python-LMDI实现及数据示例

def LMDI(*,data_t:object, data_0:object, yt:float, y0:float) -> object:    """    Args:        data_t:t期结果值,example        data_0:基期结果值        yt: t期结果值        y0: 基期结果值    Returns:        object['x']['key'] 代表x的key,x为自变量        object['x']['key']['x0']: 基期值        object['x']['key']['xt']: t期值        object['x']['key']['change']: 变动值        object['x']['key']['changeRate']: 变动率，即同比值        object['x']['key']['contribute']: LMDI计算得贡献度        object['x']['key']['contributeRate']: 基期贡献率, LMDI计算得贡献度 / y0        object['x']['key']['changeContributeRate']: 变动值贡献率, LMDI计算得贡献度 / object['y']['change']        object['y'] y代表因变量        object['y']['y0']: 基期值        object['y']['yt']: 本期值        object['y']['change']: 变动值        object['y']['changeRate']: 变动率，即同比值    Raises:        ValueError: data_t/data_0的内容相乘不等于yt/y0, data_t和data_0的key名称及数量不相等    """    from functools import reduce    import numpy as np     # 对参数进行校验    data_0_comp = reduce(lambda x,y:x*y,data_0.values())    data_t_comp = reduce(lambda x,y:x*y,data_t.values())    if ( data_t_comp - yt > 1 or data_t_comp - yt <-1) :  # 考虑到float的计算精度，这里放了gap值不能大于1        raise ValueError('data_t的内容相乘不等于tt')    elif (data_0_comp - y0 > 1 or data_0_comp - y0 <-1):        raise ValueError('data_0的内容相乘不等于tt')    elif data_t.keys() != data_0.keys():        raise ValueError('data_t和data_0的key名称及数量不相等')    def Delta_XX(*,yt,y0,xt,x0):        # 计算LMDI中每个参数的Δ值        def L(yt,y0):            if yt == y0:                return 0            else:                return (yt-y0)/(np.log(yt) - np.log(y0))        return L(yt,y0)*np.log(xt/x0)        x = {}    for key in data_t.keys():         x[key] = {}        x[key]['x0'] = data_0[key]        x[key]['xt'] = data_t[key]        x[key]['change'] = data_t[key]- data_0[key]        x[key]['changeRate'] = 0 if data_0[key]==0 or data_0[key]==0 or data_0[key]=="" else (data_t[key]- data_0[key]) / data_0[key]        x[key]['contribute'] = Delta_XX(yt=yt,y0=y0,xt=data_t[key], x0=data_0[key])         x[key]['contributeRate'] = 0 if y0==0 else x[key]['contribute']  / y0        x[key]['changeContributeRate'] = 0 if yt-y0 == 0 else  x[key]['contribute'] / (yt-y0)    y = {}    y['y0'] = y0    y['yt'] = yt    y['change'] = yt - y0    y['changeRate'] = 0 if yt ==0 or y0==0 else (yt-y0)/yt        result = {        "x":x,        "y":y    }    return result# 计算结果y0 = 1078122 # 基期结果值yt = 1469699  # t期结果值data_t = {    "uv":19087,    "m": 0.25,    "d": 308} # t期分解值集合data_0 = {    "uv":20032,    "m": 0.23,    "d": 234} # 基期分解值集合LMDI(data_t=data_t,data_0=data_0,yt=yt,y0=y0)

参考：LMDI 理论推导详解【从理论到Python-MATLAB实现（编程实现）】_春风惹人醉的博客-CSDN博客_lmdi模型python实现

来源地址：https://blog.csdn.net/fzcg1994/article/details/128922961