plt实现动态画图 | 易学教程

用pycharm跑的没有出现动态线条的话：

1、点击setting，输入关键字Scien...搜索出Python Scientific，在右侧去掉对勾（默认是勾选的），然后右下角Apply--OK，即可完美解决。

2、这是在网上找的代码(原来是有问题的，我稍微修改了下，可以直接运行)：

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


def add_layer(inputs, in_size, out_size, activation_funiction=None):
    Weights = tf.Variable(tf.random_normal([in_size, out_size]))
    biases = tf.Variable(tf.zeros([1, out_size]) + 0.1)
    Wx_plus_b = tf.matmul(inputs, Weights) + biases
    if activation_funiction is None:
        outputs = Wx_plus_b
    else:
        outputs = activation_funiction(Wx_plus_b)
    return outputs


x_data = np.linspace(-1, 1, 300)[:, np.newaxis]
noise = np.random.normal(0, 0.05, x_data.shape)
y_data = np.square(x_data) - 0.5 + noise

xs = tf.placeholder(tf.float32, [None, 1])
ys = tf.placeholder(tf.float32, [None, 1])

# add hidden layer
l1 = add_layer(xs, 1, 10, activation_funiction=tf.nn.relu)
# add output layer
prediction = add_layer(l1, 10, 1, activation_funiction=None)

# the error between prediction and real data
loss = tf.reduce_mean(tf.reduce_sum(tf.square(ys - prediction), reduction_indices=[1]))
train_step = tf.train.GradientDescentOptimizer(0.1).minimize(loss)

init = tf.initialize_all_variables()

with tf.Session() as sess:
    sess.run(init)

    fig = plt.figure()
    ax = fig.add_subplot(1, 1, 1)
    ax.scatter(x_data, y_data)
    plt.ion()  # 将画图模式改为交互模式
    plt.show()
    for i in range(1000):
        sess.run(train_step, feed_dict={xs: x_data, ys: y_data})
        if i % 50 == 0:
            plt.pause(0.1)
        try:
            ax.lines.remove(lines[0])
        except Exception:
            pass
        prediction_value = sess.run(prediction, feed_dict={xs: x_data})
        lines = ax.plot(x_data, prediction_value, 'r-', lw=5)
        # print(sess.run(loss, feed_dict={xs: x_data, ys: y_data}))

        plt.ioff()
plt.show()

参考:https://www.jianshu.com/p/f659c421a5ac

来源：oschina

链接：https://my.oschina.net/u/4324321/blog/3621448

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