# -*- coding: UTF-8 -*-
"""
@Project -> File   ：IoD_data_analysis_tool -> outlierprocessing
@IDE    ：PyCharm
@Author ：rengengchen
@Date   ：2022/4/26 10:24
@Desc   ：
"""
from typing import Union

import pandas as pd


def MAD(data: pd.Series, n: float = 2.5, constant=1.4826, axis=0):
    """
    MAD = median(|Xi - median(X)|)
    @return pandas.Index
    """
    x = data.median()
    MC = (data - x).abs().median()
    MAD = MC * constant
    offset = n * MAD
    if isinstance(data, pd.DataFrame):
        return data.clip(lower=x - offset, upper=x + offset, axis=axis)
    else:
        return data.clip(lower=x - offset, upper=x + offset)


def three_sigma(data: pd.Series):
    miu = data.mean()
    sigma = data.std()
    low = miu - 3 * sigma
    up = miu + 3 * sigma
    return data.index[(data < low) | (data > up)]


def box_plot(data: pd.Series, q1: float = 0.25, q3: float = 0.75, k: float = 1.5):
    q = data.quantile(q=[q1, q3])
    IQR = q[q3] - q[q1]
    lower_whisker_limit = q[q1] - k * IQR
    upper_whisker_limit = q[q3] + k * IQR
    return data.index[(data < lower_whisker_limit) | (data > upper_whisker_limit)]


def regex_match(data: pd.Series, *patterns):
    pattern = '|'.join(patterns)
    return data.index[data.astype(str).str.contains(pattern, regex=True)]


def empty(data: Union[pd.Series, pd.DataFrame]):
    return any(data.isnull())