Numpy/Scipy/Matplotlib on Raspberry Pi

Notice:  The method posted here worked great and was faster.  Try this first:

If that does not work then try this:

Ok, so this is the second time I had to stumble through this. Here the commands I used to finally get it to work. Total compile time was a few hours. The third and forth steps, contributed by Ty Rudder, are for an optional performance boost.

$ sudo apt-get install libblas-dev        ## 1-2 minutes
$ sudo apt-get install liblapack-dev      ## 1-2 minutes
[$ sudo apt-get install python-dev        ## Optional]
[$ sudo apt-get install libatlas-base-dev ## Optional speed up execution]
$ sudo apt-get install gfortran           ## 2-3 minutes
$ sudo apt-get install python-setuptools  ## ?
$ sudo easy_install scipy                 ## 2-3 hours
$ ## previous might also work: python-scipy without all dependencancies
$ sudo apt-get install python-matplotlib  ## 1 hour

… and the result is being able to do some nice processing on this blood pressure data. Below is 200 Hz pressure data, bandpass filtered between .5 and 5 Hz. You can clearly see the arterial pulses.

While I am jotting down hints, here is how to forward your X11 windows as root though ssh.

  1. From remote $ ssh -X pi@ # change to pi’s IP address
  2. On Raspberry Pi $ sudo cp /home/pi/.Xauthority /root
  3. Now run your graphical program.  Window should display on remote computer.

Install Node (install webide or from source…):

  1. Download tarball from
  2. ./configure
  3. make
  4. make install 

Install simplejson (easy_install simplejson)

Install PIL (sudo apt-get install python-imaging)

Install PySerial (sudo apt-get install python-serial)

when installing power switch without RTC– both scripts rely on /etc/rc.local  if hwclock is not found, then script exits and does not run  FIX: run before hwclock

FIX SD CARD: use Ubuntu boot disk creator to format disk, then dd newest distro