OpenBB/openbb_terminal/common/technical_analysis/volume_model.py

"""Volume Technical Analysis"""
__docformat__ = "numpy"

import logging

import pandas as pd
import pandas_ta as ta

from openbb_terminal.decorators import log_start_end

logger = logging.getLogger(__name__)


@log_start_end(log=logger)
def ad(data: pd.DataFrame, use_open: bool = False) -> pd.DataFrame:
    """Calculate AD technical indicator

    Parameters
    ----------
    data : pd.DataFrame
        Dataframe of prices with OHLC and Volume
    use_open : bool
        Whether to use open prices

    Returns
    -------
    pd.DataFrame
        Dataframe with technical indicator
    """
    if use_open:
        df_ta = ta.ad(
            high=data["High"],
            low=data["Low"],
            close=data["Close"],
            volume=data["Volume"],
            open_=data["Open"],
        ).dropna()
    # Do not use open stock values
    else:
        df_ta = ta.ad(
            high=data["High"],
            low=data["Low"],
            close=data["Close"],
            volume=data["Volume"],
        ).dropna()
    return pd.DataFrame(df_ta)


@log_start_end(log=logger)
def adosc(
    data: pd.DataFrame, use_open: bool = False, fast: int = 3, slow: int = 10
) -> pd.DataFrame:
    """Calculate AD oscillator technical indicator

    Parameters
    ----------
    data : pd.DataFrame
        Dataframe of OHLC prices
    use_open : bool
        Whether to use open prices
    fast: int
        Fast value
    slow: int
        Slow value

    Returns
    -------
    pd.DataFrame
        Dataframe with technical indicator
    """
    if use_open:
        df_ta = ta.adosc(
            high=data["High"],
            low=data["Low"],
            close=data["Close"],
            volume=data["Volume"],
            open_=data["Open"],
            fast=fast,
            slow=slow,
        ).dropna()
    else:
        df_ta = ta.adosc(
            high=data["High"],
            low=data["Low"],
            close=data["Close"],
            volume=data["Volume"],
            fast=fast,
            slow=slow,
        ).dropna()
    return pd.DataFrame(df_ta)


@log_start_end(log=logger)
def obv(data: pd.DataFrame) -> pd.DataFrame:
    """On Balance Volume

    Parameters
    ----------
    data: pd.DataFrame
        Dataframe of OHLC prices

    Returns
    -------
    pd.DataFrame
        Dataframe with technical indicator
    """
    return pd.DataFrame(ta.obv(close=data["Adj Close"], volume=data["Volume"]).dropna())