bartorch.linop.Identity#
- class bartorch.linop.Identity(shape)#
The identity on
shape, BART’slinop_identity.It is what an empty product is:
A ** 0returns one, and it is the term to add when an operator needs a multiple of the identity beside it, as inA + 0.1 * Identity(A.ishape).- Parameters:
shape (tuple of int) – The shape it maps to itself, C order.
- __init__(shape)#
Methods
A(x, **kwargs)A x, underdeepinv's name.A_adjoint(y, **kwargs)A^H y, underdeepinv's name, recorded for autograd.A_adjoint_A(x, **kwargs)A^H A x, underdeepinv's name, recorded for autograd.A_dagger(y, **kwargs)The pseudo-inverse, under
deepinv's name.__init__(shape)adjoint(y[, out])A^H y, without recording for autograd.cogram()A A^Has an operator.conj()conj(A): conjugate the input, apply, conjugate the output.forward(x[, out])A x, without recording for autograd.gram()A^H Aas an operator.normal(x[, out])A^H A x.opnorm()The spectral norm, by BART's power iteration on
A^H A.pinv(y[, damp])(A^H A + damp I)^-1 A^H y, the damped least-squares solution.to_nonlinear()The same operator as a
NonlinearOperator.Attributes
HA^H, from BART's own adjoint constructor.TA^T, the adjoint without the conjugation, asconj(A).H.codim_rankHow many axes the codomain has.
codim_shapeThe codomain, under pyxu's name for it; the same as
oshape.codim_sizeHow many elements the codomain holds.
devicedim_rankHow many axes the domain has.
dim_shapeThe domain, under pyxu's name for it; the same as
ishape.dim_sizeHow many elements the domain holds.
ishapeoshape