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Jiahao Chen Describe Julia semantics
over 8 years ago
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year = {2010}
}
@article{Bezanson2012,
author = {Bezanson, J. and Karpinski, S. and Shah, V.~B. and Edelman, A.},
title = {{J}ulia: A Fast Dynamic Language for Technical Computing},
journal = {ArXiv},
archivePrefix = "arXiv",
eprint = {1209.5145},
primaryClass = "cs.PL",
year = 2012,
}
@Manual{Rlang,
title = {R: A Language and Environment for Statistical Computing},
author = {{R Core Team}},
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\subsection{Julia}
Julia is a dynamic for technical computing, whose base library features
generous functionality for linear algebraic
operations.~\cite{Bezanson2009} operations.~\cite{Bezanson2012}
Julia's multiplication operator, \verb|*|, implements matrix--matrix and
matrix--vector products, as well as scalings of vectors and matrices, on top of
ordinary scalar multiplication.
Julia's division \verb|x/y| is equivalent to multiplication of \verb|x| by the
inverse of \verb|y| on the right. For non-scalar \verb|y|, the inverse is
generalized to matrix inverses and pseudoinverses (in the least-squares sense)
where appropriate.
Julia's transposition operator, \verb|'|, promotes vectors to column matrices
before transposing them. Thus we have that vector transposition is not
idempotent, \verb|x''|$\ne$\verb|x|.
Julia's current semantics lead to some unexpected behavior. Expressions like
\verb|a'*b| for the inner product produce a vector of length 1, which do not
have the semantics of scalars. Other identities, like $(xy^\prime)z =
x(y^\prime z)$, also fail to hold in code, since \verb|x*(y'z)| becomes the
product of a vector with a 1-vector, which is not defined.
\subsection{R}