Higher precision in JavaScript - javascript

I am trying to calculate with higher precision numbers in JavaScript to be able to zoom in more on the Mandlebrot set.
(after a certain amount of zooming the results get "pixelated", because of the low precision)
I have looked at this question, so I tried using a library such as BigNumber but it was unusably slow.
I have been trying to figure this out for a while and I think the only way is to use a slow library.
Is there a faster library?
Is there any other way to calculate with higher precision numbers?
Is there any other way to be able to zoom in more on the Mandlebrot set?
Probably unneceseary to add this code, but this is the function I use to check if a point is in the Mandlebrot set.
function mandelbrot(x, y, it) {
var z = [0, 0]
var c1 = [x, y]
for (var i = 0; i < it; i++) {
z = [z[0]*z[0] - z[1]*z[1] + c1[0], 2*z[0]*z[1] + c1[1]]
if (Math.abs(z[0]) > 2, Math.abs(z[1]) > 2) {
break
}
}
return i
}

The key is not so much the raw numeric precision of JavaScript numbers (though that of course has its effects), but the way the basic Mandelbrot "escape" test works, specifically the threshold iteration counts. To compute whether a point in the complex plane is in or out of the set, you iterate on the formula (which I don't exactly remember and don't feel like looking up) for the point over and over again until the point obviously diverges (the formula "escapes" from the origin of the complex plane by a lot) or doesn't before the iteration threshold is reached.
The iteration threshold when rendering a view of the set that covers most of it around the origin of the complex plane (about 2 units in all directions from the origin) can be as low as 500 to get a pretty good rendering of the whole set at a reasonable magnification on a modern computer. As you zoom in, however, the iteration threshold needs to increase in inverse proportion to the size of the "window" onto the complex plane. If it doesn't, then the "escape" test doesn't work with sufficient accuracy to delineate fine details at higher magnifications.
The formula I used in my JavaScript implementation is
maxIterations = 400 * Math.log(1/dz0)
where dz0 is (arbitrarily) the width of the window onto the plane. As one zooms into a view of the set (well, the "edge" of the set, where things are interesting), dz0 gets pretty small so the iteration threshold gets up into the thousands.
The iteration count, of course, for points that do "escape" (that is, points that are not part of the Mandelbrot set) can be used as a sort of "distance" measurement. A point that escapes within a few iterations is clearly not "close to" the set, while a point that escapes only after 2000 iterations is much closer. That distance quality can be used in various ways in visualizations, either to provide a color value (common) or possibly a z-axis value if the set is being rendered as a 3D view (with the set as a sort of "mesa" in three dimensions and the borders being a vertical "cliff" off the sides).

Related

Multiplayer Game - Client Interpolation Calculation?

I am creating a Multiplayer game using socket io in javascript. The game works perfectly at the moment aside from the client interpolation. Right now, when I get a packet from the server, I simply set the clients position to the position sent by the server. Here is what I have tried to do:
getServerInfo(packet) {
var otherPlayer = players[packet.id]; // GET PLAYER
otherPlayer.setTarget(packet.x, packet.y); // SET TARGET TO MOVE TO
...
}
So I set the players Target position. And then in the Players Update method I simply did this:
var update = function(delta) {
if (x != target.x || y != target.y){
var direction = Math.atan2((target.y - y), (target.x - x));
x += (delta* speed) * Math.cos(direction);
y += (delta* speed) * Math.sin(direction);
var dist = Math.sqrt((x - target.x) * (x - target.x) + (y - target.y)
* (y - target.y));
if (dist < treshhold){
x = target.x;
y = target.y;
}
}
}
This basically moves the player in the direction of the target at a fixed speed. The issue is that the player arrives at the target either before or after the next information arrives from the server.
Edit: I have just read Gabriel Bambettas Article on this subject, and he mentions this:
Say you receive position data at t = 1000. You already had received data at t = 900, so you know where the player was at t = 900 and t = 1000. So, from t = 1000 and t = 1100, you show what the other player did from t = 900 to t = 1000. This way you’re always showing the user actual movement data, except you’re showing it 100 ms “late”.
This again assumed that it is exactly 100ms late. If your ping varies a lot, this will not work.
Would you be able to provide some pseudo code so I can get an Idea of how to do this?
I have found this question online here. But none of the answers provide an example of how to do it, only suggestions.
I'm completely fresh to multiplayer game client/server architecture and algorithms, however in reading this question the first thing that came to mind was implementing second-order (or higher) Kalman filters on the relevant variables for each player.
Specifically, the Kalman prediction steps which are much better than simple dead-reckoning. Also the fact that Kalman prediction and update steps work somewhat as weighted or optimal interpolators. And futhermore, the dynamics of players could be encoded directly rather than playing around with abstracted parameterizations used in other methods.
Meanwhile, a quick search led me to this:
An improvement of dead reckoning algorithm using kalman filter for minimizing network traffic of 3d on-line games
The abstract:
Online 3D games require efficient and fast user interaction support
over network, and the networking support is usually implemented using
network game engine. The network game engine should minimize the
network delay and mitigate the network traffic congestion. To minimize
the network traffic between game users, a client-based prediction
(dead reckoning algorithm) is used. Each game entity uses the
algorithm to estimates its own movement (also other entities'
movement), and when the estimation error is over threshold, the entity
sends the UPDATE (including position, velocity, etc) packet to other
entities. As the estimation accuracy is increased, each entity can
minimize the transmission of the UPDATE packet. To improve the
prediction accuracy of dead reckoning algorithm, we propose the Kalman
filter based dead reckoning approach. To show real demonstration, we
use a popular network game (BZFlag), and improve the game optimized
dead reckoning algorithm using Kalman filter. We improve the
prediction accuracy and reduce the network traffic by 12 percents.
Might seem wordy and like a whole new problem to learn what it's all about... and discrete state-space for that matter.
Briefly, I'd say a Kalman filter is a filter that takes into account uncertainty, which is what you've got here. It normally works on measurement uncertainty at a known sample rate, but it could be re-tooled to work with uncertainty in measurement period/phase.
The idea being that in lieu of a proper measurement, you'd simply update with the kalman predictions. The tactic is similar to target tracking applications.
I was recommended them on stackexchange myself - took about a week to figure out how they were relevant but I've since implemented them successfully in vision processing work.
(...it's making me want to experiment with your problem now !)
As I wanted more direct control over the filter, I copied someone else's roll-your-own implementation of a Kalman filter in matlab into openCV (in C++):
void Marker::kalmanPredict(){
//Prediction for state vector
Xx = A * Xx;
Xy = A * Xy;
//and covariance
Px = A * Px * A.t() + Q;
Py = A * Py * A.t() + Q;
}
void Marker::kalmanUpdate(Point2d& measuredPosition){
//Kalman gain K:
Mat tempINVx = Mat(2, 2, CV_64F);
Mat tempINVy = Mat(2, 2, CV_64F);
tempINVx = C*Px*C.t() + R;
tempINVy = C*Py*C.t() + R;
Kx = Px*C.t() * tempINVx.inv(DECOMP_CHOLESKY);
Ky = Py*C.t() * tempINVy.inv(DECOMP_CHOLESKY);
//Estimate of velocity
//units are pixels.s^-1
Point2d measuredVelocity = Point2d(measuredPosition.x - Xx.at<double>(0), measuredPosition.y - Xy.at<double>(0));
Mat zx = (Mat_<double>(2,1) << measuredPosition.x, measuredVelocity.x);
Mat zy = (Mat_<double>(2,1) << measuredPosition.y, measuredVelocity.y);
//kalman correction based on position measurement and velocity estimate:
Xx = Xx + Kx*(zx - C*Xx);
Xy = Xy + Ky*(zy - C*Xy);
//and covariance again
Px = Px - Kx*C*Px;
Py = Py - Ky*C*Py;
}
I don't expect you to be able to use this directly though, but if anyone comes across it and understand what 'A', 'P', 'Q' and 'C' are in state-space (hint hint, state-space understanding is a pre-req here) they'll likely see how connect the dots.
(both matlab and openCV have their own Kalman filter implementations included by the way...)
This question is being left open with a request for more detail, so I’ll try to fill in the gaps of Patrick Klug’s answer. He suggested, reasonably, that you transmit both the current position and the current velocity at each time point.
Since two position and two velocity measurements give a system of four equations, it enables us to solve for a system of four unknowns, namely a cubic spline (which has four coefficients, a, b, c and d). In order for this spline to be smooth, the first and second derivatives (velocity and acceleration) should be equal at the endpoints. There are two standard, equivalent ways of calculating this: Hermite splines (https://en.wikipedia.org/wiki/Cubic_Hermite_spline) and Bézier splines (http://mathfaculty.fullerton.edu/mathews/n2003/BezierCurveMod.html). For a two-dimensional problem such as this, I suggested separating variables and finding splines for both x and y based on the tangent data in the updates, which is called a clamped piecewise cubic Hermite spline. This has several advantages over the splines in the link above, such as cardinal splines, which do not take advantage of that information. The locations and velocities at the control points will match, you can interpolate up to the last update rather than the one before, and you can apply this method just as easily to polar coordinates if the game world is inherently polar like Space wars. (Another approach sometimes used for periodic data is to perform a FFT and do trigonometric interpolation in the frequency domain, but that doesn’t sound applicable here.)
What originally appeared here was a derivation of the Hermite spline using linear algebra in a somewhat unusual way that (unless I made a mistake entering it) would have worked. However, the comments convinced me it would be more helpful to give the standard names for what I was talking about. If you are interested in the mathematical details of how and why this works, this is a better explanation: https://math.stackexchange.com/questions/62360/natural-cubic-splines-vs-piecewise-hermite-splines
A better algorithm than the one I gave is to represent the sample points and first derivatives as a tridiagonal matrix that, multiplied by a column vector of coefficients, produces the boundary conditions, and solve for the coefficients. An alternative is to add control points to a Bézier curve where the tangent lines at the sampled points intersect and on the tangent lines at the endpoints. Both methods produce the same, unique, smooth cubic spline.
One situation you might be able to avoid if you were choosing the points rather than receiving updates is if you get a bad sample of points. You can’t, for example, intersect parallel tangent lines, or tell what happened if it’s back in the same place with a nonzero first derivative. You’d never choose those points for a piecewise spline, but you might get them if an object made a swerve between updates.
If my computer weren’t broken right now, here is where I would put fancy graphics like the ones I posted to TeX.SX. Unfortunately, I have to bow out of those for now.
Is this better than straight linear interpolation? Definitely: linear interpolation will get you straight- line paths, quadratic splines won't be smooth, and higher-order polynomials will likely be overfitted. Cubic splines are the standard way to solve that problem.
Are they better for extrapolation, where you try to predict where a game object will go? Possibly not: this way, you’re assuming that a player who’s accelerating will keep accelerating, rather than that they will immediately stop accelerating, and that could put you much further off. However, the time between updates should be short, so you shouldn’t get too far off.
Finally, you might make things a lot easier on yourself by programming in a bit more conservation of momentum. If there’s a limit to how quickly objects can turn, accelerate or decelerate, their paths will not be able to diverge as much from where you predict based on their last positions and velocities.
Depending on your game you might want to prefer smooth player movement over super-precise location. If so, then I'd suggest to aim for 'eventual consistency'. I think your idea of keeping 'real' and 'simulated' data-points is a good one. Just make sure that from time to time you force the simulated to converge with the real, otherwise the gap will get too big.
Regarding your concern about different movement speed I'd suggest you include the current velocity and direction of the player in addition to the current position in your packet. This will enable you to more smoothly predict where the player would be based on your own framerate/update timing.
Essentially you would calculate the current simulated velocity and direction taking into account the last simulated location and velocity as well as last known location and velocity (put more emphasis on the second) and then simulate new position based on that.
If the gap between simulated and known gets too big, just put more emphasis on the known location and the otherPlayer will catch up quicker.

Calculate Angle between two 3D Vectors

Note: I have absolutely no clue about Vector math, especially not in 3D.
I am currently working on some Javascript code that determines if a Finger that got captured by a Leap Motion Controller is extended (i.e. completely straight) or not.
Leap Motion provides us with an API that gives us Object for Hands, Fingers and Bones. Bones in particular have several properties, such as position Vectors, direction Vectors and so on, see here for the Documentation.
My idea was to take the Distal Phalang (tip of your finger) and Proximal Phalang (first bone of your finger), calculate the angle between them by getting the dot product of the two direction Vectors of the bones and then decide if it is straight or not. Like this, essentially:
var a = hand.indexFinger.distal.direction();
var b = hand.indexFinger.proximal.direction();
var dot = Leap.vec3.dot(a,b);
var degree = Math.acos(dot)*180/Math.PI;
The issue here is that these values are not reliable, especially if other fingers move about. It seems like the direction Vectors of the bones change when other fingers change direction (???).
For example, when all my Fingers are extended, the value of degree is roughly 0 and fluctuates between -5 and 5. When I make a fist, the value shoots up to 10, 15, 20. Logging the values of the direction Vectors reveals that they indeed do get changed, but how does this make sense? The Finger doesn't move, so its direction should stay the same.
Even worse for the thumb, the values don't add up there at all. An extended thumb can get values similar to the IndexFinger, but rotation the thumb upwards or downwards has changes in the range of 60 degrees!
I've tried using positional values instead, which gives me NaN results because the values seem to be to big.
So, my question is: how could I reliably calculate the angle between two Vectors? What am I missing here?
The correct formula is
cos(angle) = dot(a,b)/(norm(a)*norm(b))
where norm is the euclidean norm or length.
You should have gotten a wrong result, but the lengths of a and b should be constant, so the result should have been consistently wrong…
dot product is the cosine of the angle between vectors if those vectors are normalized. So be sure that a and b are normalized prior to calculate the dot product

JS Canvas get pixel value very frequently

I am creating a video game based on Node.js/WebGL/Canvas/PIXI.js.
In this game, blocks have a generic size: they can be circles, polygons, or everything. So, my physical engine needs to know where exactly the things are, what pixels are walls and what pixels are not. Since I think PIXI don't allow this, I create an invisible canvas where I put all the wall's images of the map. Then, I use the function getImageData to create a function "isWall" at (x, y):
function isWall(x, y):
return canvas.getImageData(x, y, 1, 1).data[3] != 0;
However, this is very slow (it takes up to 70% of the CPU time of the game, according to Chrome profiling). Also, since I introduced this function, I sometimes got the error "Oops, WebGL crashed" without any additional advice.
Is there a better method to access the value of the pixel? I thought about storing everything in a static bit array (walls have a fixed size), with 1 corresponding to a wall and 0 to a non-wall. Is it reasonable to have a 10-million-cells array in memory?
Some thoughts:
For first check: Use collision regions for all of your objects. The regions can even be defined for each side depending on shape (ie. complex shapes). Only check for collisions inside intersecting regions.
Use half resolution for hit-test bitmaps (or even 25% if your scenario allow). Our brains are not capable of detecting pixel-accurate collisions when things are moving so this can be taken advantage of.
For complex shapes, pre-store the whole bitmap for it (based on its region(s)) but transform it to a single value typed array like Uint8Array with high and low values (re-use this instead of getting one and one pixels via the context). Subtract object's position and use the result as a delta for your shape region, then hit-testing the "bitmap". If the shape rotates, transform incoming check points accordingly (there is probably a sweet-spot here where updating bitmap becomes faster than transforming a bunch of points etc. You need to test for your scenario).
For close-to-square shaped objects do a compromise and use a simple rectangle check
For circles and ellipses use un-squared values to check distances for radius.
In some cases you can perhaps use collision predictions which you calculate before the games starts and when knowing all objects positions, directions and velocities (calculate the complete motion path, find intersections for those paths, calculate time/distance to those intersections). If your objects change direction etc. due to other events during their path, this will of course not work so well (or try and see if re-calculating is beneficial or not).
I'm sure why you would need 10m stored in memory, it's doable though - but you will need to use something like a quad-tree and split the array up, so it becomes efficient to look up a pixel state. IMO you will only need to store "bits" for the complex shapes, and you can limit it further by defining multiple regions per shape. For simpler shapes just use vectors (rectangles, radius/distance). Do performance tests often to find the right balance.
In any case - these sort of things has to be hand-optimized for the very scenario, so this is just a general take on it. Other factors will affect the approach such as high velocities, rotation, reflection etc. and it will quickly become very broad. Hope this gives some input though.
I use bit arrays to store 0 || 1 info and it works very well.
The information is stored compactly and gets/sets are very fast.
Here is the bit library I use:
https://github.com/drslump/Bits-js/blob/master/lib/Bits.js
I've not tried with 10m bits so you'll have to try it on your own dataset.
The solution you propose is very "flat", meaning each pixel must have a corresponding bit. This results in a large amount of memory being required--even if information is stored as bits.
An alternative testing data ranges instead of testing each pixel:
If the number of wall pixels is small versus the total number of pixels you might try storing each wall as a series of "runs". For example, a wall run might be stored in an object like this (warning: untested code!):
// an object containing all horizontal wall runs
var xRuns={}
// an object containing all vertical wall runs
var yRuns={}
// define a wall that runs on y=50 from x=100 to x=185
// and then runs on x=185 from y=50 to y=225
var y=50;
var x=185;
if(!xRuns[y]){ xRuns[y]=[]; }
xRuns[y].push({start:100,end:185});
if(!yRuns[x]){ yRuns[x]=[]; }
yRuns[x].push({start:50,end:225});
Then you can quickly test an [x,y] against the wall runs like this (warning untested code!):
function isWall(x,y){
if(xRuns[y]){
var a=xRuns[y];
var i=a.length;
do while(i--){
var run=a[i];
if(x>=run.start && x<=run.end){return(true);}
}
}
if(yRuns[x]){
var a=yRuns[x];
var i=a.length;
do while(i--){
var run=a[i];
if(y>=run.start && y<=run.end){return(true);}
}
}
return(false);
}
This should require very few tests because the x & y exactly specify which array of xRuns and yRuns need to be tested.
It may (or may not) be faster than testing the "flat" model because there is overhead getting to the specified element of the flat model. You'd have to perf test using both methods.
The wall-run method would likely require much less memory.
Hope this helps...Keep in mind the wall-run alternative is just off the top of my head and probably requires tweaking ;-)

What is the math behind this ray-like animation?

I have unobfuscated and simplified this animation into a jsfiddle available here. Nevertheless, I still don't quite understand the math behind it.
Does someone have any insight explaining the animation?
Your fiddle link wasn't working for me due to a missing interval speed, should be using getElementById too (just because it works in Internet Explorer doesn't make it cross-browser).
Here, I forked it, use this one instead:
http://jsfiddle.net/spechackers/hJhCz/
I have also cleaned up the code in your first link:
<pre id="p">
<script type="text/javascript">
var charMap=['p','.'];
var n=0;
function myInterval()
{
n+=7;//this is the amount of screen to "scroll" per interval
var outString="";
//this loop will execute exactly 4096 times. Once for each character we will be working with.
//Our display screen will consist of 32 lines or rows and 128 characters on each line
for(var i=64; i>0; i-=1/64)
{
//Note mod operations can result in numbers like 1.984375 if working with non-integer numbers like we currently are
var mod2=i%2;
if(mod2==0)
{
outString+="\n";
}else{
var tmp=(mod2*(64/i))-(64/i);//a number between 0.9846153846153847 and -4032
tmp=tmp+(n/64);//still working with floating points.
tmp=tmp^(64/i);//this is a bitwise XOR operation. The result will always be an integer
tmp=tmp&1;//this is a bitwise AND operation. Basically we just want to know if the first bit is a 1 or 0.
outString+=charMap[tmp];
}
}//for
document.getElementById("p").innerHTML=outString;
}
myInterval();
setInterval(myInterval,64);
</script>
</pre>
The result of the code in the two links you provided are very different from one another.
However the logic in the code is quite similar. Both use a for-loop to loop through all the characters, a mod operation on a non-integer number, and a bitwise xor operation.
How does it all work, well basically all I can tell you is to pay attention to the variables changing as the input and output change.
All the logic appears to be some sort of bitwise cryptic way to decide which of 2 characters or a line break to add to the page.
I don't quite follow it myself from a calculus or trigonometry sort of perspective.
Consider that each line, as it sweeps across the rectangular area, is actually a rotation of (4?) lines about a fixed origin.
The background appears to "move" according to optical illusion. What actually happens is that the area in between the sweep lines is toggling between two char's as the lines rotate through them.
Here is the rotation eq in 2 dimensions:
first, visualize an (x,y) coordinate pair in one of the lines, before and after rotation (motion):
So, you could make a collection of points for each line and rotate them through arbitrarily sized angles, depending upon how "smooth" you want the animation.
The answer above me looks at the whole plane being transformed with the given formulae.
I tried to simplify it here -
The formula above is a trigonometric equation for rotation it is more simply solved
with a matrix.
x1 is the x coordinate before the the rotation transformation (or operator) acts.
same for y1. say the x1 = 0 and y1 = 1. these are the x,y coordinates of of the end of the
vector in the xy plane - currently your screen. if you plug any angle you will get new
coordinates with the 'tail' of the vector fixes in the same position.
If you do it many times (number of times depends on the angle you choose) you will come back to 0 x = 0 and y =1.
as for the bitwise operation - I don't have any insight as for why exactly this was used.
each iteration there the bitwise operation acts to decide if the point the plane will be drawn or not. note k how the power of k changes the result.
Further reading -
http://en.wikipedia.org/wiki/Linear_algebra#Linear_transformations
http://www.youtube.com/user/khanacademy/videos?query=linear+algebra

Click detection in a 2D isometric grid?

I've been doing web development for years now and I'm slowly getting myself involved with game development and for my current project I've got this isometric map, where I need to use an algorithm to detect which field is being clicked on. This is all in the browser with Javascript by the way.
The map
It looks like this and I've added some numbers to show you the structure of the fields (tiles) and their IDs. All the fields have a center point (array of x,y) which the four corners are based on when drawn.
As you can see it's not a diamond shape, but a zig-zag map and there's no angle (top-down view) which is why I can't find an answer myself considering that all articles and calculations are usually based on a diamond shape with an angle.
The numbers
It's a dynamic map and all sizes and numbers can be changed to generate a new map.
I know it isn't a lot of data, but the map is generated based on the map and field sizes.
- Map Size: x:800 y:400
- Field Size: 80x80 (between corners)
- Center position of all the fields (x,y)
The goal
To come up with an algorithm which tells the client (game) which field the mouse is located in at any given event (click, movement etc).
Disclaimer
I do want to mention that I've already come up with a working solution myself, however I'm 100% certain it could be written in a better way (my solution involves a lot of nested if-statements and loops), and that's why I'm asking here.
Here's an example of my solution where I basically find a square with corners in the nearest 4 known positions and then I get my result based on the smallest square between the 2 nearest fields. Does that make any sense?
Ask if I missed something.
Here's what I came up with,
function posInGrid(x, y, length) {
xFromColCenter = x % length - length / 2;
yFromRowCenter = y % length - length / 2;
col = (x - xFromColCenter) / length;
row = (y - yFromRowCenter) / length;
if (yFromRowCenter < xFromColCenter) {
if (yFromRowCenter < (-xFromColCenter))--row;
else++col;
} else if (yFromRowCenter > xFromColCenter) {
if (yFromRowCenter < (-xFromColCenter))--col;
else++row;
}
return "Col:"+col+", Row:"+row+", xFC:"+xFromColCenter+", yFC:"+yFromRowCenter;
}
X and Y are the coords in the image, and length is the spacing of the grid.
Right now it returns a string, just for testing.. result should be row and col, and those are the coordinates I chose: your tile 1 has coords (1,0) tile 2 is(3,0), tile 10 is (0,1), tile 11 is (2,1). You could convert my coordinates to your numbered tiles in a line or two.
And a JSFiddle for testing http://jsfiddle.net/NHV3y/
Cheers.
EDIT: changed the return statement, had some variables I used for debugging left in.
A pixel perfect way of hit detection I've used in the past (in OpenGL, but the concept stands here too) is an off screen rendering of the scene where the different objects are identified with different colors.
This approach requires double the memory and double the rendering but the hit detection of arbitrarily complex scenes is done with a simple color lookup.
Since you want to detect a cell in a grid there are probably more efficient solutions but I wanted to mention this one for it's simplicity and flexibility.
This has been solved before, let me consult my notes...
Here's a couple of good resources:
From Laserbrain Studios, The basics of isometric programming
Useful article in the thread posted here, in Java
Let me know if this helps, and good luck with your game!
This code calculates the position in the grid given the uneven spacing. Should be pretty fast; almost all operations are done mathematically, using just one loop. I'll ponder the other part of the problem later.
def cspot(x,y,length):
l=length
lp=length+1
vlist = [ (l*(k%2))+(lp*((k+1)%2)) for k in range(1,y+1) ]
vlist.append(1)
return x + sum(vlist)

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