#-*- encoding:utf-8 -*-

'''
@Author : dingjiawen
@Date : 2023/5/22 20:33
@Usage : 
@Desc : lttb算法的实现：保留时序数据波动细节的算法
'''

import numpy as np
import pandas as pd
import lttb
def lttb_try(a):
    length, = a.shape
    print(length,":",length)
    b = np.array([range(length),a]).T
    print(b)
    print(b.shape)
    return lttb.downsample(b,n_out=int(length/10))

if __name__ == '__main__':
    cms_data_path = r"E:\data\cmsDemo\华能三塘湖项目（一期）_D3-29_Shaft2_径向_25600_加速度g_14.41RPM_20180618003450.csv"
    cms_data_df = pd.read_csv(cms_data_path, encoding='gbk', header=None)
    cms_data_df = cms_data_df.values[0]
    data_before = cms_data_df[:1000]
    down_sample = lttb_try(data_before)
    print(down_sample.shape)

    import matplotlib.pyplot as plt

    plt.subplot(2, 1, 1)
    plt.plot(data_before)
    plt.subplot(2, 1, 2)
    plt.plot(down_sample[:, 1])
    plt.show()

    # assert small_data.shape == (20, 2)

    # print(cms_send_data.shape)