I am kinda stuck with my basic voxel physics right now. It's very, very choppy and I am pretty sure my maths is broken somewhere, but let's see what you have to say:
// SOMEWHERE AT CLASS LEVEL (so not being reinstantiated every frame, but persisted instead!)
glm::vec3 oldPos;
// ACTUAL IMPL
glm::vec3 distanceToGravityCenter =
this->entity->getPosition() -
((this->entity->getPosition() - gravityCenter) * 0.005d); // TODO multiply by time
if (!entity->grounded) {
glm::vec3 entityPosition = entity->getPosition();
if (getBlock(floorf(entityPosition.x), floorf(entityPosition.y), floorf(entityPosition.z))) {
glm::vec3 dir = entityPosition - oldPos; // Actually no need to normalize as we check for lesser, bigger or equal to 0
std::cout << "falling dir: " << glm::to_string(dir) << std::endl;
// Calculate offset (where to put after hit)
int x = dir.x;
int y = dir.y;
int z = dir.z;
if (dir.x >= 0) {
x = -1;
} else if (dir.x < 0) {
x = 1;
}
if (dir.y >= 0) {
y = -1;
} else if (dir.y < 0) {
y = 1;
}
if (dir.z >= 0) {
z = -1;
} else if (dir.z < 0) {
z = 1;
}
glm::vec3 newPos = oldPos + glm::vec3(x, y, z);
this->entity->setPosition(newPos);
entity->grounded = true; // If some update happens, grounded needs to be changed
} else {
oldPos = entity->getPosition();
this->entity->setPosition(distanceToGravityCenter);
}
}
Basic idea was to determine from which direction entityt would hit the surface and then just position it one "unit" back into that direction. But obviously I am doing something wrong as that will always move entity back to the point where it came from, effectively holding it at the spawn point.
Also this could probably be much easier and I am overthinking it.
As #CompuChip already pointed out, your ifs could be further simplified.
But what is more important is one logical issue that would explain the "choppiness" you describe (Sadly you did not provide any footage, so this is my best guess)
From the code you posted:
First you check if entity is grounded. If so you continue with checking if there is a collision and lastly, if there is not, you set the position.
You have to invert that a bit.
Save old position
Check if grounded
Set the position already to the new one!
Do collision detection
Reset to old position IF you registered a collision!
So basically:
glm::vec3 distanceToGravityCenter =
this->entity->getPosition() -
((this->entity->getPosition() - gravityCenter) * 0.005d); // TODO multiply by time
oldPos = entity->getPosition(); // 1.
if (!entity->grounded) { // 2.
this->fallingStar->setPosition(distanceToGravityPoint); // 3
glm::vec3 entityPosition = entity->getPosition();
if (getBlock(floorf(entityPosition.x), floorf(entityPosition.y), floorf(entityPosition.z))) { // 4, 5
this->entity->setPosition(oldPos);
entity->grounded = true; // If some update happens, grounded needs to be changed
}
}
This should get you started :)
I want to elaborate a bit more:
If you check for collision first and then set position you create an "infinite loop" upon first collision/hit as you collide, then if there is a collision (which there is) you set back to the old position. Basically just mathematic inaccuracy will make you move, as on every check you are set back to the old position.
Consider the if-statements for one of your coordinates:
if (dir.x >= 0) {
x = -1;
}
if (dir.x < 0) {
x = 1;
}
Suppose that dir.x < 0. Then you will skip the first if, enter the second, and x will be set to 1.
If dir.x >= 0, you will enter the first if and x will be set to -1. Now x < 0 is true, so you will enter the second if as well, and x gets set to 1 again.
Probably what you want is to either set x to 1 or to -1, depending on dir.x. You should only execute the second if when the first one was not entered, so you need an else if:
if (dir.x >= 0) {
x = -1;
} else if (dir.x < 0) {
x = 1;
}
which can be condensed, if you so please, into
x = (dir.x >= 0) ? -1 : 1;
Related
I am currently working on a very simple 'Falling Sand' simulation game in C++ and SDL2, and am having problems with getting water to flow in a more realistic manner. I basically have a grid of cells that I iterate through bottom-to-top, left-to-right and if I find a water cell, I just check below, down to left, down to the right, left then right for empty cells and it moves into the first one its finds (it makes a random choice if both diagonal cells or both horizontal cells are free). I then mark the cell it moved into as processed so that it is not checked again for the rest of that loop.
My problem is a sort of 'left-bias' in how the particles move; if I spawn a square of water cells above a barrier, they will basically all shift to left without moving once the particles begin to reach the barrier, while the cells on the right will run down in the proper way. So instead of forming a nice triangular shape flowing out evenly to both sides, the whole shape will just move to the left. This effect is reversed whenever I iterate left-to-right, so I know it's something to do with that but so far I've been stumped trying to fix it. I initially thought it was a problem with how I marked the cells as processed but I've found no obvious bugs with that system in many hours of testing. Has anyone faced any similar challeneges in developing a simulation like this, or knows something that I'm missing? Any help would be very much appreciated.
EDIT:
Ok so I've made a little progress, however I've ran into another bug that seems to be unrelated to iteration, since now I save a copy of the old cells and read from that to decide an update, then update the original cells and display that. This already made the sand work better, however water, which checks horizontally for free cells, now 'disappears' when it does move horizontally. I've been testing it all morning and have yet to find a solution, I thought it might've been someting to do with how I was copying the arrays over, but it seems to work as far as I can tell.
New snippets:
Simulation.cpp
void Simulation::update()
{
copyStates(m_cells, m_oldCells); // so now oldcells is the last new state
for(int y = m_height - 1; y>= 0; y--)
for(int x = 0; x < m_width; x++)
{
Cell* c = getOldCell(x, y); // check in the old state for possible updates
switch(c->m_type)
{
case EMPTY:
break;
case SAND:
if(c->m_visited == false) update_sand(x, y);
break;
case WATER:
if(c->m_visited == false) update_water(x, y);
break;
default:
break;
}
}
}
void Simulation::update_water(int x, int y)
{
bool down = (getOldCell(x, y+1)->m_type == EMPTY) && checkBounds(x, y+1) && !getOldCell(x, y+1)->m_visited;
bool d_left = (getOldCell(x-1, y+1)->m_type == EMPTY) && checkBounds(x-1, y+1) && !getOldCell(x-1, y+1)->m_visited;
bool d_right = (getOldCell(x+1, y+1)->m_type == EMPTY) && checkBounds(x+1, y+1) && !getOldCell(x+1, y+1)->m_visited ;
bool left = (getOldCell(x-1, y)->m_type == EMPTY) && checkBounds(x-1, y) && !getOldCell(x-1, y)->m_visited ;
bool right = (getOldCell(x+1, y)->m_type == EMPTY) && checkBounds(x+1, y) && !getOldCell(x+1, y)->m_visited ;
// choose random dir if both are possible
if(d_left && d_right)
{
int r = rand() % 2;
if(r) d_right = false;
else d_left = false;
}
if(left && right)
{
int r = rand() % 2;
if(r) right = false;
else left = false;
}
if(down)
{
getCell(x, y+1)->m_type = WATER; // we now update the new state
getOldCell(x, y+1)->m_visited = true; // mark as visited so it will not be checked again in update()
} else if(d_left)
{
getCell(x-1, y+1)->m_type = WATER;
getOldCell(x-1, y+1)->m_visited = true;
} else if(d_right)
{
getCell(x+1, y+1)->m_type = WATER;
getOldCell(x+1, y+1)->m_visited = true;
} else if(left)
{
getCell(x-1, y)->m_type = WATER;
getOldCell(x-1, y)->m_visited = true;
} else if(right)
{
getCell(x+1, y)->m_type = WATER;
getOldCell(x+1, y)->m_visited = true;
}
if(down || d_right || d_left || left || right) // the original cell is now empty; update the new state
{
getCell(x, y)->m_type = EMPTY;
}
}
void Simulation::copyStates(Cell* from, Cell* to)
{
for(int x = 0; x < m_width; x++)
for(int y = 0; y < m_height; y++)
{
to[x + y * m_width].m_type = from[x + y * m_width].m_type;
to[x + y * m_width].m_visited = from[x + y * m_width].m_visited;
}
}
Main.cpp
sim.update();
Uint32 c_sand = 0xedec9a00;
for(int y = 0; y < sim.m_height; y++)
for(int x = 0; x < sim.m_width; x++)
{
sim.getCell(x, y)->m_visited = false;
if(sim.getCell(x, y)->m_type == 0) screen.setPixel(x, y, 0);
if(sim.getCell(x, y)->m_type == 1) screen.setPixel(x, y, c_sand);
if(sim.getCell(x, y)->m_type == 2) screen.setPixel(x, y, 0x0000cc00);
}
screen.render();
I've attached a gif showing the problem, hopefully this might help make it a little clearer. You can see the sand being placed normally, then the water and the strange patterns it makes after being placed (notice how it moves off to the left when it's spawned, unlike the sand)
You also have to mark the destination postion as visited to stop multiple cells moving in to the same place.
I know my title isn't very specific but that's because I have no idea where the problem comes from. I'm stuck with this problem since 2 or 3 hours and in theory everything should be working, but it's not.
This piece of code:
for ( int x = -1; x <= 1; x++ ) { //Iterate through the 8 neighbour cells plus the one indicated
for ( int y = -1; y <= 1; y++ ) {
neighbour = coords(locX + x, locY + y, width); //Get the cell index in the array
if (existsInOrtho(ortho, neighbour)) { //If the index exists in the array
if (ortho[neighbour] == 0) { //Cell is dead
cnt--; //Remove one from the number of alive neighbour cells
}
} else { //Cell is not in the zone
cnt--; //Remove one from the number of alive neighbour cells
}
}
}
Iterates through all the neighbour cells to get their value in the array (1 for alive, 0 for dead). The "coords" function, shown here:
int coords(int locX, int locY, int width)
{
int res = -1;
locX = locX - 1; //Remove one from both coordinates, since an index starts at 0 (and the zone starts at (1;1) )
locY = locY - 1;
res = locX * width + locY; //Small calculation to get the index of the pixel in the array
return res;
}
Gets the index of the cell in the array. But when I run the code, it doesn't work, the number of neighbour cells is not correct (it's like a cell is not counted every time there's some alive in the neighborhood). I tried decomposing everything manually, and it works, so I don't know what ruins everything in the final code... Here is the complete code. Sorry if I made any English mistake, it's not my native language.
This code ...
for ( int x = -1; x <= 1; x++ ) { //Iterate through the 8 neighbour cells plus the one indicated
for ( int y = -1; y <= 1; y++ ) {
Actually checks 9 cells. Perhaps you forgot that it checks (x,y) = (0,0). That would include the cell itself as well as its neighbours.
A simple fix is:
for ( int x = -1; x <= 1; x++ ) { //Iterate through the 8 neighbour cells plus the one indicated
for ( int y = -1; y <= 1; y++ ) {
if (x || y) {
Also, the simulate function (from your link) makes the common mistake of updating the value of the cell in the same array before processing state changes required for the cells beside it. The easiest fix is to keep two arrays -- two complete copies of the grid (two ortho arrays, in your code). When reading from orthoA, update orthoB. And then on the next generation, flip. Read from orthoB and write to orthoA.
I'm trying out some sample code for a bigger project, and I'm having trouble getting my rectangle to bounce between two lines.
function draw() {
print(frameCount)
background(255)
var x = 150 + frameCount;
rect(x,200,15,15);
line(150,0,150,400);
line(250,0,250,400);
if (x >= 250) {
background(255)
x = 350-frameCount;
rect(x,200,15,15);
line(250,0,250,400);
line(150,0,150,400);
} if (x <= 145) {
background(255)
x = 145 + (frameCount % 100);
rect(x,200,15,15);
line(250,0,250,400);
line(150,0,150,400);
}
}
I'm getting the feeling that after the first instance, it's disregarding the original if statement, which dictates a bounce to the left. I'm really not sure what's going wrong, and any help would be appreciated.
You probably just want to store the current position and speed in a set of variables, and then move the rectangle based on those. Here's an example:
var x = 0;
var speed = 1;
function draw(){
x += speed;
if(x < 0 || x > width){
speed *= -1;
}
background(64);
line(x, 0, x, height);
}
I've written a tutorial on this available here. That's for regular Processing, but the ideas are the same in P5.js.
I'm trying to add Alpha Beta pruning into my minimax, but I can't understand where I'm going wrong.
At the moment I'm going through 5,000 iterations, where I should be going through approximately 16,000 according to a friend. When choosing the first position, it is returning -1 (a loss) whereas it should be able to definitely return a 0 at this point (a draw) as it should be able to draw from an empty board, however I can't see where I'm going wrong as I follow my code it seems to be fine
Strangely if I switch returning Alpha and Beta inside my checks (to achieve returning 0) the computer will attempt to draw but never initiate any winning moves, only blocks
My logical flow
If we are looking for alpha:
If the score > alpha, change alpha. if alpha and beta are overlapping, return alpha
If we are looking for beta:
If the score < beta, change beta. if alpha and beta are overlapping, return beta
Here is my
Recursive call
int MinimaxAB(TGameBoard* GameBoard, int iPlayer, bool _bFindAlpha, int _iAlpha, int _iBeta)
{
//How is the position like for player (their turn) on iGameBoard?
int iWinner = CheckForWin(GameBoard);
bool bFull = CheckForFullBoard(GameBoard);
//If the board is full or there is a winner on this board, return the winner
if(iWinner != NONE || bFull == true)
{
//Will return 1 or -1 depending on winner
return iWinner*iPlayer;
}
//Initial invalid move (just follows i in for loop)
int iMove = -1;
//Set the score to be instantly beaten
int iScore = INVALID_SCORE;
for(int i = 0; i < 9; ++i)
{
//Check if the move is possible
if(GameBoard->iBoard[i] == 0)
{
//Put the move in
GameBoard->iBoard[i] = iPlayer;
//Recall function
int iBestPositionSoFar = -MinimaxAB(GameBoard, Switch(iPlayer), !_bFindAlpha, _iAlpha, _iBeta);
//Replace Alpha and Beta variables if they fit the conditions - stops checking for situations that will never happen
if (_bFindAlpha == false)
{
if (iBestPositionSoFar < _iBeta)
{
//If the beta is larger, make the beta smaller
_iBeta = iBestPositionSoFar;
iMove = i;
if (_iAlpha >= _iBeta)
{
GameBoard->iBoard[i] = EMPTY;
//If alpha and beta are overlapping, exit the loop
++g_iIterations;
return _iBeta;
}
}
}
else
{
if (iBestPositionSoFar > _iAlpha)
{
//If the alpha is smaller, make the alpha bigger
_iAlpha = iBestPositionSoFar;
iMove = i;
if (_iAlpha >= _iBeta)
{
GameBoard->iBoard[i] = EMPTY;
//If alpha and beta are overlapping, exit the loop
++g_iIterations;
return _iAlpha;
}
}
}
//Remove the move you just placed
GameBoard->iBoard[i] = EMPTY;
}
}
++g_iIterations;
if (_bFindAlpha == true)
{
return _iAlpha;
}
else
{
return _iBeta;
}
}
Initial call (when computer should choose a position)
int iMove = -1; //Invalid
int iScore = INVALID_SCORE;
for(int i = 0; i < 9; ++i)
{
if(GameBoard->iBoard[i] == EMPTY)
{
GameBoard->iBoard[i] = CROSS;
int tempScore = -MinimaxAB(GameBoard, NAUGHT, true, -1000000, 1000000);
GameBoard->iBoard[i] = EMPTY;
//Choosing best value here
if (tempScore > iScore)
{
iScore = tempScore;
iMove = i;
}
}
}
//returns a score based on Minimax tree at a given node.
GameBoard->iBoard[iMove] = CROSS;
Any help regarding my logical flow that would make the computer return the correct results and make intelligent moves would be appreciated
Does your algorithm work perfectly without alpha-beta pruning? Your initial call should be given with false for _bFindAlpha as the root node behaves like an alpha node, but it doesn't look like this will make a difference:
int tempScore = -MinimaxAB(GameBoard, NAUGHT, false, -1000000, 1000000);
Thus I will recommend for you to abandon this _bFindAlpha nonsense and convert your algorithm to negamax. It behaves identically to minimax but makes your code shorter and clearer. Instead of checking whether to maximize alpha or minimize beta, you can just swap and negate when recursively invoking (this is the same reason you can return the negated value of the function right now). Here's a slightly edited version of the Wikipedia pseudocode:
function negamax(node, α, β, player)
if node is a terminal node
return color * the heuristic value of node
else
foreach child of node
val := -negamax(child, -β, -α, -player)
if val ≥ β
return val
if val > α
α := val
return α
Unless you love stepping through search trees, I think that you will find it easier to just write a clean, correct version of negamax than debug your current implementation.
I have been working on a project that will, in short, generate a 2D matrix of numbers, with "empty" spaces are represented by 0's. Each number is connected by a list of nodes. The nodes contain the number value, the number's X and Y position, and a list of all spaces adjacent to it (its "neighbors"), with the exception of spaces diagonally adjacent to the point, due to the algorithm only allowing movements of up, down, left, and right. The issue that I am having is that, as the title would suggest, I am experiencing some stack overflow issues. I will post my code below, if anyone could help, I would be most appreciative.
CoordList* Puzzle::GeneratePath(CoordList* Path, int GoalX, int GoalY)
{
int CurrX;
int CurrY;
CurrX = Path->NeighborX;
CurrY = Path->NeighborY;
if(CurrX == GoalX && CurrY == GoalY)
{
return(Path);
}
else
{
int NewX;
int NewY;
double NewDistance;
int OldX;
int OldY;
double OldDistance;
CoordList* PointNeighbors = NULL;
CoordList* BestChoice = NULL;
for(int i = 0; i < NumDirections; i++)
{
CoordList* NewNeighbor = new CoordList;
NewX = CurrX + DirectsX[i];
NewY = CurrY + DirectsY[i];
if(IsPossible(NewX, NewY))
{
NewNeighbor->NeighborX = NewX;
NewNeighbor->NeighborY = NewY;
if(PointNeighbors == NULL)
{
NewNeighbor->next = NULL;
PointNeighbors = NewNeighbor;
}
else
{
NewNeighbor->next = PointNeighbors;
PointNeighbors = NewNeighbor;
}
}
//delete NewNeighbor;
}
while(PointNeighbors != NULL)
{
if(BestChoice == NULL)
{
CoordList* AChoice = new CoordList;
AChoice->next = NULL;
NewX = PointNeighbors->NeighborX;
NewY = PointNeighbors->NeighborY;
AChoice->NeighborX = NewX;
AChoice->NeighborY = NewY;
BestChoice = AChoice;
PointNeighbors = PointNeighbors->next;
//delete AChoice;
}
else
{
NewX = PointNeighbors->NeighborX;
NewY = PointNeighbors->NeighborY;
NewDistance = DetermineDistance(NewX, NewY, GoalX, GoalY);
OldX = BestChoice->NeighborX;
OldY = BestChoice->NeighborY;
OldDistance = DetermineDistance(OldX, OldY, GoalX, GoalY);
if(NewDistance < OldDistance)
{
BestChoice->NeighborX = NewX;
BestChoice->NeighborY = NewY;
}
PointNeighbors = PointNeighbors->next;
}
}
BestChoice->next = Path;
Path = BestChoice;
return(GeneratePath(Path, GoalX, GoalY));
}
}
I was asked to provide my determine distance function. This is just a simple implementation of the traditional Point Distance formula. Provided below.
double Puzzle::DetermineDistance(int OneX, int OneY, int TwoX, int TwoY)
{
int DifX;
int DifY;
double PointSum;
DifX = (TwoX - OneX);
DifY = (TwoY - OneY);
DifX = (DifX * DifX);
DifY = (DifY * DifY);
PointSum = (DifX + DifY);
return (sqrt(PointSum));
}
The following is the IsPossible function, which determines if an X and Y value lies within the possible grid space.
bool Puzzle::IsPossible(int x, int y)
{
if(x + 1 > Size - 1 || x - 1 < 0
|| y + 1 > Size - 1 || y - 1 < 0)
{
return false;
}
return true;
}
You might have a infinite recursion loop that causes the stackoverflow, as you make new local variables every recursion, especially with your observered oscillation behaviour. I assume you dont have that problem with small matrices. Its just a shot in the dark :-)
The oscillation problem indicates that you dont check whether you have already been on one place already?
Anyways, maybe you want to reconsider using another pathfinding algorithm. I would suggest a agent based solution. I used to use the following solution to solve a maze of similar structure: I started an agent with a "PositionsList" of spots where it have been, so in the beginning only with the starting point. Then it copied itself to every reachable position not being in his own PositionList, adding the new position to that list and destroying itself then. Repeat that pattern with all new agents until the first agent reaches the goal. That way you are guaranteed to find the optimal path. But it might get pretty memory heavy for big matrices, especially when there are a lot different ways to get to the goal and a lot of possible directions per position! But there are plenty of other very good pathfinding algorithms out there. Maybe one of them suits you well :-)
Good Luck!