时序分析 45 -- 时序数据转为空间数据 (四) 格拉姆角场 python 实践（下）

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最新推荐文章于 2025-05-04 10:49:22 发布

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分类专栏：金融模型时序分析

本文链接：https://blog.youkuaiyun.com/weixin_43171270/article/details/127029166

格拉姆角场

python实践（下）

… 接上
下面我们将采用CNN模型来基于格拉姆角场python实践上的结果（时序数据已转化为图像数据）进行金融预测。

import tensorflow as tf
from tensorflow.keras.optimizers import Adam
from tensorflow.keras.preprocessing.image import ImageDataGenerator
from tensorflow.keras.callbacks import ReduceLROnPlateau
from tensorflow.keras.layers import *
import datetime as dt
import glob
import os

定义函数来处理数据

# Chunks DataFrames in a way that part of the data points is found in the previous chunk
def chunker(seq: pd.DataFrame, size: int, loops: int) -> Generator:
    """
    :param seq: As DataFrame
    :param size: As Integer
    :param loops: As integer
    :return: Generator with overlapping index DataFrames
    """
    rem = (seq.shape[0] - size)
    rem_split = rem // loops
    for i in range(10):
        yield seq.iloc[(i * rem_split): -(rem - (i * rem_split))]

def ensemble_data(networks_chunks: int, path: str) -> List[pd.DataFrame]:
    """
    :param networks_chunks: As Integer
    :param path: As String
    :return: List of overlapping index DataFrames
    """
    dataframes = []
    for sub_folder in ['LONG', 'SHORT']:
        images = glob.glob(path + '/{}/*.png'.format(sub_folder))  # Get path to images
        dates = [dt.split('/')[-1].split('\\')[-1].split('.')[0].replace('_', '-') for dt in images]
        data_slice = pd.DataFrame({
   
   'Images': images, 'Labels': [sub_folder] * len