In a compute shader (with Unity) I have a raycast finding intersections with mesh triangles. At some point I would like to return how many intersections are found.
I can clearly see how many intersections there are by marking the pixels, however if I simply increment a global int for every intersection in the compute shader (and return via a buffer), the number I get back makes no sense. I assume this is because I'm creating a race condition.
I see that opengl has "atomic counters" : https://www.opengl.org/wiki/Atomic_Counter, which seem like what I need in this situation. I have had no luck finding such a feature in either the Unity nor the DirectCompute documentation. Is there a good way to do this?
I could create an appendBuffer, but it seems silly as I literally need to return just a single int.
HA! That was easy. I'll leave this here just in-case someone runs into the same problem.
HLSL has a whole set of "interlocked" functions that prevent this sort of thing from happening:
https://msdn.microsoft.com/en-us/library/windows/desktop/ff476334(v=vs.85).aspx
In my case it was:
InterlockedAdd(collisionCount, 1);
To replace
collisionCount++;
And that's it!
Related
In a Unity code base, I saw this:
// the game object currently has no mesh attached
MeshFilter mFilter = gameObject.AddComponent<MeshFilter>();
gameObject.AddComponent<MeshRenderer>();
// no problem so far
mFilter.mesh = MakeASmallQuadMesh(0.1f);
// great stuff
mFilter.mesh.bounds = SomeSpecificBounds();
// what ?
The function "MakeASmallQuadMesh" has the usual completely normal code for making a mesh, so
Mesh mesh = new Mesh();
mesh.SetVertices(verts);
mesh.SetIndices(indices);
mesh.SetUVs(0, uvs);
mesh.RecalculateNormals();
mesh.RecalculateBounds();
return mesh;
No worries there. It makes a quad 10cm across.
But what about the line of code
mFilter.mesh.bounds = SomeSpecificBounds();
I was amazed to learn you can set mesh.bounds, I assumed it would be read-only.
What possible "meaning" is there to "setting" the bounds? It would be like: there's a written measurement in a doctor's office stating that Jane is 6'. You change the record to 5'10". Of course, Jane's height does not change at all. You've just, bizarrely made the record wrong.
Could it be that: so, the bounds of a mesh are used by various, indeed many, Unity systems. (Culling, etc etc.) Could the pattern be that by "forcing" the bounds like this (the bounds are now "totally wrong" for the object - they're just some value you forced in there) the programmer wanted (for some reason) Unity's system (say, culling) to use those forced, nonsensical (to the actual object) values?
Wild guess, maybe there's a pattern (I have never heard of) where you "force" the bounds of object A to be the same as object B - for some reason I cannot guess at?
What could possibly be the pattern / reason here?
I would just assume it's a basic mistake, but assumptions kill.
I was actually curious about this myself, and I happened to have a program that explicitly generated large numbers of custom meshes, so I decided to test a few things.
The first thing I wanted to confirm was that the bounds were in fact set automatically. A rudimentary inspection revealed that this was indeed the case: Specifically, a mesh's bounds are automatically recalculated any time you set the mesh.vertices property. This probably explains why the property is a fixed length array rather than a list. (fun side note: If you try to assign secondary properties like uv coords or normals to the mesh before assigning vertex positions, unity gently nags you about mismatched array lengths before promptly exploding. So Don't Do That.)
As for what this actually impacts, I had a hunch: I set the extents of my mesh bounds to be 0. Immediately, meshes at the corner of my viewport stated getting visually culled. This tells us a few things:
Setting bounds explicitly does have an effect.
Unity does actually make use of custom bounds data.
Unity uses mesh bounds to perform frustum culling.
According to Unity's manual, there are three cases where the Bounds class is used: Mesh.bounds, Renderer.bounds, and Collider.bounds. Of those three, Mesh.bounds is the only property that isn't read only.
As for the question of why anybody would want to set mesh bounds explicitly, it's not impossible that you could perform some clever culling optimization like looking at a complex mesh through a window or some such, but if I had to guess, whoever wrote that code didn't trust Unity to set mesh bounds accurately or explicitly.
So, I'm attempting to create a simple dynamic endless terrain using simplex noise.
So far I've got the noise working just fine - however I am having issues with the terrain having discontinuities at the edges. At first I thought this was due to the fact that I was not calling SetNeighbors on the Terrain objects, but adding this did not seem to yield any improvement.
terrain.GetComponent<Terrain>().SetNeighbors(left, top, right, bottom);
This problem seems to be caused by the slight differences in height between each terrain position - but making these set the same will effect the terrain quality (will reduce how jagged the terrain can be in certain cases) and generally seems inelegant. I've been going through the unity docs trying to find how to address this, but have yet to find anything.
Is there something I'm missing? Or is my only option to fiddle the heights on one of the sides to match the other?
Thanks for reading, appreciated as always.
Terrain image for reference
A couple things-
First, make sure you're setting SetNeighbors() on ALL the terrain objects, not just one.
Secondly, if the terrain don't match up exactly, it either means that the terrains aren't calculating their data quite correctly, or there's some floating point error going on. However, I have a suspicion that it's the first one, given that manually changing the points affects the quality. Make sure you know that terrains have n^2 + 1 points, and also make sure that the point to query from your simplex function with is calculated in world space.
If you can't figure it out, post your code and I'll take a look.
Also, your terrain might look better if you used octaved (a.k.a factal) noise on your Simplex noise function, depending on what you're looking for.
Cheers!
Given a set of non-rotated AABB bounds, I'm hoping to create a simpler set of bounds from the original set, that allows for a specified amount of inaccuracy.
Some examples:
I'm working with this in Unity with Bounds, but it's just basic AABB comparison stuff, nothing Unity-specific. I figure someone must have worked out a system for this at some point in the past, but I had no luck searching around. Encapsulating bounds are easy but this is harder, since you can't just iterate through each bounds one by one. Sometimes a simpler solution can only be seen by looking at the whole thing.
Fast performance isn't critical but would be nice. Inaccuracy is OK in both directions (i.e. the bounds may cover a little less than the actual size or a little more). If it helps, I can expect all bounds in the original set to be connected somewhere - no free-floating pieces in a separate group.
I don't expect anyone to write up a whole system to solve this, I'm more hoping that it's already been solved or that maybe there's an obvious process to achieve it that I haven't thought of yet.
This sounds something that could be handled with Surface Area Heuristics (SAH). SAH is commonly used in ray tracing to build better tree like structures were the triangles are stored. There are multiple sources discussing it more. One good is Wald's thesis chapter 7.3.
The basic idea in the SAH built is to start with the whole space and divide it recursively. Division position is decided by sweeping through all reasonable positions and calculating surface area of both child nodes. The reasonable positions are the positions were any triangle has its upper or lower bound. After sweeping through all the candidates, the division with the smallest total surface area in the children is used.
If SAH is not a good idea for your application, you could use similar sweeping through all candidates, but calculate for example the extra space inside the AABBs.
I am making a game that involves solving a path through graphs. Depending on the size of the graph this can take a little while so I want to cache my results.
This has me looking for an algorithm to hash a graph to find duplicates.
This is straightforward for exact copies of a graph, I simply use the node positions relative to the top corner. It becomes quite a bit more complicated for rotated or even reflected graphs. I suspect this isn't a new problem, but I'm unsure of what the terminology for it is?
My specific case is on a grid, so a node (if present) will always be connected to its four neighbors, north, south, east and west. In my current implementation each node stores an array of its adjacent nodes.
Suggestions for further reading or even complete algorithms are much appreciated.
My current hashing implementation starts at the first found node in the graph which depends on how i iterate over the playfield, then notes the position of all nodes relative to it. The base graph will have a hash that might be something like: 0:1,0:2,1:2,1:3,-1:1,
I suggest you do this:
Make a function to generate a hash for any graph, position-independent. It sounds like you already have this.
When you first generate the pathfinding solution for a graph, cache it by the hash for that graph...
...Then also generate the 7 other unique forms of that graph (rotated 90deg; rotated 270deg; flipped x; flipped y; flipped x & y; flipped along one diagonal axis; flipped along the other diagonal axis). You can of course generate these using simple vector/matrix transformations. For each of these 7 transformed graphs, you also generate that graph's hash, and cache the same pathfinding solution (which you first apply the same transform to, so the solution maps appropriately to the new graph configuration).
You're done. Later your code will look up the pathfinding solution for a graph, and even if it's an alternate (rotated, flipped) form of the graph you found the earlier solution for, the cache already contains the correct solution.
I spent some time this morning thinking about this and I think this is probably the most optimal solution. But I'll share the other over-analyzed versions of the solution that I was also thinking about...
I was considering the fact that what you really needed was a function that would take a graph G, and return the "canonical version" of G (which I'll call G'), AND the transform matrix required to convert G to G'. (It seemed like you would need the transform so you could apply it to the pathfinding data and get the correct path for G, since you would have just stored the pathfinding data for G'.) You could, of course, look up pathfinding data for G', apply the transform matrix to it, and have your pathfinding solution.
The problem is that I don't think there's any unambiguous and performant way to determine a "canonical version" of G, because it means you have to recognize all 8 variants of G and always pick the same one as G' based on some criteria. I thought I could do something clever by looking at each axis of the graph, counting the number of points along each row/column in that axis, and then rotating/flipping to put the more imbalanced half of the axis always in the top-or-left... in other words, if you pass in "d", "q", "b", "d", "p", etc. shapes, you would always get back the "p" shape (where the imbalance is towards the top-left). This would have the nice property that it should recognize when the graph was symmetrical along a given axis, and not bother to distinguish between the flipped versions on that axis, since they were the same.
So basically I just took the row-by-row/column-by-column point counts, counting the points in each half of the shape, and then rotating/flipping until the count is higher in the top-left. (Note that it doesn't matter that the count would sometimes be the same for different shapes, because all the function was concerned with was transforming the shape into a single canonical version out of all the different possible permutations.)
Where it fell down for me was deciding which axis was which in the canonical case - basically handling the case of whether to invert along the diagonal axis. Once again, for shapes that are symmetrical about a diagonal axis, the function should recognize this and not care; for any other case, it should have a criteria for saying "the axis of the shape that has the property [???] is, in the canonical version, the x axis of the shape, while the other axis will be the y axis". And without this kind of criteria, you can't distinguish two graphs that are flipped about the diagonal axis (e.g. "p" versus "σ"/sigma). The criteria I was trying to use was again "imbalance", but this turned out to be harder and harder to determine, at least the way I was approaching it. (Maybe I should have just applied the technique I was using for the x/y axes to the diagonal axes? I haven't thought through how that would work.) If you wanted to go with such a solution, you'd either need to solve this problem I failed to solve, or else give up on worrying about treating versions that are flipped about the diagonal axis as equivalent.
Although I was trying to focus on solutions that just involved calculating simple sums, I realized that even this kind of summing is going to end up being somewhat expensive to do (especially on large graphs) at runtime in pathfinding code (which needs to be as performant as possible, and which is the real point of your problem). In other words I realized that we were probably both overthinking it. You're much better off just taking a slight hit on the initial caching side and then having lightning-fast lookups based on the graph's position-independent hash, which also seems like a pretty foolproof solution as well.
Based on the twitter conversation, let me rephrase the problem (I hope I got it right):
How to compare graphs (planar, on a grid) that are treated as invariant under 90deg rotations and reflection. Bonus points if it uses hashes.
I don't have a full answer for you, but a few ideas that might be helpful:
Divide the problem into subproblems that are independently solvable. That would make
How to compare the graphs given the invariance conditions
How to transform them into a canonical basis
How to hash this canonical basis subject to tradeoffs (speed, size, collisions, ...)
You could try to solve 1 and 2 in a singe step. A naive geometric approach could be as follows:
For rotation invariance, you could try to count the edges in each direction and rotate the graph so that the major direction always point to the right. If there is no main direction you could see the graph as a point cloud of its vertices and use Eigenvectors and Priciple Compoment Analysis (PCA) to obtain the main direction and rotate it accordingly.
I don't have a smart solution for the reflection problem. My brute force way would be to just create the reflected graph all the time. Say you have a graph g and the reflected graph r(g). If you want to know if some other graph h == g you have to answer h == g || h == r(g).
Now onto the hashing:
For the hashing you probably have to trade off speed, size and collisions. If you just use the string of edges, you are high on speed and size and low on collisions. If you just take this string and apply some generic string hasher to it, you get different results.
If you use a short hash, with more frequent collisions, you can get achieve a rather small cost for comparing non matching graphs. The cost for matching graphs is a bit higher then, as you have to do a full comparison to see if they actually match.
Hope this makes some kind of sense...
best, Simon
update: another thought on the rotation problem if the edges don't give a clear winner: Compute the center of mass of the vertices and see to which side of the center of the bounding box it falls. Rotate accordingly.
I want to ask about jelly physics ( http://www.youtube.com/watch?v=I74rJFB_W1k ), where I can find some good place to start making things like that ? I want to make simulation of cars crash and I want use this jelly physics, but I can't find a lot about them. I don't want use existing physics engine, I want write my own :)
Something like what you see in the video you linked to could be accomplished with a mass-spring system. However, as you vary the number of masses and springs, keeping your spring constants the same, you will get wildly varying results. In short, mass-spring systems are not good approximations of a continuum of matter.
Typically, these sorts of animations are created using what is called the Finite Element Method (FEM). The FEM does converge to a continuum, which is nice. And although it does require a bit more know-how than a mass-spring system, it really isn't too bad. The basic idea, derived from the study of continuum mechanics, can be put this way:
Break the volume of your object up into many small pieces (elements), usually tetrahedra. Let's call the entire collection of these elements the mesh. You'll actually want to make two copies of this mesh. Label one the "rest" mesh, and the other the "world" mesh. I'll tell you why next.
For each tetrahedron in your world mesh, measure how deformed it is relative to its corresponding rest tetrahedron. The measure of how deformed it is is called "strain". This is typically accomplished by first measuring what is known as the deformation gradient (often denoted F). There are several good papers that describe how to do this. Once you have F, one very typical way to define the strain (e) is:
e = 1/2(F^T * F) - I. This is known as Green's strain. It is invariant to rotations, which makes it very convenient.
Using the properties of the material you are trying to simulate (gelatin, rubber, steel, etc.), and using the strain you measured in the step above, derive the "stress" of each tetrahdron.
For each tetrahedron, visit each node (vertex, corner, point (these all mean the same thing)) and average the area-weighted normal vectors (in the rest shape) of the three triangular faces that share that node. Multiply the tetrahedron's stress by that averaged vector, and there's the elastic force acting on that node due to the stress of that tetrahedron. Of course, each node could potentially belong to multiple tetrahedra, so you'll want to be able to sum up these forces.
Integrate! There are easy ways to do this, and hard ways. Either way, you'll want to loop over every node in your world mesh and divide its forces by its mass to determine its acceleration. The easy way to proceed from here is to:
Multiply its acceleration by some small time value dt. This gives you a change in velocity, dv.
Add dv to the node's current velocity to get a new total velocity.
Multiply that velocity by dt to get a change in position, dx.
Add dx to the node's current position to get a new position.
This approach is known as explicit forward Euler integration. You will have to use very small values of dt to get it to work without blowing up, but it is so easy to implement that it works well as a starting point.
Repeat steps 2 through 5 for as long as you want.
I've left out a lot of details and fancy extras, but hopefully you can infer a lot of what I've left out. Here is a link to some instructions I used the first time I did this. The webpage contains some useful pseudocode, as well as links to some relevant material.
http://sealab.cs.utah.edu/Courses/CS6967-F08/Project-2/
The following link is also very useful:
http://sealab.cs.utah.edu/Courses/CS6967-F08/FE-notes.pdf
This is a really fun topic, and I wish you the best of luck! If you get stuck, just drop me a comment.
That rolling jelly cube video was made with Blender, which uses the Bullet physics engine for soft body simulation. The bullet documentation in general is very sparse and for soft body dynamics almost nonexistent. You're best bet would be to read the source code.
Then write your own version ;)
Here is a page with some pretty good tutorials on it. The one you are looking for is probably in the (inverse) Kinematics and Mass & Spring Models sections.
Hint: A jelly can be seen as a 3 dimensional cloth ;-)
Also, try having a look at the search results for spring pressure soft body model - they might get you going in the right direction :-)
See this guy's page Maciej Matyka, topic of soft body
Unfortunately 2d only but might be something to start with is JellyPhysics and JellyCar