Source code for pandas_ta.trend.amat

# -*- coding: utf-8 -*-
from pandas import DataFrame
from .long_run import long_run
from .short_run import short_run
from pandas_ta.overlap import ma
from pandas_ta.utils import get_offset, verify_series

[docs]def amat(close=None, fast=None, slow=None, lookback=None, mamode=None, offset=None, **kwargs): """Indicator: Archer Moving Averages Trends (AMAT)""" # Validate Arguments fast = int(fast) if fast and fast > 0 else 8 slow = int(slow) if slow and slow > 0 else 21 lookback = int(lookback) if lookback and lookback > 0 else 2 mamode = mamode.lower() if isinstance(mamode, str) else "ema" close = verify_series(close, max(fast, slow, lookback)) offset = get_offset(offset) if "length" in kwargs: kwargs.pop("length") if close is None: return # # Calculate Result fast_ma = ma(mamode, close, length=fast, **kwargs) slow_ma = ma(mamode, close, length=slow, **kwargs) mas_long = long_run(fast_ma, slow_ma, length=lookback) mas_short = short_run(fast_ma, slow_ma, length=lookback) # Offset if offset != 0: mas_long = mas_long.shift(offset) mas_short = mas_short.shift(offset) # # Handle fills if "fillna" in kwargs: mas_long.fillna(kwargs["fillna"], inplace=True) mas_short.fillna(kwargs["fillna"], inplace=True) if "fill_method" in kwargs: mas_long.fillna(method=kwargs["fill_method"], inplace=True) mas_short.fillna(method=kwargs["fill_method"], inplace=True) # Prepare DataFrame to return amatdf = DataFrame({ f"AMAT{mamode[0]}_LR_{fast}_{slow}_{lookback}": mas_long, f"AMAT{mamode[0]}_SR_{fast}_{slow}_{lookback}": mas_short }) # Name and Categorize it = f"AMAT{mamode[0]}_{fast}_{slow}_{lookback}" amatdf.category = "trend" return amatdf