code: def wma(
      close, length=None, asc=None, talib=None, offset=None, **kwargs
  ):
      """Indicator: Weighted Moving Average (WMA)"""
      # Validate Arguments
      length = int(length) if length and length > 0 else 10
      asc = asc if asc else True
      close = verify_series(close, length)
      offset = get_offset(offset)
      mode_tal = bool(talib) if isinstance(talib, bool) else True
  
      if close is None:
          return
  
      # Calculate Result
      if Imports["talib"] and mode_tal:
          from talib import WMA
  
          wma = WMA(close, length)
      else:
          from numpy import arange as npArange
          from numpy import dot as npDot
  
          total_weight = 0.5 * length * (length + 1)
          weights_ = Series(npArange(1, length + 1))
          weights = weights_ if asc else weights_[::-1]
  
          def linear(w):
              def _compute(x):
                  return npDot(x, w) / total_weight
  
              return _compute
  
          close_ = close.rolling(length, min_periods=length)
          wma = close_.apply(linear(weights), raw=True)
  
      # Offset
      if offset != 0:
          wma = wma.shift(offset)
  
      # Handle fills
      if "fillna" in kwargs:
          wma.fillna(kwargs["fillna"], inplace=True)
      if "fill_method" in kwargs:
          wma.fillna(method=kwargs["fill_method"], inplace=True)
  
      # Name & Category
      wma.name = f"WMA_{length}"
      wma.category = "overlap"
  
      return wma
  
label_desc: Use image node_id 1 for calling a global function with example usage: wma(close, length, asc, talib, offset) and returns: wma, _compute, unknown