# -*- coding: utf-8 -*-
from pandas_ta.utils import get_drift, get_offset, is_percent, verify_series
[docs]def increasing(close, length=None, strict=None, asint=None, percent=None, drift=None, offset=None, **kwargs):
"""Indicator: Increasing"""
# Validate Arguments
length = int(length) if length and length > 0 else 1
strict = strict if isinstance(strict, bool) else False
asint = asint if isinstance(asint, bool) else True
close = verify_series(close, length)
drift = get_drift(drift)
offset = get_offset(offset)
percent = float(percent) if is_percent(percent) else False
if close is None: return
# Calculate Result
close_ = (1 + 0.01 * percent) * close if percent else close
if strict:
# Returns value as float64? Have to cast to bool
increasing = close > close_.shift(drift)
for x in range(3, length + 1):
increasing = increasing & (close.shift(x - (drift + 1)) > close_.shift(x - drift))
increasing.fillna(0, inplace=True)
increasing = increasing.astype(bool)
else:
increasing = close_.diff(length) > 0
if asint:
increasing = increasing.astype(int)
# Offset
if offset != 0:
increasing = increasing.shift(offset)
# Handle fills
if "fillna" in kwargs:
increasing.fillna(kwargs["fillna"], inplace=True)
if "fill_method" in kwargs:
increasing.fillna(method=kwargs["fill_method"], inplace=True)
# Name and Categorize it
_percent = f"_{0.01 * percent}" if percent else ''
_props = f"{'S' if strict else ''}INC{'p' if percent else ''}"
increasing.name = f"{_props}_{length}{_percent}"
increasing.category = "trend"
return increasing
increasing.__doc__ = \
"""Increasing
Returns True if the series is increasing over a period, False otherwise.
If the kwarg 'strict' is True, it returns True if it is continuously increasing
over the period. When using the kwarg 'asint', then it returns 1 for True
or 0 for False.
Calculation:
if strict:
increasing = all(i < j for i, j in zip(close[-length:], close[1:]))
else:
increasing = close.diff(length) > 0
if asint:
increasing = increasing.astype(int)
Args:
close (pd.Series): Series of 'close's
length (int): It's period. Default: 1
strict (bool): If True, checks if the series is continuously increasing over the period. Default: False
percent (float): Percent as an integer. Default: None
asint (bool): Returns as binary. Default: True
drift (int): The difference period. Default: 1
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.
"""