I'm writing a program in C that adds two matrices (I'm also using BLAS). I want to see how this is done in numpy, to make sure I do matrix addition efficiently:
https://github.com/numpy/numpy
Can anyone help me find the C source code in numpy Github repository that does matrix addition?
Related
I am ultimately trying to create a pseudoinverse function using svd methodology. I want to first create a SVD function that will give me the U, E and V matrices that I will later use in the formula below to get the pseudoinverse:
I am not sure how to code these matrices. I understand how to do this by hand through eigen values and vectors but not sure how to translate that to c code.
I have already created functions for Transpose and matrix multiplication. Now its a matter of finding these 3 matrices.
You can see a similar asked question with a link to a source file.
They recommend to use openCV built-in function - you can find it here - the purpose is to use a ready function from the openCV library.
I am quite new to vba coding. I have written a code which reads some data generates a matrix and a vector inverts the matrix and then multiples the inverted matrix with the vector, so nothing big. But now I want that the elements of the matrix and vector are strings or symbols. I hope that i will be able to get a more general solution. Is this somehow possible? Both objects are arrays.
The stringe i use do not have numerical values. In other words I am looking for a oppertunity to calculat with symbols like an algebra program like mathematica or maxia does.
I've used x=B/A (mrdivide) in Matlab to find x in equation xA=B. I am trying to achieve this without Matlab environment using a C based fixed point library for microcontrollers called libfixmatrix.
How would I proceed with using QR Decomposition and Solve function's of libfixmatrix to solve xA=B?
QR Decomposition and Solving is equivalent to solving for Ax=B. But I have a scenario where x is in equation xA=B
It was mentioned in the readme of the repository that :
Libfixmatrix is suited well for tasks involving small matrices (often
less than 10x10)
Is it efficient to use libfixmatrix for say 80*80 ?
just a silly suggestion:
x.A = B
x.A.inverse(A) = B.inverse(A)
x = B.inverse(A)
So you just need to compute Inverse matrix and matrix multiplication which are basic operations. Use Sub-determinant approach. Also if A,B are not square matrices resize them so they are.
I have some matrices in Matlab that I need to load as arrays in C. I used the dlmwrite function in MATLAB to do this. Can someone link to a tutorial on how to load in C? Or maybe there’s already a function someone has written that can do this?
Also, just curious how long this process takes to load. The matrices aren’t terribly large, with the largest being 3136 by 2. I’ve switched to C for this particular application since it’s proving to be much faster than MATLAB, but I don’t want to slow the C code down too much by loading too much stuff.
I’m being a bit lazy by not translating part of my code to C (it’s a mesh generator that I didn’t write, so I don’t know the finer details), but this would make my life a lot easier.
There is a C API for reading MATLAB .MAT files.
http://www.mathworks.se/help/matlab/read-and-write-matlab-mat-files-in-c-c-and-fortran.html
I know that Intel Fortran has libraries with functions and subroutines for working with sparse matricies, but I'm wondering if there is also some sort of data type or automated method for creating the sparse matricies in the first place.
BACKGROUND: I have a program that uses some 3 & 4 dimensional arrays that can be very large in the first 2 dimensions (~10k to ~100k elements in each dimension, maybe more). In the first 2 dimensions, each array is mostly (95% or so) populated w/ zeroes. To make the program friendly to machines with a "normal" amount of RAM available, I'd like to convert to sparse matricies. The manner in which the current conventional arrays are handled & updated throughout the code is pretty dependent on the code application, so I'm looking for a way to convert to sparse matrix storage without significant modification to the code. Basically, I'm lazy, and I don't want to revise the entire memory management implementation or write an entire new module where my arrays live and are managed. Is there a library or something else for Fortran that would implement a data type or something so that I can use sparse matrix storage without re-engineering each array and how it is handled? Thanks for the help. Cheers.
There are many different sparse formats and many different libraries for handling sparse matrices in Fortran (e.g. sparskit, petsc, ...) However, none of them can offer that compact array handling formalism, which is available in Fortran for intrinsic dense arrays (especially the subarray notation). So, you'll have to touch your code at several places, when you want to change it to use sparse matrices.