I have implemented a script that does constrained optimization for solving the optimal parameters of Support Vector Machines model. I noticed that my script for some reason gives inaccurate results (although very close to the real value). For example the typical situation is that the result of a calculation should...

I've a two matrices A = [0 0 0; 0 0 0; 0 0 0] and B = [2 3 4;] How will I get A = [0 0 0; 2 3 4; 0 0 0]...

I have the following code: //Start MPI... MPI_Init(&argc, &argv); int size = atoi(argv[1]); int delta = 10; int rnk; int p; int root = 0; MPI_Status mystatus; MPI_Comm_rank(MPI_COMM_WORLD, &rnk); MPI_Comm_size(MPI_COMM_WORLD, &p); //Checking compatibility of size and number of processors assert(size % p == 0); //Initialize vector... double *vector = NULL;...

I wanted to make matrix of points and rotate them for a custom angle. I get a bunch of 0's when I enter the desired angle, can't figure out why. Might be a pretty simple mistake, I'm kind of new to programming in C, trying to learn. Here's my code:...

This question already has an answer here: Create a matrix with A(i, j) = i*j 3 answers I want to declare a function that takes (n, m) as inputs an return mt as a n-by-m matrix. and if I assume that the row number (rn) and the column number...

By matrix multiplication I get the following matrix, which, let's say, shows how many customers who purchased product A, sooner or later, also purchased product B, product C and so on. Obviously, the diagonal values represent 100% of all purchases of a particular product. I'm looking for a way of...

this here is an attempt to a Hill Cipher, so far so good until multiplication of the 2nd and 3rd trigram. I really don't understand where my mistake is. Basicly what I have to do is a list multiplication. with this code I create a list of list key=[k[x:x+3] for...

I'm learning three.js and am trying to multiply two translation matrices together to get a single matrix that describes both translations: | 1 0 0 -2 | | 1 0 0 3 | | 0 1 0 7 | * | 0 1 0 4 | | 0 0 1...

In MATLAB I want to multiply an Nx4 matrix by a 4xN matrix and get an Nx1 vector out of it. I'm also dividing the result element-wise by another vector. In a loop, it would be: A=rand(10,4); B=rand(4,10); L=rand(10,1); for i=1:10 result(i)=A(i,:)*B(:,i)/L(i); end The only non-loop method I can think...

The given task is to call a function from within another function, where both functions are handling matrices. Now lets call this function 1 which is in its own file: A = (1/dot(v,v))*(Ps'*Ps); Function 1 is called with the command: bpt = matok(P); Now in another file in the same...

I have two arrays to compare. Label True/False from a comparing b : a=c(2.9,3.7,3.8, 2.7,3.3, 3.9) and b=c(18,21, 30 ,21, 17, 27) And I use compare=outer(a,a,'>=') & outer(b,b,'>=') # Return True if a[1]>=a[2] and b[1]>=b[2], etc to get a boolean matrix: [,1] [,2] [,3] [,4] [,5] [,6] [1,] TRUE FALSE...

I have matrix A and matrices [U,S,V], such that [U, S, V] = svd(A). How could I amend my script in matlab to get the 10 columns of U that correspond to the 10 largest singular values of A (i.e. the largest values in S)? Thanks...

I'm not really sure how to word this correctly but I would like to count the number of times there are similarities among the columns. Imagine I have the 3 NFL teams listed below. Zeroes are losses and ones are victories. The rows are the week of the NFL season....

In the case of multiple of same matrix matA, like matA.transpose()*matA, You dont have to compute all result product, becouse the result matrix is symmetric(so only if the m>n), in my specific case is always symmetric! square. So ith enough the compute only for. ex. lower trinagular part and rest...

Currently, I made a neural networks program in the cuda c. Because I needed to manipulate the matrix multiplication, I did not use CUBLAS for MM. I use the following code for MM. I was wondering if any one has some advice to make it faster which can be very...

I have a large data matrix and I want calculate the similarity matrix of that large matrix but due to memory limitation I want to split the calculation. Lets assume I have following: For the example I have taken a smaller matrix data1 = data/np.linalg.norm(data,axis=1)[:,None] (Pdb) data1 array([[ 0. ,...

I am trying to do an element-wise multiplication for two large sparse matrices. Both are of size around (400K X 500K), with around 100M elements. However, they might not have non-zero elements in the same positions, and they might not have the same number of non-zero elements. In either situation,...

I am wondering is there a way of calculating matrix multiplication using NumericMatrix and NumericVector class. I am wondering if there is any simple way to help me avoid the following loop to conduct this calculation. I just want to calculate X%*%beta. // assume X and beta are initialized and...

Let m, n be integers such that 0<= m,n< N. Define: Algorithm A: Computes m + n in time O(A(N)) Algorithm B: Computes m*n in time O(B(N)) Algorithm C: Computes m mod n in time O(C(N)) Using any combination of algorithms A, B and C describe an algorithm for N...

I'm building a suite of functions to work with a multidimensional-array data structure and I want to be able to define arbitrary slices of the arrays so I can implement a generalized inner product of two arbitrary matrices (aka Tensors or n-d arrays). An APL paper I read (I honestly...

An algorithm I'm working on requires computing, in a couple places, a type of matrix triple product. The operation takes three square matrices with identical dimensions, and produces a 3-index tensor. Labeling the operands A, B and C, the (i,j,k)-th element of the result is X[i,j,k] = \sum_a A[i,a] B[a,j]...

I have a matrix, say, P of size (X,Y). Also, I have two matrices, say, Kx and Ky of size (M,N) both, a matrix pk of size (M,N) and two vectors u and v of X and Y respectively. For example, they can be defined as follows: import numpy as...

I'm currently developing a CrossPlatform Graphic Engine, and the performance analysis says that I should optimize the matrixmultiplication. Y check the matrices for modifications so I don't update the matrices if there is no change, but anyway, the world matrix multiplications are using a lot of processing percent. Is there...

a = 1 2 3 b = 1 2 3 a.*b ans = 1 2 3 2 4 6 3 6 9 I used the .* operator to multiply a row vector and a column vector in Octave to see the results. I dont understand how the answer is obtained....

I'm trying to multiple two matrices, A and B, where B has more columns than A using python and numpy preferably. Example: A = numpy.matrix([[2,3,15],[5,8,12],[1,13,4]], dtype=numpy.object) B = numpy.matrix([[2,15,6,15,8,14],[17,19,17,7,18,14],[24,14,0,24,2,11]], dtype=numpy.object) ( A*B ) = [[415,297,63,411,100,235],[434,395,166,419,208,314], [319,318,227,202,250,240]] I've found some examples if they are arrays but none if they are matrices....

EDITED (the example contained mistake so I replaced it with another one) The following code is just an example how does it work: CATransform3D temp = CATransform3DIdentity; temp.m34 = -0.002; temp = CATransform3DTranslate(temp, 0, -230, 0); temp = CATransform3DRotate(temp, -M_PI / 5, 1, 0, 0); temp = CATransform3DTranslate(temp, 0, 230,...

We've got a columnvector m x 1 and a matrix m x n. For the value in row i in the columnvector we want to multiply this value with each value in the same row i of the matrix, and then sum all of these up. This is to be...

During my acquaintance with CUDA in Python (numba lib), I implemented matrix provide methods: Just with numpy.dot() Strassen algorithm with numpy.dot() Blocks method on GPU Strassen algorithm on GPU So I tested it on 2 types of data: numpy.random.randint(0, 5, (N, N)) # with int32 elements numpy.random.random((N, N)) # with...

I have written this program and I am having some trouble understanding how to use multiple blocks by using dim3 variable in the kernel call line. This code works fine when I am doing 1000*1000 matrix multiplication, but not getting correct answer for lower dimensions like 100*100 , 200*200. #include...

I'm doing some large stochastic matrices (at least 1000x1000) calculation in C++, using the Eigen Library, my code consists of the following functions : Eigen::VectorXd grid(...); initializes (element by element) a sorted vector of log-normally distributed values, using the quicksort algorithm and the ran1 algorithm, let's say of size N,...

I am trying to speed up matrix multiplication on multicore architecture. For this end, I try to use threads and SIMD at the same time. But my results are not good. I test speed up over sequential matrix multiplication: void sequentialMatMul(void* params) { cout << "SequentialMatMul started."; int i, j,...

I'm attempting to add a small value to a World Matrix in order to replicate the accuracy of a fired weapon [pistol, assault rifle] Currently, my World Matrix resides at a Parent Objects' position, with the ability to rotate about the Y axis exclusively. I've done this in Unity3D, running...

If I have a numpy.ndarray A and a scipy.sparse.csc_matrix B, how do I take A dot B? I can do B dot A by saying B.dot(A), but the other way I can only think of this: B.T.dot(A.T).T Is there a more direct method to do this? ...

I'm working on a threaded implementation of matrix multiplication to work with my custom Matrix class, and I'm running into some issues with speed-up. Setting up and calling the operation looks like this: Matrix<double> left(2,2); left[0][0] = 1; left[0][1] = 2; left[1][0] = 3; left[1][1] = 4; Matrix<double> right(2,2); right[0][0]...

Let matrices a, b be [ 1, 2, 3, 4 ] i.e of (1 x 4) dimension. On applying numpy.dot(a, b) the result is 30 instead of raising exception that both the matrices shapes are not aligned. How can a (m x n) matrix be multiplied with (m x n)...