00:00
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'"stoploss": -0.1',
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2018-01-07 01:12:32 +00:00
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]
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for line in exists:
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assert line in caplog.text
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2018-01-08 01:45:31 +00:00
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def test_fmin_throw_value_error(mocker, caplog):
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2018-01-31 17:37:38 +00:00
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caplog.set_level(logging.INFO)
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2018-01-08 01:45:31 +00:00
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mocker.patch('freqtrade.optimize.hyperopt.MongoTrials', return_value=create_trials(mocker))
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2018-01-10 22:03:05 +00:00
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mocker.patch('freqtrade.optimize.tickerdata_to_dataframe')
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2018-01-08 01:45:31 +00:00
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mocker.patch('freqtrade.optimize.load_data')
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mocker.patch('freqtrade.optimize.hyperopt.fmin', side_effect=ValueError())
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2018-01-15 21:25:02 +00:00
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args = mocker.Mock(epochs=1, config='config.json.example',
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2018-02-09 18:59:06 +00:00
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timerange=None, spaces='all')
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2018-01-08 01:45:31 +00:00
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start(args)
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exists = [
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'Best Result:',
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'Sorry, Hyperopt was not able to find good parameters. Please try with more epochs '
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'(param: -e).',
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]
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for line in exists:
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assert line in caplog.text
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2018-01-09 09:37:27 +00:00
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def test_resuming_previous_hyperopt_results_succeeds(mocker):
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import freqtrade.optimize.hyperopt as hyperopt
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trials = create_trials(mocker)
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mocker.patch('freqtrade.optimize.hyperopt.TRIALS',
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return_value=trials)
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mocker.patch('freqtrade.optimize.hyperopt.os.path.exists',
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return_value=True)
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mocker.patch('freqtrade.optimize.hyperopt.len',
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return_value=len(trials.results))
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mock_read = mocker.patch('freqtrade.optimize.hyperopt.read_trials',
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return_value=trials)
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mock_save = mocker.patch('freqtrade.optimize.hyperopt.save_trials',
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return_value=None)
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mocker.patch('freqtrade.optimize.hyperopt.sorted',
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return_value=trials.results)
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mocker.patch('freqtrade.optimize.preprocess')
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mocker.patch('freqtrade.optimize.load_data')
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mocker.patch('freqtrade.optimize.hyperopt.fmin',
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return_value={})
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args = mocker.Mock(epochs=1,
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config='config.json.example',
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2018-01-15 21:25:02 +00:00
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mongodb=False,
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2018-02-09 18:59:06 +00:00
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timerange=None,
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spaces='all')
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2018-01-09 09:37:27 +00:00
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start(args)
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mock_read.assert_called_once()
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mock_save.assert_called_once()
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current_tries = hyperopt._CURRENT_TRIES
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total_tries = hyperopt.TOTAL_TRIES
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assert current_tries == len(trials.results)
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assert total_tries == (current_tries + len(trials.results))
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2018-01-09 10:19:44 +00:00
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def test_save_trials_saves_trials(mocker):
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trials = create_trials(mocker)
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mock_dump = mocker.patch('freqtrade.optimize.hyperopt.pickle.dump',
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return_value=None)
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trials_path = mocker.patch('freqtrade.optimize.hyperopt.TRIALS_FILE',
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return_value='ut_trials.pickle')
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mocker.patch('freqtrade.optimize.hyperopt.open',
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return_value=trials_path)
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save_trials(trials, trials_path)
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mock_dump.assert_called_once_with(trials, trials_path)
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def test_read_trials_returns_trials_file(mocker):
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trials = create_trials(mocker)
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mock_load = mocker.patch('freqtrade.optimize.hyperopt.pickle.load',
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return_value=trials)
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mock_open = mocker.patch('freqtrade.optimize.hyperopt.open',
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return_value=mock_load)
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assert read_trials() == trials
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mock_open.assert_called_once()
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mock_load.assert_called_once()
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2018-01-25 08:45:53 +00:00
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def test_roi_table_generation():
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params = {
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'roi_t1': 5,
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'roi_t2': 10,
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'roi_t3': 15,
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'roi_p1': 1,
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'roi_p2': 2,
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'roi_p3': 3,
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}
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assert generate_roi_table(params) == {'0': 6, '15': 3, '25': 1, '30': 0}
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2018-02-08 19:49:43 +00:00
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# test log_trials_result
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# test buy_strategy_generator def populate_buy_trend
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# test optimizer if 'ro_t1' in params
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def test_format_results():
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trades = [('BTC_ETH', 2, 2, 123),
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('BTC_LTC', 1, 1, 123),
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('BTC_XRP', -1, -2, -246)]
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labels = ['currency', 'profit_percent', 'profit_BTC', 'duration']
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df = pd.DataFrame.from_records(trades, columns=labels)
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x = hyperopt.format_results(df)
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assert x.find(' 66.67%')
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def test_signal_handler(mocker):
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m = MagicMock()
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mocker.patch('sys.exit', m)
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mocker.patch('freqtrade.optimize.hyperopt.save_trials', m)
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mocker.patch('freqtrade.optimize.hyperopt.log_trials_result', m)
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hyperopt.signal_handler(9, None)
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assert m.call_count == 3
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2018-02-09 18:59:06 +00:00
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def test_has_space():
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2018-02-11 17:22:13 +00:00
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assert has_space(['buy', 'roi'], 'roi')
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assert has_space(['buy', 'roi'], 'buy')
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assert not has_space(['buy', 'roi'], 'stoploss')
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assert has_space(['all'], 'buy')
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