mirror of
https://github.com/webclinic017/drift.git
synced 2026-07-27 18:57:55 +00:00
Mark Aron Szulyovszky
44 lines
1.1 KiB
Python
44 lines
1.1 KiB
Python
import pandas as pd
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import numpy as np
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def STOK(close, low, high, n):
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STOK = (
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(close - low.rolling(n).min()) / (high.rolling(n).max() - low.rolling(n).min())
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) * 100
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return STOK
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def STOD(close, low, high, n):
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STOK = (
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(close - low.rolling(n).min()) / (high.rolling(n).max() - low.rolling(n).min())
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) * 100
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STOD = STOK.rolling(3).mean()
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return STOD
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def RSI(series, period):
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delta = series.diff().dropna()
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u = delta * 0
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d = u.copy()
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u[delta > 0] = delta[delta > 0]
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d[delta < 0] = -delta[delta < 0]
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u[u.index[period - 1]] = np.mean(
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u[:period]
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) # first value is sum of avg gains u = u.drop(u.index[:(period-1)])
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d[d.index[period - 1]] = np.mean(
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d[:period]
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) # first value is sum of avg losses d = d.drop(d.index[:(period-1)])
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rs = (
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u.ewm(com=period - 1, adjust=False).mean()
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/ d.ewm(com=period - 1, adjust=False).mean()
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)
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return 100 - 100 / (1 + rs)
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def ROC(df, n):
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M = df.diff(n - 1)
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N = df.shift(n - 1)
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ROC = pd.Series(((M / N) * 100), name="ROC_" + str(n))
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return ROC
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