def pwma(close, length=None, asc=None, offset=None, **kwargs):
"""Indicator: Pascals Weighted Moving Average (PWMA)"""
# Validate Arguments
close = verify_series(close)
length = int(length) if length and length > 0 else 10
min_periods = int(
kwargs["min_periods"]) if "min_periods" in kwargs and kwargs[
"min_periods"] is not None else length
asc = asc if asc else True
offset = get_offset(offset)
# Calculate Result
triangle = pascals_triangle(n=length - 1, weighted=True)
pwma = close.rolling(length, min_periods=length).apply(weights(triangle),
raw=True)
# Offset
if offset != 0:
pwma = pwma.shift(offset)
# Name & Category
pwma.name = f"PWMA_{length}"
pwma.category = "overlap"
return pwma
def pwma(close, length=None, asc=None, offset=None, **kwargs):
"""Indicator: Pascals Weighted Moving Average (PWMA)"""
# 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)
if close is None: return
# Calculate Result
triangle = pascals_triangle(n=length - 1, weighted=True)
pwma = close.rolling(length, min_periods=length).apply(weights(triangle), raw=True)
# Offset
if offset != 0:
pwma = pwma.shift(offset)
# Handle fills
if "fillna" in kwargs:
pwma.fillna(kwargs["fillna"], inplace=True)
if "fill_method" in kwargs:
pwma.fillna(method=kwargs["fill_method"], inplace=True)
# Name & Category
pwma.name = f"PWMA_{length}"
pwma.category = "overlap"
return pwma