test.py

#coding=utf-8
import numpy as np
import matplotlib.pyplot as plt
from mpl_toolkits.mplot3d import Axes3D

import sys
import numpy as np
import matplotlib.pyplot as plt
import tensorflow as tf
from mpl_toolkits.mplot3d import Axes3D

def calc_loss(a,b,x,y):
    tmp = y - (a * x + b)
    tmp = tmp ** 2  # 对矩阵内的每一个元素平方
    SSE = sum(tmp) / (2 * len(x))
    return SSE

# 计算x,y坐标对应的高度值
def draw_hill(x, y):
    a = np.linspace(-1, 1, 2)
    print(a)
    b = np.linspace(-1, 1, 2)
    x = np.array(x)
    y = np.array(y)

    allSSE = np.zeros(shape=(len(a),len(b))) #Height是个 3*3 的数组，记录地图上 9 个点的高度汇总

    for ai in range(0,len(a)):
        for bi in range(0,len(b)):
            a0 = a[ai]
            b0 = b[bi]
            SSE = calc_loss(a=a0, b=b0, x=x, y=y)
            allSSE[ai][bi] = SSE

    a,b = np.meshgrid(a, b)
    return [a, b, allSSE]


x = [0.1, 0.5]
y = [0.2, 0.9]

[ha, hb, hallSSE] = draw_hill(x, y)

hallSSE = np.matrix([[10,20],[40,50]])

hallSSE = hallSSE.T # 重要，将所有的losses做一个转置。原因是矩阵是以左上角至右下角顺序排列元素，而绘图是以左下角为原点。

fig = plt.figure(1, figsize=(12, 8))
# 绘制图1的曲面
ax = fig.add_subplot(2, 1, 1, projection='3d')
ax.set_top_view()
ax.plot_surface(ha, hb, hallSSE, rstride=2, cstride=2, cmap='rainbow')

# 绘制图2的等高线图
plt.subplot(2,1,2)
plt.contourf(ha, hb, hallSSE, 15, alpha=0.5, cmap=plt.cm.hot)
C = plt.contour(ha, hb, hallSSE, 15, colors='black')
plt.clabel(C, inline=True)
plt.xlabel('opt param: a')
plt.ylabel('opt param: b')

plt.show()




# # 生成x,y的数据
# n = 256
# x = np.linspace(-3, 3, n)
# y = np.linspace(-3, 3, n)
#
# # 把x,y数据生成mesh网格状的数据，因为等高线的显示是在网格的基础上添加上高度值
# X, Y = np.meshgrid(x, y)
#
# # 填充等高线
# plt.contourf(X, Y, f(X, Y), 20, cmap=plt.cm.hot)
# # 添加等高线
# C = plt.contour(X, Y, f(X, Y), 20)
# plt.clabel(C, inline=True, fontsize=12)
# # 显示图表
# plt.show()

# 绘制两点间直线
# plt.plot([10, 15], [-20, -55], 'r-')
# plt.plot([15, 25], [-55, -90], 'r-')
# plt.show()