Python How to increase the acceptance ratio

AI Thread Summary
The discussion centers around generating a random distribution using the exponential function λe^(-λy) and implementing it in Python with NumPy and Matplotlib. The user shares code for generating random samples and creating histograms to visualize the distribution. They express a desire to improve the acceptance ratio in their sampling method by using a linear function f(x) = 1 - ax, inquiring about the optimal choice for 'a'. Additionally, there is a mention of a mathematical concept regarding the relationship between flat distributions and the function f, suggesting a deeper theoretical aspect of the problem. The thread concludes with a note that the question has been deemed a duplicate and is directed to a homework forum for further assistance.
Othman0111
Messages
27
Reaction score
0
I trying to generate a random distribution

λe-λy
Which distributed exponentially.
Python:
%matplotlib inline
import numpy as np
from matplotlib import pyplot

N = 1000
r = np.random.random(N)

xlambda = 0.1
x = -np.log(r)/xlambda

binwidth=xlambda*5
pyplot.hist(x,bins=np.arange(0.,100., binwidth),density=True);
pyplot.plot(np.arange(0.,100.,binwidth),xlambda*np.exp(-xlambda*np.arange(0.,100.,binwidth)),ls='-',c='red',lw=3);N = 10000

xmax = 100
ymax = xlambda

rx = np.random.random(N)*xmax
ry = np.random.random(N)*ymax

values = []

Nin = 0
for i in range(N):
    if(ry[i] <= xlambda*np.exp(-xlambda*rx[i])):
        # Accept
        values.append(rx[i])
        Nin += 1    

x = np.asarray(values)

print("Acceptance Ratio: ",Nin/float(N))

binwidth=xlambda*5
pyplot.hist(x,bins=np.arange(0.,100., binwidth),density=True);
pyplot.plot(np.arange(0.,100.,binwidth),xlambda*np.exp(-xlambda*np.arange(0.,100.,binwidth)),ls='-',c='red',lw=3);

I want to Improve the acceptance ratio by using a linear function f(x)=1-ax. is there a certain choice for a?
 
Technology news on Phys.org
This homework ? Then please post in the homework forum.

Do you know that if ##F'=f## then a flat distribution of F yields a distribution like ##f## ?
 
BvU said:
This homework ? Then please post in the homework forum.

Do you know that if ##F'=f## then a flat distribution of F yields a distribution like ##f## ?
I didn't get what you're saying
 
Thread closed. There's a duplicate of the question here: https://www.physicsforums.com/threads/how-to-increase-the-acceptance-ratio-in-python.966421/
 
Thread 'Is this public key encryption?'
I've tried to intuit public key encryption but never quite managed. But this seems to wrap it up in a bow. This seems to be a very elegant way of transmitting a message publicly that only the sender and receiver can decipher. Is this how PKE works? No, it cant be. In the above case, the requester knows the target's "secret" key - because they have his ID, and therefore knows his birthdate.
I tried a web search "the loss of programming ", and found an article saying that all aspects of writing, developing, and testing software programs will one day all be handled through artificial intelligence. One must wonder then, who is responsible. WHO is responsible for any problems, bugs, deficiencies, or whatever malfunctions which the programs make their users endure? Things may work wrong however the "wrong" happens. AI needs to fix the problems for the users. Any way to...

Similar threads

Replies
1
Views
1K
Replies
6
Views
3K
Back
Top