Lucid sar to Python

[illi4]

I am trying to refactor the pinescript code to have an ability to calculate lucid SAR in Python. I am not having success and need some guidance / advice. Could someone please advice what I am doing wrong here?

def sar_v2(data, initial=0.02, increment=0.02, maximum=0.2):
  """
  Calculates the Lucid SAR indicator for a given DataFrame.

  Args:
      data: DataFrame containing columns for high, close, open, and low prices.
      initial: Initial acceleration factor.
      increment: Increment for acceleration factor.
      maximum: Maximum value for acceleration factor.

  Returns:
      A new DataFrame with an additional column named 'SAR' containing the Lucid SAR values.
  """
  data['SAR'] = float(data.loc[1, 'low'])  # Initialize SAR column with NaNs
  data['EP'] = float(data.loc[1, 'high'])  # Initialize EP column with NaNs
  data['AF'] = float(initial)  # Initialize AF column with NaNs
  data['uptrend'] = True     # Initialize uptrend flag (assuming uptrend starts)
  data['new_trend'] = False  # Initialize new_trend flag
  reversal_state = 0

  # Start from the 3rd candle to avoid NaNs
  for i in range(2, len(data)):
    # Handle previous values (avoid indexing issues)
    prev_uptrend = data.loc[i-1, 'uptrend']
    prev_new_trend = data.loc[i-1, 'new_trend']
    prev_EP = data.loc[i-1, 'EP']
    prev_SAR = data.loc[i-1, 'SAR']
    prev_AF = data.loc[i-1, 'AF']

    # Check reversal state
    if reversal_state == 0:
        if prev_uptrend:
            data.loc[i, 'EP'] = max(data.loc[i, 'high'], prev_EP)
        else:
            data.loc[i, 'EP'] = min(data.loc[i, 'low'], prev_EP)

        if prev_new_trend:
            data.loc[i, 'AF'] = initial
        else:
            if data.loc[i, 'EP'] != prev_EP:
                data.loc[i, 'AF'] = min(maximum, prev_AF + increment)
            else:
                data.loc[i, 'AF'] = prev_AF

        data.loc[i, 'SAR'] = prev_SAR + data.loc[i, 'AF'] * (data.loc[i, 'EP'] - prev_SAR)

        if prev_uptrend:
            data.loc[i, 'SAR'] = min(data.loc[i, 'SAR'], data.loc[i-1, 'low'])
            data.loc[i, 'SAR'] = min(data.loc[i, 'SAR'], data.loc[i-2, 'low'])
            if data.loc[i, 'SAR'] > data.loc[i, 'low']:
                data.loc[i, 'uptrend'] = False
                data.loc[i, 'new_trend'] = True
                data.loc[i, 'SAR'] = max(data.loc[i, 'high'], data.loc[i-1, 'EP'])
                data.loc[i, 'EP'] = min(data.loc[i, 'low'], data.loc[i-1, 'low'])
                reversal_state = 2
            else:
                data.loc[i, 'uptrend'] = True
                data.loc[i, 'new_trend'] = False
        else: #99
            data.loc[i, 'SAR'] = max(data.loc[i, 'SAR'], data.loc[i-1, 'high'])
            data.loc[i, 'SAR'] = max(data.loc[i, 'SAR'], data.loc[i-2, 'high'])
            if data.loc[i, 'SAR'] < data.loc[i, 'high']:
                data.loc[i, 'uptrend'] = True
                data.loc[i, 'new_trend'] = True
                data.loc[i, 'SAR'] = min(data.loc[i, 'low'], data.loc[i-1, 'EP'])
                data.loc[i, 'EP'] = max(data.loc[i, 'high'], data.loc[i-1, 'high'])
                reversal_state = 1
            else:
                data.loc[i, 'uptrend'] = False
                data.loc[i, 'new_trend'] = False
    # 111
    else:
        if reversal_state == 1:
            data.loc[i, 'EP'] = data.loc[i, 'high']
            if data.loc[i, 'low'] < data.loc[i, 'SAR']:
                data.loc[i, 'SAR'] = data.loc[i, 'EP']
                data.loc[i, 'EP'] = data.loc[i, 'low']
                reversal_state = 2  
                data.loc[i, 'uptrend'] = False
        else:
            data.loc[i, 'EP'] = data.loc[i, 'low']
            if data.loc[i, 'high'] > data.loc[i, 'SAR']:
                data.loc[i, 'SAR'] = data.loc[i, 'EP']
                data.loc[i, 'EP'] = data.loc[i, 'high']
                reversal_state = 1
                data.loc[i, 'uptrend'] = True

  return data

[illi4]

And another attempt that gives PSAR result rather than Lucid SAR even though the rule to never move the SAR into the previous day’s range or today’s range are in:

def get_psar(barsdata, iaf=0.02, maxaf=0.2):

    length = len(barsdata)
    high = list(barsdata['high'])
    low = list(barsdata['low'])
    close = list(barsdata['close'])
    psar = close[0:len(close)]
    psarbull = [None] * length
    psarbear = [None] * length
    bull = True
    af = iaf
    ep = low[0]
    hp = high[0]
    lp = low[0]

    for i in range(2,length):
        if bull:
            psar[i] = psar[i - 1] + af * (hp - psar[i - 1])
        else:
            psar[i] = psar[i - 1] + af * (lp - psar[i - 1])

        reverse = False

        if bull:
            if low[i] < psar[i]:
                bull = False
                reverse = True
                psar[i] = hp
                lp = low[i]
                af = iaf
        else:
            if high[i] > psar[i]:
                bull = True
                reverse = True
                psar[i] = lp
                hp = high[i]
                af = iaf

        if not reverse:
            if bull:
                if high[i] > hp:
                    hp = high[i]
                    af = min(af + iaf, maxaf)
                if low[i - 1] < psar[i]:
                    psar[i] = low[i - 1]
                if low[i - 2] < psar[i]:
                    psar[i] = low[i - 2]
            else:
                if low[i] < lp:
                    lp = low[i]
                    af = min(af + iaf, maxaf)
                if high[i - 1] > psar[i]:
                    psar[i] = high[i - 1]
                if high[i - 2] > psar[i]:
                    psar[i] = high[i - 2]

        if bull:
            psarbull[i] = psar[i]
            barsdata.loc[i, 'PSAR_direction'] = 1
            barsdata.loc[i, 'PSAR_val'] = psar[i]
        else:
            psarbear[i] = psar[i]
            barsdata.loc[i, 'PSAR_direction'] = -1
            barsdata.loc[i, 'PSAR_val'] = psar[i]

    return barsdata