"Expression is problematic. Please submit this as a bug."

[Kuratius]

import sympy as sp
n=sp.Symbol('n')

def f(n):
    return 1/(1+sp.exp(-n))

T=50
x=sp.Symbol('x')

def expit(x):
    return sp.Sum(f(T*(x-n)),(n,0,3))

sp.plot(expit(x), (x,0,3))

[MohitKumar020291]

Hello @Kuratius , the issue will be simply solved by using summation instead of sum.

[Kuratius]

@MohitKumar020291 Please read the error message. You misunderstood why I opened this issue.

[MohitKumar020291]

Thanks @Kuratius for your response. It is the problem because you have not imported expit() function , for importing it you should know that there should be a PYTHONPATH in which you must have a file defining expit() so , you are getting error because you are using it in jupyter notebook , these are general error when you use jupyter notebook as it does have all directories or file to progress.
secondly, failback method means your solution is not efficient , it does not means to inaccurate and it is showing your solution is not efficient because it has taken expit() for use from expit_module.py which is a user defined not inbuilt.
I hope that helps.
Please free to ask me and make me more correct.

[Kuratius]

You don't understand how python namespaces work.

Wait, are you using a chatbot to reply to this?

[MohitKumar020291]

@Kuratius Yes , I do not know Python namespaces even and using chatbot. Asking questions to AI is not a good practice? How did you get to know that , did you used it also?

[oscarbenjamin]

Asking questions to AI is not a good practice?

No, it is not a good practice. Feel free to talk to the chatbot yourself but if you're going to talk to people on this platform then you should write messages yourself.

[oscarbenjamin]

@Kuratius thanks for reporting this. This is a common problem and relates to the plotting module's use of experimental_lambdify rather than actual lambdify.

[SamLubelsky]

This warning no longer appears because of the switch from experimental_lambdify to lambdify, looks like this issue can be safely closed.