BNW/sourcecodes/add_inv.php, branch main

Guard fopen() results with a false-check before fwrite/fprintf/fclose

2026-08-17T19:53:08+00:00

On PHP 7.4, calling fwrite()/fprintf()/fclose() with a false handle (a failed fopen(), e.g. from a bad path, missing directory, or permissions issue) just emits a warning and no-ops. On PHP 8.0+, these functions require a resource argument and throw an uncaught TypeError instead, turning what used to be a silent degradation into a fatal crash of the whole request. This patch wraps every fopen()-then-write call site in the codebase (18 files) with an `if ($handle !== false) { ... }` check, matching the existing pattern used elsewhere in the codebase. Where the same $fpvar handle is threaded through shared helper functions (enter_ban_list/banlist/whitelist, duplicated across remove_variables_processing.php, remove_variables_processing_default.php, modify_structure_learning.php and tier_description_processing_gom.php), the guard was added inside those functions too for consistency, even though the call sites are currently dead/commented-out in three of the four files — so the same landmine doesn't reappear if that code is ever re-enabled. Verified empirically against PHP 8.3.28: fopen() on an unwritable path followed by fwrite() on the resulting `false` throws TypeError: fwrite(): Argument #1 ($stream) must be of type resource, false given without the guard; with the guard, the call is skipped instead of crashing. The normal (successful fopen) path was also re-run through mat_structure.php's structure_change() and still produces identical output to before the change. Reviewed by: Frederick M Muriithi

Moving final GENENET8 version to master

2021-02-24T21:19:03+00:00

GENENET8 update

2021-02-24T20:36:59+00:00

Jan 28 2019 update

2019-01-28T22:31:54+00:00

New parameter learning options

2018-09-14T04:59:20+00:00

The main change here is in the parameter learning methods. The parameters that are learned at first (i.e., if there is no evidence) are the distributions that are found directly in the data. I had to create or significantly modify several BNT files for this. If there is evidence, the parameters are learned using a Dirichlet prior. This only required a couple of small changes to the BNW parameter learning files.

Bug fixes, code comments, and minor changes

2018-04-25T21:43:19+00:00

Separating Octave and php calculations

2018-03-15T04:19:16+00:00

BNW using Octave instead of Matlab.

2017-09-28T20:04:40+00:00

This version of BNW should perform the same as the original version. The only difference is that it uses Octave instead of Matlab when running BayesNet Toolbox during parameter learning. I am calling this BNW_1.02. It can be accessed at: compbio.uthsc.edu/BNW_1.02

Add files via upload

2017-09-14T20:57:50+00:00