I'm trying to rewrite a script to Python, but I can't figure out how pivothigh() and pivotlow() function work, and I can't find source code, I know how to calculate Pivot Points, but what leftbars and rightbars means in this two function? Please help.
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Have you created the function? Can you share the code? – Krzysztof Maliszewski Feb 22 '21 at 05:03
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Were you able to create a more generic code which you could share? Thanks! – Mayank Jain Aug 25 '21 at 01:12
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Any updates there? – Frumda Grayforce Feb 11 '22 at 13:12
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1Please avoid using Pivothigh() and pivotlow() in strategy. They are good for indicator. If in strategy, you are going to have some decision based on pivothi or pivotlo then watchout because it 'kicks back' e.g. instead of giving buy signal at current bar, you will get at previous bar if pivothi() / pivotlo() finds pivot at previous bar... – cyberspider789 Dec 24 '22 at 02:45
10 Answers
Leftbars and rightbars are number of bars that the pivot
functions looks when is searching for a pivot.
For example:
pivothigh(10,10)
will search for high price that was not exceeded during 10 bars to the left (past data) and 10 bars to the right (future data). Note that the function won't be able to determine the pivot if there is less than 10 bars to the right.

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Does this mean that a pivotHigh or Low will not be drawn on the chart until at least 10 bars later? Like, suuuper lagging indicator? – Birrel Jan 21 '21 at 21:51
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I too had a need to better understand how the pivothigh()
and pivotlow()
functions work internally so I made the effort to code a Pine Script version (using version 5 of Pine Script) for myself and tested it side-by-side with the ta.pivotlow()
and ta.pivothigh()
functions and it seems to work well. Maybe this will help you as well.
my_pivothigh(float _series = high, int _leftBars, int _rightBars) =>
float _pivotHigh = na
int _pivotRange = ( _leftBars + _rightBars )
float _leftEdgeValue = nz(_series[_pivotRange], na)
if not na(_series) and _leftBars > 0 and _rightBars > 0 and not na(_leftEdgeValue)
float _possiblePivotHigh = _series[_rightBars]
float[] _arrayOfSeriesValues = array.new_float(0)
for _barIndex = _pivotRange to 0
array.push(_arrayOfSeriesValues, _series[_barIndex])
//end for
int _pivotHighRightBars = array.size(_arrayOfSeriesValues) - array.lastindexof(_arrayOfSeriesValues, array.max(_arrayOfSeriesValues)) - 1
_pivotHigh := ( _pivotHighRightBars == _rightBars ) ? _possiblePivotHigh : na
//end if
_pivotHigh
my_pivotlow(float _series = low, int _leftBars, int _rightBars) =>
float _pivotLow = na
int _pivotRange = ( _leftBars + _rightBars )
float _leftEdgeValue = nz(_series[_pivotRange], na)
if not na(_series) and _leftBars > 0 and _rightBars > 0 and not na(_leftEdgeValue)
float _possiblePivotLow = _series[_rightBars]
float[] _arrayOfSeriesValues = array.new_float(0)
for _barIndex = _pivotRange to 0
array.push(_arrayOfSeriesValues, _series[_barIndex])
//end for
int _pivotLowRightBars = array.size(_arrayOfSeriesValues) - array.lastindexof(_arrayOfSeriesValues, array.min(_arrayOfSeriesValues)) - 1
_pivotLow := ( _pivotLowRightBars == _rightBars ) ? _possiblePivotLow : na
//end if
_pivotLow

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I know this is an old post but I've made a very simple python implementation that anyone can build on, it does the same thing as Pine Scripts ta.pivot functions.
code:
def pivots_high(data, LBR, LBL):
pivots = []
for i in range(len(data)-LBR):
pivots.append(0)
pivot = True
if i > LBL:
for j in range(LBL + 1):
if data[i - j] > data[I]: # do if data[i - j] < data[i] for pivot low
pivot = False
for j in range(LBR + 1):
if data[i + j] > data[I]: # do if data[i + j] < data[i] for pivot low
pivot = False
if pivot is True:
pivots[len(pivots)-1] = data[i]
for p in range(LBR):
pivots.append(0) # This is so the pivots length matches your data length
return pivots # The Pivots will be any value that is not 0 and it will be where the lowest/highest value is
the lookback variables simply means that if you take one price point and look n(Looback left) candles left and n(lookback right) candles right, and still its the lowest/highest then that's the pivot
UPDATE
I ran into some problems with this code with different combinations of numbers on large datasets so I had to completely change it to always match up with tradingview.
New Code:
def checkhl(data_back, data_forward, hl):
if hl == 'high' or hl == 'High':
ref = data_back[len(data_back)-1]
for i in range(len(data_back)-1):
if ref < data_back[i]:
return 0
for i in range(len(data_forward)):
if ref <= data_forward[i]:
return 0
return 1
if hl == 'low' or hl == 'Low':
ref = data_back[len(data_back)-1]
for i in range(len(data_back)-1):
if ref > data_back[i]:
return 0
for i in range(len(data_forward)):
if ref >= data_forward[i]:
return 0
return 1
def pivot(osc, LBL, LBR, highlow)
left = []
right = []
for i in range(len(osc)):
pivots.append(0.0)
if i < LBL + 1:
left.append(osc[i])
if i > LBL:
right.append(osc[i])
if i > LBL + LBR:
left.append(right[0])
left.pop(0)
right.pop(0)
if checkhl(left, right, highlow):
pivots[i - LBR] = osc[i - LBR]
return pivots
then just do:
pivots_low = pivot(data, lbl, lbr, 'low')
pivots_high = pivot(data, lbl, lbr, 'high')
output is pivots in their actual location with 0.0s otherwise.

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You could construct something similar with a one-liner with pandas:
pivots = high_column.shift(-len_right, fill_value=0).rolling(len_left).max()
For 'High' pivots pd.Series 'high_column' and:
pivots = low_column.shift(-len_right, fill_value=0).rolling(len_left).min()
for the 'Lows'. It avoids using loops and is a fast vectorized function.
This is my implementation of ta.pivotHigh for javascript, hope this helps.
const pivotHigh = (series, period) => {
let ph = 0;
let phIndex = 0;
// left + right bars + 1 pivot bar
for ( let i = period + period + 1, len = series.length; i--; ) {
const cur = series[len - i];
// [!] > -1 logic. can also checks: NaN
if ( cur > -1 ) {} else {
break;
}
if ( cur > ph ) {
ph = cur;
phIndex = len - i;
}
}
// found?
return phIndex === period
? ph
: 0;
};
usage:
const series = [0,1,2,3,4,5,4,3,2,1,0];
const period = 5;
const ph = pivotHigh(series, period);
Here is my humble approach
import numpy as np
from talib import MAX, MIN
def PIVOTHIGH(high: np.ndarray, left:int, right: int):
pivots = np.roll(MAX(high, left + 1 + right), -right)
pivots[pivots != high] = np.NaN
return pivots
def PIVOTLOW(low: np.ndarray, left:int, right: int):
pivots = np.roll(MIN(low, left + 1 + right), -right)
pivots[pivots != low] = np.NaN
return pivots
Use them like this:
a = np.array([1, 1, 2., 2., 2., 3., 4., 5., 6., 7., 8., 9., 8., 7., 6., 7., 8., 9., 10, 9., 8., 9., 10])
PIVOTHIGH(a, 2, 2)
#output
array([nan, nan, 2., nan, nan, nan, nan, nan, nan, nan, nan, 9., nan,
nan, nan, nan, nan, nan, 10., nan, nan, nan, nan])
PIVOTLOW(a, 2, 2)
#output
array([nan, nan, nan, nan, 2., nan, nan, nan, nan, nan, nan, nan, nan,
nan, 6., nan, nan, nan, nan, nan, 8., nan, nan])

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I've tried to create a simple version of it in Pine Script, which does not uses pivothigh/pivotlow - instead does the candlestick comparison.
https://www.tradingview.com/script/BYHsrYPG-Broken-Fractal-Someone-s-broken-dream-is-your-profit
I was also able to convert this into Ruby code (Python code should be as easy).
if (candles[i-1][:h] > candles[i-2][:h]) and (candles[i-1][:h] > candles[i][:h])
puts "DownFractal"
end
if (candles[i-1][:l] < candles[i-2][:l]) and (candles[i-1][:l] < candles[i][:l])
puts "UpFractal"
end

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Here's my Python implementation. Works exactly as ta.pivothigh
and ta.pivotlow
.
Pivot high:
def get_pivot_high(ohlcvs: List[OHLCV], left_bars: int, right_bars: int, key_name: str = 'high_price') -> Optional[float]:
if len(ohlcvs) < left_bars + right_bars:
return None
highest_value = max(ohlcv.get(key_name) for ohlcv in ohlcvs[-(left_bars + right_bars + 1):])
return highest_value if highest_value == ohlcvs[-right_bars].get(key_name) else None
Pivot low:
def get_pivot_low(ohlcvs: List[OHLCV], left_bars: int, right_bars: int, key_name: str = 'low_price') -> Optional[float]:
if len(ohlcvs) < left_bars + right_bars:
return None
lowest_value = min(ohlcv.get(key_name) for ohlcv in ohlcvs[-(left_bars + right_bars + 1):])
return lowest_value if lowest_value == ohlcvs[-right_bars].get(key_name) else None

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Oneliner same as the tradingview Pivots HL:
LEN = 50 #Lookback and Lookforward
OHLC['PivotHigh'] = OHLC['high'] == OHLC['high'].rolling(2 * LEN + 1, center=True).max()
OHLC['PivotLow'] = OHLC['low'] == OHLC['low'].rolling(2 * LEN + 1, center=True).min()
(Left and right will be the same length)

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I had found this thread after I have searched for this kind of implementation. Here is my own implementation for those that have been utilizing the Binance API. (Written in java)
From my own testings, it has the same results as the pine script.
private boolean checkHighOrLow(Candlestick candlestick , int lengthForCheck, int currentCandleIndex, boolean checkForHigh) {
double currentCandleStickClosePrice = Double.parseDouble(candlestick.getClose());
for (int i = 0; i < lengthForCheck; i++) {
double afterCandleStick = Double.parseDouble(candlestickList.get(currentCandleIndex + i + 1).getClose());
double beforeCandleStick = Double.parseDouble(candlestickList.get(currentCandleIndex - i - 1).getClose());
if(checkForHigh) {
if (afterCandleStick > currentCandleStickClosePrice)
return false;
if (beforeCandleStick > currentCandleStickClosePrice)
return false;
}else{
if(afterCandleStick < currentCandleStickClosePrice)
return false;
if(beforeCandleStick < currentCandleStickClosePrice)
return false;
}
}
return true;
}
public void findHighsAndLows(){
int lengthForCheck = 1;
int numOfCandles = candlestickList.size();
for(int i = lengthForCheck; i < numOfCandles - lengthForCheck; i ++)
{
Candlestick currentCandle = candlestickList.get(i);
if(checkHighOrLow(currentCandle,numOfCandles,lengthForCheck,i,true))
highs.add(currentCandle);
if(checkHighOrLow(currentCandle,numOfCandles,lengthForCheck,i,false))
lows.add(currentCandle);
}
}
Logic still applies. Enjoy
Result:
FOUND LOW | Wed Aug 25 04:20:00 IDT 2021
FOUND HIGH | Wed Aug 25 05:05:00 IDT 2021
FOUND LOW | Wed Aug 25 05:20:00 IDT 2021
FOUND HIGH | Wed Aug 25 05:30:00 IDT 2021
FOUND LOW | Wed Aug 25 05:35:00 IDT 2021
FOUND HIGH | Wed Aug 25 05:45:00 IDT 2021
FOUND LOW | Wed Aug 25 06:15:00 IDT 2021
FOUND HIGH | Wed Aug 25 06:25:00 IDT 2021
FOUND LOW | Wed Aug 25 06:35:00 IDT 2021
FOUND HIGH | Wed Aug 25 06:40:00 IDT 2021
FOUND LOW | Wed Aug 25 06:55:00 IDT 2021
FOUND HIGH | Wed Aug 25 07:05:00 IDT 2021
FOUND LOW | Wed Aug 25 07:25:00 IDT 2021
FOUND HIGH | Wed Aug 25 07:45:00 IDT 2021
FOUND LOW | Wed Aug 25 07:50:00 IDT 2021
FOUND HIGH | Wed Aug 25 08:20:00 IDT 2021
FOUND LOW | Wed Aug 25 08:25:00 IDT 2021
FOUND HIGH | Wed Aug 25 08:35:00 IDT 2021
FOUND LOW | Wed Aug 25 08:45:00 IDT 2021
FOUND HIGH | Wed Aug 25 08:50:00 IDT 2021
FOUND LOW | Wed Aug 25 09:15:00 IDT 2021
FOUND HIGH | Wed Aug 25 09:30:00 IDT 2021
FOUND LOW | Wed Aug 25 09:35:00 IDT 2021
FOUND HIGH | Wed Aug 25 09:40:00 IDT 2021
FOUND LOW | Wed Aug 25 09:55:00 IDT 2021
FOUND HIGH | Wed Aug 25 10:00:00 IDT 2021
FOUND LOW | Wed Aug 25 10:05:00 IDT 2021
FOUND HIGH | Wed Aug 25 10:15:00 IDT 2021
FOUND LOW | Wed Aug 25 10:45:00 IDT 2021
FOUND HIGH | Wed Aug 25 10:50:00 IDT 2021
FOUND LOW | Wed Aug 25 11:15:00 IDT 2021
FOUND HIGH | Wed Aug 25 11:20:00 IDT 2021
FOUND LOW | Wed Aug 25 11:35:00 IDT 2021
FOUND HIGH | Wed Aug 25 11:45:00 IDT 2021
FOUND LOW | Wed Aug 25 11:55:00 IDT 2021
FOUND HIGH | Wed Aug 25 12:15:00 IDT 2021

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