Python implementa una red neuronal artificial para aproximar el precio de las acciones 1 Se trazan datos básicos

 Código fuente

# encoding:utf-8

import tensorflow as tf
import numpy as np
import matplotlib.pyplot as plt

# 线性增长
date = np.linspace(1, 15, 15)

# 当天的收盘价格
endPrice = np.array([2511.90,2538.26,2510.68,2591.66,2732.98,2701.69,2701.29,2678.67,2726.50,2681.50,2739.17,2715.07,2823.58,2864.90,2919.08]
)

# 当天的开盘价格
beginPrice = np.array([2438.71,2500.88,2534.95,2512.52,2594.04,2743.26,2697.47,2695.24,2678.23,2722.13,2674.93,2744.13,2717.46,2832.73,2877.40])

# print(date)  # 打印日期

plt.figure()
for i in range(0,15):
    # 通过循环遍历数据画出柱状图
    # x坐标
    dateOne = np.zeros([2])
    dateOne[0] = i
    dateOne[1] = i
#     print(dateOne)
    # y坐标
    priceOne = np.zeros([2])
    priceOne[0] = beginPrice[i]
    priceOne[1] = endPrice[i]
    if endPrice[i] > beginPrice[i]:
        # 如果收盘价格大于开盘价格说明股票上涨 用红色表示 lw为线条粗细
        plt.plot(dateOne, priceOne,'r',lw=8)
    else:
        # 如果收盘价格小于开盘价格说明股票下跌 用绿色表示 lw为线条粗细
        plt.plot(dateOne, priceOne,'g',lw=5)
plt.show()

Efecto