# -*- coding: utf-8 -*-
from pandas import DataFrame, Series
from pandas_ta._typing import DictLike, Int, IntFloat
from pandas_ta.ma import ma
from pandas_ta.utils import (
    non_zero_range,
    v_drift,
    v_mamode,
    v_offset,
    v_pos_default,
    v_series
)



def accbands(
    high: Series, low: Series, close: Series, length: Int = None,
    c: IntFloat = None, drift: Int = None, mamode: str = None,
    offset: Int = None, **kwargs: DictLike
) -> DataFrame:
    """Acceleration Bands

    This indicator, by Price Headley, creates lower and upper bands centered
    around a moving average based on a ratio of it's High-Low range.

    Sources:
        * [tradingtechnologies](https://www.tradingtechnologies.com/help/x-study/technical-indicator-definitions/acceleration-bands-abands/)

    Parameters:
        high (Series): ```high``` Series
        low (Series): ```low``` Series
        close (Series): ```close``` Series
        length (int): The period. Default: ```10```
        c (int): Multiplier. Default: ```4```
        mamode (str): See ```help(ta.ma)```. Default: ```"sma"```
        drift (int): Difference amount. Default: ```1```
        offset (int): Post shift. Default: ```0```

    Other Parameters:
        fillna (value): ```pd.DataFrame.fillna(value)```

    Returns:
        (DataFrame): 3 columns
    """
    # Validate
    length = v_pos_default(length, 20)
    high = v_series(high, length)
    low = v_series(low, length)
    close = v_series(close, length)

    if high is None or low is None or close is None:
        return

    c = v_pos_default(c, 4)
    mamode = v_mamode(mamode, "sma")
    drift = v_drift(drift)
    offset = v_offset(offset)

    # Calculate
    high_low_range = non_zero_range(high, low)
    hl_ratio = high_low_range / (high + low)
    hl_ratio *= c
    _lower = low * (1 - hl_ratio)
    _upper = high * (1 + hl_ratio)

    lower = ma(mamode, _lower, length=length)
    mid = ma(mamode, close, length=length)
    upper = ma(mamode, _upper, length=length)

    # Offset
    if offset != 0:
        lower = lower.shift(offset)
        mid = mid.shift(offset)
        upper = upper.shift(offset)

    # Fill
    if "fillna" in kwargs:
        lower.fillna(kwargs["fillna"], inplace=True)
        mid.fillna(kwargs["fillna"], inplace=True)
        upper.fillna(kwargs["fillna"], inplace=True)

    # Name and Category
    lower.name = f"ACCBL_{length}"
    mid.name = f"ACCBM_{length}"
    upper.name = f"ACCBU_{length}"
    mid.category = upper.category = lower.category = "volatility"

    data = {lower.name: lower, mid.name: mid, upper.name: upper}
    df = DataFrame(data, index=close.index)
    df.name = f"ACCBANDS_{length}"
    df.category = mid.category

    return df