Vehicle-Anti-Theft-Face-Rec.../venv/Lib/site-packages/scipy/integrate/tests/test_odeint_jac.py

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import numpy as np
from numpy.testing import assert_equal, assert_allclose
from scipy.integrate import odeint
import scipy.integrate._test_odeint_banded as banded5x5
def rhs(y, t):
dydt = np.zeros_like(y)
banded5x5.banded5x5(t, y, dydt)
return dydt
def jac(y, t):
n = len(y)
jac = np.zeros((n, n), order='F')
banded5x5.banded5x5_jac(t, y, 1, 1, jac)
return jac
def bjac(y, t):
n = len(y)
bjac = np.zeros((4, n), order='F')
banded5x5.banded5x5_bjac(t, y, 1, 1, bjac)
return bjac
JACTYPE_FULL = 1
JACTYPE_BANDED = 4
def check_odeint(jactype):
if jactype == JACTYPE_FULL:
ml = None
mu = None
jacobian = jac
elif jactype == JACTYPE_BANDED:
ml = 2
mu = 1
jacobian = bjac
else:
raise ValueError("invalid jactype: %r" % (jactype,))
y0 = np.arange(1.0, 6.0)
# These tolerances must match the tolerances used in banded5x5.f.
rtol = 1e-11
atol = 1e-13
dt = 0.125
nsteps = 64
t = dt * np.arange(nsteps+1)
sol, info = odeint(rhs, y0, t,
Dfun=jacobian, ml=ml, mu=mu,
atol=atol, rtol=rtol, full_output=True)
yfinal = sol[-1]
odeint_nst = info['nst'][-1]
odeint_nfe = info['nfe'][-1]
odeint_nje = info['nje'][-1]
y1 = y0.copy()
# Pure Fortran solution. y1 is modified in-place.
nst, nfe, nje = banded5x5.banded5x5_solve(y1, nsteps, dt, jactype)
# It is likely that yfinal and y1 are *exactly* the same, but
# we'll be cautious and use assert_allclose.
assert_allclose(yfinal, y1, rtol=1e-12)
assert_equal((odeint_nst, odeint_nfe, odeint_nje), (nst, nfe, nje))
def test_odeint_full_jac():
check_odeint(JACTYPE_FULL)
def test_odeint_banded_jac():
check_odeint(JACTYPE_BANDED)