problem about sparse-matrix-Collection of common programming errors

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  Tweet
  java matrix sparse-matrix matrix-multiplication
  I need simple opinion from all Guru!I developed a program to do some matrix calculations. It work all fine with small matrix. However when I start calculating BIG thousands column row matrix. It kills the speed. I was thinking to do processing on each row and write the result in a file then free the memory and start processing 2nd row and write in a file, so and so forth. Will it help in improving speed? I have to make big changes to implement this change. Thats why I need your opinion. What d
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  amit-agrawal
  r matrix linear-algebra sparse-matrix eigenvalue
  How expensive is it to compute the eigenvalues of a matrix? What is the complexity of the best algorithms? How long might it take in practice if I have a 1000×1000 matrix? I assume it helps if the matrix is sparse?Are there any cases where the eigenvalue computation would not terminate? In R, I can compute the eigenvalues as in the following toy example:> m<-matrix( c(13,2, 5,4), ncol=2, nrow=2 ) > eigen(m, only.values=1) $values [1] 14 3Does anyone know what algorithm it uses? Are the
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  EvilTeach
  c++ memory-management sparse-matrix
  I know there are quite a few good ways to store a sparse matrix without taking up much memory. But I’m wondering whether there is a good way to store a sparse matrix during the construction of it? Here is the more detailed scenario: the program constructs a sparse matrix by figuring out where to put a non-zero value on each iteration; and since the coordinates of the non-zero value will not be known until runtime, they are totally random and unpredictable.I’m programming in C++. So is there a wa
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  user236215
  c++ boost sparse-matrix
  The boost ublas::compressed_matrix should only allocate space for non-zero elements. But in the below example, I am getting strange results.#include <boost/numeric/ublas/matrix_sparse.hpp> #include <boost/numeric/ublas/io.hpp>using namespace std; using namespace boost::numeric::ublas;int main () { {compressed_matrix<double,row_major> m (4, 4, 2*2);cout << sizeof(m) << “\n”; // prints 56cout << m << std::endl; }{matrix<double> m (4, 4);cout <&
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  Chthonic Project
  java matrix sparse-matrix colt
  I am using parallel colt wherein I need to find the rank of a matrix. The API documentation says the following about the following about DoubleAlgebra#rank:rank(DoubleMatrix2D A)Returns the effective numerical rank of matrix A, obtained from Singular Value Decomposition.But when I use it in my code, I get an IllegalArgumentException at runtime:Exception in thread “main” java.lang.IllegalArgumentException: Matrix must be denseat cern.colt.matrix.tdouble.algo.DoubleProperty.checkDense(Unknown Sour
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  GorillaInR
  r matrix sparse-matrix
  Is there a built-in function in either slam package or Matrix package to convert a sparse matrix in simple triplet matrix form (from slam package) to a sparse matrix in dgTMatrix/dgCMatrix form (from Matrix package) ? And is there a built-in way to access non-zero entries from simple triplet matrix ?I’m working in R
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  Amro
  c matlab sparse-matrix mex sparse
  This file is in C:\Program Files\MATLAB\R2013a\extern\examples\refbook. After mex it, I used : aa = [1 2 3 ; 4 5 6] fulltosparse(aa)At the first time, the command maybe works. But try fulltosparse(aa) for more times. You will find it will crash. Could anyone tell me why ? mex -largeArrayDims fulltosparse.c aa = [1 2 3; 4 5 7]; fulltosparse(aa); fulltosparse(aa); fulltosparse(aa); fulltosparse(aa); fulltosparse(aa); fulltosparse(aa);
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  Sean
  matlab machine-learning sparse-matrix pca sparse
  I have about 1000 vectors x_i of dimension 50000, but they are very sparse; each has only about 50-100 nonzero elements. I want to do PCA on this dataset (in MATLAB) to reduce the unneeded extreme dimensionality of the data.Unfortunately, I don’t know any way to do this without an intermediate full matrix due to the need to subtract the means from all examples. And of course, a 1000×50000 matrix is too big to fit into memory (it actually crashes my entire computer for some reason when I try). Ma
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  Veivi
  perl grid sparse-matrix
  I have a Perl script, which parses datafile and writes 5 output files filled with 1100 x 1300 grid. The script works, but in my opinion, it’s clumsy and probably non-efficient. The script is also inherited code, which I have modified a little to make it more readable. Still, it’s a mess.At the moment, the script reads the datafile(~4Mb) and puts it into array. Then it loops through array parsing its content and pushing values to another array and finally printing them to file in another for loop
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  Bill
  java generics sparse-matrix
  I have an assignment where Im supposed to finish the implementation on a generic sparse matrix. Im stuck on the addition part. The matrix is only going to support numbers so I had it extend Number hoping I could then add the numbers, thats wrong. The data structure is NOT an array, it is essentially 2 linked lists. (one for rows and one for columns) Here is the code in question:public MatrixSparse<? extends Number> addition(MatrixSparse<? extends Number> A, MatrixSparse<? extends
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  Adam Siegel
  javascript jquery multidimensional-array sparse-matrix
  I wrote this code to scrape a sparse array from a series of dom elements. when done in one dimension the code works but in 2 dimensions it fails. Is there something i’m missing?23 function initCellHover(){ 24 $cells.each(function(){ 25 var arrayX = $(this).position().left/cellWidth; 26 var arrayY = $(this).position().top/cellHeight; 27 var arrayValue = $(this); 28 cellLookup[ar

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