Is it possible to implement weight clipping in a custom learning rule?

[GiovanniOrani]

Hi Lava community,

I'm currently trying to implement in Lava a learning rule that was originally written with Brian2.
Here the original implmentation:

on_pre='''gin+=w
          pre += 1
          w = clip(w-a2min*post*lr, 0, Wmax_h)''',
on_post='''post += 1
           m += 1
           w = clip(w+a3plus*pre*m*lr, 0, Wmax_h)''',

I was able to convert it into Lava using a custom learning rule, as shown below.

dw = f"{self.learning_rate} * {self.A_minus} * x0 * y1 +" \
     f"{self.learning_rate} * {self.A_plus} * y0 * x1 * y2"

The two learning rules behave consistently.
However, the problem concerns the value clipping used in the Brian2 version, which I haven't been able to replicate.

Has anyone dealt with a similar problem?
Is there a way to clip the weight to keep it within a certain range?

Any suggestions would be greatly appreciated.
Thanks in advance for your help!

Best regards!
Giovanni.