Plot Probability Density of an Histogram

[Python_TLS]

Hi,

Please =i have a code wich plot a histogram for each iteration
and i want to plot the Probability Density of each histogram
how can i do this please ?

you find attached the code

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

importdata=open('Hmz_OT_MULC_Discrete5_TOPO.dens','r+')
data=importdata.readlines()
importdata.close()



tri=[]
j=0
for i in range(len(data)):
    if 'iter' in data[i]:
        l=i
        nbre_iter=[]        
        while l+1 < len(data) and 'iter' not in data [l+1]:    
            l+=1
            nbre_iter.append(data[l])  

        tri.append(nbre_iter)
        j+=1


tri_final=[]    
for i in range(len(tri)):
    extract_density=[]   
    for j in range(len(tri[0])):
        extract_density.append(tri[i][j][12 :])
    tri_final.append(extract_density) 
       

convert_into_float=[]    
for i in range(len(tri_final)):
    convert=[]   
    for j in range(len(tri_final[0])):
        convert.append(float(tri_final[i][j]))
    convert_into_float.append(convert)        
 
for i in range(len(convert_into_float)):
    nbre_elements=np.zeros(10)
    for j in range(len(convert_into_float[0])):       
        if 0<= convert_into_float[i][j]< 0.1:
            nbre_elements[0]+=1
        elif 0.1<= convert_into_float[i][j] <0.2:
            nbre_elements[1]+=1
        elif 0.2<= convert_into_float[i][j] <0.3:
            nbre_elements[2]+=1
        elif 0.3<= convert_into_float[i][j] <0.4:
            nbre_elements[3]+=1                         
        elif 0.4<= convert_into_float[i][j] <0.5:
            nbre_elements[4]+=1                               
        elif 0.5<= convert_into_float[i][j] <0.6:
            nbre_elements[5]+=1                
        elif 0.6<= convert_into_float[i][j] <0.7:
            nbre_elements[6]+=1       
        elif 0.7<= convert_into_float[i][j] <0.8:
            nbre_elements[7]+=1
        elif 0.8<= convert_into_float[i][j] <0.9:
            nbre_elements[8]+=1
        elif 0.9<= convert_into_float[i][j] <=1:
            nbre_elements[9]+=1

                                         
    fig, ax = plt.subplots()
    x=[1,2,3,4,5,6,7,8,9,10]
    width = 1.0
    BarName = ['0.0-0.1','0.1-0.2','0.2-0.3','0.3-0.4','0.4-0.5','0.5-0.6','0.6-0.7','0.7-0.8','0.8-0.9','0.9-1']
    rects=plt.bar(x, nbre_elements, width, color='b' )
 
    def autolabel(rects):
        # attach some text labels
        for rect in rects:
            height = rect.get_height()
            ax.text(rect.get_x()+rect.get_width()/2., 1.0*height, '%d'%int(height),
                    ha='center', va='bottom')
    plt.xlabel('Densite')        
    plt.ylabel('Nombre d elements')
    plt.title('NNombre d elements en fonction de leur densite_ITER_'+str(i))
    nom_figure='Histogramme'+str(i)+ '.png'
    pylab.xticks(x, BarName, rotation=40)
    autolabel(rects)
    plt.savefig(nom_figure)
    plt.show()