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use TA-lib to calculate StochRSI

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This commit is contained in:
Janne Sinivirta 2017-09-02 11:41:30 +03:00
parent c2d7854d62
commit 0643438580
1 changed files with 8 additions and 10 deletions
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18
analyze.py
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@ -5,6 +5,7 @@ import arrow
import requests
from pandas.io.json import json_normalize
from stockstats import StockDataFrame
import talib.abstract as ta
logging.basicConfig(level=logging.DEBUG,
format='%(asctime)s - %(name)s - %(levelname)s - %(message)s')
@ -42,12 +43,9 @@ def get_ticker_dataframe(pair: str) -> StockDataFrame:
dataframe = StockDataFrame(json_normalize(data))
# calculate StochRSI
window = 14
rsi = dataframe['rsi_{}'.format(window)]
rolling = rsi.rolling(window=window, center=False)
low = rolling.min()
high = rolling.max()
dataframe['stochrsi'] = (rsi - low) / (high - low)
stochrsi = ta.STOCHRSI(dataframe)
dataframe['stochrsi'] = stochrsi['fastd'] # values between 0-100, not 0-1
return dataframe
@ -59,13 +57,13 @@ def populate_trends(dataframe: StockDataFrame) -> StockDataFrame:
"""
"""
dataframe.loc[
(dataframe['stochrsi'] < 0.20)
(dataframe['stochrsi'] < 20)
& (dataframe['close_30_ema'] > (1 + 0.0025) * dataframe['close_60_ema']),
'underpriced'
] = 1
"""
dataframe.loc[
(dataframe['stochrsi'] < 0.20)
(dataframe['stochrsi'] < 20)
& (dataframe['macd'] > dataframe['macds']),
'underpriced'
] = 1
@ -123,8 +121,8 @@ def plot_dataframe(dataframe: StockDataFrame, pair: str) -> None:
ax2.legend()
ax3.plot(dataframe.index.values, dataframe['stochrsi'], label='StochRSI')
ax3.plot(dataframe.index.values, [0.80] * len(dataframe.index.values))
ax3.plot(dataframe.index.values, [0.20] * len(dataframe.index.values))
ax3.plot(dataframe.index.values, [80] * len(dataframe.index.values))
ax3.plot(dataframe.index.values, [20] * len(dataframe.index.values))
ax3.legend()
# Fine-tune figure; make subplots close to each other and hide x ticks for