Half trend

[bibinvargheset]

The half trend code is not working as it should very different from TV

import ta_py as tapy
import pandas as pd
import pandas_ta as ta

df = pd.read_csv('/mnt/f/python/stocks/neo/data/bn_5min.csv')
# %%
df = df[:5000]
df.date = pd.to_datetime(df.date)
df.ta.ha(append=True)
data = df[['HA_high', 'HA_close', 'HA_low']].values.tolist()
[df2.csv](https://github.com/Bitvested/ta.py/files/9432276/df2.csv)

datahs = tapy.halftrend(data, 100, 2, 2)
df1 = pd.DataFrame(datahs, columns=['atrHigh', 'HalfTrend', 'atrLow', 'HS'])
df1.index=(df1.index+(len(df)-len(df1)))
df2 = pd.merge(df, df1, left_index=True, right_index=True)

Attaching the ouptu file

please check on tv by symbol BANKNIFTY 5 min HS(2,2)

The values and signals are very different

[bibinvargheset]

df2_1.csv
Expected result

from finta import TA
import numpy as np
import pandas as pd
import pandas_ta as ta

#%%
def half_trend(data, amplitude=2, channel_deviation=2):
    '''
    HalfTrend indicator, originally by Alex Orekhov (everget) on TradingView.

    Parameters:
        data (dataframe): OHLC price data

        amplitude (int): lookback window

        channel_deviation (int): ATR channel deviation factor

    (translated to Python 15/11/21)
    '''

    # Initialisation
    atr2 = data.ta.atr(100) / 2
    dev = channel_deviation * atr2
    high_price = data.High.rolling(amplitude).max().fillna(0)
    low_price = data.Low.rolling(amplitude).min().fillna(0)
    highma = TA.SMA(data, period=amplitude, column='High')
    lowma = TA.SMA(data, period=amplitude, column='Low')

    trend = np.zeros(len(data))
    next_trend = np.zeros(len(data))
    max_low_price = np.zeros(len(data))
    max_low_price[0] = data.Low[0]
    min_high_price = np.zeros(len(data))
    min_high_price[0] = data.High[0]

    for i in range(1, len(data)):
        if next_trend[i - 1] == 1:
            max_low_price[i] = max(low_price[i - 1], max_low_price[i - 1])

            if highma[i] < max_low_price[i] and data.Close[i] < data.Low[i - 1]:
                trend[i] = 1
                next_trend[i] = 0
                min_high_price[i] = high_price[i]
            else:
                # assign previous values again
                trend[i] = trend[i - 1]
                next_trend[i] = next_trend[i - 1]
                min_high_price[i] = min_high_price[i - 1]
        else:
            min_high_price[i] = min(high_price[i - 1], min_high_price[i - 1])

            if lowma[i] > min_high_price[i] and data.Close[i] > data.High[i - 1]:
                trend[i] = 0
                next_trend[i] = 1
                max_low_price[i] = low_price[i]
            else:
                # assign previous values again
                trend[i] = trend[i - 1]
                next_trend[i] = next_trend[i - 1]
                max_low_price[i] = max_low_price[i - 1]

    up = np.zeros(len(data))
    up[0] = max_low_price[0]
    down = np.zeros(len(data))
    down[0] = min_high_price[0]
    atr_high = np.zeros(len(data))
    atr_low = np.zeros(len(data))
    arrow_up = np.zeros(len(data))
    arrow_down = np.zeros(len(data))

    for i in range(1, len(data)):
        if trend[i] == 0:
            if trend[i - 1] != 0:
                up[i] = down[i - 1]
                arrow_up[i] = up[i] - atr2[i]
            else:
                up[i] = max(max_low_price[i - 1], up[i - 1])

            atr_high[i] = up[i] + dev[i]
            atr_low[i] = up[i] - dev[i]

        else:
            if trend[i - 1] != 1:
                down[i] = up[i - 1]
                arrow_down[i] = down[i] + atr2[i]
            else:
                down[i] = min(min_high_price[i - 1], down[i - 1])

            atr_high[i] = down[i] + dev[i]
            atr_low[i] = down[i] - dev[i]

    halftrend = np.where(trend == 0, up, down)
    buy = np.where((trend == 0) & (np.roll(trend, 1) == 1), 1, 0)
    sell = np.where((trend == 1) & (np.roll(trend, 1) == 0), 1, 0)

    # Construct DataFrame
    htdf = pd.DataFrame(data={'halftrend': halftrend,
                              'atrHigh': atr_high,
                              'atrLow': atr_low,
                              'arrowUp': arrow_up,
                              'arrowDown': arrow_down,
                              'buy': buy,
                              'sell': sell},
                        index=data.index)

    return htdf

[Vultwo]

Where did you find this function?
I'll use this function if the license allows it.