bartorch.linop.Convolve

class bartorch.linop.Convolve(kernel, shape, axes, mode='same', direction=None)

Convolution with a fixed kernel, BART’s linop_conv.

Parameters:

• kernel (tensor) – What to convolve with, with one axis per axis of shape; an axis it has only one of is left alone.

• shape (tuple of int) – The domain, C order.

• axes (int or tuple of int) – Which axes to convolve along.

• mode (str) – How the ends are treated, under numpy’s names: "wrap" (circular), "same" (the input’s size, truncated), "valid" (only where the kernel fits) or "full" (extended).

• direction (str, optional) – "symmetric", "causal" or "anticausal". BART only plans a "valid" or "full" convolution as a causal one, so leaving this out picks causal for those two and symmetric for the others rather than failing inside BART’s planner.

__init__(kernel, shape, axes, mode='same', direction=None)

Methods

A(x, **kwargs)	A x, under deepinv's name.
A_adjoint(y, **kwargs)	A^H y, under deepinv's name, recorded for autograd.
A_adjoint_A(x, **kwargs)	A^H A x, under deepinv's name, recorded for autograd.
A_dagger(y, **kwargs)	The pseudo-inverse, under deepinv's name.
__init__(kernel, shape, axes[, mode, direction])
adjoint(y[, out])	A^H y, without recording for autograd.
cogram()	A A^H as an operator.
conj()	conj(A): conjugate the input, apply, conjugate the output.
forward(x[, out])	A x, without recording for autograd.
gram()	A^H A as 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

H	A^H, from BART's own adjoint constructor.
T	A^T, the adjoint without the conjugation, as conj(A).H.
codim_rank	How many axes the codomain has.
codim_shape	The codomain, under pyxu's name for it; the same as oshape.
codim_size	How many elements the codomain holds.
device
dim_rank	How many axes the domain has.
dim_shape	The domain, under pyxu's name for it; the same as ishape.
dim_size	How many elements the domain holds.
ishape
oshape