How to convert pine script stdev to Python code?

Question

I'm trying to convert pine script stdev to Python code but it seems I'm doing it wrong.

Pine script:

//the same on pine
isZero(val, eps) => abs(val) <= eps
SUM(fst, snd) =>
 EPS = 1e-10
 res = fst + snd
 if isZero(res, EPS)
 res := 0
 else
 if not isZero(res, 1e-4)
 res := res
 else
 15
pine_stdev(src, length) =>
 avg = sma(src, length)
 sumOfSquareDeviations = 0.0
 for i = 0 to length - 1
 sum = SUM(src[i], -avg)
 sumOfSquareDeviations := sumOfSquareDeviations + sum * sum
 stdev = sqrt(sumOfSquareDeviations / length)

Python code:

import talib as ta
def isZero(val, eps):
 if abs(val) <= eps:
 return True
 else:
 return False
def SUM(fst, snd):
 EPS = 1e-10
 res = fst + snd
 if isZero(res, EPS):
 res += 0
 else:
 if not isZero(res, 1e-4):
 res = res
 else:
 res = 15
 return res
def pine_stdev(src, length):
 avg = ta.SMA(src, length)
 sumOfSquareDeviations = 0.0
 for i in range(length - 1):
 s = SUM(src.iloc[i], -avg.iloc[i])
 sumOfSquareDeviations = sumOfSquareDeviations + s * s
 stdev = (sumOfSquareDeviations / length)*(sumOfSquareDeviations / length)

What am I doing wrong? And why does the SUM function return 15?

Answer 1

Trading View has made a mistake in the code on the site. The number "15" should be written as "1e-5". You can use this code:

def SUM(fst, snd):
 EPS = 1e-10
 res = fst + snd
 if isZero(res, EPS):
 res = 0
 else:
 if not isZero(res, 1e-4):
 res = res
 else:
 res = 1e-5
 return res

Answer 2

I was able to figure it out using numpy and using vectorization which is faster than doing a for loop for every bar

I start at length - 1 because before length is just nan values so you don't need to work with those

on tradingview stdev website they say na values in the source series are ignored; the function calculates on the length quantity of non-na values.

https://www.tradingview.com/pine-script-reference/v5/#fun_ta.stdev

import numpy as np
import plotly.graph_objects as go
def sma_calc(source: np.array, length: int):
 arr = np.cumsum(source, dtype=np.float_)
 arr[length:] = arr[length:] - arr[:-length]
 sma = np.full_like(source, np.nan)
 sma[length - 1 :] = arr[length - 1 :] / length
 return sma
def stdev(source, length):
 avg = sma_calc(source=source, length=length)
 sum_square_dev = np.full_like(avg, np.nan)
 looper = length - 1
 for i in range(looper, avg.size):
 res = source[i - looper : i + 1] + -avg[i]
 res_2 = np.where(np.absolute(res) <= 1e-10, 0, res)
 sum = np.where((np.absolute(res_2) < 1e-4) & (np.absolute(res_2) > 1e-10), 1e-5, res_2)
 sum_square_dev[i] = (sum * sum).sum()
 final = np.sqrt(sum_square_dev / length)
 return final
multi = 2
length = 20
basis = sma_calc(source=close, length=length)
dev = multi * stdev(source=close, length=length)
upper = basis + dev
lower = basis - dev
multi = 2
length = 20
basis = sma_calc(source=close, length=length)
dev = multi * stdev(source=close, length=length)
upper = basis + dev
lower = basis - dev
datetimes = pd.to_datetime(candles[:, 0], unit="ms")
fig = go.Figure(
 data=[
 go.Candlestick(
 x=datetimes,
 open=candles[:, 1],
 high=candles[:, 2],
 low=candles[:, 3],
 close=candles[:, 4],
 name="Candles",
 ),
 go.Scatter(
 x=datetimes,
 y=upper,
 name="upper",
 ),
 go.Scatter(
 x=datetimes,
 y=basis,
 name="bases",
 ),
 go.Scatter(
 x=datetimes,
 y=lower,
 name="lower",
 ),
 ]
)
fig.update_layout(height=600, xaxis_rangeslider_visible=False)
fig.show()