Question

下面给出了从文件中读取值并绘制它们的代码。我正在阅读大约36000个值。我正在使用matplotlib来绘制它们。如果值低于某个阈值，我将删除并旋转我为绘图制作的网格。

def readdata():
    global mul
    global fig
    global S
    global flag
    global k
    global line_number
    global readcount
    global angle_deviate
    global true_counter
    global fail_flag
    global loop_count
    global ts
    global xlist
    global ylist
    while k<S:
        line_number=line_number+1
        line=linecache.getline("data.txt", line_number)
        if line_number==1:
            x=float(line)*math.cos(0)
            y=float(line)*math.sin(0)
            xlist.append(300+x)
            ylist.append(300+y)
        else:
            x=float(line)*math.cos((readcount-1)*mul/samp_rate)
            y=float(line)*math.sin((readcount-1)*mul/samp_rate)
            xlist.append(300+x)
            ylist.append(300+y)
        plt.plot(xlist, ylist, lw=1, color='#ee8d18')
        if true_counter <(samp_rate*t[k]): #true counter to determine if the stage is complete or not
            if k<S-1 and k!=S-1:
                if p[k]<float(line):
                    true_counter=true_counter+1
                    fail_flag=1
                    point=plt.plot(300+x, 300+y, '.', markersize=3, color='#ee8d18')
                    loop_count+=1
                    pts.append(point)
                    readcount+=1
                    plt.pause(0.1) #first pause in plotting for 0.1 seconds
                    continue
                else:
                    readcount+=1
                    true_counter=0
                    point=plt.plot(300+x, 300+y, '.', markersize=3, color='#ee8d18')
                    loop_count+=1
                    pts.append(point)
                    plt.pause(0.1) #first pause in plotting for 0.1 seconds
                    deleteplot(k, fail_flag, loop_count)
            if k==S-1:
                if p[k]<float(line):
                    readcount+=1
                    true_counter=true_counter+1
                    x=float(line)*math.cos((readcount-1)*mul/samp_rate)
                    y=float(line)*math.sin((readcount-1)*mul/samp_rate)
                    point=plt.plot(300+x, 300+y, '.', markersize=3, color='#ee8d18')
                    loop_count+=1
                    pts.append(point)
                    plt.pause(0.1) #first pause in plotting for 0.1 seconds
                    continue
                else:
                    readcount+=1
                    true_counter=0
                    point=plt.plot(300+x, 300+y, '.', markersize=3, color='#ee8d18')
                    loop_count+=1
                    pts.append(point)
                    plt.pause(0.1) #first pause in plotting for 0.1 seconds
                    deleteplot(k, fail_flag, loop_count)
        else:
            true_counter=0
            k+=1
            fail_flag=0
            line_number=line_number-1
            loop_count=0
            i=0
            while i<S+1:
                cumulative_theta[i]=rotate_theta[i]
                i+=1

问题是这段代码像任何东西一样使用内存。它从30MB开始，一小时左右就达到260-300 MB。如何减少内存使用量？我还能做些什么来减少CPU负载和内存中断？

Answer 1

我怀疑你想要这样的东西：

from matplotlib import pyplot as plt

# make figure + axes
fig, ax = plt.subplots(1, 1)
# make base line
ln, = ax.plot([], [], 'r')
for j in range(50):
      # get current data
      x_data = list(ln.get_xdata())
      y_data = list(ln.get_ydata())
      # append new data, or do what ever you want to it

      x_data.append(j)
      y_data.append(j * j)
      # to keep just last n points, x_data = x_data[-n:]
      # set data of existing line
      ln.set_xdata(x_data)
      ln.set_ydata(y_data)
      # auto-scale the view limits
      ax.relim()
      ax.autoscale()
      # force the canvas to redraw
      plt.draw()
      # pause to give the gui time to refresh
      plt.pause(.1)

不会在内部循环中创建任何新对象，只需更新现有对象。

我还会研究animation模块示例。

Matplotlib过度使用内存

1 个答案: