Installing the scientific computing package numpy and SciPy in Python

In Python, most toolkit installation is simple. You only need to execute the & ldquo; pythonsetup. pyinstall & rdquo; command. However, the installation process is complicated due to the dependency between SciPy and numpy scientific computing packages. Online tutorials are messy and cannot be used. After carefully studying the README and INSTALL in each package, the installation was successful. The following is a record. System Environment: OS: RedHat5Pytho

In Python, the installation of most toolkit is very simple. You only need to execute the "python setup. py install" command. However, the installation process is complicated due to the dependency between SciPy and numpy scientific computing packages. Online tutorials are messy and cannot be used. After carefully studying the README and INSTALL in each package, the installation was successful. The following is a record.

System Environment:
OS: RedHat5
Python version: Python2.7.3
Gcc version: 4.1.2

Installation Package versions:
Scipy-0.11.0
Numpy-1.6.2
Nose-1.2.1
Lapack-3.4.2
Atlas 3.10.0
Dependency: the installation of scipy depends on numpy, lapack, and atlas (the latter two are linear algebra toolkit, and google is unclear ...), The running of numpy and sci test programs depends on nose. Therefore, the entire installation process must be executed in sequence. Otherwise, the installation process cannot proceed.

Installation steps:
1. Install nose
This installation is relatively simple. decompress the nose Installation File, enter the nose directory, and run setup. py directly:
Tar-zxvf nose-1.2.1.tar.gz
CDS nose-1.2.1
Python setup. py install
2. Install lapack
Because the latest version of ATLAS can be directly integrated with the lapack installation compressed file for compilation, if you only use it in python, you do not need to install lapack. Just download the compressed file: lapack-3.4.2.tgz.
3. Install ATLAS
This installation mainly involves configuration of some options, including configuration to 64-bit library files, location-independent and shared link libraries. Detailed configuration instructions are in the PDF file under the atlas installation package doc. Available.
The following is my installation process:
Tar-jxvf atlas3.10.0.tar.bz2
Cd ATLAS
Mkdir obj64
.. /Configure-B 64-Fa alg-fPIC-shared -- prefix =/configure the atlas installation path/atlas -- with-netlib-lapack-tarfile =/lapack install the directory where the compressed files are stored lapack-3.4.2.tgz
(Note: This configuration takes about 1 hour for Core i7 processing)
Make
(The following are some inspection procedures to ensure that there is no problem before installation)
Make check
Make time
Make install
So far, the installation of atlas is complete. However, we need to record the fortran compiler type used in the compilation process. This information should be used when numpy and scipy are installed below. Or in the directory obj64/, execute
Fgrep 'f77 = 'make. inc
We can see that F77 = gfortran
Write down this compiler type gfortran.
4. Install numpy
The numpy and scipy installation processes must explicitly specify the type of the fortran compiler used, and be consistent with the previous compilation of atlas (in this article: gfortran), which is very important, otherwise, many functions will go wrong.
First, configure the site. cfg file under the numpy directory to specify the location of the atlas Library:
Tar-zxvf numpy-1.6.2.tar.gz
Cd numpy-1.6.2
Cp site. cfg. example site. cfg
Vim site. cfg
The configuration format is as follows:
[DEFAULT]
Library_dirs =/usr/local/lib:/atlas installation directory/atlas/lib
Include_dirs =/usr/local/include:/atlas installation directory/include
[Blas_opt]
Libraries = f77blas, cblas, atlas
[Lapack_opt]
Libraries = lapack, f77blas, cblas, atlas
[Amd]
Amd_libs = amd
[Umfpack]
Umfpack_libs = umfpack
Next, configure the required Fortran compiler type for numpy installation:
If the previous Fortran compiler is gfortran, run:
Pythonsetup. py build -- fcompiler = gnu95
If the previous Fortran compiler is g77, run:
Python setup. py build -- fcompiler = gnu
Then execute
Python setup. py install
Installation Complete
5. Install scipy
Similar to installing numpy:
Tar-zxvf scipy-0.11.0.tar.gz
Cd scipy-0.11.0
Vim site. cfg
The configuration format is as follows:
[DEFAULT]
Library_dirs =/usr/local/lib:/atlas installation directory/atlas/lib
Include_dirs =/usr/local/include:/atlas installation directory/include
[Blas_opt]
Libraries = f77blas, cblas, atlas
[Lapack_opt]
Libraries = lapack, f77blas, cblas, atlas
[Amd]
Amd_libs = amd
[Umfpack]
Umfpack_libs = umfpack
Next, configure the required Fortran compiler type for numpy installation:
If the previous Fortran compiler is gfortran, run:
Python setup. py build -- fcompiler = gnu95
If the previous Fortran compiler is g77, run:
Python setup. py build -- fcompiler = gnu
Then execute
Python setup. py install
Installation Complete
Then you can run the corresponding test program in python:
Python
>>> Import nose
>>> Import numpy
>>> Import scipy
>>> Numpy. test ('full ')
Wait ....
>>> Scipy. test ('full ')
The entire installation process ends.

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