Converting linreg function from pinescript to Python?

Question

I am trying to convert a TradingView indicator into Python (also using pandas to store its result).

This is the indicator public code I want to convert into a python indicator:

https://www.tradingview.com/script/sU9molfV/

And I am stuck creating that pine script linereg default function.

This is the fragment of the pinescript indicator I have troubles with:

lrc = linreg(src, length, 0)
lrc1 = linreg(src,length,1)
lrs = (lrc-lrc1)
TSF = linreg(src, length, 0)+lrs

This is its documentation:

Linear regression curve. A line that best fits the prices specified over a user-defined time period. It is calculated using the least squares method. The result of this function is calculated using the formula: linreg = intercept + slope * (length - 1 - offset), where length is the y argument, offset is the z argument, intercept and slope are the values calculated with the least squares method on source series (x argument). linreg(source, length, offset) ? series[float]

Source:

https://www.tradingview.com/pine-script-reference/#fun_linreg

I have found this mql4 code and tried to follow it step by step in order to convert it and finally to create a function linreg in Python in order to use it further for building that pine script indicator:

https://www.mql5.com/en/code/8016

And this is my code so far:

# calculate linear regression:
# https://www.mql5.com/en/code/8016
barsToCount = 14
# sumy+=Close[i];
df['sumy'] = df['Close'].rolling(window=barsToCount).mean()

# sumxy+=Close[i]*i;
tmp = []
sumxy_lst = []
for window in df['Close'].rolling(window=barsToCount):
    for index in range(len(window)):
        tmp.append(window[index] * index)
    sumxy_lst.append(sum(tmp))
    del tmp[:]
df.loc[:,'sumxy'] = sumxy_lst
# sumx+=i;
sumx = 0
for i in range(barsToCount):
    sumx += i
# sumx2+=i*i;
sumx2 = 0
for i in range(barsToCount):
    sumx2 += i * i
# c=sumx2*barsToCount-sumx*sumx;
c = sumx2*barsToCount - sumx*sumx
# Line equation:
# b=(sumxy*barsToCount-sumx*sumy)/c;
df['b'] = ((df['sumxy']*barsToCount)-(sumx*df['sumy']))/c
# a=(sumy-sumx*b)/barsToCount;
df['a'] = (df['sumy']-sumx*df['b'])/barsToCount
# Linear regression line in buffer:
df['LR_line'] = 0.0
for x in range(barsToCount):
    # LR_line[x]=a+b*x;
    df['LR_line'].iloc[x] = df['a'].iloc[x] + df['b'].iloc[x] * x
    # print(x, df['a'].iloc[x], df['b'].iloc[x], df['b'].iloc[x]*x)
print(df.tail(50))
print(list(df))

It doesn't work.

Any idea how to create a similar pine script linereg function into python, please?

Thank you in advance!

Answer 1

我使用 talib 计算收盘价的斜率和截距，然后意识到 talib 也提供了完整的计算。结果看起来与 TradingView 相同（只是目测）。

在 jupyterlab 中做了以下操作：

import pandas as pd
import numpy as np
import talib as tl
from pandas_datareader import data
%run "../../plt_setup.py"

asset = data.DataReader('^AXJO', 'yahoo', start='1/1/2015')

n = 270
(asset
 .assign(linreg = tl.LINEARREG(asset.Close, n))
 [['Close', 'linreg']]
 .dropna()
 .loc['2019-01-01':]
 .plot()
);