optimization

问题 I have a collection of 43 to 50 numbers ranging from 0.133 to 0.005 (but mostly on the small side). I would like to find, if possible, all combinations that have a sum between L and R, which are very close together.* The brute-force method takes 2 43 to 2 50 steps, which isn't feasible. What's a good method to use here? Edit: The combinations will be used in a calculation and discarded. (If you're writing code, you can assume they're simply output; I'll modify as needed.) The number of

问题 I am attempting to perform a numerical optimisation of a "black box" function in Mathematica. Schematically it goes like this: NMinimize[{comb[x,y,z], x > 0}, {x,y,z}] where comb[x,y,z] is defined similarly to this: comb[x_,y_,z_] := Module[{}, Print[x,y,z]; M = FindMaximum[SkewNormal[a,x,y,z], {a,x}] // First; val = f[x,y,z,M]; Return[val]; ]; However, all of the minimisation functions I have tried seem to not immediately provide comb[x,y,z] with numerical values, and it ends up trying to

问题 I'm working on a project with Zend Framework 1.11, Doctrine 2, some Symfony 2 componenents and others tools & libraries. I'm trying to optimize performance using Xdebug & Webgrind. I've already found some bottlenecks like parsing Ini config, etc.. and cached that. Now, I just realize that the autoloading is the most costly part of my application: Opl\Autoloader\ApcLoader->loadClass 274 31.36 43.86 Zend_Loader_PluginLoader->load 150 4.80 12.29 Zend_Loader_Autoloader->getClassAutoloaders 278 1

问题 Fast means better than O(N), which is as good as find() is capable of. I know there is ismembc and ismembc2 , but I don't think either of them are what I am looking for. I read the documentation and it seems they search for a member equal to x, but I want the index of first value greater than x. Now if either of these functions is capable of doing this, could somebody please give an example, because I can't figure it out. Ideal behaviour: first_greater_than([0, 3, 3, 4, 7], 1) returns 2, the

问题 I'm a rookie hobbyist and I nest for loops when I write python, like so: dict = { key1: {subkey/value1: value2} ... keyn: {subkeyn/valuen: valuen+1} } for key in dict: for subkey/value in key: do it to it I'm aware of a "next" keyword that would accomplish the same goal in one line (I asked a question about how to use it but I didn't quite understand it). So to me, a nested for loop is much more readable. Why, then do people use "next"? I read somewhere that Python is a dynamically-typed and

问题 This is a very basic question about the Java optimization. If you have a simple for loop to iterate through an array and use array.length in the header of the loop rather than evaluating it before so that you do it only once (which is what I almost always do): for(int i=0; i<array.length;i++) { ... } Can the statement be optimized so that the JVM knows whether the array is changing for the duration of the loop so that it does not reevaluate array.length every time? 回答1: if another thread is

问题 I've just upgraded a native C++ project from VS2005-SP1 to VS2008-SP1 The first thing I tested was a very basic functionality test of the application and the first thing I noticed is that the main number-crunching algorithm performs three times slower in the VS2008 binary. I tested again the VS2005 binary to make sure there isn't any other difference and it still performed as it did before. Did anyone stumble into this? 回答1: Strangest. Thing. Ever. It seems that the project upgrade wizard of

问题 I'm trying to vectorize some extremely performance critical code. At a high level, each loop iteration reads six floats from non-contiguous positions in a small array, then converts these values to double precision and adds them to six different double precision accumulators. These accumulators are the same across iterations, so they can live in registers. Due to the nature of the algorithm, it's not feasible to make the memory access pattern contiguous. The array is small enough to fit in L1

问题 While playing with VS11 beta I noticed something weird: this code couts f took 0 milliseconds int main() { std::vector<int> v; size_t length =64*1024*1024; for (int i = 0; i < length; i++) { v.push_back(rand()); } uint64_t sum=0; auto t1 = std::chrono::system_clock::now(); for (size_t i=0;i<v.size();++i) sum+=v[i]; //std::cout << sum << std::endl; auto t2 = std::chrono::system_clock::now(); std::cout << "f() took " << std::chrono::duration_cast<std::chrono::milliseconds>(t2-t1).count() << "

问题 I need to count the number of elements corresponding to the intersection of two big arrays of strings and do it very fast. I am using the following code: arr1[i].Intersect(arr2[j]).Count() For CPU Time, VS Profiler indicates 85.1% in System.Linq.Enumerable.Count() 0.3% in System.Linq.Enumerable.Intersect() Unfortunately it might to take hours to do all work. How to do it faster? 回答1: You can use HashSet with arr2 HashSet<string> arr2Set = new HashSet<string>(arr2); arr1.Where(x=>arr2Set