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[diderot] Annotation of /trunk/doc/report/types.tex
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Annotation of /trunk/doc/report/types.tex

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1 : jhr 101 %!TEX root = report.tex
2 :     %
3 :     \chapter{Types}
4 :     \label{chap:types}
5 :    
6 :     The grammar of Diderot types is as follows:
7 :     \begin{Grammar}
8 :     \TypeRULES{}
9 :     \end{Grammar}%
10 :    
11 :     \section{Value types}
12 :     Diderot supports four types of concrete values: booleans, integers, strings, and tensors.
13 :     The grammar of these types is
14 :     \begin{Grammar}
15 :     \ValueTypeRULES{}
16 :     \DimensionsRULES{}
17 :     \end{Grammar}%
18 :    
19 :     The tensor type \mbox{\kw{tensor}\kw{[}$d_1,\ldots{},d_n$\kw{]}} is the of type order-$n$ tensors
20 :     with shape $d_1,\ldots{},d_n$.
21 :     Tensors include scalars (order-0) and vectors (order-1).
22 :     Because these types are frequently used, Diderot supports the following predefined type definitions:
23 :     \begin{center}
24 :     \begin{tabular}{r@{$\quad\equiv\quad$}l}
25 :     \kw{real} & \texttt{\kw{tensor}\kw{[}\kw{]}} \\
26 :     \kw{vec2} & \texttt{\kw{tensor}\kw{[}2\kw{]}} \\
27 :     \kw{vec3} & \texttt{\kw{tensor}\kw{[}3\kw{]}} \\
28 :     \kw{vec4} & \texttt{\kw{tensor}\kw{[}4\kw{]}}
29 :     \end{tabular}
30 :     \end{center}%
31 :    
32 :     \section{Images}
33 :    
34 :     \section{Fields}
35 :    
36 :     \section{Kernels}
37 :     Kernels are abstract types that represent the \emph{convolution kernels} used
38 :     to reconstruct continuous fields from image data.
39 :     The syntax of a kernel type is \mbox{\kw{kernel}\kw{\#}$k$}, where
40 :     $k \geq 0$ gives the number of levels of differentiation supported by the
41 :     kernel.

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