SpanSelector与傅立叶分析

Question

我正在尝试使用matplotlib小部件SpanSelector来找出在某些用户点击的时间间隔的情节的频率。我试图用matplotlib小部件SpanSelector来做到这一点，但我不确定如何做到这一点。我尝试修改给出的示例http://matplotlib.org/examples/widgets/span_selector.html ，但它不起作用，仍然只在选定区域中放大。这里是我的代码，我想一起工作：

import numpy as np 
import matplotlib.pyplot as plt 
from matplotlib.widgets import SpanSelector 

fig = plt.figure(figsize=(8,6)) 
ax = fig.add_subplot(211, axisbg='#FFFFCC') 

def make_f(start,end): 
    sum = 0 
    for n in range(start,end+1): 
     sum += np.cos(n * np.pi *time) 
    return sum 

time = np.linspace(0,10,2000) 
signal = make_f(1,10) 

ax.plot(time, signal, '-') 
#ax.set_ylim(-2,2) 
ax.set_title('Press left mouse button and drag to test') 


fourier = np.fft.rfft(signal) 
n = signal.size 
rate = time[1]-time[0] 

ax2 = fig.add_subplot(212, axisbg='#FFFFCC') 
line2, = ax2.plot(np.fft.rfftfreq(n,rate), 20*np.log10(fourier), '-') 


def onselect(xmin, xmax): 
    indmin, indmax = np.searchsorted(time, (xmin, xmax)) 
    indmax = min(len(time)-1, indmax) 

    thisx = time[indmin:indmax] 
    thisy = signal[indmin:indmax] 
    line2.set_data(thisx, thisy) 
    ax2.set_xlim(thisx[0], thisx[-1]) 
    ax2.set_ylim(thisy.min(), thisy.max()) 
    fig.canvas.draw() 

# set useblit True on gtkagg for enhanced performance 
def make_fourier(): 
    signal = SpanSelector(ax, onselect, 'horizontal', useblit=True, 
        rectprops=dict(alpha=0.5, facecolor='red')) 
    fourier = np.fft.rfft(signal) 
    n = signal.size 
    rate = time[1]-time[0] 
    return fourier 

span = make_fourier() 
plt.show() 

Answer 1

我想出最好的办法是做在ONSELECT功能的变化。所以新的源代码将是：

# -*- coding: utf-8 -*- 
""" 
Created on Tue May 19 10:45:47 2015 

@author: greenthumbtack 
""" 

import numpy as np 
import matplotlib.pyplot as plt 
from matplotlib.widgets import SpanSelector 


fig,axarr = plt.subplots(2,3) 
#fig = plt.figure(figsize=(10,8)) 

def make_f(start,end): 
    sum = 0 
    for n in range(start,end+1): 
     sum += np.cos(2 * n * np.pi *time) + 2* np.random.random() 
    return sum 

time = np.linspace(0,10,1001) 
signal = make_f(1,10) 

axarr[0,0].plot(time, signal, '-') 
#ax.set_ylim(-2,2) 
axarr[0,0].set_title('Press left mouse button and drag to test') 


fourier = np.fft.rfft(signal) 
n = signal.size 
rate = time[1]-time[0] 

axarr[1,0].plot(np.fft.rfftfreq(n,rate), 20*np.log10(fourier), '-') 
axarr[0,1].plot(time, signal) 
axarr[1,1].plot(np.fft.rfftfreq(n,rate), 20*np.log10(fourier), '-') 
axarr[0,2].plot(time, signal) 
axarr[1,2].plot(np.fft.rfftfreq(n,rate), 20*np.log10(fourier), '-') 


def onselect(xmin, xmax): 
    indmin, indmax = np.searchsorted(time, (xmin, xmax)) 
    indmax = min(len(time)-1, indmax) 

    thisx = time[indmin:indmax] 
    thisy = signal[indmin:indmax] 
    thisy_fourier = np.fft.rfft(thisy) 
    thisx_n = thisx.size 
    rate = thisx[1] - thisx[0] 
    axarr[1,0].clear() 
    axarr[1,0].plot(np.fft.rfftfreq(thisx_n,rate), 20*np.log10(thisy_fourier)) 
    axarr[1,0].set_xlim(0, 11) 
    #ax2.set_ylim(0, thisy.max()) 
    fig.canvas.draw() 

def onselect2(xmin, xmax): 
    indmin, indmax = np.searchsorted(time, (xmin, xmax)) 
    indmax = min(len(time)-1, indmax) 

    thisx = time[indmin:indmax] 
    thisy = signal[indmin:indmax] 
    thisy_fourier = np.fft.rfft(thisy) 
    thisx_n = thisx.size 
    rate = thisx[1] - thisx[0] 
    axarr[1,1].clear() 
    axarr[1,1].plot(np.fft.rfftfreq(thisx_n,rate), 20*np.log10(thisy_fourier)) 
    axarr[1,1].set_xlim(0, 11) 
    #ax2.set_ylim(0, thisy.max()) 
    fig.canvas.draw() 

def onselect3(xmin, xmax): 
    indmin, indmax = np.searchsorted(time, (xmin, xmax)) 
    indmax = min(len(time)-1, indmax) 

    thisx = time[indmin:indmax] 
    thisy = signal[indmin:indmax] 
    thisy_fourier = np.fft.rfft(thisy) 
    thisx_n = thisx.size 
    rate = thisx[1] - thisx[0] 
    axarr[1,2].clear() 
    axarr[1,2].plot(np.fft.rfftfreq(thisx_n,rate), 20*np.log10(thisy_fourier)) 
    axarr[1,2].set_xlim(0, 11) 
    #ax2.set_ylim(0, thisy.max()) 
    fig.canvas.draw() 

span = SpanSelector(axarr[0,0], onselect, 'horizontal', useblit=True, 
        rectprops=dict(alpha=0.5, facecolor='red')) 
span2 = SpanSelector(axarr[0,1], onselect2, 'horizontal', useblit=True, 
        rectprops=dict(alpha=0.5, facecolor='red')) 
span3 = SpanSelector(axarr[0,2], onselect3, 'horizontal', useblit=True, 
        rectprops=dict(alpha=0.5, facecolor='red')) 

我也做了一些其他的编辑。它现在有一个2×3的格子，有3个格子可以执行fft，每个格子都可以单独完成。这很简单，只要我意识到需要在onselect函数中进行任何修改。