Source code for nifty8.minimization.quadratic_energy

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# NIFTy is being developed at the Max-Planck-Institut fuer Astrophysik.

from .energy import Energy


[docs] class QuadraticEnergy(Energy): """The Energy for a quadratic form. The most important aspect of this energy is that its metric must be position-independent. """
[docs] def __init__(self, position, A, b, _grad=None): super(QuadraticEnergy, self).__init__(position=position) self._A = A self._b = b if _grad is not None: self._grad = _grad Ax = _grad if b is None else _grad + b else: Ax = self._A(self._position) self._grad = Ax if b is None else Ax - b self._value = 0.5*self._position.s_vdot(Ax).real if b is not None: self._value -= b.s_vdot(self._position).real
[docs] def at(self, position): return QuadraticEnergy(position, self._A, self._b)
[docs] def at_with_grad(self, position, grad): """Specialized version of `at`, taking also a gradient. This custom method is meant for use within :class:ConjugateGradient` minimizers, which already have the gradient available. It saves time by not recomputing it. Parameters ---------- position : :class:`nifty8.field.Field` Location in parameter space for the new Energy object. grad : :class:`nifty8.field.Field` Energy gradient at the new position. Returns ------- Energy Energy object at new position. """ return QuadraticEnergy(position, self._A, self._b, grad)
@property def value(self): return self._value @property def gradient(self): return self._grad @property def metric(self): return self._A
[docs] def apply_metric(self, x): return self._A(x)