使用matplotlib画图时有时会收到来自matplotlib的runtime warming的警告，原因可能是同时打开太多张图，最常见的情况是在一个循环中画图，每次循环都新建一个图，但是未关闭新建的图，当循环次数多了之后内存就吃不消了。
有两种解决方法，一是只建一个图，每次循环结束后通过plt.cla()清除图的内容，下次循环可以使用同一张图作画，例子如下：
import os
import scipy
import tensorflow as tf
import numpy as np
import matplotlib.pyplot as plt
from tqdm import tqdmdata_path = r"D:\PycharmProjects\dataset"def load_mnist():path = os.path.join(data_path, 'mnist')fd = open(os.path.join(path, 't10k-images-idx3-ubyte'))loaded = np.fromfile(file=fd, dtype=np.uint8)teX = loaded[16:].reshape((10000, 28, 28, 1)).astype(np.float)teX = teX / 255.return teXteX = load_mnist()
fig, ax = plt.subplots(nrows=5, ncols=5, sharex='all', sharey='all') # 只建一张包含25个子图的图
ax = ax.flatten()
for j in range(3):for i in range(25):img = teX[i + j * 25].reshape(28, 28)ax[i].imshow(img, cmap='Greys', interpolation='nearest')ax[0].set_xticks([])ax[0].set_yticks([])plt.tight_layout() # 自动紧凑布局plt.savefig(r"D:\test\%d.png" % j)plt.cla() # 清除内容第二种方法是每次循环都新建一张图，但是每次循环结束后关闭这张图，例子如下：
import os
import scipy
import tensorflow as tf
import numpy as np
import matplotlib.pyplot as plt
from tqdm import tqdmdata_path = r"D:\PycharmProjects\dataset"def load_mnist():path = os.path.join(data_path, 'mnist')fd = open(os.path.join(path, 't10k-images-idx3-ubyte'))loaded = np.fromfile(file=fd, dtype=np.uint8)teX = loaded[16:].reshape((10000, 28, 28, 1)).astype(np.float)teX = teX / 255.return teXteX = load_mnist() # 获取mnist的测试数据for j in range(3): # 画三张图fig, ax = plt.subplots(nrows=5, ncols=5, sharex='all', sharey='all') # 每次都新建一张包含25个子图的图ax = ax.flatten()for i in range(25):img = teX[i + j * 25].reshape(28, 28)ax[i].imshow(img, cmap='Greys', interpolation='nearest')ax[0].set_xticks([])ax[0].set_yticks([])plt.tight_layout() # 自动紧凑布局plt.savefig(r"D:\test\%d.png" % j)plt.close()实验证明，用第二种方法会比第一种方法快很多
