Source code for pandas_ta.overlap.pwma

```# -*- coding: utf-8 -*-
from pandas_ta.utils import get_offset, pascals_triangle, verify_series, weights

[docs]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

pwma.__doc__ = \
"""Pascal's Weighted Moving Average (PWMA)

Pascal's Weighted Moving Average is similar to a symmetric triangular window
except PWMA's weights are based on Pascal's Triangle.

Source: Kevin Johnson

Calculation:
Default Inputs:
length=10

def weights(w):
def _compute(x):
return np.dot(w * x)
return _compute

triangle = utils.pascals_triangle(length + 1)
PWMA = close.rolling(length)_.apply(weights(triangle), raw=True)

Args:
close (pd.Series): Series of 'close's
length (int): It's period.  Default: 10
asc (bool): Recent values weigh more. Default: True
offset (int): How many periods to offset the result. Default: 0

Kwargs:
fillna (value, optional): pd.DataFrame.fillna(value)
fill_method (value, optional): Type of fill method

Returns:
pd.Series: New feature generated.
"""
```