"""
PySB Benchmark
--------------
This file allows the benchmarking of AMICI vs PySB simulations. Simulations
times are averages of N_REPEATS simulations at reference values.
"""

import importlib
import os
import sys
import timeit

import amici
import matplotlib.pyplot as plt
import numpy as np
import pandas as pd
import pysb
from amici.pysb_import import pysb2amici
from pysb.simulator import ScipyOdeSimulator

sys.path.insert(0, os.path.join("..", "tests"))
from test_pysb import pysb_models

simulation_times = dict()

N_REPEATS = 100

atol = 1e-8
rtol = 1e-8

for example in pysb_models:
    simulation_times[example] = dict()

    with amici.add_path(os.path.dirname(pysb.examples.__file__)):
        with amici.add_path(
            os.path.join(os.path.dirname(__file__), "..", "tests", "pysb_test_models")
        ):
            pysb.SelfExporter.cleanup()  # reset pysb
            pysb.SelfExporter.do_export = True

            module = importlib.import_module(example)
            pysb_model = module.model
            pysb_model.name = pysb_model.name.replace("pysb.examples.", "")
            # avoid naming clash for custom pysb models
            pysb_model.name += "_amici"

            # pysb part
            tspan = np.linspace(0, 100, 101)
            sim = ScipyOdeSimulator(
                pysb_model,
                tspan=tspan,
                integrator_options={"rtol": rtol, "atol": atol},
            )
            time_pysb = (
                timeit.Timer("pysb_simres = sim.run()", globals={"sim": sim}).timeit(
                    number=N_REPEATS
                )
                / N_REPEATS
            )

            simulation_times[example]["pysb"] = time_pysb
            print(f"PySB average simulation time {example}: {time_pysb}")

            # amici part
            outdir = pysb_model.name

            if pysb_model.name in ["move_connected_amici"]:
                compute_conservation_laws = False
            else:
                compute_conservation_laws = True

            pysb2amici(
                pysb_model,
                outdir,
                compute_conservation_laws=compute_conservation_laws,
                observables=list(pysb_model.observables.keys()),
            )

            amici_model_module = amici.import_model_module(pysb_model.name, outdir)

            model_pysb = amici_model_module.getModel()

            model_pysb.setTimepoints(tspan)

            solver = model_pysb.getSolver()
            solver.setMaxSteps(int(1e6))
            solver.setAbsoluteTolerance(atol)
            solver.setRelativeTolerance(rtol)
            time_amici = (
                timeit.Timer(
                    "rdata = amici.runAmiciSimulation(model, solver)",
                    globals={"model": model_pysb, "solver": solver, "amici": amici},
                ).timeit(number=N_REPEATS)
                / N_REPEATS
            )
            simulation_times[example]["amici"] = time_amici
            print(f"AMICI average simulation time {example}: {time_amici}")

times = pd.DataFrame(simulation_times)

ax = times.T.plot(kind="scatter", x="pysb", y="amici")
ax.set_xscale("log")
ax.set_yscale("log")
ax.set_aspect("equal")
xy_min = np.min([ax.get_xlim()[0], ax.get_ylim()[0]])
xy_max = np.max([ax.get_xlim()[1], ax.get_ylim()[1]])

ax.set_xlim([xy_min, xy_max])
ax.set_ylim([xy_min, xy_max])
ax.set_ylabel("simulation time AMICI [s]")
ax.set_xlabel("simulation time PySB [s]")
ax.plot([xy_min, xy_max], [xy_min, xy_max], "k:")
plt.tight_layout()
plt.savefig("benchmark_pysb.eps")
