If you need to do a LU decomposition of a Scipy Sparse Matrix (pretty useful for solving systems of differential equations), keep in mind that Cholesky decomposition is generally more stable and rapid for the Hermitian Symmetric positive definite matrixes. In my case, the default LU decompsition method from scipy.sparse.linalg was failing because of the procedural problems.
However you cannot just apply Numpy.linalg.cholesky because the a scipy.sparse.lil_matrix is seen as a linked list and is not a 2D matrix. A solution for this is to use the cholesky decomposition from the scikit.sparse module
First of all, if you have weird errors while trying to install neo4j server on a machine running under CentOS, it looks like you are trying to perform installation from a folder within your $HOME directory. Which the newly created neo4j user (if you do a default installation) won’t be able to access. In order to avoid it, unpack the neo4j-community-x.x.x package to the /opt/ directory and
You will also need to install the Oracle Java to support the neo4j installation. A good explanation of how to do it can be found on the ubuntu stack overflow. To sum up:
sudo apt-get install python-software-properties
sudo add-apt-repository ppa:webupd8team/java
sudo apt-get update
sudo apt-get install oracle-java8-installer
sudo apt-get install oracle-java8-set-default
Only install oracle java as default if you don’t have other programs relying on the
If you meet the “java heap out of space error”, what you have to do is to go to the $NEO4J_HOME directorty (where you’ve installed the neo4j files), then to config and then in the neo4j-wrapper.conf file edit the following lines:
wrapper.java.initmemory = 64
wrapper.java.maxmemory = 512 (increase to 1-4 Gb if you have >4Gb of RAM)
On CentOS 5 and 6 you unfortunately cannot install a newer version of python instead of the default one, because the package controller “yum” depends on it. The only way to go is to make an altinstall. The following article describes it really well:
in order to make python2.7 command available to the root now (typically for the module installation), add python2.7 to root’s path:
Now you can safely install all the fancy python modules you want. Well, almost all.
Building Scipy with alternative install of Python isn’t really a piece of cake neither, since it requires to first install LAPACK, ATLAS and BLAS packages, which is not completely direct for complete newcomers. This tutorial explains well how to do it exactly:
Btw, once you’ve installed all the modules listed in the link above, you can just do
sudo pip install scipy
and wait until it finishes compiling.