更新Matplotlib CheckButton部件

Question

我是編程，python和stackflow的新手，所以請耐心等我解釋一下。

我正在寫一個python腳本，其中有4組數據集中的值集（a，b，c & x0）。我有3個這樣的數據集。

目前，我正在使用單選按鈕在數據集之間切換，並且它工作得很好。

在後一階段中，需要顯示的數據之間的分佈的比較組1 & 2,1 & 3,2 & 3或1,2- & 3出現我管理使用單選按鈕來實現（見下文PIC）

我現在正在使用的檢查按鈕，而不是單選按鈕的，因爲它可以讓我達到同樣的效果與使用僅3標籤（數據集1，數據集2的單選按鈕，&數據Set3）而不是7.

但是，我不知道如何更新檢查按鈕，使他們執行比較。

我的代碼如下所示：

import numpy as np 
print np.__version__ 
import scipy 
print scipy.__version__ 
from scipy.stats import norm, lognorm, stats, uniform 
import matplotlib 
print matplotlib.__version__ 
import matplotlib.pyplot as plt 
from matplotlib.widgets import Slider, Button, RadioButtons 
from matplotlib.patches import Polygon 



#####Importing Data from csv file##### 

dataset1 = np.genfromtxt('dataSet1.csv', dtype = float, delimiter = ',', skip_header = 1, names = ['a', 'b', 'c', 'x0']) 
dataset2 = np.genfromtxt('dataSet2.csv', dtype = float, delimiter = ',', skip_header = 1, names = ['a', 'b', 'c', 'x0']) 
dataset3 = np.genfromtxt('dataSet3.csv', dtype = float, delimiter = ',', skip_header = 1, names = ['a', 'b', 'c', 'x0']) 

#####_____##### 



#####Creating Subplots##### 

fig = plt.figure() 
plt.subplots_adjust(left=0.13,right=0.99,bottom=0.05) 

ax1 = fig.add_subplot(331)             #Subplot 1 
ax1.set_xlabel('a' , fontsize = 14) 
ax1.grid(True) 

ax2 = fig.add_subplot(334)             #Subplot 2 
ax2.set_xlabel('b', fontsize = 14) 
ax2.grid(True) 

ax3 = fig.add_subplot(337)             #Subplot 3 
ax3.set_xlabel('c', fontsize = 14) 
ax3.grid(True) 

ax4 = fig.add_subplot(132)             #Subplot 4 
ax4.set_xlabel('x0', fontsize = 14) 
ax4.set_ylabel('PDF', fontsize = 14) 
ax4.grid(True) 

ax5 = fig.add_subplot(133)             #Subplot 5 
ax5.set_xlabel('x0', fontsize = 14) 
ax5.set_ylabel('CDF', fontsize = 14) 
ax5.grid(True) 

#####_____##### 



#####Plotting Distributions##### 

[n1,bins1,patches] = ax1.hist(dataset1['a'], bins=50, color = 'red',alpha = 0.5, normed = True) 
[n2,bins2,patches] = ax2.hist(dataset1['b'], bins=50, color = 'red',alpha = 0.5, normed = True) 
[n3,bins3,patches] = ax3.hist(dataset1['c'], bins=50, color = 'red',alpha = 0.5, normed = True) 
[n4,bins4,patches] = ax4.hist(dataset1['x0'], bins=50, color = 'red',alpha = 0.5, normed = True) 
dx = bins4[1] - bins4[0] 
CDF = np.cumsum(n4)*dx 
ax5.plot(bins4[1:], CDF) 

#####_____##### 



#######Creating Radio Buttons##### 

axcolor = 'lightgoldenrodyellow' 
rax = plt.axes([0.015, 0.86, 0.08, 0.13], axisbg=axcolor) 
radio1 = RadioButtons(rax, ('Data Set1', 'Data Set2', 'Data Set3', 'Data Set 1&2', 'Data Set 1&3', 'Data Set 2&3', 'Data Set 1,2&3')) 

#####_____##### 



#####Updating Radio Button##### 

radio1_label = 'Data Set1' 
func = {'Data Set1': dataset1, 'Data Set2': dataset2, 'Data Set3': dataset3, 'Data Set 1&2': dataset1, 'Data Set 1&3': dataset1, 'Data Set 2&3': dataset1, 'Data Set 1,2&3': dataset1} 
axcl = {'Data Set1': 'red', 'Data Set2': 'blue', 'Data Set3': 'green', 'Data Set 1&2': None, 'Data Set 1&3': None, 'Data Set 2&3': None, 'Data Set 1,2&3': None} 

def update_radio1(label): 
    global radio1_label    #so we can overwrite the variable defined above and not create a local one 
    radio1_label = label 
    print radio1_label 
    ax1.clear() 
    ax2.clear() 
    ax3.clear() 
    ax4.clear() 
    [n1,bins1,patches] = ax1.hist(func[radio1_label]['a'], bins=50, color = axcl[radio1_label], normed = True, alpha = 0.5) 
    [n2,bins2,patches] = ax2.hist(func[radio1_label]['b'], bins=50, color = axcl[radio1_label], normed = True, alpha = 0.5) 
    [n3,bins3,patches] = ax3.hist(func[radio1_label]['c'], bins=50, color = axcl[radio1_label], normed = True, alpha = 0.5) 
    [n4,bins4,patches] = ax4.hist(func[radio1_label]['x0'], bins=50, color = axcl[radio1_label], normed = True, alpha = 0.5) 
    ax1.grid(True) 
    ax2.grid(True) 
    ax3.grid(True) 
    ax4.grid(True) 
    ax5.grid(True) 
    if radio1_label == 'Data Set 1&2': 
     ax1.clear() 
     ax2.clear() 
     ax3.clear() 
     ax4.clear() 
     ax1.grid(True) 
     ax2.grid(True) 
     ax3.grid(True) 
     ax4.grid(True) 
     ax5.grid(True) 
     [n1,bins1,patches] = ax1.hist(dataset1['a'], bins=50, color = 'red', normed = True, alpha = 0.5) 
     [n2,bins2,patches] = ax2.hist(dataset1['b'], bins=50, color = 'red', normed = True, alpha = 0.5) 
     [n3,bins3,patches] = ax3.hist(dataset1['c'], bins=50, color = 'red', normed = True, alpha = 0.5) 
     [n4,bins4,patches] = ax4.hist(dataset1['x0'], bins=50, color = 'red', normed = True, alpha = 0.5) 

     [n1,bins1,patches] = ax1.hist(dataset2['a'], bins=50, color = 'blue', normed = True, alpha = 0.5) 
     [n2,bins2,patches] = ax2.hist(dataset2['b'], bins=50, color = 'blue', normed = True, alpha = 0.5) 
     [n3,bins3,patches] = ax3.hist(dataset2['c'], bins=50, color = 'blue', normed = True, alpha = 0.5) 
     [n4,bins4,patches] = ax4.hist(dataset2['x0'], bins=50, color = 'blue', normed = True, alpha = 0.5) 
    if radio1_label == 'Data Set 1&3': 
     ax1.clear() 
     ax2.clear() 
     ax3.clear() 
     ax4.clear() 
     ax1.grid(True) 
     ax2.grid(True) 
     ax3.grid(True) 
     ax4.grid(True) 
     ax5.grid(True) 
     [n1,bins1,patches] = ax1.hist(dataset1['a'], bins=50, color = 'red', normed = True, alpha = 0.5) 
     [n2,bins2,patches] = ax2.hist(dataset1['b'], bins=50, color = 'red', normed = True, alpha = 0.5) 
     [n3,bins3,patches] = ax3.hist(dataset1['c'], bins=50, color = 'red', normed = True, alpha = 0.5) 
     [n4,bins4,patches] = ax4.hist(dataset1['x0'], bins=50, color = 'red', normed = True, alpha = 0.5) 

     [n1,bins1,patches] = ax1.hist(dataset3['a'], bins=50, color = 'green', normed = True, alpha = 0.5) 
     [n2,bins2,patches] = ax2.hist(dataset3['b'], bins=50, color = 'green', normed = True, alpha = 0.5) 
     [n3,bins3,patches] = ax3.hist(dataset3['c'], bins=50, color = 'green', normed = True, alpha = 0.5) 
     [n4,bins4,patches] = ax4.hist(dataset3['x0'], bins=50, color = 'green', normed = True, alpha = 0.5) 
    if radio1_label == 'Data Set 2&3': 
     ax1.clear() 
     ax2.clear() 
     ax3.clear() 
     ax4.clear() 
     ax1.grid(True) 
     ax2.grid(True) 
     ax3.grid(True) 
     ax4.grid(True) 
     [n1,bins1,patches] = ax1.hist(dataset2['a'], bins=50, color = 'blue', normed = True, alpha = 0.5) 
     [n2,bins2,patches] = ax2.hist(dataset2['b'], bins=50, color = 'blue', normed = True, alpha = 0.5) 
     [n3,bins3,patches] = ax3.hist(dataset2['c'], bins=50, color = 'blue', normed = True, alpha = 0.5) 
     [n4,bins4,patches] = ax4.hist(dataset2['x0'], bins=50, color = 'blue', normed = True, alpha = 0.5) 

     [n1,bins1,patches] = ax1.hist(dataset3['a'], bins=50, color = 'green', normed = True, alpha = 0.5) 
     [n2,bins2,patches] = ax2.hist(dataset3['b'], bins=50, color = 'green', normed = True, alpha = 0.5) 
     [n3,bins3,patches] = ax3.hist(dataset3['c'], bins=50, color = 'green', normed = True, alpha = 0.5) 
     [n4,bins4,patches] = ax4.hist(dataset3['x0'], bins=50, color = 'green', normed = True, alpha = 0.5) 
    if radio1_label == 'Data Set 1,2&3': 
     ax1.clear() 
     ax2.clear() 
     ax3.clear() 
     ax4.clear() 
     ax1.grid(True) 
     ax2.grid(True) 
     ax3.grid(True) 
     ax4.grid(True) 
     [n1,bins1,patches] = ax1.hist(dataset1['a'], bins=50, color = 'red', normed = True, alpha = 0.5) 
     [n2,bins2,patches] = ax2.hist(dataset1['b'], bins=50, color = 'red', normed = True, alpha = 0.5) 
     [n3,bins3,patches] = ax3.hist(dataset1['c'], bins=50, color = 'red', normed = True, alpha = 0.5) 
     [n4,bins4,patches] = ax4.hist(dataset1['x0'], bins=50, color = 'red', normed = True, alpha = 0.5) 

     [n1,bins1,patches] = ax1.hist(dataset2['a'], bins=50, color = 'blue', normed = True, alpha = 0.5) 
     [n2,bins2,patches] = ax2.hist(dataset2['b'], bins=50, color = 'blue', normed = True, alpha = 0.5) 
     [n3,bins3,patches] = ax3.hist(dataset2['c'], bins=50, color = 'blue', normed = True, alpha = 0.5) 
     [n4,bins4,patches] = ax4.hist(dataset2['x0'], bins=50, color = 'blue', normed = True, alpha = 0.5) 

     [n1,bins1,patches] = ax1.hist(dataset3['a'], bins=50, color = 'green', normed = True, alpha = 0.5) 
     [n2,bins2,patches] = ax2.hist(dataset3['b'], bins=50, color = 'green', normed = True, alpha = 0.5) 
     [n3,bins3,patches] = ax3.hist(dataset3['c'], bins=50, color = 'green', normed = True, alpha = 0.5) 
     [n4,bins4,patches] = ax4.hist(dataset3['x0'], bins=50, color = 'green', normed = True, alpha = 0.5) 



    plt.draw() 



radio1.on_clicked(update_radio1) 

#####_____##### 




plt.show() 

您的援助將得到高度讚賞。

在此先感謝。

Answer 1

import numpy as np 
print np.__version__ 
import scipy 
print scipy.__version__ 
import matplotlib 
print matplotlib.__version__ 
import matplotlib.pyplot as plt 
from matplotlib.widgets import CheckButtons 


#####Importing Data from csv file##### 

dataset1 = np.genfromtxt('dataSet1.csv', dtype = float, delimiter = ',', skip_header = 1, names = ['a', 'b', 'c', 'x0']) 
dataset2 = np.genfromtxt('dataSet2.csv', dtype = float, delimiter = ',', skip_header = 1, names = ['a', 'b', 'c', 'x0']) 
dataset3 = np.genfromtxt('dataSet3.csv', dtype = float, delimiter = ',', skip_header = 1, names = ['a', 'b', 'c', 'x0']) 

#####_____##### 


#####Creating Subplots##### 

fig = plt.figure() 
plt.subplots_adjust(left=0.13,right=0.99,bottom=0.05) 

ax1 = fig.add_subplot(331)             #Subplot 1 
ax1.set_xlabel('a' , fontsize = 14) 

ax2 = fig.add_subplot(334)             #Subplot 2 
ax2.set_xlabel('b', fontsize = 14) 

ax3 = fig.add_subplot(337)             #Subplot 3 
ax3.set_xlabel('c', fontsize = 14) 

ax4 = fig.add_subplot(132)             #Subplot 4 
ax4.set_xlabel('x0', fontsize = 14) 
ax4.set_ylabel('PDF', fontsize = 14) 

ax5 = fig.add_subplot(133)             #Subplot 5 
ax5.set_xlabel('x0', fontsize = 14) 
ax5.set_ylabel('CDF', fontsize = 14) 
ax5.grid(True) 

#####_____##### 

radio1_label = 'Data Set1' 

properties = [ 
    ['Data Set1', dataset1, 'red'], 
    ['Data Set2', dataset2, 'blue'], 
    ['Data Set3', dataset3, 'green'] 
] 
func = {} 
axcl = {} 
flags = {} 
for p in properties: 
    func[p[0]] = p[1] 
    axcl[p[0]] = p[2] 
    flags[p[0]] = p[0] == 'Data Set1' 

#####Plotting Distributions##### 
def plot_hists(): 
    ax1.clear() 
    ax2.clear() 
    ax3.clear() 
    ax4.clear() 
    for p in properties: 
     lbl = p[0] 
     ax1.hist(func[lbl]['a'], bins=50, color=axcl[lbl], normed=True, alpha=0.5, visible=flags[lbl]) 
     ax2.hist(func[lbl]['b'], bins=50, color=axcl[lbl], normed=True, alpha=0.5, visible=flags[lbl]) 
     ax3.hist(func[lbl]['c'], bins=50, color=axcl[lbl], normed=True, alpha=0.5, visible=flags[lbl]) 
     n4, bins4, patches = ax4.hist(func[lbl]['x0'], bins=50,color=axcl[lbl], normed=True, alpha=0.5, visible=flags[lbl]) 
    ax1.grid(True) 
    ax2.grid(True) 
    ax3.grid(True) 
    ax4.grid(True) 
    return n4, bins4 

n4, bins4 = plot_hists() 
dx = bins4[1] - bins4[0] 
CDF = np.cumsum(n4)*dx 
ax5.plot(bins4[1:], CDF) 

#######Creating Check Buttons##### 

axcolor = 'lightgoldenrodyellow' 
rax = plt.axes([0.015, 0.86, 0.08, 0.13], axisbg=axcolor) 

check = CheckButtons(rax, ('Data Set1', 'Data Set2', 'Data Set3'), (True, False, False)) 
#####_____##### 



#####Updating Check Button##### 

def update_check1(label): 
    global radio1_label    #so we can overwrite the variable defined above and not create a local one 
    radio1_label = label 
    print radio1_label 

    flags[label] = not flags[label] 

    plot_hists() 
    ax5.grid(True) 

    plt.draw() 

check.on_clicked(update_check1) 
#####_____##### 




plt.show()