sim_benchmark.py

import sys
import re
import importlib
import time
from pysb.simulator import ScipyOdeSimulator
import pysb.bng
import numpy as np


def benchmark(model, sim_kwargs):

    tspan = np.linspace(0, 10000, 1000)
    start = time.time()
    sim = ScipyOdeSimulator(model, tspan, **sim_kwargs)
    end = time.time()
    print("    simulator init:  %.3g" % (end-start))

    start = time.time()
    sim.run()
    end = time.time()
    print("    first sim:       %.3g" % (end-start))

    times = []
    for i in range(10):
        start = time.time()
        sim.run()
        end = time.time()
        times.append(end-start)
    # Discard worst two times.
    times = sorted(times)[:-2]
    mean = np.mean(times)
    std = np.std(times)
    print("    subsequent sims: %.3g +/- %.3g" % (mean, std))


model = importlib.import_module(sys.argv[1]).model
print(f"Model: {model.name}")

ge_kwargs = {}
sim_kwargs = {}
if model.name.endswith('.egfr_extended'):
    print("==> egfr_extended detected")
    ge_kwargs['max_iter'] = 5
elif model.name == 'MARM1':
    print("==> MARM1 detected")
    import pandas as pd
    param_sets = pd.read_csv('parameter_sets.csv', index_col=0)
    param_sets = param_sets.drop('chi2', axis=1)
    params = param_sets.iloc[0].to_dict()
    sim_kwargs['param_values'] = params
    model.initials = [
        ic for i, ic in enumerate(model.initials) if i not in (0, 1)
    ]
for arg in sys.argv[2:]:
    k, v = arg.split("=")
    if v == "True":
        v = True
    elif v == "False":
        v = False
    elif not re.search(r'[^0-9]', v):
        v = int(v)
    else:
        try:
            v = float(v)
        except ValueError:
            pass
    sim_kwargs[k] = v

if not model.reactions:
    print("Generating equations...")
    pysb.bng.generate_equations(model, **ge_kwargs)

print()
print("Running benchmark...")
benchmark(model, sim_kwargs)