Related
I need to generate such a field:
Photo
But I don't know how to do it. What happened to me:
My result
My code:
[ContextMenu("Generate grid")]
public void GenerateGrid()
{
for(int x = 0; x < _gridSize.x; x++)
{
for (int z = 0; z < _gridSize.z; z++)
{
var meshSize = _cell.GetComponent<MeshRenderer>().bounds.size;
var position = new Vector3(x * (meshSize.x + _offset), 0, z * (meshSize.z + _offset));
var cell = Instantiate(_cell, position, Quaternion.Euler(_rotationOffset), _parent.transform);
cell.GridActions = GridActions;
cell.Position = new Vector2(x, z);
cell.name = $"Cell: x:{x}, z:{z}";
GridActions.AllCell.Add(cell);
}
}
}
Simply for every odd z value, move the cell up/down by half a cell size, and move them inward toward the previous cell half a cell size. I didnt test it, but here is the code that might do that, not sure tho, again I didnt test this.
[ContextMenu("Generate grid")]
public void GenerateGrid()
{
for(int x = 0; x < _gridSize.x; x++)
{
for (int z = 0; z < _gridSize.z; z++)
{
int xResize = 0;
int zResize = 0;
if (z % 2 == 1) {
xResize = meshSize.x / 2;
zResize = meshSize.z / 2;
}
var meshSize = _cell.GetComponent<MeshRenderer>().bounds.size;
var position = new Vector3(x * (meshSize.x + _offset - xResize), 0, z * (meshSize.z + _offset - zResize));
var cell = Instantiate(_cell, position, Quaternion.Euler(_rotationOffset), _parent.transform);
cell.GridActions = GridActions;
cell.Position = new Vector2(x, z);
cell.name = $"Cell: x:{x}, z:{z}";
GridActions.AllCell.Add(cell);
}
}
}
So I put together a procedural generated map, and when I click it, the map randomly changes. What it does is it loops through the plane and randomly generates a mesh depending on the square's placement compared to randomfillpercent. If the map coordinate is marked 1, it's a wall, and if it's 0, its open space. I'm having an issue where if I click the map, the player sphere ends up inside the randomly generated wall. I want to make it so if the player's position is equal to a map coordinate that's a wall, then move it down the map until it reaches open space. Unfortunately, I keep getting null reference errors. I anyone could give me some ideas, I would appreciate it. Here's my variables and my RandomFillMap function. I'm not showing the whole code. If there's something you need to see, let me know. Thank you.
public class MapGeneratorCave : MonoBehaviour {
public int width;
public int height;
public string seed;
public bool useRandomSeed;
public GameObject player;
int[,] playerPosition;
[Range(0, 100)]
public int randomFillPercent;
int[,] map;
void Start()
{
GenerateMap();
}
void Update()
{
if (Input.GetMouseButtonDown(0))
{
GenerateMap();
}
}
void GenerateMap()
{
map = new int[width, height];
RandomFillMap();
for (int i = 0; i < 5; i++)
{
SmoothMap();
}
ProcessMap();
int borderSize = 1;
int[,] borderedMap = new int[width + borderSize * 2, height + borderSize * 2];
for (int x = 0; x < borderedMap.GetLength(0); x++)
{
for (int y = 0; y < borderedMap.GetLength(1); y++)
{
if (x >= borderSize && x < width + borderSize && y >= borderSize && y < height + borderSize)
{
borderedMap[x, y] = map[x - borderSize, y - borderSize];
}
else
{
borderedMap[x, y] = 1;
}
}
}
MeshGenerator meshGen = GetComponent<MeshGenerator>();
meshGen.GenerateMesh(borderedMap, 1);
}
void RandomFillMap()
{
int playerX = (int)player.transform.position.x;
int playerY = (int)player.transform.position.y;
if (useRandomSeed)
{
seed = Time.time.ToString();
}
System.Random pseudoRandom = new System.Random(seed.GetHashCode());
for (int x = 0; x < width; x++)
{
for (int y = 0; y < height; y++)
{
if (x == 0 || x == width - 1 || y == 0 || y == height - 1)
{
map[x, y] = 1;
}
else
{
map[x, y] = (pseudoRandom.Next(0, 100) < randomFillPercent) ? 1 : 0;
}
if (playerPosition[playerX, playerY] == map[x, y] && map[x, y] == 1)
{
playerPosition[playerX, playerY] = map[x, y - 1];
}
}
}
}
You're probably getting null references because playerPosition[playerX, playerY] doesn't exist.
What you should be using instead of a multi dimensional array (int[,]) is a Vector2
Then you would do something like this:
for (int x = 0; x < width; x++)
{
for (int y = 0; y < height; y++)
{
if (x == 0 || x == width - 1 || y == 0 || y == height - 1)
{
map[x, y] = 1;
}
else
{
map[x, y] = (pseudoRandom.Next(0, 100) < randomFillPercent) ? 1 : 0;
}
}
}
while(map[playerPosition.x, playerPosition.y] == 1){
playerPosition.y --;
// make sure you aren't out of bounds and such
}
In my program, I want to have triangles that spin and follow your mouse position. I had it working but it was ugly because I didn't use any classes (I'm new) and just pasted the triangle over and changed the variables. This is the class I came up with.
class Enemy {
float x = random(-width, 0);
float y = random(0, height);
float x1;
float x2 = -20;
float x3 = 20;
float y1 = (+(sqrt(3)/3)*40);
float y2 = (-(sqrt(3)/3)*40);
float y3 = (-(sqrt(3)/3)*40);
float speed;
float slope;
float atanSlope;
Enemy(float tempSpeed) {
speed = tempSpeed;
}
void rotateEnemy() {
float x1Rotated = rotateX(x1, y1, theta2, 0);
y1 = rotateY(x1, y1, theta2, 0);
x1 = x1Rotated;
float x2Rotated = rotateX(x2, x2, theta2, 0);
x2 = rotateY(x2, x2, theta2, 0);
x2 = x2Rotated;
float x3Rotated = rotateX(x3, x3, theta2, 0);
x3 = rotateY(x3, x3, theta2, 0);
x3 = x3Rotated;
}
void move() {
slope = (y - mouseY)/(x-mouseX);
atanSlope = atan(slope);
if (slope < 0 && mouseY < y ) {
x += cos(atanSlope)*(speed + speedChange);
y += sin(atanSlope)*(speed + speedChange);
} else if (slope >= 0 && mouseY < y) {
x -= cos(atanSlope)*(speed + speedChange);
y -= sin(atanSlope)*(speed + speedChange);
} else if (slope > 0) {
x += cos(atanSlope)*(speed + speedChange);
y += sin(atanSlope)*(speed + speedChange);
} else {
x -= cos(atanSlope)*(speed + speedChange);
y -= sin(atanSlope)*(speed + speedChange);
}
}
void drawEnemy() {
translate(x, y);
triangle(x1, y1, x2, x2, x3, x3);
translate(-x, -y);
}
void collisionDetect() {
if (abs(mouseX-x) + abs(mouseY-y) < 80)
if (isDeadly) {
respawn();
energy -= height/16;
points += 500;
} else
energy = 0;
}
void respawn() {
int ranQuadrant1 = (int)random(0, 2);
int ranSide1 = (int)random(0, 2);
if (ranQuadrant1 == 0)
if (ranSide1 == 0)
x = random(0, -width/2);
else {
x = random(width, 3*width/2);
y = random(-height/2, 3*height/2);
} else
if (ranSide1 == 0)
y = random(0, -height/2);
else {
y = random(height, 3*height/2);
x = random(-width/2, 3*width/2);
}
}
}
And I use it like this
ArrayList<Enemy> enemies = new ArrayList<Enemy>();
void setup() {
for (i = 0; i<difficulty; i++);
enemies.add(new Enemy(i*5));
for (i = 0; i<enemies.size()-1; i++)
enemies.get(i).respawn();
}
void draw() {
for(i = enemies.size()-1; i>=0; i--) {
enemies.get(i).rotateEnemy();
enemies.get(i).move();
enemies.get(i).drawEnemy();
enemies.get(i).collisionDetect();
}
When I run it, the triangles don't draw. Not only that, some ellipses I wrote that come right after trying to draw the triangles don't draw either. The square that follows your mouse along with a timer and other things DO draw though. Please help. Thank you!
Now, this isn't the whole program. I'm making a game for a project and these triangles are the enemies.
If you want to see the whole program for context/if I didn't put enough, I put it in a pastebin: https://pastebin.com/Bfd4Fk6t
Okay I figured it out, turns out I'm a dummy.
Look at the rotateEnemy function for the 2nd and 3rd points. There are no y's only x's. I was using a lot of find and replace when copying it over so I must have gotten rid of the y's and replaced them with x's. Another error is in drawEnemy, I draw the triangle with parameters (x1,y1,x2,x2,x3,x3). No y's again. Geez I'm a smart guy lol.
I found a completely different answer to this question, the whole original question makes no sense anymore. However, the answer way be useful, so I modify it a bit...
I want to sum up three double numbers, say a, b, and c, in the most numerically stable way possible.
I think using a Kahan Sum would be the way to go.
However, a strange thought occured to me: Would it make sense to:
First sum up a, b, and c and remember the (absolute value of the) compensation.
Then sum up a, c, b
If the (absolute value of the) compensation of the second sum is smaller, use this sum instead.
Proceed similar with b, a, c and other permutations of the numbers.
Return the sum with the smallest associated absolute compensation.
Would I get a more "stable" Addition of three numbers this way? Or does the order of numbers in the sum have no (use-able) impact on the compensation left at the end of the Summation? With (use-able) I mean to ask whether the compensation value itself is stable enough to contain Information that I can use?
(I am using the Java programming language, although I think this does not matter here.)
Many thanks,
Thomas.
I think I found a much more reliable way to solve the "Add 3" (or "Add 4" or "Add N" numbers problem.
First of all, I implemented my idea from the original post. It resulted into quite some big code which seemed, initially, to work. However, it failed in the following case: add Double.MAX_VALUE, 1, and -Double.MAX_VALUE. The result was 0.
#njuffa's comments inspired me dig somewhat deeper and at http://code.activestate.com/recipes/393090-binary-floating-point-summation-accurate-to-full-p/, I found that in Python, this problem has been solved quite nicely. To see the full code, I downloaded the Python source (Python 3.5.1rc1 - 2015-11-23) from https://www.python.org/getit/source/, where we can find the following method (under PYTHON SOFTWARE FOUNDATION LICENSE VERSION 2):
static PyObject*
math_fsum(PyObject *self, PyObject *seq)
{
PyObject *item, *iter, *sum = NULL;
Py_ssize_t i, j, n = 0, m = NUM_PARTIALS;
double x, y, t, ps[NUM_PARTIALS], *p = ps;
double xsave, special_sum = 0.0, inf_sum = 0.0;
volatile double hi, yr, lo;
iter = PyObject_GetIter(seq);
if (iter == NULL)
return NULL;
PyFPE_START_PROTECT("fsum", Py_DECREF(iter); return NULL)
for(;;) { /* for x in iterable */
assert(0 <= n && n <= m);
assert((m == NUM_PARTIALS && p == ps) ||
(m > NUM_PARTIALS && p != NULL));
item = PyIter_Next(iter);
if (item == NULL) {
if (PyErr_Occurred())
goto _fsum_error;
break;
}
x = PyFloat_AsDouble(item);
Py_DECREF(item);
if (PyErr_Occurred())
goto _fsum_error;
xsave = x;
for (i = j = 0; j < n; j++) { /* for y in partials */
y = p[j];
if (fabs(x) < fabs(y)) {
t = x; x = y; y = t;
}
hi = x + y;
yr = hi - x;
lo = y - yr;
if (lo != 0.0)
p[i++] = lo;
x = hi;
}
n = i; /* ps[i:] = [x] */
if (x != 0.0) {
if (! Py_IS_FINITE(x)) {
/* a nonfinite x could arise either as
a result of intermediate overflow, or
as a result of a nan or inf in the
summands */
if (Py_IS_FINITE(xsave)) {
PyErr_SetString(PyExc_OverflowError,
"intermediate overflow in fsum");
goto _fsum_error;
}
if (Py_IS_INFINITY(xsave))
inf_sum += xsave;
special_sum += xsave;
/* reset partials */
n = 0;
}
else if (n >= m && _fsum_realloc(&p, n, ps, &m))
goto _fsum_error;
else
p[n++] = x;
}
}
if (special_sum != 0.0) {
if (Py_IS_NAN(inf_sum))
PyErr_SetString(PyExc_ValueError,
"-inf + inf in fsum");
else
sum = PyFloat_FromDouble(special_sum);
goto _fsum_error;
}
hi = 0.0;
if (n > 0) {
hi = p[--n];
/* sum_exact(ps, hi) from the top, stop when the sum becomes
inexact. */
while (n > 0) {
x = hi;
y = p[--n];
assert(fabs(y) < fabs(x));
hi = x + y;
yr = hi - x;
lo = y - yr;
if (lo != 0.0)
break;
}
/* Make half-even rounding work across multiple partials.
Needed so that sum([1e-16, 1, 1e16]) will round-up the last
digit to two instead of down to zero (the 1e-16 makes the 1
slightly closer to two). With a potential 1 ULP rounding
error fixed-up, math.fsum() can guarantee commutativity. */
if (n > 0 && ((lo < 0.0 && p[n-1] < 0.0) ||
(lo > 0.0 && p[n-1] > 0.0))) {
y = lo * 2.0;
x = hi + y;
yr = x - hi;
if (y == yr)
hi = x;
}
}
sum = PyFloat_FromDouble(hi);
_fsum_error:
PyFPE_END_PROTECT(hi)
Py_DECREF(iter);
if (p != ps)
PyMem_Free(p);
return sum;
}
This summation method is different from Kahan's method, it uses a variable number of compensation variables. When adding the ith number, at most i additional compensation variables (stored in the array p) get used. This means if I want to add 3 numbers, I may need 3 additional variables. For 4 numbers, I may need 4 additional variables. Since the number of used variables may increase from n to n+1 only after the nth summand is loaded, I can translate the above code to Java as follows:
/**
* Compute the exact sum of the values in the given array
* {#code summands} while destroying the contents of said array.
*
* #param summands
* the summand array – will be summed up and destroyed
* #return the accurate sum of the elements of {#code summands}
*/
private static final double __destructiveSum(final double[] summands) {
int i, j, n;
double x, y, t, xsave, hi, yr, lo;
boolean ninf, pinf;
n = 0;
lo = 0d;
ninf = pinf = false;
for (double summand : summands) {
xsave = summand;
for (i = j = 0; j < n; j++) {
y = summands[j];
if (Math.abs(summand) < Math.abs(y)) {
t = summand;
summand = y;
y = t;
}
hi = summand + y;
yr = hi - summand;
lo = y - yr;
if (lo != 0.0) {
summands[i++] = lo;
}
summand = hi;
}
n = i; /* ps[i:] = [summand] */
if (summand != 0d) {
if ((summand > Double.NEGATIVE_INFINITY)
&& (summand < Double.POSITIVE_INFINITY)) {
summands[n++] = summand;// all finite, good, continue
} else {
if (xsave <= Double.NEGATIVE_INFINITY) {
if (pinf) {
return Double.NaN;
}
ninf = true;
} else {
if (xsave >= Double.POSITIVE_INFINITY) {
if (ninf) {
return Double.NaN;
}
pinf = true;
} else {
return Double.NaN;
}
}
n = 0;
}
}
}
if (pinf) {
return Double.POSITIVE_INFINITY;
}
if (ninf) {
return Double.NEGATIVE_INFINITY;
}
hi = 0d;
if (n > 0) {
hi = summands[--n];
/*
* sum_exact(ps, hi) from the top, stop when the sum becomes inexact.
*/
while (n > 0) {
x = hi;
y = summands[--n];
hi = x + y;
yr = hi - x;
lo = y - yr;
if (lo != 0d) {
break;
}
}
/*
* Make half-even rounding work across multiple partials. Needed so
* that sum([1e-16, 1, 1e16]) will round-up the last digit to two
* instead of down to zero (the 1e-16 makes the 1 slightly closer to
* two). With a potential 1 ULP rounding error fixed-up, math.fsum()
* can guarantee commutativity.
*/
if ((n > 0) && (((lo < 0d) && (summands[n - 1] < 0d)) || //
((lo > 0d) && (summands[n - 1] > 0d)))) {
y = lo * 2d;
x = hi + y;
yr = x - hi;
if (y == yr) {
hi = x;
}
}
}
return hi;
}
This function will take the array summands and add up the elements while simultaneously using it to store the compensation variables. Since we load the summand at index i before the array element at said index may become used for compensation, this will work.
Since the array will be small if the number of variables to add is small and won't escape the scope of our method, I think there is a decent chance that it will be allocated directly on the stack by the JIT, which may make the code quite fast.
I admit that I did not fully understand why the authors of the original code handled infinities, overflows, and NaNs the way they did. Here my code deviates from the original. (I hope I did not mess it up.)
Either way, I can now sum up 3, 4, or n double numbers by doing:
public static final double add3(final double x0, final double x1,
final double x2) {
return __destructiveSum(new double[] { x0, x1, x2 });
}
public static final double add4(final double x0, final double x1,
final double x2, final double x3) {
return __destructiveSum(new double[] { x0, x1, x2, x3 });
}
If I want to sum up 3 or 4 long numbers and obtain the precise result as double, I will have to deal with the fact that doubles can only represent longs in -9007199254740992..9007199254740992L. But this can easily be done by splitting each long into two parts:
public static final long add3(final long x0, final long x1,
final long x2) {
double lx;
return __destructiveSum(new long[] {new double[] { //
lx = x0, //
(x0 - ((long) lx)), //
lx = x1, //
(x1 - ((long) lx)), //
lx = x2, //
(x2 - ((long) lx)), //
});
}
public static final long add4(final long x0, final long x1,
final long x2, final long x3) {
double lx;
return __destructiveSum(new long[] {new double[] { //
lx = x0, //
(x0 - ((long) lx)), //
lx = x1, //
(x1 - ((long) lx)), //
lx = x2, //
(x2 - ((long) lx)), //
lx = x3, //
(x3 - ((long) lx)), //
});
}
I think this should be about right. At least I can now add Double.MAX_VALUE, 1, and -Double.MAX_VALUE and get 1 as result.
I have an image of connected components(circles filled).If i want to segment them i can use watershed algorithm.I prefer writing my own function for watershed instead of using the inbuilt function in OPENCV.I have successfu How do i find the regionalmax of objects using opencv?
I wrote a function myself. My results were quite similar to MATLAB, although not exact. This function is implemented for CV_32F but it can easily be modified for other types.
I mark all the points that are not part of a minimum region by checking all the neighbors. The remaining regions are either minima, maxima or areas of inflection.
I use connected components to label each region.
I check each region for any point belonging to a maxima, if yes then I push that label into a vector.
Finally I sort the bad labels, erase all duplicates and then mark all the points in the output as not minima.
All that remains are the regions of minima.
Here is the code:
// output is a binary image
// 1: not a min region
// 0: part of a min region
// 2: not sure if min or not
// 3: uninitialized
void imregionalmin(cv::Mat& img, cv::Mat& out_img)
{
// pad the border of img with 1 and copy to img_pad
cv::Mat img_pad;
cv::copyMakeBorder(img, img_pad, 1, 1, 1, 1, IPL_BORDER_CONSTANT, 1);
// initialize binary output to 2, unknown if min
out_img = cv::Mat::ones(img.rows, img.cols, CV_8U)+2;
// initialize pointers to matrices
float* in = (float *)(img_pad.data);
uchar* out = (uchar *)(out_img.data);
// size of matrix
int in_size = img_pad.cols*img_pad.rows;
int out_size = img.cols*img.rows;
int x, y;
for (int i = 0; i < out_size; i++) {
// find x, y indexes
y = i % img.cols;
x = i / img.cols;
neighborCheck(in, out, i, x, y, img_pad.cols); // all regions are either min or max
}
cv::Mat label;
cv::connectedComponents(out_img, label);
int* lab = (int *)(label.data);
in = (float *)(img.data);
in_size = img.cols*img.rows;
std::vector<int> bad_labels;
for (int i = 0; i < out_size; i++) {
// find x, y indexes
y = i % img.cols;
x = i / img.cols;
if (lab[i] != 0) {
if (neighborCleanup(in, out, i, x, y, img.rows, img.cols) == 1) {
bad_labels.push_back(lab[i]);
}
}
}
std::sort(bad_labels.begin(), bad_labels.end());
bad_labels.erase(std::unique(bad_labels.begin(), bad_labels.end()), bad_labels.end());
for (int i = 0; i < out_size; ++i) {
if (lab[i] != 0) {
if (std::find(bad_labels.begin(), bad_labels.end(), lab[i]) != bad_labels.end()) {
out[i] = 0;
}
}
}
}
int inline neighborCleanup(float* in, uchar* out, int i, int x, int y, int x_lim, int y_lim)
{
int index;
for (int xx = x - 1; xx < x + 2; ++xx) {
for (int yy = y - 1; yy < y + 2; ++yy) {
if (((xx == x) && (yy==y)) || xx < 0 || yy < 0 || xx >= x_lim || yy >= y_lim)
continue;
index = xx*y_lim + yy;
if ((in[i] == in[index]) && (out[index] == 0))
return 1;
}
}
return 0;
}
void inline neighborCheck(float* in, uchar* out, int i, int x, int y, int x_lim)
{
int indexes[8], cur_index;
indexes[0] = x*x_lim + y;
indexes[1] = x*x_lim + y+1;
indexes[2] = x*x_lim + y+2;
indexes[3] = (x+1)*x_lim + y+2;
indexes[4] = (x + 2)*x_lim + y+2;
indexes[5] = (x + 2)*x_lim + y + 1;
indexes[6] = (x + 2)*x_lim + y;
indexes[7] = (x + 1)*x_lim + y;
cur_index = (x + 1)*x_lim + y+1;
for (int t = 0; t < 8; t++) {
if (in[indexes[t]] < in[cur_index]) {
out[i] = 0;
break;
}
}
if (out[i] == 3)
out[i] = 1;
}
The following listing is a function similar to Matlab's "imregionalmax". It looks for at most nLocMax local maxima above threshold, where the found local maxima are at least minDistBtwLocMax pixels apart. It returns the actual number of local maxima found. Notice that it uses OpenCV's minMaxLoc to find global maxima. It is "opencv-self-contained" except for the (easy to implement) function vdist, which computes the (euclidian) distance between points (r,c) and (row,col).
input is one-channel CV_32F matrix, and locations is nLocMax (rows) by 2 (columns) CV_32S matrix.
int imregionalmax(Mat input, int nLocMax, float threshold, float minDistBtwLocMax, Mat locations)
{
Mat scratch = input.clone();
int nFoundLocMax = 0;
for (int i = 0; i < nLocMax; i++) {
Point location;
double maxVal;
minMaxLoc(scratch, NULL, &maxVal, NULL, &location);
if (maxVal > threshold) {
nFoundLocMax += 1;
int row = location.y;
int col = location.x;
locations.at<int>(i,0) = row;
locations.at<int>(i,1) = col;
int r0 = (row-minDistBtwLocMax > -1 ? row-minDistBtwLocMax : 0);
int r1 = (row+minDistBtwLocMax < scratch.rows ? row+minDistBtwLocMax : scratch.rows-1);
int c0 = (col-minDistBtwLocMax > -1 ? col-minDistBtwLocMax : 0);
int c1 = (col+minDistBtwLocMax < scratch.cols ? col+minDistBtwLocMax : scratch.cols-1);
for (int r = r0; r <= r1; r++) {
for (int c = c0; c <= c1; c++) {
if (vdist(Point2DMake(r, c),Point2DMake(row, col)) <= minDistBtwLocMax) {
scratch.at<float>(r,c) = 0.0;
}
}
}
} else {
break;
}
}
return nFoundLocMax;
}
I do not know if it is what you want, but in my answer to this post, I gave some code to find local maxima (peaks) in a grayscale image (resulting from distance transform).
The approach relies on subtracting the original image from the dilated image and finding the zero pixels).
I hope it helps,
Good luck
I had the same problem some time ago, and the solution was to reimplement the imregionalmax algorithm in OpenCV/Cpp. It is not that complicated, because you can find the C++ source code of the function in the Matlab distribution. (somewhere in toolbox). All you have to do is to read carefully and understand the algorithm described there. Then rewrite it or remove the matlab-specific checks and you'll have it.