如何在简单的UI中为python程序显示实时图形? [英] How do I display real-time graphs in a simple UI for a python program?

问题描述

我有一个复杂的算法，可以更新存储在数组中的3个直方图.我想调试算法，因此我想在用户界面中将数组显示为直方图.什么是最简单的方法. (快速的应用程序开发比优化的代码更重要.)

I have a complicated algorithm that updates 3 histograms that are stored in arrays. I want to debug my algorithm, so I was thinking of showing the arrays as histograms in a user interface. What is the easiest way to do this. (Rapid application development is more important than optimized code.)

我对Qt(在C ++中)有一些经验，对matplotlib也有一些经验.

I have some experience with Qt (in C++) and some experience with matplotlib.

(我将把这个问题搁置一两天，因为在没有很多我没有的经验的情况下，我很难评估解决方案.希望社区的投票将有助于选择最佳答案)

(I'm going to leave this question open for a day or two because it's hard for me to evaluate the solutions without a lot more experience that I don't have. Hopefully, the community's votes will help choose the best answer.)

推荐答案

如今，使用matplotlib.animation更容易，更好:

Nowadays, it is easier and better to use matplotlib.animation:

import numpy as np
import matplotlib.pyplot as plt
import matplotlib.animation as animation


def animate(frameno):
    x = mu + sigma * np.random.randn(10000)
    n, _ = np.histogram(x, bins, normed=True)
    for rect, h in zip(patches, n):
        rect.set_height(h)
    return patches    

mu, sigma = 100, 15
fig, ax = plt.subplots()
x = mu + sigma * np.random.randn(10000)
n, bins, patches = plt.hist(x, 50, normed=1, facecolor='green', alpha=0.75)

ani = animation.FuncAnimation(fig, animate, blit=True, interval=10,
                              repeat=True)
plt.show()

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在此处有一个制作动画图的示例. 在此示例的基础上，您可以尝试类似的操作:

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There is an example of making an animated graph here. Building on this example, you might try something like:

import numpy as np
import matplotlib.pyplot as plt

plt.ion()
mu, sigma = 100, 15
fig = plt.figure()
x = mu + sigma*np.random.randn(10000)
n, bins, patches = plt.hist(x, 50, normed=1, facecolor='green', alpha=0.75)
for i in range(50):
    x = mu + sigma*np.random.randn(10000)
    n, bins = np.histogram(x, bins, normed=True)
    for rect,h in zip(patches,n):
        rect.set_height(h)
    fig.canvas.draw()

通过这种方式，我每秒可以得到大约14帧，而使用代码

I can get about 14 frames per second this way, compared to 4 frames per second using the code I first posted. The trick is to avoid asking matplotlib to draw complete figures. Instead call plt.hist once, then manipulate the existing matplotlib.patches.Rectangles in patches to update the histogram, and call fig.canvas.draw() to make the updates visible.

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