Vector(rand()%100 - 50,rand()%100 - 50,rand()%100 - 50); // I could exchange the rand for a mersenne twister I suppose.
Vector.normalize();
Generate a random unit vector.
Author
Are there any well-known ways to quickly generate a random unit vector in 3D space?
Heres what I'm doing now: (In C++)
Why is normalize a problem? Too slow? Here;s some code used to generate random unit vectors, without normalize, well not 100%. But I doubt if its any faster. If you have bad luck, you'll have to try alot of time before a proper vector comes out.
Greetings,
Rick
repeat v[0] := (random(1000)*0.001) * 2 - 1; // -1 .. +1 v[1] := (random(1000)*0.001) * 2 - 1; v[2] := (random(1000)*0.001) * 2 - 1; len := vectorDotProduct(v, v);until not ((len < 0.9 * 0.9) or (len > 1.1 * 1.1));result := vectorScale( v, 1.0 / sqrt(len) );Greetings,
Rick
Quote:Original post by spekrepeat v[0] := (random(1000)*0.001) * 2 - 1; // -1 .. +1 v[1] := (random(1000)*0.001) * 2 - 1; v[2] := (random(1000)*0.001) * 2 - 1; len := vectorDotProduct(v, v);until not ((len < 0.9 * 0.9) or (len > 1.1 * 1.1));result := vectorScale( v, 1.0 / sqrt(len) );
This method is worse than the originally suggested one.
The last step normalises the vector, like in the original method.
The loop before that is just a waste of time and does not even have a predictable runtime.
edit: fixed typo
Quote:Original post by Rattenhirn
Start with a unit vector and rotate it randomly.
I'd recommend this too. Your current method won't distribute the unit vectors uniformly as you're sampling within a cube (there's more possibilities along the diagonals than the cardinal axes), and there's the slim chance you'll end up with a zero vector. Rotating a unit vector will result in a more uniform distribution.
Alternatively you can convert spherical coordinates to cartesian, which should be the same. But now I think of it, it will be tricky to get a uniform spherical distribution from rotations and spherical coordinates as well...
If you need to uniformly generate a unit vector you can do something like this.
That way you don't have higher chances of choosing one vector over others. This assumes that RandomRange will uniformly choose a float between the two arguments and RandomChooseOneArgument will return one of the two arguments uniformly.
Basically all this does is find a random point on the unit disc in the xy-plane and then finds the z-height of the sphere at that point. It will choose either positive or negative height to choose either the top or bottom half of the sphere.
Vector3 UniformUnitVector(){ float theta = RandomRange( 0.0f, 2.0f * Pi ); float r = sqrt( RandomRange( 0.0f, 1.0f ) ); float z = sqrt( 1.0f - r*r ) * RandomChooseOneArgument( -1.0f, 1.0f ); return Vector3( r * cos(theta), r * sin(theta), z );}That way you don't have higher chances of choosing one vector over others. This assumes that RandomRange will uniformly choose a float between the two arguments and RandomChooseOneArgument will return one of the two arguments uniformly.
Basically all this does is find a random point on the unit disc in the xy-plane and then finds the z-height of the sphere at that point. It will choose either positive or negative height to choose either the top or bottom half of the sphere.
I did a Google search on random spherical distribution, and got this Q&A. This seems analogous to your problem, so I hope it's useful.
Author
Thanks guys for the replies, they were all very informative. It seems that rotating a unit vector randomly is the best method, however, I am not overly concerned with the accuracy of the result, rather the speed.
I think putting my problem into context is a good idea here. I am using the random unit vector to help generate a random position to sample a ray occlusion test from a volume light source in a ray tracer (To produce soft-shadows). When the unit vector is generated, I would multiply it by the radius of the light (Which can vary) and use that as the position.
I tried another method like so:
Which is slightly faster, but offcourse generates a volume cube. Does it matter that much for a raytracer though? Do volume lightsources look better in the shape of a cube or a sphere? I realise I've gone waaay off the original point of this post, but I'm hoping that someone could direct me to a whole new method of generating volume light positions for ray tracing soft shadows.
I think putting my problem into context is a good idea here. I am using the random unit vector to help generate a random position to sample a ray occlusion test from a volume light source in a ray tracer (To produce soft-shadows). When the unit vector is generated, I would multiply it by the radius of the light (Which can vary) and use that as the position.
I tried another method like so:
float halfLightRadius = lightRadius * 0.5f;Vector(rand()%lightRadius - halfLightRadius, rand()%lightRadius - halfLightRadius, rand()%lightRadius - halfLightRadius);Which is slightly faster, but offcourse generates a volume cube. Does it matter that much for a raytracer though? Do volume lightsources look better in the shape of a cube or a sphere? I realise I've gone waaay off the original point of this post, but I'm hoping that someone could direct me to a whole new method of generating volume light positions for ray tracing soft shadows.
From my random vector library:
These were well researched, and will give uniform distributions over 2- and 3-spheres.
As for your theory question, you will need to have a unit vector, and for lights in a ray-tracer it is best to have a uniform distribution.
// the function Random() returns a float in the range [0,1]float2 RandomDirection2D(){ float azimuth = Random() * 2 * pi; return float2(cos(azimuth), sin(azimuth);}float3 RandomDirection3D(){ float z = (2*Random()) - 1; // z is in the range [-1,1] float2 planar = RandomDirection2D() * sqrt(1-z*z); return float3(planar.x, planar.y, z);}These were well researched, and will give uniform distributions over 2- and 3-spheres.
As for your theory question, you will need to have a unit vector, and for lights in a ray-tracer it is best to have a uniform distribution.
BlindSide's original method creates a higher density in the corners.
Spek's method rejects a lot of vectors and also creates slightly higher density in the corners, but not as bad.
It would work and be more efficient if
until not ((len < 0.9 * 0.9) or (len > 1.1 * 1.1));
is deplaced by
until (len > 0.001 and len < 1);
(len > 0.001 is used to prevent division by zero later on).
Rattenhirn: How do you randomly rotate a vector? I'm not sure if for instance using a random yaw, pitch and roll creates a uniform distribution.
I think Lexdysic's and Symphonic's methods are exactly the same, but Symphonic's doesn't use the "choose -1 or 1 randomly" thing, so it should be faster. Both produce very nice results, though.
- Lutz
Spek's method rejects a lot of vectors and also creates slightly higher density in the corners, but not as bad.
It would work and be more efficient if
until not ((len < 0.9 * 0.9) or (len > 1.1 * 1.1));
is deplaced by
until (len > 0.001 and len < 1);
(len > 0.001 is used to prevent division by zero later on).
Rattenhirn: How do you randomly rotate a vector? I'm not sure if for instance using a random yaw, pitch and roll creates a uniform distribution.
I think Lexdysic's and Symphonic's methods are exactly the same, but Symphonic's doesn't use the "choose -1 or 1 randomly" thing, so it should be faster. Both produce very nice results, though.
- Lutz
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