Purpose
-------
The purpose of this module is to read and write
Comma Separated Values (CSV) data files.
The goal of this toolbox is to improve the flexibility, consistency and speed of
CSV reading and writing with respect to Scilab built-in
write_csv and read_csv functions.
On some large data files, we observed a 100x improvement of the
speed.
Features
--------
* csv_default : Get or set defaults for csv files.
* csv_getToolboxPath: Returns the path to the current module.
* csv_read: Read comma-separated value file
* csv_stringtodouble: Convert a matrix of strings to a matrix of doubles.
* csv_textscan: Read comma-separated value in a matrix of strings
* csv_write: Write comma-separated value file
* csv_isnum: tests if a string represents a number
To compare speed:
with optimized functions:
stacksize('max');
M = ones(1000, 1000);
tic();
csv_write(M, TMPDIR + "/csv_write_1.csv");
toc()
tic();
r = csv_read(TMPDIR + "/csv_write_1.csv")
toc()
with default scilab functions (be patient):
stacksize('max');
M = ones(1000, 1000);
tic();
write_csv(M, TMPDIR + "/csv_write_1.csv");
toc()
tic();
r = read_csv(TMPDIR + "/csv_write_1.csv")
toc()
csv_readwrite (0.6) - February 2012
* This version requires Scilab 5.4.0
* Factorized code with new code in Scilab.
* Uses assert functions for tests.
* Add also %pi, %inf, %nan as format for pi, inf and nan number.
* Update demos with some benchs.
* Add csv_isnum function x10 (or more) faster than isnum scilab function
* Fixed ticket #637: module did not start in -NWNI mode
* Fixed ticket #644: csv_read did not support empty fields
