I have a painting app which at any given time interactively shows content from an array of 200 or so CALayers via an UIImageView. I get reasonable performance, but I'm wondering if there could be any performance benefits with using CAMetalLayers instead. In particular, I'm curious if I could benefit from blitting textures directly to each CAMetalLayer, and would there be any hardware considerations with stacking/displaying so many CAMetalLayers at once.
Are there any gotchas I should consider before implementing, and should I continue using an UIImageView (or other) to host these newly Metal-backed sublayers? Any thoughts would be appreciated.
That’s not going to work. You should be keeping track of your stroke’s data. For example an array of points would be a single stroke and then you should have an array of those strokes. It could be only points (x, y) or more probably also containing color, size and other variables. You should know what do you need to describe your stroke.
Then use that to draw (stamp at those locations). When you want to undo, just start drawing from the beginning all the strokes in the array until n-1, n-2, etc...
Related
I am trying to create multiple SKSpriteNodes that each have their own independent variables that I can change/modify. I would like to be able to run a function when the app starts, for example "createSprites(5)" which would create 5 sprites with the image/texture "shape.png" at random x and y coordinates and add all 5 Sprites to an array that I can access and edit different Sprite's positioning based on the index value. I would then like to be able to have another function "addSprite()" which, each time it is called, create a new Sprite with the same "shape.png" texture, place it at another random X and Y coordinate and also add it to the array of all Sprites to, again, be able to access later and change coordinates etc.
I have been looking through so many other Stack Overflow pages and can not seem to find a solution. My ideal solution would simply be the two functions I stated earlier. One to create an "n" number of Sprites and another function to create and add one more sprite to the array each time it is called.
Hope that makes sense, I'm fairly new to Swift and all this Sprite stuff, so simple informative answers would be very much appreciated.
You're not going to find an ideal solution from the past because nobody has likely had exactly the same desire with both Swift and SpriteKit. Having said that, there's likely partial answers you can blend together, and get the result you want or, at least, an understanding of how to do it.
Sprite Positioning in SK is probably the first thing to read up on:
https://developer.apple.com/library/content/documentation/GraphicsAnimation/Conceptual/SpriteKit_PG/Sprites/Sprites.html
having gotten that figured out, you can move to random positions.
Random positioning of Sprites:
Duplicate Sprite in Random Positions with SpriteKit
Sprite Kit random positions
Both use earlier versions of randomisation that aren't as powerful as what's available now, in GameplayKit. So... Generating random numbers in Swift with GameplayKit:
https://www.hackingwithswift.com/read/35/overview
It's hard to overstate the importance of understanding the various possibilities of game design implications of varying types of randomisation, so probably wise to read this, from Apple:
https://developer.apple.com/library/content/documentation/General/Conceptual/GameplayKit_Guide/RandomSources.html
After that, it's a case of needing to determine what constitutes a time or event at which to create more sprites at more random positions, and how fussy you want to be about proximity to other sprites, and overlaps.
I am using GL_LINE_LOOP to draw a circle in C and openGL! Is it possible for me to fill the circle with colors?
If needed, this is the code I'm using:
const int circle_points=100;
const float cx=50+i, cy=50+x, r=50;
const float pi = 3.14159f;
int i = 50;
glColor3f(1, 1, 1);
glBegin(GL_LINE_LOOP);
for(i=0;i<circle_points;i++)
{
const float theta=(2*pi*i)/circle_points;
glVertex2f(cx+r*cos(theta),cy+r*sin(theta));
}
glEnd();
Lookup polygon triangulation!
I hope something here is somehow useful to someone, even though this question was asked in February. There are many answers, even though a lot of people would give none. I could witter forever, but I'll try to finish before then.
Some would even say, "You never would," or, "That's not appropriate for OpenGL," I'd like to say more than them about why. Converting polygons into the triangles that OpenGL likes so much is outside of OpenGL's job-spec, and is probably better done on the processor side anyway. Calculate that stage in advance, as few times as possible, rather than repeatedly sending such a chunky problem on every draw call.
Perhaps the original questioner drifted away from OpenGL since February, or perhaps they've become an expert. Perhaps I'll re-inspire them to look at it again, to hack away at some original 'imposters'. Or maybe they'll say it's not the tool for them after all, but that would be disappointing. Whatever graphics code you're writing, you know that OpenGL can speed it up!
Triangles for convex polygons are easy
Do you just want a circle? Make a triangle fan with the shared point at the circle's origin. GL_POLYGON was, for better or worse, deprecated then killed off entirely; it will not work with current or future implementations of OpenGL.
Triangles for concave polygons are hard
You'll want more general polygons later? Well, there are some tricks you could play with, for all manner of convex polygons, but concave ones will soon get difficult. It would be easy to start five different solutions without finishing a single one. Then it would be difficult, on finishing one, to make it quick, and nearly impossible to be sure that it's the quickest.
To achieve it in a future-proofed way you really want to stick with triangles -- so "polygon triangulation" is the subject you want to search for. OpenGL will always be great for drawing triangles. Triangle strips are popular because they reuse many vertices, and a whole mesh can be covered with only triangle strips, (perhaps including the odd lone triangle or pair of triangles). Drawing with only one primitive usually means the entire mesh can be rendered with a single draw call, which could improve performance. (Number of draw calls is one performance consideration, but not always the most important.)
Polygon triangulation gets more complex when you allow convex polygons or polygons with holes. (Finding algorithms for triangulating a general polygon, robustly yet quickly, is actually an area of ongoing research. Nonetheless, you can find some pretty good solutions out there that are probably fit for purpose.)
But is this what you want?
Is a filled polygon crucial to your final goals in OpenGL? Or did you simply choose what felt like it would be a simple early lesson?
Frustratingly, although drawing a filled polygon seems like a simple thing to do -- and indeed is one of the simplest things to do in many languages -- the solution in OpenGL is likely to be quite complicated. Of course, it can be done if we're clever enough -- but that could be a lot of effort, without being the best route to take towards your later goals.
Even in languages that implement filled polygons in a way that is simple to program with, you don't always know how much strain it puts on the CPU or GPU. If you send a sequence of vertices, to be linked and filled, once every animation frame, will it be slow? If a polygon doesn't change shape, perhaps you should do the difficult part of the calculation just once? You will be doing just that, if you triangulate a polygon once using the CPU, then repeatedly send those triangles to OpenGL for rendering.
OpenGL is very, very good at doing certain things, very quickly, taking advantage of hardware acceleration. It is worth appreciating what it is and is not optimal for, to decide your best route towards your final goals with OpenGL.
If you're looking for a simple early lesson, rotating brightly coloured tetrahedrons is ideal, and happens early in most tutorials.
If on the other hand, you're planning a project that you currently envision using filled polygons a great deal -- say, a stylized cartoon rendering engine for instance -- I still advise going to the tutorials, and even more so! Find a good one; stick with it to the end; you can then think better about OpenGL functions that are and aren't available to you. What can you take advantage of? What do you need or want to redo in software? And is it worth writing your own code for apparently simple things -- like drawing filled polygons -- that are 'missing from' (or at least inappropriate to) OpenGL?
Is there a higher level graphics library, free to use -- perhaps relying on OpenGL for rasterisation -- that can already do want you want? If so, how much freedom does it give you, to mess with the nuts and bolts of OpenGL itself?
OpenGL is very good at drawing points, lines, and triangles, and hardware accelerating certain common operations such as clipping, face culling, perspective divides, perspective texture accesses (very useful for lighting) and so on. It offers you a chance to write special programs called shaders, which operate at various stages of the rendering pipeline, maximising your chance to insert your own unique cleverness while still taking advantage of hardware acceleration.
A good tutorial is one that explains the rendering pipeline and puts you in a much better position to assess what the tool of OpenGL is best used for.
Here is one such tutorial that I found recently: Learning Modern 3D Graphics Programming
by Jason L. McKesson. It doesn't appear to be complete, but if you get far enough for that to annoy you, you'll be well placed to search for the rest.
Using imposters to fill polygons
Everything in computer graphics is an imposter, but the term often has a specialised meaning. Imposters display very different geometry from what they actually have -- only more so than usual! Of course, a 3D world is very different from the pixels representing it, but with imposters, the deception goes deeper than usual.
For instance, a rectangle that OpenGL actually constructs out of two triangles can appear to be a sphere if, in its fragment shader, you write a customised depth value to the depth coordinate, calculate your own normals for lighting and so on, and discard those fragments of the square that would fall outside the outline of the sphere. (Calculating the depth on those fragments would involve a square root of a negative number, which can be used to discard the fragment.) Imposters like that are sometimes called flat cards or billboards.
(The tutorial above includes a chapter on imposters, and examples doing just what I've described here. In fact, the rectangle itself is constructed only part way through the pipeline, from a single point. I warn that the scaling of their rectangle, to account for the way that perspective distorts a sphere into an ellipse in a wide FOV, is a non-robust fudge . The correct and robust answer is tricky to work out, using mathematics that would be slightly beyond the scope of the book. I'd say it is beyond the author's algebra skills to work it out but I could be wrong; he'd certainly understand a worked example. However, when you have the correct solution, it is computationally inexpensive; it involves only linear operations plus two square roots, to find the four limits of a horizontally- or vertically-translated sphere. To generalise that technique for other displacements requires one more square root, for a vector normalisation to find the correct rotation, and one application of that rotation matrix when you render the rectangle.)
So just to suggest an original solution that others aren't likely to provide, you could use an inequality (like x * x + y * y <= 1 for a circle or x * x - y * y <= 1 for a hyperbola) or a system of inequalities (like three straight line forms to bound a triangle) to decide how to discard a fragment. Note that if inequalities have more than linear order, they can encode perfect curves, and render them just as smoothly as your pixelated screen will allow -- with no limitation on the 'geometric detail' of the curve. You can also combine straight and curved edges in a single polygon, in this way.
For instance, a fragment shader (which would be written in GLSL) for a semi-circle might have something like this:
if (y < 0) discard;
float rSq = x * x + y * y;
if (1 < rSq) discard;
// We're inside the semi-circle; put further shader computations here
However, the polygons that are easy to draw, in this way, are very different from the ones that you're used to being easy. Converting a sequence of connected nodes into inequalities means yet more code to write, and deciding on the Boolean logic, to deal with combining those inequalities, could then get quite complex -- especially for concave polygons. Performing inequalities in a sensible order, so that some can be culled based on the results of others, is another ill-posed headache of a problem, if it needs to be general, even though it is easy to hard-code an optimal solution for a single case like a square.
I suggest using imposters mainly for its contrast with the triangulation method. Something like either one could be a route to pursue, depending on what you're hoping to achieve in the end, and the nature of your polygons.
Have fun...
P.S. have a related topic... Polygon triangulation into triangle strips for OpenGL ES
As long as the link lasts, it's a more detailed explanation of 'polygon triangulation' than mine. Those are the two words to search for if the link ever dies.
A line loop is just an outline.
To fill the middle as well, you want to use GL_POLYGON.
I'm interested in different algorithms people use to visualise millions of particles in a box. I know you can use Cloud-In-Cell, adaptive mesh, Kernel smoothing, nearest grid point methods etc to reduce the load in memory but there is very little documentation on how to do these things online.
i.e. I have array with:
x,y,z
1,2,3
4,5,6
6,7,8
xi,yi,zi
for i = 100 million for example. I don't want a package like Mayavi/Paraview to do it, I want to code this myself then load the decomposed matrix into Mayavi (rather than on-the-fly rendering) My poor 8Gb Macbook explodes if I try and use the particle positions. Any tutorials would be appreciated.
Analysing and creating visualisations for complex multi-dimensional data is complex. The best visualisation almost always depends on what the data is, and what relationships exists within the data. Of course, you are probably wanting to create visualisation of the data to show and explore relationships. Ultimately, this comes down to trying different posibilities.
My advice is to think about the data, and try to find sensible ways to slice up the dimensions. 3D plots, like surface plots or voxel renderings may be what you want. Personally, I prefer trying to find 2D representations, because they are easier to understand and to communicate to other people. Contour plots are great because they show 3D information in a 2D form. You can show a sequence of contour plots side by side, or in a timelapse to add a fourth dimension. There are also creative ways to use colour to add dimensions, while keeping the visualisation comprehensible -- which is the most important thing.
I see you want to write the code yourself. I understand that. Doing so will take a non-trivial effort, and afterwards, you might not have an effective visualisation. My advice is this: use a tool to help you prototype visualisations first! I've used gnuplot with some success, although I'm sure there are other options.
Once you have a good handle on the data, and how to communicate what it means, then you will be well positioned to code a good visualisation.
UPDATE
I'll offer a suggestion for the data you have described. It sounds as though you want/need a point density map. These are popular in geographical information systems, but have other uses. I haven't used one before, but the basic idea is to use a function to enstimate the density in a 3D space. The density becomes the fourth dimension. Something relatively simple, like the equation below, may be good enough.
The point density map might be easier to slice, summarise and render than the raw particle data.
The data I have analysed has been of a different nature, so I have not used this particular method before. Hopefully it proves helpful.
PS. I've just seen your comment below, and I'm not sure that this information will help you with that. However, I am posting my update anyway, just in case it is useful information.
I have custom control - chart with size, for example, 300x300 pixels and more than one million points (maybe less) in it. And its clear that now he works very slowly. I am searching for algoritm which will show only few points with minimal visual difference.
I have a link to the component which have functionallity exactly what i need
(2 million points demo):
I will be grateful for any matherials, links or thoughts how to realize such functionallity.
If I understand your question correctly, then you are looking to plot a graph of a dataset where you have ~1M points, but the chart's horizontal resolution is much smaller? If so, you can down-sample your dataset to get about the number of available x values. If your data is sorted in equal intervals, you can extract every N'th point and plot it. Choose N such that the number of points is, say, double the resolution (in this case, N=2000 will give you 500 points to display).
If the intervals are very different from eachother (not regularly spaced), you can approximate your graph with a polynomial, or spline or any other method that fits, and then interpolate 300-600 points from that approximation.
EDIT:
Depending on the nature of the data, you may end up with aliasing artifacts when you simply sample every N't point. There are probably better methods for coping with this problem, but again - it depends on what exactly you want to plot.
You could always buy the control - it is for sale!
John-Daniel Trask (Co-founder of Mindscape ;-)
I have to make an application that recognizes inside an black and white image a piece of tetris given by the user. I read the image to analyze into an array.
How can I do something like this using C?
Assuming that you already loaded the images into arrays, what about using regular expressions?
You don't need exact shape matching but approximately, so why not give it a try!
Edit: I downloaded your doc file. You must identify a random pattern among random figures on a 2D array so regex isn't suitable for this problem, lets say that's the bad news. The good news is that your homework is not exactly image processing, and it's much easier.
It's your homework so I won't create the code for you but I can give you directions.
You need a routine that can create a new piece from the original pattern/piece rotated. (note: with piece I mean the 4x4 square - all the cells of it)
You need a routine that checks if a piece matches an area from the 2D image at position x,y - the matching area would have corners (x-2, y-2, x+1, y+1).
You search by checking every image position (x,y) for a match.
Since you must use parallelism you can create 4 threads and assign to each thread a different rotation to search.
You might not want to implement that from scratch (unless required, of course) ... I'd recommend looking for a suitable library. I've heard that OpenCV is good, but never done any work with machine vision myself so I haven't tested it.
Search for connected components (i.e. using depth-first search; you might want to avoid recursion if efficiency is an issue; use your own stack instead). The largest connected component should be your tetris piece. You can then further analyze it (using the shape, the size or some kind of border description)
Looking at the shapes given for tetris pieces in Wikipedia, called "I,J,L,O,S,T,Z", it seems that the ratios of the sides of the bounding box (easy to find given a binary image and C) reveal whether you have I (4:1) or O (1:1); the other shapes are 2:3.
To detect which of the remaining shapes you have (J,L,S,T, or Z), it looks like you could collect the length and position of the shape's edges that fall on the bounding box's edges. Thus, T would show 3 and 1 along the 3-sides, and 1 and 1 along the 2 sides. Keeping track of the positions helps distinguish J from L, S from Z.