# Constructed data: cell counts at 0, 24, 48, 72 and 96 h for a wild-type (WT) and a knockout (KO) line, 3 wells
# each, in 3 independent experiments. True rates: WT 0.035 per hour (doubling time 19.8 h), KO 0.030 per hour
# (23.1 h); confluence at 400,000 cells. The seed (1) was the first one run; it was not selected.
import numpy as np, pandas as pd
from model import experiment, TIMES
rng = np.random.default_rng(1); rows = []
for e in range(1, 4):
    for line, r in (("WT", 0.035), ("KO", 0.030)):
        x = experiment(rng, r)
        for w in range(3):
            for j, t in enumerate(TIMES):
                rows.append((e, line, w + 1, int(t), int(round(x[w, j]))))
pd.DataFrame(rows, columns=["experiment", "line", "well", "hour", "cells"]).to_csv("counts.csv", index=False)