Hi everyone,

I am new to Stan (with Pystan for the interface). I am currently trying to solve a simple inference problem involving differential equation for modeling bacterial growth rate, which code as attached below. I keep getting “*RuntimeError: Initialization failed*.” error.

```
functions {
real[] growth(real t, real[] y, real[] p, real[] x_r, int[] x_i) {
real dydt[1];
dydt[1] = (p[1] * (1 - (y[1]/p[2]))) * y[1];
return dydt;
}
}
data {
int<lower=1> T;
real y[T, 1];
real t0;
real ts[T];
}
transformed data {
real x_r[0];
int x_i[0];
}
parameters {
real<lower=0> sigma;
real y0[1]; //infer the initial state
real p[2]; //model parameters
}
model {
real y_hat[T, 1];
sigma ~ uniform(0.1, 0.5);
p[1] ~ uniform(0, 1);
p[2] ~ uniform(0, 2);
y0[1] ~ uniform(0, 0.2);
y_hat = integrate_ode_rk45(growth, y0, t0, ts, p, x_r, x_i);
for (t in 1:T)
y[t] ~ normal(y_hat[t], sigma);
}
}
```

What did I do wrong here? Here is the input dictionary in Python:

```
data = {
'T': len(od),
'ts': od.index, #timeframe as the index for the data
'y': od, #data to be fitted
't0': 0
}
```

Also, when I was trying to find a solution for ODE inference from the internet, I found some people put the integrate_ode_rk45 function in the transformed parameters block, and some others put it in the model block. Which one is the correct way to do this?

Thanks in advance for the help and suggestions!

Here is the full error message, if it helps:

```
---------------------------------------------------------------------------
RuntimeError Traceback (most recent call last)
<ipython-input-54-7445a20b3355> in <module>
51
52 # Train the model and generate samples
---> 53 fit = sm.sampling(data=data, iter=100, chains=2, n_jobs=1)
54 print(fit)
~/Documents/Notebook/env/lib/python3.9/site-packages/pystan/model.py in sampling(self, data, pars, chains, iter, warmup, thin, seed, init, sample_file, diagnostic_file, verbose, algorithm, control, n_jobs, **kwargs)
811 call_sampler_args = izip(itertools.repeat(data), args_list, itertools.repeat(pars))
812 call_sampler_star = self.module._call_sampler_star
--> 813 ret_and_samples = _map_parallel(call_sampler_star, call_sampler_args, n_jobs)
814 samples = [smpl for _, smpl in ret_and_samples]
815
~/Documents/Notebook/env/lib/python3.9/site-packages/pystan/model.py in _map_parallel(function, args, n_jobs)
88 pool.join()
89 else:
---> 90 map_result = list(map(function, args))
91 return map_result
92
stanfit4anon_model_4b7224b9f462e46cebdf72f52a562750_685902710779344041.pyx in stanfit4anon_model_4b7224b9f462e46cebdf72f52a562750_685902710779344041._call_sampler_star()
stanfit4anon_model_4b7224b9f462e46cebdf72f52a562750_685902710779344041.pyx in stanfit4anon_model_4b7224b9f462e46cebdf72f52a562750_685902710779344041._call_sampler()
RuntimeError: Initialization failed.
```