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12 commits

Author SHA1 Message Date
8dc6580da1 clean-up: update links embedded into API-doc (Doxygen)
Notably some links on the **Gnome documentation** pages are problematic,
since there was seemingly an infrastructure change -- which unfortunately
leads to loosing several deep-links into the GTK-3 related documentation
and tutorials.

While the differences to GTK-4 are often rather minimal, I would still prefer
to link to those documentation pages used as reference at implementation time
of our related library and GUI functionality.

In several cases I have thus looked up the old URLs at Archive.org
2025-09-19 19:51:28 +02:00
20f3252892 Upgrade: down with typename!!
Yet another chainsaw massacre.

One of the most obnoxious annoyances with C++ metaprogramming
is the need to insert `typename` and `template` qualifiers into
most definitions, to help the compiler to cope with the syntax,
which is not context-free.

The recent standards adds several clarifications, so that most
of these qualifiers are redundant now, at least at places where
it is unambiguously clear that only a type can be given.

GCC already supports most of these relaxing rules
(Clang unfortunately lags way behind with support of newer language features...)
2025-07-06 01:19:08 +02:00
806db414dd Copyright: clarify and simplify the file headers
* Lumiera source code always was copyrighted by individual contributors
 * there is no entity "Lumiera.org" which holds any copyrights
 * Lumiera source code is provided under the GPL Version 2+

== Explanations ==
Lumiera as a whole is distributed under Copyleft, GNU General Public License Version 2 or above.
For this to become legally effective, the ''File COPYING in the root directory is sufficient.''

The licensing header in each file is not strictly necessary, yet considered good practice;
attaching a licence notice increases the likeliness that this information is retained
in case someone extracts individual code files. However, it is not by the presence of some
text, that legally binding licensing terms become effective; rather the fact matters that a
given piece of code was provably copyrighted and published under a license. Even reformatting
the code, renaming some variables or deleting parts of the code will not alter this legal
situation, but rather creates a derivative work, which is likewise covered by the GPL!

The most relevant information in the file header is the notice regarding the
time of the first individual copyright claim. By virtue of this initial copyright,
the first author is entitled to choose the terms of licensing. All further
modifications are permitted and covered by the License. The specific wording
or format of the copyright header is not legally relevant, as long as the
intention to publish under the GPL remains clear. The extended wording was
based on a recommendation by the FSF. It can be shortened, because the full terms
of the license are provided alongside the distribution, in the file COPYING.
2024-11-17 23:42:55 +01:00
a20e233ca0 Library: now using controlled seed and replaced rand (closes #1378)
After augmenting our `lib/random.hpp` abstraction framework to add the necessary flexibility,
a common seeding scheme was ''built into the Test-Runner.''
 * all tests relying on some kind of randomness should invoke `seedRand()`
 * this draws a seed from the `entropyGen` — which is also documented in the log
 * individual tests can now be launched with `--seed` to force a dedicated seed
 * moreover, tests should build a coherent structure of linked generators,
   especially when running concurrently. The existing tests were adapted accordingly

All usages of `rand()` in the code base were investigated and replaced
by suitable calls to our abstraction framework; the code base is thus
isolated from the actual implementation, simplifying further adaptation.
2024-11-17 19:45:41 +01:00
064484450e Library: adapt some existing usages to the convenience API 2024-11-12 22:35:54 +01:00
2883a8619f Library: investigate usage of rand() and consider replacement
As it turns out, by far margin we mostly use rand() to generate
test values within a limited interval, using the ''modulo trick''
and thus excluding the upper bound.

Looking into the implementation of the distributions in the
libStdC++ shows that ''constructing'' a distribution on-the-fly
is cheap and boils down to checking and then storing the bounds;
so basically there is no need to keep ''cached distribution objects''
around, because for all practical purposes these behave like free functions

What is required occasionally is a non-zero HashValue, and sometimes
an interval of floating-point number or a normal distribution seem useful.

Providing these as free-standing convenience functions,
implicitly accessing the default PRNG.
2024-11-12 21:10:14 +01:00
cffa2cd6c2 Library: implement test access to hidden global RandomSequencer
this seems to be the ''classical problem situation''
where a »clean« Dependency-Injection would require to waste storage
for a pointer to the same global resource in each and every distinct test class.

Since the Test-Suite is effectively global — even more so now due to
the reliance on "the" global `RandomSequencer` (PNRG) — we'll have to
bite the bullet and access a global static variable hidden behind teh scenes.
2024-11-10 16:22:46 +01:00
92bc044e9e Library: consider how to handle randomness in tests
Using random or pseudo-random numbers as input for tests
can be a very effective tool to spot unintended behaviour in
corner cases, and also helps writing more principled test verifications.
However, investigating failures in randomised tests can be challenging.

A well-proven solution is to exploit the **determinism** of pseudo-random-numbers
by documenting a randomly generated seed, that can be re-injected for investigation.

Up to now, most tests rely on the old library function `rand()`, while
at some places already the C++ standard framework for random number generation
is used, packaged into a custom wrapper. Adding adequate support for
documented seed values seems to be easy to achieve, after switching
existing usages of `rand()` to a suitable drop-in replacement.

After some consideration, I decided ''against'' wiring random generator instances
explicitly, while allowing to do so on occasion, when necessary. Thus
the planned seeding mechanism will rather re-seed a ''implicit default''
generator, which could then be used to construct explicit generator instances
when required (e.g. for multithreaded tests)

As a starting point, this changeset replaces the `randomise()` API call
by a direct access to the ''reseeding functionality'' exposed by the
C++ framework and all default generators. Since we already provide a
dedicated static instance of the plattform entropy source, re-randomisation
can be achieved by seeding from there.

NOTE: there was extended debate in the net, questioning the viability
of the `std::random_seq` -- these arguments, while valid from a theoretical
point of view, seem rather moot when placed into a practical context,
where even 2^32 different generation-paths(cycles) are more than enough
to provide sufficient diffusion of results (unless the goal is really to
engage into Monte-Carlo simulations for scientific research or large model
simulations).

Notable most of the more catchy reprovals raised by Melissa O'Neill
have been refuted by experts of the field, even while being still propagated
at various places in the net, often combined with promoting PCG-Random.
2024-11-10 03:25:45 +01:00
7960017403 Invocation: add some test coverage for the basic genrator function
Nothing surprising here...

Writing just some dull tests to avoid biting my nails while watching the US election....
2024-11-06 04:13:49 +01:00
aa93bf9285 Library: cover statistic functions and linear regression 2024-03-16 03:05:49 +01:00
b426ea4921 Library: simple default implementation for random sequences
Since this is a much more complicated topic,
for now I decided to establish two instances through global variables:
 * a sequence seeded with a fixed starting value
 * another sequence seeded from a true entropy source

What we actually need however is some kind of execution framework
to define points of random-seeding and to capture seed values for
reproducible tests.
2024-03-12 02:34:19 +01:00
7a3e4098c8 Library: some first thoughts regarding random number generation
Relying on random numbers for verification and measurements is known to be problematic.
At some point we are bound to control the seed values -- and in the actual
application usage we want to record sequence seeding in the event log.

Some initial thoughts regarding this intricate topic.
 * a low-ceremony drop-in replacement for rand() is required
 * we want the ability to pick-up and control each and every usage eventually
 * however, some usages explicitly require true randomness
 * the ability to use separate streams of random-number generation is desirable
2024-03-12 00:48:11 +01:00