# Constructed data: daily clinical scores (0-5, steps of 0.5) from day 7 to day 28 in 10 vehicle and 10 drug mice.
# True model (model.py): vehicle incidence 90%, mean peak 3.0; drug incidence 70%, mean peak 2.2, onset 1 day later.
# The seed (1) was the first one run; it was not selected.
import numpy as np, pandas as pd
from model import simulate, DAYS
rng = np.random.default_rng(1)
rows = []
for grp, (p, peak, delay) in {"vehicle": (0.9, 3.0, 0), "drug": (0.7, 2.2, 1)}.items():
    s = simulate(rng, 10, p, peak, delay)
    for i in range(10):
        for j, day in enumerate(DAYS):
            rows.append((f"{grp[0]}{i+1}", grp, int(day), s[i, j]))
pd.DataFrame(rows, columns=["mouse", "group", "day", "score"]).to_csv("scores.csv", index=False)