时间序列：简易prophet

之前介绍过的时间序列综述： https://blog.csdn.net/weixin_38812492/article/details/113205598

安装

pip install pystan
pip install convertdate
pip install fbprophet

quick start

主要按照文档简单跑了一下，还需要对参数比较了解

import sys
sys.path.append('..')

import pandas as pd
import matplotlib.pyplot as plt
from fbprophet import Prophet
from tf_trainer import *


def train():
    label = pd.read_csv('../data/labels.csv', parse_dates=[0],
                        date_parser=lambda x: pd.datetime.strptime(str(x), '%Y-%m-%d %H:%M:%S'))
    label = aggregate2day(label)
    x_train = label.loc[:, ['timestamp', 'hv']]
    x_train.rename(columns={'timestamp': 'ds', 'hv': 'y'}, inplace=True)
    print(label)

    model = Prophet()
    model.fit(x_train)

    future = model.make_future_dataframe(periods=14)
    print(future.tail())

    forecast = model.predict(future)
    forecast[['ds', 'yhat']].tail()

    model.plot(forecast)
    plt.show()


if __name__ == '__main__':
    train()