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Published on 2010-04-28T21:43:18Z
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2010/04/28
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I'm trying to figure out the best way to solve a pentadiagonal matrix. Is there something faster than gaussian elimination?
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Given a large sparse matrix (say 10k+ by 1M+) I need to find a subset, not necessarily continuous, of the rows and columns that form a dense matrix (all non-zero elements). I want this sub matrix to be as large as possible (not the largest sum, but the largest number of elements) within some aspect…
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I have a "SquareMatrix" template class which inherits "Matrix" template class, like below:
SquareMatrix.h:
#ifndef SQUAREMATRIX_H
#define SQUAREMATRIX_H
#include "Matrix.h"
template <class T> class SquareMatrix : public Matrix<T>
{
public:
T GetDeterminant();
};
template…
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I'm trying figure out how to get an OpenGL specified object to be displayed correctly according to the device orientation (ie. according to the gravity vector from the accelerometer, and heading from compass).
The GLGravity sample project has an example which is almost like this (despite ignoring…
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I'm trying figure out how to get an OpenGL specified object to be displayed correctly according to the device orientation (ie. according to the gravity vector from the accelerometer, and heading from compass).
The GLGravity sample project has an example which is almost like this (despite ignoring…
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Hi
I'm learning templates in C++ so I decied to write matrix class which would be a template class. In Matrix.h file I wrote
#pragma once
#include "stdafx.h"
#include <vector>
using namespace std;
template<class T>
class Matrix
{
public:
Matrix();
~Matrix();
GetDataVector();
…
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I have two sparse matrices, m1 and m2:
> m1 <- Matrix(data=0,nrow=2, ncol=1, sparse=TRUE, dimnames=list(c("b","d"),NULL))
> m2 <- Matrix(data=0,nrow=2, ncol=1, sparse=TRUE, dimnames=list(c("a","b"),NULL))
> m1["b",1]<- 4
> m2["a",1]<- 5
> m1
2 x 1 sparse Matrix of class…
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Given a large sparse matrix (say 10k+ by 1M+) I need to find a subset, not necessarily continuous, of the rows and columns that form a dense matrix (all non-zero elements). I want this sub matrix to be as large as possible (not the largest sum, but the largest number of elements) within some aspect…
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I'm looking for an a command or trick to convert two arrays to a sparse matrix. The two arrays contain x-values and y-values, which gives a coordinate in the cartesian coordinate system. I want to group the coordinates, which if the value is between some value on the x-axes and the y-axes.
% MATLAB
x_i…
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Hi,
I have a m x n matrix where each row consists of zeros and same values for each row.
an example would be:
M = -0.6 1.8 -2.3 0 0 0; 0 0 0 3.4 -3.8 -4.3; -0.6 0 0 3.4 0 0
In this example the first column consists of 0s and -0.6, second 0 and 1.8, third -2.3 and so on.
In such case I would like…
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The following code runs too slowly even though everything seems to be vectorized.
from numpy import *
from scipy.sparse import *
n = 100000;
i = xrange(n); j = xrange(n);
data = ones(n);
A=csr_matrix((data,(i,j)));
x = A[i,j]
The problem seems to be that the indexing operation is implemented…
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