Notes to self: plans for next release

Future versions will involve a complete re-write in order to:

Update on notes to self (2004/5)

Development on psignifit is now frozen, so none of the above will in fact happen.

Version 2.5.6 (18-Jan-2005)


Matlab toolbox:

Version 2.5.41 (10-Sep-2002)

This is simply an update to the toolbox m-files, to iron out the glitches caused by backward-incompatibilities in the new Matlab R13.

Further slight changes were also made to the toolbox:

The C source should be functionally identical to 2.5.4, so I have not recompiled the binaries.

Version 2.5.4 (18-Apr-2002)

(What happened to 2.5.3? I decided to follow the convention of using even numbers in the least significant digit of the version number, in case some people think that the release might not be "stable" - in fact my development process is not so sophisticated that I ever release "cutting edge" builds or anything whose development hasn't reached a "stable" point. My version numbers are in fact assigned more or less haphazardly, and are based on how drastic the differences seem to be since I last managed to get a release posted. The next version will be 3.0.)

With this release, the name of the program has changed from "psychofit" to "psignifit". This is to avoid confusion with other software - the name "psychofit" has been used before by others. All of the source files now have lower-case names, and some of them have been renamed in other ways.

This version compiles in gcc in the new-look cygwin, and can make executables and mex files that run either natively or on top of cygwin. A primitive makefile is included.

A few bugs were fixed in the C code:

Also, a glitch in the Matlab function psychostats.m was ironed out, whereby polynomial fits to deviance residuals were carried out even if not enough residuals existed, leading to an error.

Also in version 2.5.4, pfcmp was released. This is an extension to the Matlab toolbox, for comparing two psychometric functions by Monte Carlo simulation.

Version 2.5.2 (01-Oct-2001)

This version was used for extensive testing of bootstrap methods by Hill (D.Phil. thesis, University of Oxford, 2001). It was not released, except on the CD accompanying the thesis. It includes minor bug fixes and improvements over 2.5.1 as follows:

Version 2.5.1 (03-Apr-2000)

First success at making a Windows32 Matlab mex file - using Matlab 5.3 in conjunction with the free gcc port from Cygnus (cygwin-b20).

New features (see the file "psych_options" for documentation)

Minor bug fixes:

Internal changes:

Backward-compatibiliy of toolbox m-files with Matlab 5.1.x:
(not yet tried with Matlab 5.0.x)

Version 2.5 (25-Nov-1999)

First release fully compliant with the Wichmann & Hill papers. Engine compiled and ran successfully under MacOS on PowerPC, Digital UNIX on a DEC Alpha, and Linux, 16-bit DOS and 32-bit DOS on Intel machines. No mex file yet available for Windows Matlab: this is only because I don't know how to make one...

(The above changes required extensive changes various aspects of the engine source code, removal of a great deal of Matlab code in the toolbox that now became redundant, and changes to the input options syntax - see updated "options" documentation)

Version 2.0 (standalone version 2.0-alpha) (22-Jul-1999)

First general release. Re-coded from scratch, in "strict ANSI C" with a view towards portability and optimization. All input was as text, so that mex-file and standalone versions were just "wrappers" round the same core routines. The engine compiled and ran correctly under MacOS on a PowerPC, and Digital UNIX on a DEC Alpha. Not for use on Intel systems.

Version 1 (1997-9)

Implemented fitting and simulation as a compiled binary plug-in to Matlab (mex file) which worked on Macintosh PowerPCs. This cut processing times by a factor of 50-100, but was still poorly optimized. Functionality was very limited.

Version 0 (1996/7)

First attempt at Monte Carlo simulation of a multi-dimensional Simplex search fitting psychometric functions according to maximum likelihood. Implementation was Matlab scripts only: took 20-30 mins to do 1000 simulations. Often failed to converge.