matplotlib非常慢.正常吗

问题描述

我正在使用matplotlib创建几个pdf绘图，其中包括400个子图.每个只有5个数据点.好的计算机上需要420秒才能保存5张pdf图片.有什么方法可以优化代码，或者对于matplotlib来说是正常的吗?

I am creating a couple of pdf plots with matplotlib which is composed of 400 subplots. Each one has only 5 data points. It takes 420 s on a good computer to save 5 pdf picture. Is there any way to optimize the code or it is just normal for matplotlib?

用于绘制的代码部分:

plot_cnt = 1
for k in np.arange(K_min, K_max + 1):
    for l in np.arange(L_min, L_max + 1):
        ax = plt.subplot(grid[0], grid[1], plot_cnt)
        plot_cnt += 1
        plt.setp(ax, 'frame_on', False)
        ax.set_ylim([-0.1, 1.1])
        ax.set_xlabel('K={},L={}'.format(k, l), size=3)
        ax.set_xlim([-0.1, 4.1])
        ax.set_xticks([])
        ax.set_yticks([])
        ax.grid('off')
        ax.plot(np.arange(5), (data['S1']['Azimuth'][:, k - 1, l + offset_l] + \
                data['S1']['Delta Speed'][:, k - 1, l + offset_l] + \
                data['S1']['Speed'][:, k - 1, l + offset_l]) / 3,
                'r-o', ms=1, mew=0, mfc='r')
        ax.plot(np.arange(5), data['S2'][case][:, k - 1, l + offset_l],
                'b-o', ms=1, mew=0, mfc='b')
plt.savefig(os.path.join(os.getcwd(), 'plot-average.pdf'))
plt.clf()
print 'Final plot created.'

最终图片:

推荐答案

以@rowman所说的内容为基础，您可以在一个轴上完成所有操作(关闭所有刻度线等).像这样:

Building off of what @rowman said, you can do this all in one axes (as you turn off all the ticks etc). Something like:

K_max = 20
K_min = 0
L_max = 20
L_min = 0
ax = plt.subplot(111)
x_offset = 7 # tune these
y_offset = 7 # tune these
plt.setp(ax, 'frame_on', False)
ax.set_ylim([0, (K_max-K_min +1)*y_offset ])
ax.set_xlim([0, (L_max - L_min+1)*x_offset])
ax.set_xticks([])
ax.set_yticks([])
ax.grid('off')



for k in np.arange(K_min, K_max + 1):
    for l in np.arange(L_min, L_max + 1):
        ax.plot(np.arange(5) + l*x_offset, 5+rand(5) + k*y_offset,
                'r-o', ms=1, mew=0, mfc='r')
        ax.plot(np.arange(5) + l*x_offset, 3+rand(5) + k*y_offset,
                'b-o', ms=1, mew=0, mfc='b')
        ax.annotate('K={},L={}'.format(k, l), (2.5+ (k)*x_offset,l*y_offset), size=3,ha='center')
plt.savefig(os.path.join(os.getcwd(), 'plot-average.pdf'))

print 'Final plot created.'

运行大约一两秒.我认为所有时间都花在设置axes对象上，该对象内部非常复杂.

Runs in about a second or two. I think all of the time is spent setting up the axes object which are rather complex internally.

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