Files
OpenBB/gamestonk_terminal/common/technical_analysis/volume_model.py
LBolte29 6426b76771 decorated functions (#1282)
* decorated functions and removed assertion tests that are now caught by decorator logs
* modified functions with @property
* fixed bc of coingecko
* fixed outedated tests
2022-01-31 20:37:16 +01:00

106 lines
2.4 KiB
Python

"""Volume Technical Analysis"""
__docformat__ = "numpy"
import logging
import pandas as pd
import pandas_ta as ta
from gamestonk_terminal.decorators import log_start_end
logger = logging.getLogger(__name__)
@log_start_end(log=logger)
def ad(df_stock: pd.DataFrame, use_open: bool = False) -> pd.DataFrame:
"""Calculate AD technical indicator
Parameters
----------
df_stock : 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=df_stock["High"],
low=df_stock["Low"],
close=df_stock["Close"],
volume=df_stock["Volume"],
open_=df_stock["Open"],
).dropna()
# Do not use open stock values
else:
df_ta = ta.ad(
high=df_stock["High"],
low=df_stock["Low"],
close=df_stock["Close"],
volume=df_stock["Volume"],
).dropna()
return pd.DataFrame(df_ta)
@log_start_end(log=logger)
def adosc(
df_stock: pd.DataFrame, use_open: bool = False, fast: int = 3, slow: int = 10
) -> pd.DataFrame:
"""Calculate AD oscillator technical indicator
Parameters
----------
df_stock : pd.DataFrame
Dataframe of prices
use_open : bool
Whether to use open prices
Returns
-------
pd.DataFrame
Dataframe with technical indicator
"""
if use_open:
df_ta = ta.adosc(
high=df_stock["High"],
low=df_stock["Low"],
close=df_stock["Close"],
volume=df_stock["Volume"],
open_=df_stock["Open"],
fast=fast,
slow=slow,
).dropna()
else:
df_ta = ta.adosc(
high=df_stock["High"],
low=df_stock["Low"],
close=df_stock["Close"],
volume=df_stock["Volume"],
fast=fast,
slow=slow,
).dropna()
return pd.DataFrame(df_ta)
@log_start_end(log=logger)
def obv(df_stock: pd.DataFrame) -> pd.DataFrame:
"""On Balance Volume
Parameters
----------
df_stock: pd.DataFrame
Dataframe of stock prices
Returns
-------
pd.DataFrame
Dataframe with technical indicator
"""
return pd.DataFrame(
ta.obv(close=df_stock["Adj Close"], volume=df_stock["Volume"]).dropna()
)