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]