lapack

LAPACK inversion routine strangely mixes up all variables

我怕爱的太早我们不能终老 提交于 2020-01-25 02:19:10
问题 I'm programming in fortran and trying to use the DGETRI matrix inverter from the Lapack package: http://www.netlib.org/lapack/explore-html/df/da4/dgetri_8f.html But very strangely it seems to be messing with all my variables. In this very simple example, my matrix A initialised at the beginning of the program changes as DGETRI is applied, even though DGETRI doesn't involve A… Can anybody tell me what is going on? Thanks! PROGRAM solvelinear REAL(8), dimension(2,2) :: A,Ainv REAL(8)

dangerous behavior of lapack routin zheev [duplicate]

有些话、适合烂在心里 提交于 2020-01-24 21:27:28
问题 This question already has answers here : Incorrect/inconsistent results from zgeev() LAPACK (2 answers) Closed 2 years ago . I stumbled upon an odd behavior when using the lapack routine zheev() . There are two issues which I do not understand 1) One of my global variables seems to be overwritten by zheev() . The following small program shows it: [compiled with gfortran -o test test.f90 -llapack -lblas ] program test implicit none integer, parameter :: dp = 8 integer, parameter :: dim = 3

Any reason why Octave, R, Numpy and LAPACK yield different SVD results on the same matrix?

佐手、 提交于 2020-01-22 18:38:10
问题 I'm using Octave and R to compute SVD using a simple matrix and getting two different answers! The code is listed below: R > a<-matrix(c(1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,0,0,0,0,0,0,1,1,1,0,0,0,0,0,0,0,0,0,1,1,1), 9, 4) > a [,1] [,2] [,3] [,4] [1,] 1 1 0 0 [2,] 1 1 0 0 [3,] 1 1 0 0 [4,] 1 0 1 0 [5,] 1 0 1 0 [6,] 1 0 1 0 [7,] 1 0 0 1 [8,] 1 0 0 1 [9,] 1 0 0 1 > a.svd <- svd(a) > a.svd$d [1] 3.464102e+00 1.732051e+00 1.732051e+00 1.922963e-16 > a.svd$u [,1] [,2] [,3] [,4] [1,] -0.3333333 0.4714045

numpy.disutils.system_info.NotFoundError: no lapack/blas resources found

点点圈 提交于 2020-01-17 05:37:07
问题 Problem: Linking numpy to correct Linear Algebra libraries. Process is so complicated that I might be looking for the solution 6th time and I have no idea whats going wrong. I am on Ubuntu 12.04.5. I reinstalled blas and lapack and then reinstalled numpy using pip. I did that in system environment and then also tried in virtualenv environment. None of the things seem to be working. Here is my numpy.__config__.show() : lapack_info: NOT AVAILABLE lapack_opt_info: NOT AVAILABLE openblas_lapack

Do BLAS and LAPACK libraries comply with MISRA standard?

血红的双手。 提交于 2020-01-16 08:35:55
问题 I guess the answer is no . However, I was wondering if someone has some insight into this topic. Do BLAS and LAPACK libraries comply with MISRA standards? The MISRA standards (MISRA C:1998, MISRA C:2004, MISRA C:2012) are extremly demanding, and I believe that BLAS and LAPACK libraries do not comply with it. Hence, I should not use such libraries if my software project demands MISRA compliance. Any insight into this question would be extremly appreciated :) 回答1: Unless the library is actively

I can't allocate memory for bigger matrices then ~200x200 Lapack Visual Studio in C Here is my code [duplicate]

久未见 提交于 2020-01-07 09:42:16
问题 This question already has answers here : What and where are the stack and heap? (25 answers) Closed 5 years ago . I am bench-marking the execution time of solving matrices , and i cant get more then ~200x200, i should go probably 1500x1500 or close to that. I am running this on VS . #include <stdlib.h> #include <stdio.h> #include "lapacke.h" #include "lapacke_config.h" #include <time.h> /* Auxiliary routines prototypes */ extern void print_matrix(lapack_complex_double *a, int m, int n);

Is it possible to solve a non-square under/over constrained matrix using Accelerate/LAPACK?

眉间皱痕 提交于 2020-01-05 19:22:59
问题 Is it possible to solve a non-square under/over constrained matrix using Accelerate/LAPACK? Such as the following two matrices. If any variables are under constrained they should equal 0 instead of being infinite. So in the under constrained case: A, D & E would equal 0, while B, C & F equal -1. In the over constrained case all variables would be equal to -1. Under Constrained: ____ ____ | (A) (B) (C) (D) (E) (F) | | -1 0 0 1 0 0 | 0 | | 1 0 0 0 -1 0 | 0 | | 0 -1 1 0 0 0 | 0 | | 0 1 0 0 0 -1

Linking LAPACK/BLAS libraries

ぐ巨炮叔叔 提交于 2020-01-05 08:32:20
问题 Background: I am working on a project written in a mix of C and Fortran 77 and now need to link the LAPACK/BLAS libraries to the project (all in a Linux environment). The LAPACK in question is version 3.2.1 (including BLAS) from netlib.org. The libraries were compiled using the top level Makefile (make lapacklib and make blaslib). Problem: During linking, error messages claimed that certain (not all) BLAS-routines called from LAPACK-routines were undefined. This gave me some headache but the

Linking LAPACK/BLAS libraries

北城以北 提交于 2020-01-05 08:32:13
问题 Background: I am working on a project written in a mix of C and Fortran 77 and now need to link the LAPACK/BLAS libraries to the project (all in a Linux environment). The LAPACK in question is version 3.2.1 (including BLAS) from netlib.org. The libraries were compiled using the top level Makefile (make lapacklib and make blaslib). Problem: During linking, error messages claimed that certain (not all) BLAS-routines called from LAPACK-routines were undefined. This gave me some headache but the

Does the EPD Free distribution use MKL?

你离开我真会死。 提交于 2020-01-05 07:38:22
问题 According to the Enthought website, the EPD Python distribution uses MKL for numpy and scipy. Does EPD Free also use MKL? If not does it use another library for BLAS/LAPACK? I am using EPD Free 7.3-2 Also, what library does the windows binary installer for numpy that can be found on scipy.org use? 回答1: The EPD Free 7.3 installers do not include MKL. The BLAS/LAPACK libraries which they use are ATLAS on Linux & Windows and Accelerate on OSX. 回答2: According to this table, EPD Free 7.3 does not