def setUp(self):
initrv = Constant(0.1 * np.ones(1))
self.ivp = ode.logistic([0.0, 1.5], initrv)
self.step = 0.5
sol = probsolve_ivp(self.ivp, step=self.step, diffconst=1.0, which_prior="ibm1")
state_rvs = sol.kalman_posterior.filtering_posterior.state_rvs
self.ms, self.cs = state_rvs.mean, state_rvs.cov
def setUp(self):
initrv = Dirac(0.1 * np.ones(1))
self.ivp = ode.logistic([0.0, 1.5], initrv)
self.step = 0.5
sol = probsolve_ivp(self.ivp,
step=self.step,
initrv=initrv,
diffconst=1.0,
which_prior="ibm1")
state_rvs = sol._state_rvs
self.ms, self.cs = state_rvs.mean, state_rvs.cov
def setUp(self):
initrv = Constant(0.1 * np.ones(1))
self.ivp = logistic([0.0, 1.5], initrv)
step = 0.1
f = self.ivp.rhs
t0, tmax = self.ivp.timespan
y0 = self.ivp.initrv.mean
self.solution = probsolve_ivp(f,
t0,
tmax,
y0,
algo_order=3,
step=step,
adaptive=False)
def ivp():
initrv = Constant(0.1 * np.ones(1))
return ode.logistic([0.0, 1.5], initrv)
def setUp(self):
initrv = Constant(0.1 * np.ones(1))
self.ivp = logistic([0.0, 1.5], initrv)
step = 0.1
self.solution = probsolve_ivp(self.ivp, which_prior="ibm3", step=step)
def setUp(self):
"""Setup odesolver and solve a scalar ode."""
initrv = Constant(0.1 * np.ones(1))
self.ivp = ode.logistic([0.0, 1.5], initrv)
self.stps = [0.2, 0.1]