Drawing values from custom distribution

Questions
3

Thanks very much for the answer @ricardoV94 . I installed pymc4 and tried to follow your example. This is my code (leaving for the time being the last two lines):

def schechter_theano(logL, alpha, n42, a, b):
        
    L = 10. ** logL
    
    schechter = 10 ** n42 * (L / L0) ** (-alpha) * T.exp(- L / Lstar) * (L / Lstar)
    
    selfunc = 0.5 + T.erf(a * (logL - b)) + 0.5
    
    totmod = selfunc * schechter
    
    return totmod

def logp(value, alpha, n42, a, b):
    
    return pm.logp(schechter_theano, value)


with pm.Model() as model:
    
    alpha = pm.Uniform('alpha', lower=0.5, upper=4.0)
    
    n42 = pm.Uniform('n42', lower=0, upper=6)
    
    a = pm.Uniform('a', lower=1, upper=8)
    
    b = pm.Uniform('b', lower=40, upper=43)
    
    obs = pm.DensityDist('obs', alpha, n42, a, b, logp=logp, observed=realiz)
    
    trace = pm.sample(return_inferencedata=True)

But this gives me the following error:

File ~/opt/anaconda3/envs/pymc4/lib/python3.10/site-packages/pymc/distributions/logprob.py:285, in logp(rv, value)
    282 def logp(rv: TensorVariable, value) -> TensorVariable:
    283     """Return the log-probability graph of a Random Variable"""
--> 285     value = at.as_tensor_variable(value, dtype=rv.dtype)
    286     try:
    287         return logp_aeppl(rv, value)

AttributeError: 'function' object has no attribute 'dtype'

What am I doing wrong?