Here’s something you can use. Just replace the printfs with what you actually want to do. #include <stdio.h> int main() { int x[3][3] = {1, 2, 3, 4, 5, 6, 7, 8, 9}; int n = 3; for (int slice = 0; slice < 2 * n – 1; ++slice) { printf(“Slice %d: “, slice); … Read more
The above answers are too complex and hog your CPU. Your question was not arbitrary rotation, but ‘Rotate Opencv Matrix by 90, 180, 270 degrees’. UPDATE 30 JUN 2017: This functionality is supported by OpenCV, but not documented: https://github.com/opencv/opencv/blob/master/modules/core/include/opencv2/core.hpp#L1041 void rotate(InputArray src, OutputArray dst, int rotateCode); with enum RotateFlags { ROTATE_90_CLOCKWISE = 0, //Rotate 90 … Read more
logsumexp works by evaluating the right-hand side of the equation log(∑ exp[a]) = max(a) + log(∑ exp[a – max(a)]) I.e., it pulls out the max before starting to sum, to prevent overflow in exp. The same can be applied before doing vector dot products: log(exp[a] ⋅ exp[b]) = log(∑ exp[a] × exp[b]) = log(∑ exp[a … Read more
Sorry if I’m not answering this completely enough, but hopefully I can provide some insight. CSC (Compressed Sparse Column) and CSR (Compressed Sparse Row) are more compact and efficient, but difficult to construct “from scratch”. Coo (Coordinate) and DOK (Dictionary of Keys) are easier to construct, and can then be converted to CSC or CSR … Read more
A fully working example (for SQL Server 2005+) If you need it for another system, there are equivalents for the pieces of the puzzle below row_number() dense_rank() un/pivot You can find the equivalents from other Stackoverflow questions. For example, the first two are well supported by Oracle and DB2. create table t45 (id int identity, … Read more
The Python version is compiling down to a loop in C while the Clojure version is building a new intermediate sequence for each of the calls to map in this code. It is likely that the performance difference you see is coming from the difference of data structures. To get better than this you could … Read more
You could try this: In [9]: l = [[3,7,2],[1,4,5],[9,8,7]] In [10]: [sum(i) for i in zip(*l)] Out[10]: [13, 19, 14] This uses a combination of zip and * to unpack the list and then zip the items according to their index. You then use a list comprehension to iterate through the groups of similar indices, … Read more
MapQuest RouteMatrix is pretty much the same thing: http://www.mapquestapi.com/directions/
You can subclass the ndarray object like: from numpy import ndarray class myarray(ndarray): @property def H(self): return self.conj().T such that: a = np.random.rand(3, 3).view(myarray) a.H will give you the desired behavior. Edit: As suggested by @slek120, you can force to transpose only the last 2 axes with: self.swapaxes(-2, -1).conj() instead of self.conj().T.
You might find some useful results at the bottom of this link http://wiki.scipy.org/PerformancePython From the introduction, A comparison of weave with NumPy, Pyrex, Psyco, Fortran (77 and 90) and C++ for solving Laplace’s equation. It also compares MATLAB and seems to show similar speeds to when using Python and NumPy. Of course this is only … Read more