2-21 小综合：人工神经网络逼近股票价格3

import tensorflow as tf
import numpy as np
import matplotlib.pyplot as plt
date = np.linspace(1,15,15)
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])
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)
plt.figure()
for i in range(0,15):
    # 1 柱状图
    dateOne = np.zeros([2])
    dateOne[0] = i;
    dateOne[1] = i;
    priceOne = np.zeros([2])
    priceOne[0] = beginPrice[i]
    priceOne[1] = endPrice[i]
    if endPrice[i]>beginPrice[i]:
        plt.plot(dateOne,priceOne,'r',lw=8)
    else:
        plt.plot(dateOne,priceOne,'g',lw=8)
plt.show()
# A(15*1)*w1(1*10)+b1(1*10) = B(15*10)
# B(15*10)*w2(10*1)+b2(15*1) = C(15*1)
# 1 A B C
dateNormal = np.zeros([15,1])
priceNormal = np.zeros([15,1])
for i in range(0,15):
    dateNormal = i/14.0;
    priceNormal = endPrice[i]/3000.0;
x = tf.placeholder(tf.float32,[None,1])# N行1列的
y = tf.placeholder(tf.float32,[None,1])
# B
w1 = tf.Variable(tf.random_uniform([1,10],0,1))
b1 = tf.Variable(tf.zeros([1,10]))
wb1 = tf.matmul(x,w1)+b1
layer1 = tf.nn.relu(wb1) # 激励函数