Python linear_discrete_update Examples

Example #1

File: extendedkalman.py Project: yyht/probnum

def _discrete_extkalman_update(time, randvar, data, measmod, **kwargs):
    mpred, cpred = randvar.mean, randvar.cov
    if np.isscalar(mpred) and np.isscalar(cpred):
        mpred, cpred = mpred * np.ones(1), cpred * np.eye(1)
    jacob = measmod.jacobian(time, mpred, **kwargs)
    meascov = measmod.diffusionmatrix(time, **kwargs)
    meanest = measmod.dynamics(time, mpred, **kwargs)
    return linear_discrete_update(meanest, cpred, data, meascov, jacob, mpred)

Example #2

def _update_discrete_linear(time, randvar, data, measmod, **kwargs):
    mpred, cpred = randvar.mean, randvar.cov
    if np.isscalar(mpred) and np.isscalar(cpred):
        mpred, cpred = mpred * np.ones(1), cpred * np.eye(1)
    measmat = measmod.dynamicsmatrix(time, **kwargs)
    meascov = measmod.diffusionmatrix(time, **kwargs)
    meanest = measmat @ mpred
    return linear_discrete_update(meanest, cpred, data, meascov, measmat,
                                  mpred)

Example #3

def _discrete_kalman_update(time, randvar, data, measurementmodel, **kwargs):
    """Discrete Kalman update."""
    mpred, cpred = randvar.mean, randvar.cov
    if np.isscalar(mpred) and np.isscalar(cpred):
        mpred, cpred = mpred * np.ones(1), cpred * np.eye(1)
    measmat = measurementmodel.dynamicsmatrix(time, **kwargs)
    meascov = measurementmodel.diffusionmatrix(time, **kwargs)
    meanest = measmat @ mpred
    return linear_discrete_update(meanest, cpred, data, meascov, measmat,
                                  mpred)