make defining period intervals more user friendly and flexible
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@ -82,7 +82,7 @@
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"use_SVM_to_remove_outliers": true,
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"use_SVM_to_remove_outliers": true,
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"stratify": 0,
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"stratify": 0,
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"indicator_max_period": 20,
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"indicator_max_period": 20,
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"indicator_interval": 10
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"indicator_periods": [10, 20, 30]
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},
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},
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"data_split_parameters": {
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"data_split_parameters": {
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"test_size": 0.33,
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"test_size": 0.33,
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@ -77,7 +77,7 @@
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"use_SVM_to_remove_outliers": false,
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"use_SVM_to_remove_outliers": false,
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"stratify": 0,
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"stratify": 0,
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"indicator_max_period": 50,
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"indicator_max_period": 50,
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"indicator_interval": 10
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"indicator_periods": [10, 20]
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},
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},
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"data_split_parameters": {
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"data_split_parameters": {
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"test_size": 0.33,
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"test_size": 0.33,
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@ -1,7 +1,6 @@
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import logging
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import logging
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from functools import reduce
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from functools import reduce
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import numpy as np
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import pandas as pd
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import pandas as pd
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import talib.abstract as ta
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import talib.abstract as ta
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from pandas import DataFrame
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from pandas import DataFrame
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@ -90,8 +89,7 @@ class FreqaiExampleStrategy(IStrategy):
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informative = self.dp.get_pair_dataframe(pair, tf)
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informative = self.dp.get_pair_dataframe(pair, tf)
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# first loop is automatically duplicating indicators for time periods
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# first loop is automatically duplicating indicators for time periods
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for t in np.arange(10, self.freqai_info["feature_parameters"]["indicator_max_period"],
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for t in self.freqai_info["feature_parameters"]["indicator_periods"]:
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self.freqai_info["feature_parameters"]["indicator_interval"]):
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t = int(t)
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t = int(t)
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informative['%-' + coin + "rsi-period_" + str(t)] = ta.RSI(informative, timeperiod=t)
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informative['%-' + coin + "rsi-period_" + str(t)] = ta.RSI(informative, timeperiod=t)
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