Math/Random and its tests implementation by sariug · Pull Request #432 · mosra/magnum

sariug · 2020-04-06T15:20:42Z

Hello hello,

Did some simple implementation; would be happy to develop it further with the suggestions.
Prepared for one engine ("mt19937")

mosra

I really appreciate that you did a test as well 👍

Since this is your first contribution, I'm not commenting on coding style -- let's get this working first :)

mosra · 2020-04-08T15:03:45Z

+public:
+    static std::mt19937 &generator()
+    {
+        static std::mt19937 g{seeds};


static is problematic because of thread safety issues, global constructors/destructors etc. What do you think about this?

Math::RandomGenerator g; // the user is required to instantiate this first auto a = Math::randomSignedScalar(g); auto b = Math::randomUnitVector2(g);

The RandomGenerator thus wouldn't be in Implementation anymore, but will be exposed to the user, even though its only use would be to get passed to the random*() functions.

I thought about it, and tried to keep minimalistic(however you are right for the thread safety), to keep it as a 1-step function.

if you have no other proposal and think that this would be the best, then why not :)

Not sure if best, but I didn't come up with anything better yet.

I think this should be also robust in case I decide to implement my own random generator later.

Implemented some stuff. Wondering how you would find these. I feel quiteee doubtful.(Especially would love to hide the "generate" function;

mosra · 2020-04-08T15:17:05Z

+Vector2<T> randomUnitVector2()
+{
+    auto a = Implementation::RandomGenerator::generate(0.0f, 2 * Math::Constants<T>::pi());
+    return {std::cos(a), std::sin(a)};


I guess this is where things become hard 😅

I actually have no idea here -- will the distribution be still uniform if sin/cos is used? I guess it will? Ideally this would be without the extra overhead of trig functions, but I don't have any idea if that's doable ... in this thread on SO they use a Gaussian distribution as an input, but .. ¯\_(ツ)_/¯

If you have better references than me, mention them here please :)

For this case sin and cos shall not be get affected ? (sin (+ + - - )[50%], cos (+ - - + )[50%] )
So this shall be as accurate as the generator itself ?

Can you also comment about what I read here ? It looks accurate according to this. The main discussion seems like "getting 3 random numbers and normalizing" vs "2 numbers(theta and height) and calculating". The latter seems more accurate, which is sin/cos.

Yes that's a great reference, thanks -- a link to it should go in the documentation. I didn't absorb it fully yet, but yeah it sounds like a good proof.

getting 3 random numbers and normalizing

this is what you do for quaternions tho .. can the two-/three-dimensional case be extended for those as well?

Quaternion is link here.

Added both to the code :)

mosra · 2020-04-08T15:27:20Z

+bool randomBool()
+{
+    return static_cast<bool>(randomUnsignedScalar<Int>());
+}


Hmm, do we actually need this? :) The randomUnsignedScalar() for integers isn't really useful either. Maybe instead add a static_assert(IsFloatingPoint<T>::value, ""); to the RandomGenerator and remove everything related to integers? Those can be always added back later. (The trait is in Magnum/Math/TypeTraits.h.)

Well, like i said in the beginning, a initiation for a new magnum functionality :) Can grow later with demand :)

Deleting/Fixing. :)

I first deleted, and then put it back haha :D
From our initial discussion:

Float randomUnsignedScalar(); // range [0, 1] Float randomSignedScalar(); // range [-1, 1] Vector2 randomPointOnACircle(); // always length = 1 Vector3 randomPointOnASphere(); // also Quaternion randomRotation(); // always normalized

Maybe keeping it with integers to not to cast anything if we roll a dice?(randomUnsignedScalar<int>(1,6))or to see if that girl is single?(randomUnsignedScalar<int>(0,1)[bool to cast, yes. maybe type traits for numerics?])

mosra · 2020-04-08T15:30:42Z

+    {
+        CORRADE_COMPARE(Math::Random::randomRotation().length(), 1.0f);
+    }
+}


It would be great to have some sort of distribution verification in the tests, to ensure we're not accidentally skewing the distribution to something non-uniform -- how good are your statistics skills? :)

Found this on SO, it suggests using a Chi Squared test. I never did such a thing myself tho :D

We have easter incoming ! :)

Well, I put a chi square test. In testing, I couldnt see a "tolerant" testing scheme(Chi square let 1 fail; like 99% ).

mosra · 2020-04-16T11:21:06Z

Okay, great job! Everything seems to compile and pass tests except a few cases where

Value error_count is not less than 2, actual is 2 but expected < 2

I'm not sure how bad this is tho, seems to be depending on how good the standard implementation is? :)

I'll need some time to write the docs etc., but I think this can go in 🎉

sariug · 2020-04-16T18:32:14Z

Great news !

Value error_count is not less than 2, actual is 2 but expected < 2

I'm not sure how bad this is tho, seems to be depending on how good the standard implementation is? :)

So this happens in chisquare I guess, which the randomness in belong to std engine..
Let me know if i can support anyhow !

mosra · 2020-04-17T11:52:51Z

TODOs for me (adding a comment so I don't forget):

move <random> to a cpp file because it's heavy -- https://artificial-mind.net/projects/compile-health/
investigate what's up with std::seed_seq -- https://twitter.com/horenmar_ctu/status/1251044181558124544

sariug · 2020-08-23T11:13:28Z

Hey hey. Currently I was checking out Perlin noise(I've seen your "SmootherStep" :D ). Would you also like that to be implemented as an extension of this ?

Some noise here:

codecov · 2026-05-23T09:55:22Z

Codecov Report

✅ All modified and coverable lines are covered by tests.
✅ Project coverage is 78.23%. Comparing base (e507580) to head (ac52472).
⚠️ Report is 3842 commits behind head on master.

Additional details and impacted files

@@           Coverage Diff           @@
##           master     #432   +/-   ##
=======================================
  Coverage   78.22%   78.23%           
=======================================
  Files         388      390    +2     
  Lines       21083    21128   +45     
=======================================
+ Hits        16493    16530   +37     
- Misses       4590     4598    +8

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sariug added 2 commits April 5, 2020 22:04

Initial Random.h

46a026e

also some tests

8f73873

sariug changed the title ~~Math/Random amnd its tests implementation~~ Math/Random and its tests implementation Apr 6, 2020

Get rid of iosteam.

9de2987

mosra added this to the 2020.0a milestone Apr 8, 2020

mosra reviewed Apr 8, 2020

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Comment thread src/Magnum/Math/Test/RandomTest.cpp Outdated

mosra reviewed Apr 8, 2020

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Comment thread src/Magnum/Math/Test/RandomTest.cpp Outdated

sariug added 8 commits April 8, 2020 22:49

add repeated tests, use better macros!

282f3d5

Better quaternion, get rid of bool, put the links

9a0dffe

Merge branch 'master' of github.com:sariug/magnum

b201ab3

Mosra was right.

9337219

ChiSquare is implemented. seems pretty neat !

3196dac

according to travis not all the compilers like initializer lists.

7bcc433

public functions

c5e5804

no accumulate..MSVC dwants a header.

ac52472

mosra modified the milestones: 2020.0a, 2020.0b Jun 26, 2020

mosra mentioned this pull request Aug 22, 2020

Initial work on ssao mosra/magnum-examples#91

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sariug Apr 8, 2020 • edited Loading Uh oh! There was an error while loading. Please reload this page.

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mosra commented Apr 16, 2020

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sariug commented Apr 16, 2020

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mosra commented Apr 17, 2020

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sariug commented Aug 23, 2020

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codecov Bot commented May 23, 2026

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sariug Apr 8, 2020 •

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