--- trunk/doc/report/types.tex 2010/05/28 15:16:21 101 +++ trunk/doc/report/types.tex 2010/07/20 14:08:09 161 @@ -30,8 +30,25 @@ \end{center}% \section{Images} +Images are rectangular arrays of tensor data that are used to represent the data sets +that Diderot programs are analysing, as well as other data. +The syntax of an image type is +\begin{center} + \kw{image}\kw{(} $n$ \kw{)} \kw{[} $d_1,\ldots{},d_n$ \kw{]} +\end{center}% +where $n$ is the dimension of the field (typically 2 or 3) and $d_1,\ldots{},d_n$ is the +shape of the tensor data (\ie{}, the elements of the image are tensors +of type \kw{tensor[}$d_1,\ldots{},d_n$\kw{]}). \section{Fields} +Fields are functions from some $n$-dimensional vector space to some tensor type. +The syntax of a field type is +\begin{center} + \kw{field}\kw{\#} $k$ \kw{(} $n$ \kw{)} \kw{[} $d_1,\ldots{},d_n$ \kw{]} +\end{center}% +where $k \geq 0$ is the number of levels of differentiation supported by the field, +$n$ is the dimension of the field (typically 2 or 3), and $d_1,\ldots{},d_n$ is the shape of the field. +Probing the field will produce a tensor of type \kw{tensor[}$d_1,\ldots{},d_n$\kw{]}. \section{Kernels} Kernels are abstract types that represent the \emph{convolution kernels} used
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The output has ended thus: \section{Kernels} Kernels are abstract types that represent the \emph{convolution kernels} used