I just went through the frustrating but in the end rewarding experience of trying to install numpy in my school computing RHEL5 environment where I don't have sudo privileges or much control over the environment. In the end, I learned quite a bit!

My first attempt to install was through the normal path, where I activate a virtual environment created with virtualenv and then use pip to install numpy:

cd ~
virtualenv venv
source venv/bin/activate
pip install numpy

But trying to build numpy in my environment led to this error:

ImportError: home/venv/lib/python2.7/site-packages/numpy/linalg/lapack_lite.so: undefined symbol: zgelsd_

So that's the clue - something is wrong with the lapack library numpy is trying to use from my environment. It's probably linked against something broken or something incompatible... or something missing.

Here's what ldd on the broken lapack_lite.so gives:

ldd home/venv/lib/python2.7/site-packages/numpy/linalg/lapack_lite.so
        linux-vdso.so.1 =>  (0x00007fff08126000)
        libpython2.7.so.1.0 => not found
        libpthread.so.0 => /lib64/libpthread.so.0 (0x00002b39c2bc9000)
        libc.so.6 => /lib64/libc.so.6 (0x00002b39c2de5000)
        /lib64/ld-linux-x86-64.so.2 (0x0000003185e00000)

So, after some searching around, it seems like the best option was to compile the OpenBlas library and use that during the numpy build. I was able to salvage bits from this, and this to get it to work.

Build OpenBlas

Untar the OpenBlas distribution available here and build using the makefile:

make BINARY=64 FC=gfortran USE_THREAD=1
make PREFIX=/path/to/openblas install

where /path/to/openblas is the path where you'd like to install openblas. Again, since I did have sudo privilegs, I chose a non-standard location.

Build Numpy

We need to build numpy and link it with the OpenBlas library. I couldn't achieve this with the default pip install, so things had to be done manually as suggested in this post:

source venv/bin/activate
pip uninstall numpy # Uninstall the broken installation
mkdir venv/download
pip install -d venv/download numpy
mkdir venv/build
cd venv/build
tar xzf ../download/numpy-1.9.0.tar.gz
cd numpy-1.9.0

In the numpy-1.9.0 directory, create the site.cfg file to customize the libraries that numpy uses on install. We need to point things to OpenBlas. Check out the site.cfg.example file for what options you can set. This worked for me:

[DEFAULT]
library_dirs = /path/to/openblas/lib
include_dirs = /path/to/openblas/include

[atlas]
atlas_libs = openblas
libraries = openblas

[openblas]
libraries = openblas
library_dirs =  /path/to/openblas/lib
include_dirs =  /path/to/openblas/include

Next, build numpy being sure to specify the same fortran compiler that was used to build the OpenBlas library (important point mentioned in the scipy install docs). For good measure, I cleaned out all of the standard compile and linking flags from my environment to make sure I wasn't contaminating the build:

unset CPPFLAGS
unset LDFLAGS
python setup.py build --fcompiler=gnu95

When the build completes, install:

python setup.py install

Since the virtual environment is active, this will install to the virtual environment.

Finally, here's what ldd on the working lapack_lite.so library gives:

ldd home/venv/lib/python2.7/site-packages/numpy/linalg/lapack_lite.so
(venv)bash-3.2$ ldd lapack_lite.so
        linux-vdso.so.1 =>  (0x00007ffff40b9000)
        libopenblas.so.0 => ../lib/libopenblas.so.0 (0x00002b098e0a1000)
        libpython2.7.so.1.0 => not found
        libgfortran.so.3 => .../libgfortran.so.3 (0x00002b098f00c000)
        libm.so.6 => /lib64/libm.so.6 (0x00002b098f331000)
        libgcc_s.so.1 => .../libgcc_s.so.1 (0x00002b098f5b4000)
        libquadmath.so.0 => .../libquadmath.so.0 (0x00002b098f7cb000)
        libc.so.6 => /lib64/libc.so.6 (0x00002b098fa07000)
        libpthread.so.0 => /lib64/libpthread.so.0 (0x00002b098fd60000)
        /lib64/ld-linux-x86-64.so.2 (0x0000003185e00000)

Looks much healthier! (I've shortened some of the library paths)

Summary

I was able to install numpy by first building and installing OpenBlas to a non-standard location, and then manually building numpy by creating the site.cfg file to point to the OpenBlas libraries and specifying which Fortan compiler to use.