Make readable hyperopt best parameters result
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@ -204,19 +204,39 @@ signal. Given following result from hyperopt:
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```
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```
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Best parameters:
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Best parameters:
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{
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{
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"adx": 1,
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"adx": {
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"adx-value": 15.0,
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"enabled": true,
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"fastd": 1,
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"value": 15.0
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"fastd-value": 40.0,
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},
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"green_candle": 1,
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"fastd": {
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"mfi": 0,
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"enabled": true,
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"over_sar": 0,
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"value": 40.0
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"rsi": 1,
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},
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"rsi-value": 37.0,
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"green_candle": {
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"trigger": 0,
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"enabled": true
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"uptrend_long_ema": 1,
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},
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"uptrend_short_ema": 0,
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"mfi": {
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"uptrend_sma": 0
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"enabled": false
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},
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"over_sar": {
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"enabled": false
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},
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"rsi": {
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"enabled": true,
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"value": 37.0
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},
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"trigger": {
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"type": "lower_bb"
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},
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"uptrend_long_ema": {
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"enabled": true
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},
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"uptrend_short_ema": {
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"enabled": false
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},
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"uptrend_sma": {
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"enabled": false
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}
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}
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}
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Best Result:
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Best Result:
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@ -224,14 +244,14 @@ Best Result:
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```
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```
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You should understand this result like:
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You should understand this result like:
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- You should **consider** the guard "adx" (`"adx": 1,` = `adx` is true)
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- You should **consider** the guard "adx" (`"adx"` is `"enabled": true`)
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and the best value is `15.0` (`"adx-value": 15.0,`)
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and the best value is `15.0` (`"value": 15.0,`)
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- You should **consider** the guard "fastd" (`"fastd": 1,` = `fastd`
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- You should **consider** the guard "fastd" (`"fastd"` is `"enabled":
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is true) and the best value is `40.0` (`"fastd-value": 40.0,`)
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true`) and the best value is `40.0` (`"value": 40.0,`)
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- You should **consider** to enable the guard "green_candle"
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- You should **consider** to enable the guard "green_candle"
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(`"green_candle": 1,` = `candle` is true) but this guards as no
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(`"green_candle"` is `"enabled": true`) but this guards as no
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customizable value.
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customizable value.
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- You should **ignore** the guard "mfi" (`"mfi": 0,` = `mfi` is false)
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- You should **ignore** the guard "mfi" (`"mfi"` is `"enabled": false`)
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- and so on...
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- and so on...
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@ -239,8 +259,8 @@ You have to look from
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[freqtrade/optimize/hyperopt.py](https://github.com/gcarq/freqtrade/blob/develop/freqtrade/optimize/hyperopt.py#L170-L200)
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[freqtrade/optimize/hyperopt.py](https://github.com/gcarq/freqtrade/blob/develop/freqtrade/optimize/hyperopt.py#L170-L200)
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what those values match to.
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what those values match to.
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So for example you had `adx-value: 15.0` (and `adx: 1` was true) so we
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So for example you had `adx:` with the `value: 15.0` so we would look
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would look at `adx`-block from
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at `adx`-block from
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[freqtrade/optimize/hyperopt.py](https://github.com/gcarq/freqtrade/blob/develop/freqtrade/optimize/hyperopt.py#L178-L179).
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[freqtrade/optimize/hyperopt.py](https://github.com/gcarq/freqtrade/blob/develop/freqtrade/optimize/hyperopt.py#L178-L179).
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That translates to the following code block to
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That translates to the following code block to
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[analyze.populate_buy_trend()](https://github.com/gcarq/freqtrade/blob/develop/freqtrade/analyze.py#L73)
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[analyze.populate_buy_trend()](https://github.com/gcarq/freqtrade/blob/develop/freqtrade/analyze.py#L73)
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@ -8,7 +8,7 @@ from functools import reduce
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from math import exp
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from math import exp
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from operator import itemgetter
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from operator import itemgetter
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from hyperopt import fmin, tpe, hp, Trials, STATUS_OK, STATUS_FAIL
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from hyperopt import fmin, tpe, hp, Trials, STATUS_OK, STATUS_FAIL, space_eval
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from hyperopt.mongoexp import MongoTrials
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from hyperopt.mongoexp import MongoTrials
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from pandas import DataFrame
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from pandas import DataFrame
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@ -209,7 +209,7 @@ def buy_strategy_generator(params):
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def start(args):
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def start(args):
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global TOTAL_TRIES, PROCESSED
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global TOTAL_TRIES, PROCESSED, SPACE
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TOTAL_TRIES = args.epochs
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TOTAL_TRIES = args.epochs
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exchange._API = Bittrex({'key': '', 'secret': ''})
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exchange._API = Bittrex({'key': '', 'secret': ''})
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@ -236,6 +236,11 @@ def start(args):
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trials = Trials()
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trials = Trials()
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best = fmin(fn=optimizer, space=SPACE, algo=tpe.suggest, max_evals=TOTAL_TRIES, trials=trials)
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best = fmin(fn=optimizer, space=SPACE, algo=tpe.suggest, max_evals=TOTAL_TRIES, trials=trials)
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# Improve best parameter logging display
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if best:
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best = space_eval(SPACE, best)
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logger.info('Best parameters:\n%s', json.dumps(best, indent=4))
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logger.info('Best parameters:\n%s', json.dumps(best, indent=4))
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results = sorted(trials.results, key=itemgetter('loss'))
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results = sorted(trials.results, key=itemgetter('loss'))
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@ -77,3 +77,40 @@ def test_no_log_if_loss_does_not_improve(mocker):
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})
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})
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assert not logger.called
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assert not logger.called
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def test_fmin_best_results(mocker, caplog):
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fmin_result = {
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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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}
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mocker.patch('freqtrade.optimize.hyperopt.MongoTrials', return_value=create_trials(mocker))
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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', return_value=fmin_result)
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args = mocker.Mock(epochs=1, config='config.json.example')
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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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'"trigger": {\n "type": "ao_cross_zero"\n },'
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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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