import torch
import math
import numpy as np
from visdom import Visdom
import time
torch.__version__

'1.0.0'

env = Visdom() 
assert env.check_connection() #测试一下链接，链接错误的话会报错

Y = np.linspace(0, 2 * math.pi, 70)
X = np.column_stack((np.sin(Y), np.cos(Y)))

env.stem(
        X=X,
        Y=Y,
        opts=dict(legend=['Sine', 'Cosine'])
    )

'window_36f18bc34b4992'

envtest = Visdom(env='test_mesh')
assert envtest.check_connection()

x = [0, 0, 1, 1, 0, 0, 1, 1]
y = [0, 1, 1, 0, 0, 1, 1, 0]
z = [0, 0, 0, 0, 1, 1, 1, 1]
X = np.c_[x, y, z]
i = [7, 0, 0, 0, 4, 4, 6, 6, 4, 0, 3, 2]
j = [3, 4, 1, 2, 5, 6, 5, 2, 0, 1, 6, 3]
k = [0, 7, 2, 3, 6, 7, 1, 1, 5, 5, 7, 6]
Y = np.c_[i, j, k]
envtest.mesh(X=X, Y=Y, opts=dict(opacity=0.5))

'window_36f18bc533e990'

x,y=0,0
env2 = Visdom()
pane1= env2.line(
    X=np.array([x]),
    Y=np.array([y]),
    opts=dict(title='dynamic data'))

for i in range(10):
    time.sleep(1) #每隔一秒钟打印一次数据
    x+=i
    y=(y+i)*1.5
    print(x,y)
    env2.line(
        X=np.array([x]),
        Y=np.array([y]),
        win=pane1,#win参数确认使用哪一个pane
        update='append') #我们做的动作是追加，除了追加意外还有其他方式，这里我们不做介绍了

0 0.0
1 1.5
3 5.25
6 12.375
10 24.5625
15 44.34375
21 75.515625
28 123.7734375
36 197.66015625
45 309.990234375

4.2.1 使用Visdom在 PyTorch 中进行可视化¶

安装¶

坑¶

基本概念¶

Environments¶

Panes¶

VIEW¶

可视化接口¶

使用¶

绘制简单的图形¶

更新损失函数¶