I'm a novice programmer (the only reason I say this is because I'm not super familiar with all the terms yet) and I'm trying to make walls generate in respect to the wall before it. I've posted a question about it on here before
Randomly generated tunnel walls that don't jump around from one to the next
and sort of got the answer. What I was mainly looking for was the for loop that was used (I think). Th problem is I didn't know how to implement it properly without getting errors.
My problem ended up being "I couldn't figure out how to inc. this in to it. I have 41 walls altogether that i'm using and the walls are named Left1 and Right1. i had something like this
CGFloat Left1 = 14; for( int i = 0; i < 41; i++ ){
CGFloat offset = (CGFloat)arc4random_uniform(2*100) - 100;
Left1 += offset;
Right1 = Left1 + 100;
but it was telling me as a yellow text that Local declaration of "Left1" hides instance variable and then in a red text it says "Assigning to 'UIImageView *__strong' from incompatible type 'float'. i'm not sure how to fix this"
and I wasn't sure how to fix it. I realize (I think) that arc4random and arc4random_uniform are pretty much the same thing, as far as i know, with slight differences, but not the difference i'm looking for.
As I said before, i'm pretty novice so any example would really be helpful, especially with the variables i'm trying to use. Thank you.
You want a "hashing" function, and preferably a "cryptographic" one because they tend to be significantly higher quality - at the expense of requiring additional CPU resources. But on modern hardware the extra CPU power usually isn't a problem.
The basic idea is you can give any data to the function, and it will spit out a completely random result, but always the same result if you provide the same input.
Have a read up on them here:
http://en.wikipedia.org/wiki/Hash_function
http://en.wikipedia.org/wiki/Cryptographic_hash_function
There are hundreds of different algorithms in common use, which is best will depend on what you need.
Personally I recommend sha256. A quick search of "sha256 ios" here on stack overflow will show you how to make one, with the CommonCrypto library. The gist is you should create an NSString or NSData object that contains every offset, then run the entire thing through sha256. The result will be a perfectly random 256 bit number.
If 256 bits is too much, just cut it up. For example you could grab just the first 16 bits of the number, and you will have a perfectly random 16 bit number.
Related
I'm trying to use the CAMPARY library (CudA Multiple Precision ARithmetic librarY). I've downloaded the code and included it in my project. Since it supports both cpu and gpu, I'm starting with cpu to understand how it works and make sure it does what I need. But the intent is to use this with CUDA.
I'm able to instantiate an instance and assign a value, but I can't figure out how to get things back out. Consider:
#include <time.h>
#include "c:\\vss\\CAMPARY\\Doubles\\src_cpu\\multi_prec.h"
int main()
{
const char *value = "123456789012345678901234567";
multi_prec<2> a(value);
a.prettyPrint();
a.prettyPrintBin();
a.prettyPrintBin_UnevalSum();
char *cc = a.prettyPrintBF();
printf("\n%s\n", cc);
free(cc);
}
Compiles, links, runs (VS 2017). But the output is pretty unhelpful:
Prec = 2
Data[0] = 1.234568e+26
Data[1] = 7.486371e+08
Prec = 2
Data[0] = 0x1.987bf7c563caap+86;
Data[1] = 0x1.64fa5c3800000p+29;
0x1.987bf7c563caap+86 + 0x1.64fa5c3800000p+29;
1.234568e+26 7.486371e+08
Printing each of the doubles like this might be easy to do, but it doesn't tell you much about the value of the 128 number being stored. Performing highly accurate computations is of limited value if there's no way to output the results.
In addition to just printing out the value, eventually I also need to convert these numbers to ints (I'm willing to try it all in floats if there's a way to print, but I fear that both accuracy and speed will suffer). Unlike MPIR (which doesn't support CUDA), CAMPARY doesn't have any associated multi-precision int type, just floats. I can probably cobble together what I need (mostly just add/subtract/compare), but only if I can get the integer portion of CAMPARY's values back out, which I don't see a way to do.
CAMPARY doesn't seem to have any docs, so it's conceivable these capabilities are there, and I've simply overlooked them. And I'd rather ask on the CAMPARY discussion forum/mail list, but there doesn't seem to be one. That's why I'm asking here.
To sum up:
Is there any way to output the 128bit ( multi_prec<2> ) values from CAMPARY?
Is there any way to extract the integer portion from a CAMPARY multi_prec? Perhaps one of the (many) math functions in the library that I don't understand computes this?
There are really only 2 possible answers to this question:
There's another (better) multi-precision library that works on CUDA that does what you need.
Here's how to modify this library to do what you need.
The only people who could give the first answer are CUDA programmers. Unfortunately, if there were such a library, I feel confident talonmies would have known about it and mentioned it.
As for #2, why would anyone update this library if they weren't a CUDA programmer? There are other, much better multi-precision libraries out there. The ONLY benefit CAMPARY offers is that it supports CUDA. Which means the only people with any real motivation to work with or modify the library are CUDA programmers.
And, as the CUDA programmer with the most vested interest in solving this, I did figure out a solution (albeit an ugly one). I'm posting it here in the hopes that the information will be of value to future CAMPARY programmers. There's not much information out there for this library, so this is a start.
The first thing you need to understand is how CAMPARY stores its data. And, while not complex, it isn't what I expected. Coming from MPIR, I assumed that CAMPARY stored its data pretty much the same way: a fixed size exponent followed by an arbitrary number of bits for the mantissa.
But nope, CAMPARY went a different way. Looking at the code, we see:
private:
double data[prec];
Now, I assumed that this was just an arbitrary way of reserving the number of bits they needed. But no, they really do use prec doubles. Like so:
multi_prec<8> a("2633716138033644471646729489243748530829179225072491799768019505671233074369063908765111461703117249");
// Looking at a in the VS debugger:
[0] 2.6337161380336443e+99 const double
[1] 1.8496577979210756e+83 const double
[2] 1.2618399223120249e+67 const double
[3] -3.5978270144026257e+48 const double
[4] -1.1764513205926450e+32 const double
[5] -2479038053160511.0 const double
[6] 0.00000000000000000 const double
[7] 0.00000000000000000 const double
So, what they are doing is storing the max amount of precision possible in the first double, then the remainder is used to compute the next double and so on until they encompass the entire value, or run out of precision (dropping the least significant bits). Note that some of these are negative, which means the sum of the preceding values is a bit bigger than the actual value and they are correcting it downward.
With this in mind, we return to the question of how to print it.
In theory, you could just add all these together to get the right answer. But kinda by definition, we already know that C doesn't have a datatype to hold a value this size. But other libraries do (say MPIR). Now, MPIR doesn't work on CUDA, but it doesn't need to. You don't want to have your CUDA code printing out data. That's something you should be doing from the host anyway. So do the computations with the full power of CUDA, cudaMemcpy the results back, then use MPIR to print them out:
#define MPREC 8
void ShowP(const multi_prec<MPREC> value)
{
multi_prec<MPREC> temp(value), temp2;
// from mpir at mpir.org
mpf_t mp, mp2;
mpf_init2(mp, value.getPrec() * 64); // Make sure we reserve enough room
mpf_init(mp2); // Only needs to hold one double.
const double *ptr = value.getData();
mpf_set_d(mp, ptr[0]);
for (int x = 1; x < value.getPrec(); x++)
{
// MPIR doesn't have a mpf_add_d, so we need to load the value into
// an mpf_t.
mpf_set_d(mp2, ptr[x]);
mpf_add(mp, mp, mp2);
}
// Using base 10, write the full precision (0) of mp, to stdout.
mpf_out_str(stdout, 10, 0, mp);
mpf_clears(mp, mp2, NULL);
}
Used with the number stored in the multi_prec above, this outputs the exact same value. Yay.
It's not a particularly elegant solution. Having to add a second library just to print a value from the first is clearly sub-optimal. And this conversion can't be all that speedy either. But printing is typically done (much) less frequently than computing. If you do an hour's worth of computing and a handful of prints, the performance doesn't much matter. And it beats the heck out of not being able to print at all.
CAMPARY has a lot of shortcomings (undoced, unsupported, unmaintained). But for people who need mp numbers on CUDA (especially if you need sqrt), it's the best option I've found.
I need to find the number of times the accelerometer value stream attains a maximum. I made a plot of the accelerometer values obtained from an iPhones against time, using CoreMotion method to obtain the DeviceMotionUpdates. When the data was being recorded, I shook the phone 9 times (where each extremity was one of the highest points of acceleration).
I have marked the 18 (i.e. 9*2) times when acceleration had attained maximum in red boxes on the plot.
But, as you see, there are some local maxima that I do not want to consider. Can someone direct me towards an idea that will help me achieve detecting only the maxima of importance to me?
Edit: I think I have to use a low pass filter. But, how do I implement this in Swift? How do I choose the frequency of cut-off?
Edit 2:
I implemented a low pass filter and passed the raw motion data through it and obtained the graph as shown below. This is a lot better. I still need a way to avoid the insignificant maxima that can be observed. I'll work in depth with the filter and probably fix it.
Instead of trying to find the maximas, I would try to look for cycles. Especially, we note that the (main) minimas seem to be a lot more consistent than the maximas.
I am not familiar with swift, so I'll layout my idea in pseudo code. Suppose we have our values in v[i] and the derivative in dv[i] = v[i] - v[i - 1]. You can use any other differentiation scheme if you get a better result.
I would try something like
cycles = [] // list of pairs
cstart = -1
cend = -1
v_threshold = 1.8 // completely guessing these figures looking at the plot
dv_threshold = 0.01
for i in v:
if cstart < 0 and
v[i] > v_threshold and
dv[i] < dv_threshold then:
// cycle is starting here
cstart = i
else if cstart > 0 and
v[i] < v_threshold and
dv[i] < dv_threshold then:
// cycle ended
cend = i
cycles.add(pair(cstart, cend))
cstart = -1
cend = -1
end if
Now you note in comments that the user should be able to shake with different force and you should be able to recognise the motion. I would start with a simple 'hard-coded' cases as the one above, and see if you can get it to work sufficiently well. There is a lot of things you could try to get a variable threshold, but you will nevertheless always need one. However, from the data you show I strongly suggest at least limiting yourself to looking at the minimas and not the maximas.
Also: the code I suggested is written assuming you have the full data set, however you will want to run this in real time. This will be no problem, and the algorithm will still work (that is, the idea will still work but you'll have to code it somewhat differently).
In my application I need to determine what the plates a user can load on their barbell to achieve the desired weight.
For example, the user might specify they are using a 45LB bar and have 45,35,25,10,5,2.5 pound plates to use. For a weight like 115, this is an easy problem to solve as the result neatly matches a common plate. 115 - 45 / 2 = 35.
So the objective here is to find the largest to smallest plate(s) (from a selection) the user needs to achieve the weight.
My starter method looks like this...
-(void)imperialNonOlympic:(float)barbellWeight workingWeight:(float)workingWeight {
float realWeight = (workingWeight - barbellWeight);
float perSide = realWeight / 2;
.... // lots of inefficient mod and division ....
}
My thought process is to determine first what the weight per side would be. Total weight - weight of the barbell / 2. Then determine what the largest to smallest plate needed would be (and the number of each, e.g. 325 would be 45 * 3 + 5 or 45,45,45,5.
Messing around with fmodf and a couple of other ideas it occurred to me that there might be an algorithm that solves this problem. I was looking into BFS, and admit that it is above my head but still willing to give it a shot.
Appreciate any tips on where to look in algorithms or code examples.
Your problem is called Knapsack problem. You will find a lot solution for this problem. There are some variant of this problem. It is basically a Dynamic Programming (DP) problem.
One of the common approach is that, you start taking the largest weight (But less than your desired weight) and then take the largest of the remaining weight. It easy. I am adding some more links ( Link 1, Link 2, Link 3 ) so that it becomes clear. But some problems may be hard to understand, skip them and try to focus on basic knapsack problem. Good luck.. :)
Let me know if that helps.. :)
Is it preferable to store redundant information, (which can be otherwise generated from existing data,) or to instead convert the existing data each time you need access?
I've simplified my specific problem as best as I can below, hoping that the provided answers are useful as future-reference material.
Example:
Let's say we've developed a program that places data into Squares on a grid (like a super-descriptive game of Tic-Tac-Toe or something) and assigns various details, and a unique identification number to each:
Throughout our program, we often perform logic based on a square's X and/or Y coordinates (checking for 3 in a row) and other times we only need the ID (perhaps to access a string at "SquareName[ID]") - We aren't exactly certain which of these two is accessed more often, but it's a rather close competition.
Up until now we've simply stored the ID inside the square class, and converted it with some simple formulas whenever just the X or Y are needed. Say we want to get coordinates for one square in particular:
int CurrentX = (this.Square.ID - 1) % 3) + 1; // X coordinate, 1 through 3
int CurrentY = (this.Square.ID + 1) / 3; // Y, 1 through 3
Since the squares don't move around or change ID after setup, part of me believes it would be simpler just to store all 3 values inside the Square class, but my other part cringes at the redundancy since access to X and Y is already easy enough to calculate from the existing ID.
(Note, This program itself is not very memory or resource intensive, nor does the size of the grid get much larger, so it mostly comes down to which option is a better practice or rule of thumb.)
What would you do?
As a rule of thumb, for a system where the data is read/write, store your basic data without redundancy.
When performance or other considerations become a practical issue, then you should denormalize as necessary. (i.e. wait for it to be a problem, don't pre-optimize overly much).
Your goal should be the most maintainable code possible. That usually means writing the least code possible. Having extra code to maintain redundant copies of data points will make your code more brittle.
If those are values which can be determined at the moment of creation and then do not change anymore, I would go for variables populated in the constructor. It's not redundant info in so far as that it isn't stored anywhere else, but that's not my main point. When reading my code, I'd usually expect that whenever something is computed at the time of request, it might change per request. It is easy to find the point in the source where the field is populated and where it is changed, especially if it does never change, but you might end up slightly confused when looking at some calculation which will return always the same result, as it's variables can't change, and wonder whether you're just missing a case or this is really static.
Also, using a descriptive variable name, you can get rid of the comments. Not that I generally aim at not commenting, but source code which doesn't even need comments is a pretty save signal for easy to understand code, which might (/should) be your aim.
I was asked this question in an interview Plz tell me the answer :-
You have no documentation of the kernel. You only knows that you kernel supports paging.
How will you find that page size ? There is no flag or macro you have that can tell you about page size.
I was given the hint as you can use Time to get the answer. I still have no clue for it.
Run code like the following:
for (int stride = 1; stride < maxpossiblepagesize; stride += searchgranularity) {
char* somemem = (char*)malloc(veryverybigsize*stride);
starttime = getcurrentveryaccuratetime();
for (pos = somemem; pos < somemem+veryverybigsize*stride; pos += stride) {
// iterate over "veryverybigsize" chunks of size "stride"
*pos = 'Q'; // Just write something to force the page back into physical memory
}
endtime = getcurrentveryaccuratetime();
printf("stride %u, runtime %u", stride, endtime-starttime);
}
Graph the results with stride on the X axis and runtime on the Y axis. There should be a point at stride=pagesize, where the performance no longer drops.
This works by incurring a number of page faults. Once stride surpasses pagesize, the number of faults ceases to increase, so the program's performance no longer degrades noticeably.
If you want to be cleverer, you could exploit the fact that the mprotect system call must work on whole pages. Try it with something smaller, and you'll get an error. I'm sure there are other "holes" like that, too - but the code above will work on any system which supports paging and where disk access is much more expensive than RAM access. That would be every seminormal modern system.
It looks to me like a question about 'how does paging actually work'
They want you to explain the impact that changing the page size will have on the execution of the system.
I am a bit rusty on this stuff, but when a page is full, the system starts page swapping, which slows everything down. So you want to run something that will fill up the memory to different sizes, and measure the time it takes to do a task. At some point there will be a jump, where the time taken to do the task will suddenly jump.
Like I said I am a bit rusty on the implementation of doing this. But i'm pretty sure that is the shape of the answer they were after.
Whatever answer they were expecting it would almost certainly be a brittle solution. For one thing you can have multiple pages sizes so any answer you may have gotten for one small allocation may be irrelevant for the next multi-megabyte allocation (see things like Linux's Large Page support).
I suspect the question was more aimed at seeing how you approached the problem rather than the final solution you came up with.
By the way this question isn't about linux because you do have documentation for that as well as POSIX compliance, for which you just call sysconf(_SC_PAGE_SIZE).