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Update numpy imports in sample strategies
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@ -2,15 +2,15 @@
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# --- Do not remove these libs ---
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from freqtrade.strategy.interface import IStrategy
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from pandas import DataFrame
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import pandas as pd
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# --------------------------------
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# Add your lib to import here
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import talib.abstract as ta
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import freqtrade.vendor.qtpylib.indicators as qtpylib
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import numpy # noqa
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import numpy as np # noqa
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# This class is a sample. Feel free to customize it.
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class {{ strategy }}(IStrategy):
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"""
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This is a strategy template to get you started..
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@ -140,7 +140,7 @@ class {{ strategy }}(IStrategy):
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# Inverse Fisher transform on RSI, values [-1.0, 1.0] (https://goo.gl/2JGGoy)
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rsi = 0.1 * (dataframe['rsi'] - 50)
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dataframe['fisher_rsi'] = (numpy.exp(2 * rsi) - 1) / (numpy.exp(2 * rsi) + 1)
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dataframe['fisher_rsi'] = (np.exp(2 * rsi) - 1) / (np.exp(2 * rsi) + 1)
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# Inverse Fisher transform on RSI normalized, value [0.0, 100.0] (https://goo.gl/2JGGoy)
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dataframe['fisher_rsi_norma'] = 50 * (dataframe['fisher_rsi'] + 1)
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@ -7,7 +7,8 @@ from pandas import DataFrame
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# Add your lib to import here
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import talib.abstract as ta
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import freqtrade.vendor.qtpylib.indicators as qtpylib
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import numpy # noqa
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import pandas as pd # noqa
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import numpy as np # noqa
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# This class is a sample. Feel free to customize it.
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@ -147,7 +148,7 @@ class SampleStrategy(IStrategy):
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# Inverse Fisher transform on RSI, values [-1.0, 1.0] (https://goo.gl/2JGGoy)
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rsi = 0.1 * (dataframe['rsi'] - 50)
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dataframe['fisher_rsi'] = (numpy.exp(2 * rsi) - 1) / (numpy.exp(2 * rsi) + 1)
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dataframe['fisher_rsi'] = (np.exp(2 * rsi) - 1) / (np.exp(2 * rsi) + 1)
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# Inverse Fisher transform on RSI normalized, value [0.0, 100.0] (https://goo.gl/2JGGoy)
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dataframe['fisher_rsi_norma'] = 50 * (dataframe['fisher_rsi'] + 1)
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