I have an array - 2D(100 x 100 in this case) with some states limited within borders as shown on picture:
http://tinypic.com/view.php?pic=mimiw5&s=5#.UkK8WIamiBI
Each cell has its own id(color, for example green is id=1) and flag isBorder(marked as white on pic if true). What I am trying to do is exclude set of cell with one state limited with borders(Grain) so i could work on each grain separately which means i would need to store all indexes for each grain.
Any one got an idea how to solve it?
Now that I've read your question again... The algorithm is essentially the same as filling the contiguous area with color. The most common way to do it is a BFS algorithm.
Simply start within some point you are sure lays inside the current area, then gradually move in every direction, selecting traversed fields and putting them into a vector.
// Edit: A bunch of other insights, made before I understood the question.
I can possibly imagine an algorithm working like this:
vector<2dCoord> result = data.filter(DataType::Green);
for (2dCoord in result) {
// do some operations on data[2dCoord]
}
The implementation of filter in a simple unoptimized way would be to scan the whole array and push_back matching fields to the vector.
If you shall need more complicated queries, lazily-evaluated proxy objects can work miracles:
data.filter(DataType::Green)
.filter_having_neighbours(DataType::Red)
.closest(/*first*/ 100, /*from*/ 2dCoord(x,y))
.apply([](DataField& field) {
// processing here
});
Related
I am trying to make a 16x16 LED Snake game using Arduino (C++).
I need to assign a random grid index for the next food tile.
What I have is a list of indices that are occupied by the snake (snakeSquares).
So, my thought is that I need to generate a list of potential foodSquares. Then I can pick a random index from that list, and use the value there for my next food square.
I have some ideas for this but they seem kind of clunky, so I was looking for some feedback. I am using the Arduino LinkedList.h library for my lists in lieu of stdio.h (and random() in place of rand()):
Generate a list (foodSquares) containing the integers [0, 255] so that the indices correspond to the values in the list (I don't know of a quick way to do this, will probably need to use a for loop).
When generating list of snakeSquares, set foodSquares[i] = -1. Afterwards, loop through foodSquares and remove all elements that equal -1.
Then, generate a random number randNum from [0, foodSquares.size()-1] and make the next food square index equal to foodSquares[randNum].
So I guess my question is, will this approach work, and is there a better way to do it?
Thanks.
Potential approach that won't require more lists:
Calculate random integer representing number of steps.
Take head or tail as a starting tile.
For each step move at random free adjacent tile.
I couldn't understand it completely your question as some of those points are quite waste of processor time (i.e. point 1 and 2). But, the first point could be solved quite easily in n proportional complexity as follows:
for (uint8_t i = 0; i < 256; i++) {
// assuming there is a list of food_squares
food_squares[i] = i;
}
Then to the second point you would have to set every food_square to -1, for what? Anyway. A way you could implement this would be as VTT has said and I will describe it further:
Take a random number between [0..255].
Does it is one the snake_squares? If so, back to one, else, go to three.
This is the same as your third point, use this random number to set the position of the food in food_square (food_square[random_number] = some_value).
So this question has been asked a few times, but I think my C++ skills are too deficient to really appreciate the answers. What I need is a way to start with an HEVC encoded video and end with CSV that has all the motion vectors. So far, I've compiled and run the reference decoder, everything seems to be working fine. I'm not sure if this matters, but I'm interested in the motion vectors as a convenient way to analyze motion in a video. My plan at first is to average the MVs in each frame to just get a value expressing something about the average amount of movement in that frame.
The discussion here tells me about the TComDataCU class methods I need to interact with to get the MVs and talks about how to iterate over CTUs. But I still don't really understand the following:
1) what information is returned by these MV methods and in what format? With my limited knowledge, I assume that there are going to be something like 7 values associated with the MV: the frame number, an index identifying a macroblock in that frame, the size of the macroblock, the x coordinate of the macroblock (probably the top left corner?), the y coordinate of the macroblock, the x coordinate of the vector, and the y coordinate of the vector.
2) where in the code do I need to put new statements that save the data? I thought there must be some spot in TComDataCU.cpp where I can put lines in that print the data I want to a file, but I'm confused when the values are actually determined and what they are. The variable declarations look like this:
// create motion vector fields
m_pCtuAboveLeft = NULL;
m_pCtuAboveRight = NULL;
m_pCtuAbove = NULL;
m_pCtuLeft = NULL;
But I can't make much sense of those names. AboveLeft, AboveRight, Above, and Left seem like an asymmetric mix of directions?
Any help would be great! I think I would most benefit from seeing some example code. An explanation of the variables I need to pay attention to would also be very helpful.
At TEncSlice.cpp, you can access every CTU in loop
for( UInt ctuTsAddr = startCtuTsAddr; ctuTsAddr < boundingCtuTsAddr; ++ctuTsAddr )
then you can choose exact CTU by using address of CTU.
pCtu(TComDataCU class)->getCtuRsAddr().
After that,
pCtu->getCUMvField()
will return CTU's motion vector field. You can extract MV of CTU in that object.
For example,
TComMvField->getMv(g_auiRasterToZscan[y * 16 + x])->getHor()
returns specific 4x4 block MV's Horizontal element.
You can save these data after m_pcCuEncoder->compressCtu( pCtu ) because compressCtu determines all data of CTU such as CU partition and motion estimation, etc.
I hope this information helps you and other people!
I'm creating a game in Qt in c++, and I store every coordinate of specific size into a vector like :
std::vector<std::unique_ptr<Tile>> all_tiles = createWorld(bgTile);
for(auto & tile : all_tiles) {
tiles.push_back(std::move(tile));
}
Each level also has some healthpacks which are stored in a vector aswell.
std::vector<std::unique_ptr<Enemy>> all_enemies = getEnemies(nrOfEnemies);
for(auto &healthPackUniquePtr : all_healthpacks) {
std::shared_ptr<Tile> healthPackPtr{std::move(healthPackUniquePtr)};
int x = healthPackPtr->getXPos();
int y = healthPackPtr->getYPos();
int newYpos=checkOverlapPos(healthPackPtr->getXPos(),healthPackPtr->getYPos());
newYpos = checkOverlapEnemy(healthPackPtr->getXPos(),newYpos);
auto healthPack = std::make_shared<HealthPack>(healthPackPtr->getXPos(), newYpos, healthPackPtr->getValue());
healthPacks.push_back(healthPack);
}
But know I'm searching for the fastest way to check if my player position is at an healthpack position. So I have to search on 2 values in a vector : x and y position. Anyone a suggestion how to do this?
Your 'real' question:
I have to search on 2 values in a vector : x and y position. Anyone a
suggestion how to do this?"
Is a classic XY question, so I'm ignoring it!
I'm searching for the fastest way to check if my player position is at
an healthpack position.
Now we're talking. The approach you are using now won't scale well as the number of items increase, and you'll need to do something similar for every pair of objects you are interested in. Not good.
Thankfully this problem has been solved (and improved upon) for decades, you need to use a spacial partitioning scheme such as BSP, BVH, quadtree/octree, etc. The beauty of the these schemes is that a single data structure can hold the entire world in it, making arbitrary item intersection queries trivial (and fast).
You can implement a callback system. Then a player moves a tile, fire a callback to that tile which the player is on. Tiles should know its state and could add health to a player or do nothing if there is nothing on that tile. Using this technique, you don`t need searching at all.
If all_leathpacks has less than ~50 elements I wouldn't bother to improve. Simple loop is going to be sufficiently fast.
Otherwise you can split the vector into sectors and check only for the elements in the same sector as your player (and maybe a few around if it's close to the edge).
If you need something that's better for the memory you and use a KD-tree to index the healtpacks and search for them fast (O(logN) time).
I am developing an application aimed to render a huge number of shapes. Each shape can be assigned to a specific layer.
I get the input data as a list of shapes, where for each shape I have a string property that represents the layer to which the shape belongs.
Now, I need to develop a method that allows me to select (draw) only those shapes that belong to a given list of selected layers.
In pseudo-code:
void draw_if(sorted_list shapes, list<string> selected_layers)
{
for each shape in shapes
{
if (shape.layer in selected_layers)
shape.draw();
}
}
The point is that I would like to perform this operation as fast as possible; therefore I need to choose the right data structures and a proper algorithm.
The list of selected layers is a list of strings (1รท100 different layers), but if needed for performance reasons, it could be converted to other data types.
The shapes are sorted according to their z-order.
Basic intrusive solutions are often overlooked here in search of elaborate data structures and algorithms, but generally are the fastest.
Assuming you have no choice but to keep the selection separate, if you want a really fast solution, store a boolean selection flag in each layer (could be a single bit). When you form a selection, in addition to forming a list, set those flags. Deselecting a layer not only removes it from your selection, but sets that selection flag to false.
Next, turn those strings used to indicate selected layers into indices into a random-access structure (ex: std::vector or even a plain old array if the size can be determined at compile time), like so (simplified):
struct Layer
{
string name;
// Set this to true when the layer is selected, false
// when it is deselected. Use atomics if thread safety
// is required.
bool selected;
};
... and turn shape.layer into an index (or pointer/iterator) to a layer. If you have no choice but to start with a layer string to identify which layer a shape belongs to because you are given string inputs initially (ex: from a file you are loading), then translate those strings into a layer index/pointer/iterator as you are creating the shapes from those string inputs. Use a hash table or at least std::set/map here (the string search on initial shape construction should be logarithmic or better) to convert those layer strings into layer indices/pointers/iterators.
If you need a layer selection list in addition to a layer selection state, then you can do this (pseudocode):
void select(Layer layer, LayerList& layer_selection)
{
if (!layer.selected)
{
layer.selected = true;
layer_selection.insert(&layer);
}
}
void deselect(Layer layer, LayerList& layer_selection)
{
if (layer.selected)
{
layer.selected = false;
layer_selection.erase(&layer);
}
}
... Where your layer selection stores indices/pointers/iterators to layers. Both the select and deselect list insertion/removal can be done in constant-time (even during worst-case) without hashing overhead and while preserving insertion order if you get fancy with the layer selection and use a fixed allocator (this is a complex subject involving placement new, unions, and memory pools so I'll delve into it if desired, but omit it for the time being for brevity).
Now your main pseudocode code turns into something like this:
void draw_if(list shapes, list layers)
{
for each shape in shapes
{
if (layers[shape.layer].selected)
shape.draw();
}
}
... or this if you use pointers/iterators:
void draw_if(list shapes, list layers)
{
for each shape in shapes
{
if (shape.layer->selected)
shape.draw();
}
}
It's hard to beat that in terms of performance as even the most optimal hash table cannot beat a simple indexed array access into memory you would still have to access in addition with the hash. Now if you can consolidate the idea of "selected shapes" and form selected shapes in advance through the process of selecting/deselecting layers, then you can do this:
void draw_selected(list selected_shapes)
{
for each shape in selected_shapes
shape.draw();
}
... which could be even faster provided that the extra cost of forming the selected shapes list is compensated by reusing it repeatedly before it has to change. Note that you still want to convert those strings into indices in this case, because you don't want your "selected shapes" list to have to be anything more than a simple array. To form the selected shapes list:
ShapeList selected_shapes(ShapeList all_shapes, LayerList layers)
{
// Forming this in advance will help if it is reused for
// numerous drawing frames before it needs to change (ex:
// before the Z-order changes, before new elements are inserted
// or existing ones removed, before the layer selection changes).
ShapeList results;
for each shape in all_shapes:
if layers[shape.layer].selected)
results.push_back(shape);
return results;
}
... which is still even cheaper to form and access (due to spatial locality of a perfectly compact shape selection array) than a hash table thanks to that selection state we now store in layers.
This keeps everything cache-friendly and avoids expensive (relatively speaking) data structures like hash tables except during that initial string->index/pointer conversion part (which you only need to do when creating a shape from a string input). In this case, the only place that ever needs to do any kind of search (logarithmic or constant-time hash/trie) is when you convert those shape layer strings you get from user input into indices/pointers/iterators. Everything else is O(1) (even worst-case complexity) and doesn't even require hashing.
I would suggest using a set instead of a list for the selected layers, that way a binary search can be performed to determine in shape.layer is in the selected layers, and insertion while preserving order is quick. Using a list would be inefficient for keeping the order required for binary search.
Another option is to figure out some hashing algorithm and just use a hash map.
I am developing a graphics application using Qt 4.5 and am putting images in the QPixmapCache, I wanted to optimise this so that if a user inserts an image which is already in the cache it will use that.
Right now each image has a unique id which helps optimises itself on paint events. However I realise that if I could calculate a hash of the image I could lookup the cache to see if it already exists and use that (it would help more for duplicate objects of course).
My problem is that if its a large QPixmap will a hash calculation of it slow things down or is there a quicker way?
A couple of comments on this:
If you're going to be generating a hash/cache key of a pixmap, then you may want to skip the QPixmapCache and use QCache directly. This would eliminate some overhead of using QStrings as keys (unless you also want to use the file path to locate the items)
As of Qt4.4, QPixmap has a "hash" value associated with it (see QPixmap::cacheKey() ). The documentation claims "Distinct QPixmap objects can only have the same cache key if they refer to the same contents." However, since Qt uses shared-data copying, this may only apply to copied pixmaps and not to two distinct pixmaps loaded from the same image. A bit of testing would tell you if it works, and if it does, it would let you easily get a hash value.
If you really want to do a good, fairly quick cache with removing duplications, you might want to look at your own data structure that sorts according to sizes, color depths, image types, and things such as that. Then you would only need to hash the actual image data after you find the same type of image with the same dimensions, bit-depths, etc. Of course, if your users generally open a lot of images with those things the same, it wouldn't help at all.
Performance: Don't forget about the benchmarking stuff Qt added in 4.5, which would let you compare your various hashing ideas and see which one runs the fastest. I haven't checked it out yet, but it looks pretty neat.
Just in case anyone comes across this problem (and isn't too terribly experienced with hashing things, particularly something like an image), here's a VERY simple solution I used for hashing QPixmaps and entering them into a lookup table for later comparison:
qint32 HashClass::hashPixmap(QPixmap pix)
{
QImage image = pix.toImage();
qint32 hash = 0;
for(int y = 0; y < image.height(); y++)
{
for(int x = 0; x < image.width(); x++)
{
QRgb pixel = image.pixel(x,y);
hash += pixel;
hash += (hash << 10);
hash ^= (hash >> 6);
}
}
return hash;
}
Here is the hashing function itself (you can have it hash into a qint64 if you desire less collisions). As you can see I convert the pixmap into a QImage, and simply walk through its dimensions and perform a very simple one-at-a-time hash on each pixel and return the final result. There are many ways to improve this implementation (see the other answers to this question), but this is the basic gist of what needs to be done.
The OP mentioned how he would use this hashing function to then construct a lookup table for later comparing images. This would require a very simple lookup initialization function -- something like this:
void HashClass::initializeImageLookupTable()
{
imageTable.insert(hashPixmap(QPixmap(":/Image_Path1.png")), "ImageKey1");
imageTable.insert(hashPixmap(QPixmap(":/Image_Path2.png")), "ImageKey2");
imageTable.insert(hashPixmap(QPixmap(":/Image_Path3.png")), "ImageKey2");
// Etc...
}
I'm using a QMap here called imageTable which would need to be declared in the class as such:
QMap<qint32, QString> imageTable;
Then, finally, when you want to compare an image to the images in your lookup table (ie: "what image, out of the images I know it can be, is this particular image?"), you just call the hashing function on the image (which I'm assuming will also be a QPixmap) and the return QString value will allow you to figure that out. Something like this would work:
void HashClass::compareImage(const QPixmap& pixmap)
{
QString value = imageTable[hashPixmap(pixmap)];
// Do whatever needs to be done with the QString value and pixmap after this point.
}
That's it. I hope this helps someone -- it would have saved me some time, although I was happy to have the experience of figuring it out.
Hash calculations should be pretty quick (somewhere above 100 MB/s if no disk I/O involved) depending on which algorithm you use. Before hashing, you could also do some quick tests to sort out potential candidates - f.e. images must have same width and height, else it's useless to compare their hash values.
Of course, you should also keep the hash values for inserted images so you only have to calculate a hash for new images and won't have to calculate it again for the cached images.
If the images are different enough, it would perhaps be enough to not hash the whole image but a smaller thumbnail or a part of the image (f.e. first and last 10 lines), this will be faster, but will lead to more collisions.
I'm assuming you're talking about actually calculating a hash over the data of the image rather than getting the unique id generated by QT.
Depending on your images, you probably don't need to go over the whole image to calculate a hash. Maybe only read the first 10 pixels? first scan line?
Maybe a pseudo random selection of pixels from the entire image? (with a known seed so that you could repeat the sequence) Don't forget to add the size of the image to the hash as well.