Merge pull request #88883 from joaoh82/add-weighted-random-method

Add `RandomNumberGenerator::rand_weighted` method
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Rémi Verschelde 2024-03-01 15:00:32 +01:00
commit bd7637248c
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5 changed files with 48 additions and 0 deletions

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@ -42,6 +42,7 @@ void RandomNumberGenerator::_bind_methods() {
ClassDB::bind_method(D_METHOD("randfn", "mean", "deviation"), &RandomNumberGenerator::randfn, DEFVAL(0.0), DEFVAL(1.0)); ClassDB::bind_method(D_METHOD("randfn", "mean", "deviation"), &RandomNumberGenerator::randfn, DEFVAL(0.0), DEFVAL(1.0));
ClassDB::bind_method(D_METHOD("randf_range", "from", "to"), &RandomNumberGenerator::randf_range); ClassDB::bind_method(D_METHOD("randf_range", "from", "to"), &RandomNumberGenerator::randf_range);
ClassDB::bind_method(D_METHOD("randi_range", "from", "to"), &RandomNumberGenerator::randi_range); ClassDB::bind_method(D_METHOD("randi_range", "from", "to"), &RandomNumberGenerator::randi_range);
ClassDB::bind_method(D_METHOD("rand_weighted", "weights"), &RandomNumberGenerator::rand_weighted);
ClassDB::bind_method(D_METHOD("randomize"), &RandomNumberGenerator::randomize); ClassDB::bind_method(D_METHOD("randomize"), &RandomNumberGenerator::randomize);
ADD_PROPERTY(PropertyInfo(Variant::INT, "seed"), "set_seed", "get_seed"); ADD_PROPERTY(PropertyInfo(Variant::INT, "seed"), "set_seed", "get_seed");

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@ -57,6 +57,8 @@ public:
_FORCE_INLINE_ real_t randfn(real_t p_mean = 0.0, real_t p_deviation = 1.0) { return randbase.randfn(p_mean, p_deviation); } _FORCE_INLINE_ real_t randfn(real_t p_mean = 0.0, real_t p_deviation = 1.0) { return randbase.randfn(p_mean, p_deviation); }
_FORCE_INLINE_ int randi_range(int p_from, int p_to) { return randbase.random(p_from, p_to); } _FORCE_INLINE_ int randi_range(int p_from, int p_to) { return randbase.random(p_from, p_to); }
_FORCE_INLINE_ int rand_weighted(const Vector<float> &p_weights) { return randbase.rand_weighted(p_weights); }
RandomNumberGenerator() { randbase.randomize(); } RandomNumberGenerator() { randbase.randomize(); }
}; };

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@ -31,6 +31,7 @@
#include "random_pcg.h" #include "random_pcg.h"
#include "core/os/os.h" #include "core/os/os.h"
#include "core/templates/vector.h"
RandomPCG::RandomPCG(uint64_t p_seed, uint64_t p_inc) : RandomPCG::RandomPCG(uint64_t p_seed, uint64_t p_inc) :
pcg(), pcg(),
@ -42,6 +43,26 @@ void RandomPCG::randomize() {
seed(((uint64_t)OS::get_singleton()->get_unix_time() + OS::get_singleton()->get_ticks_usec()) * pcg.state + PCG_DEFAULT_INC_64); seed(((uint64_t)OS::get_singleton()->get_unix_time() + OS::get_singleton()->get_ticks_usec()) * pcg.state + PCG_DEFAULT_INC_64);
} }
int RandomPCG::rand_weighted(const Vector<float> &p_weights) {
ERR_FAIL_COND_V_MSG(p_weights.is_empty(), -1, "Weights array is empty.");
int64_t weights_size = p_weights.size();
const float *weights = p_weights.ptr();
float weights_sum = 0.0;
for (int64_t i = 0; i < weights_size; ++i) {
weights_sum += weights[i];
}
float remaining_distance = Math::randf() * weights_sum;
for (int64_t i = 0; i < weights_size; ++i) {
remaining_distance -= weights[i];
if (remaining_distance < 0) {
return i;
}
}
return -1;
}
double RandomPCG::random(double p_from, double p_to) { double RandomPCG::random(double p_from, double p_to) {
return randd() * (p_to - p_from) + p_from; return randd() * (p_to - p_from) + p_from;
} }

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@ -59,6 +59,9 @@ static int __bsr_clz32(uint32_t x) {
#define LDEXPF(s, e) ldexp(s, e) #define LDEXPF(s, e) ldexp(s, e)
#endif #endif
template <class T>
class Vector;
class RandomPCG { class RandomPCG {
pcg32_random_t pcg; pcg32_random_t pcg;
uint64_t current_seed = 0; // The seed the current generator state started from. uint64_t current_seed = 0; // The seed the current generator state started from.
@ -87,6 +90,8 @@ public:
return pcg32_boundedrand_r(&pcg, bounds); return pcg32_boundedrand_r(&pcg, bounds);
} }
int rand_weighted(const Vector<float> &p_weights);
// Obtaining floating point numbers in [0, 1] range with "good enough" uniformity. // Obtaining floating point numbers in [0, 1] range with "good enough" uniformity.
// These functions sample the output of rand() as the fraction part of an infinite binary number, // These functions sample the output of rand() as the fraction part of an infinite binary number,
// with some tricks applied to reduce ops and branching: // with some tricks applied to reduce ops and branching:

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@ -17,6 +17,25 @@
<link title="Random number generation">$DOCS_URL/tutorials/math/random_number_generation.html</link> <link title="Random number generation">$DOCS_URL/tutorials/math/random_number_generation.html</link>
</tutorials> </tutorials>
<methods> <methods>
<method name="rand_weighted">
<return type="int" />
<param index="0" name="weights" type="PackedFloat32Array" />
<description>
Returns a random index with non-uniform weights. Prints an error and returns [code]-1[/code] if the array is empty.
[codeblocks]
[gdscript]
var rnd = RandomNumberGenerator.new()
var my_array = ["one", "two", "three, "four"]
var weights = PackedFloat32Array([0.5, 1, 1, 2])
# Prints one of the four elements in `my_array`.
# It is more likely to print "four", and less likely to print "two".
print(my_array[rng.rand_weighted(weights)])
[/gdscript]
[/codeblocks]
</description>
</method>
<method name="randf"> <method name="randf">
<return type="float" /> <return type="float" />
<description> <description>