This repository now contains these modules:
- testing
- munsch: a numeric library for R6RS scheme. The name is a contraction of Num-eric Sch-eme, with Num reversed, because we schemers like to.
- yasos
- parsing: currently parses XML, it is trivial to add json, cson, and other formats.
- streams: srfi-41 verbatim.
- match: Pattern matching by Dan Friedman, Erik Hilsdale and Kent Dybvig; verbatim.
- record-with-context: add context management to R6 records, access elements with
with-<record>, and update elements (by copy) withupdate-<record>. - cut: srfi-26 verbatim.
A R6RS compatible scheme with a decent set of SRFIs installed; I'm currently using Chez (http://github.com/cisco/chezscheme). Tests also run successfully on Racket. To have them run on Guile, I needed to change '(srfi :48)' into '(ice-9 format)' and it doesn't parse R6RS strings correctly.
- Talking to Gtk3 libraries
Munsch is designed to do fast numerical array routines in a flexible way and semantic way. I'm currently developing it to interact with OpenGL functions.
Goals:
- Complete R6RS compliance, based on bytearrays
- Support for extensive slicing and dicing of numeric arrays
- Support for linear algebra
- Support for geometry
The basis for Munsch is bytearrays,
5294
on top of which we have a record-types
called f32vector and f32array (only single precesion for the moment). The
vector type contains a contiguous block of memory, being a simple wrapper
around bytevector. The f32array type contains slicing information in
addition to a reference to the raw data. A slice contains information on
offset, stride, shape and total size of the array. To perform slicing
operations on an array I have defined the f32array-cut syntax.
To perform linear algebra, I defined matrix and vector types for which some of
the well known operations on matrices are defined. These use f32vector to
store their memory, and are always contiguous. This is so that we can pass them
to OpenGL routines, but also applications using FFI to LAPACK or GSL come to
mind.
Next, on top of the linear algebra we can define a vector type that specialises in geometry operations. This is to provide semantics for vertices, vectors, polygons etc.
Apache 2.0