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faust group
faust
Commits
351612eb
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351612eb
authored
2 years ago
by
hhakim
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Remove old matfaust asLazyLinearOp function and document new aslazylinearoperator function.
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wrapper/matlab/+matfaust/+lazylinop/asLazyLinearOp.m
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-37
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wrapper/matlab/+matfaust/+lazylinop/asLazyLinearOp.m
wrapper/matlab/+matfaust/+lazylinop/aslazylinearoperator.m
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wrapper/matlab/+matfaust/+lazylinop/aslazylinearoperator.m
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37 deletions
wrapper/matlab/+matfaust/+lazylinop/asLazyLinearOp.m
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%=============================================================
%> @brief Creates a LazyLinearOp based on the object obj which must be of a linear operator compatible type.
%>
%> @note obj must support operations and attributes defined in the LazyLinearOp class.
%> Any operation not supported would raise an exception at the evaluation time.
%> @param obj: the root object on which the LazyLinearOp is based (it could
%> be a dense matrix, a sparse matrix, a Faust object or almost any
%> object that supports the same kind of functions).
%>
%> @retval L: a LazyLinearOp instance based on obj.
%>
%> @b Example
%>
%> @code
%> >> import matfaust.lazylinop.asLazyLinearOp
%> >> M = rand(10, 12);
%> >> lM = asLazyLinearOp(M);
%> >> twolM = lM + lM
%>
%> twolM =
%>
%> 10x12 LazyLinearOp array with no properties.
%>
%> >> F = matfaust.rand(10, 12);
%> >> lF = asLazyLinearOp(F);
%> >> twolF = lF + lF
%> twolF =
%>
%> 10x12 LazyLinearOp array with no properties.
%> @endcode
%>
%> @b See @b also: matfaust.rand.
%=============================================================
function
L
=
asLazyLinearOp
(
obj
)
import
matfaust
.
lazylinop
.
LazyLinearOp
L
=
LazyLinearOp
.
create
(
obj
);
end
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wrapper/matlab/+matfaust/+lazylinop/aslazylinearoperator.m
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351612eb
%=============================================================
%> @brief Creates a LazyLinearOp based on the object obj which must be of a linear operator compatible type.
%>
%> @note obj must support operations and attributes defined in the LazyLinearOp class.
%> Any operation not supported would raise an exception at the evaluation time.
%> @param obj: the root object on which the LazyLinearOp is based (it could
%> be a dense matrix, a sparse matrix, a Faust object or almost any
%> object that supports the same kind of functions).
%>
%> @retval L: a LazyLinearOp instance based on obj.
%>
%> @b Example
%>
%> @code
%> >> import matfaust.lazylinop.aslazylinearoperator
%> >> M = rand(10, 12);
%> >> lM = aslazylinearoperator(M);
%> >> twolM = lM + lM
%>
%> twolM =
%>
%> 10x12 LazyLinearOp array with no properties.
%>
%> >> F = matfaust.rand(10, 12);
%> >> lF = aslazylinearoperator(F);
%> >> twolF = lF + lF
%> twolF =
%>
%> 10x12 LazyLinearOp array with no properties.
%> @endcode
%>
%> @b See @b also: matfaust.rand.
%=============================================================
function
L
=
aslazylinearoperator
(
obj
)
import
matfaust
.
lazylinop
.
LazyLinearOp
L
=
LazyLinearOp
.
create_from_op
(
obj
);
...
...
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