VOCAL is still in it’s early stages of development, and does not yet offer an in-depth installer. As a result running VOCAL requires you to setup the development environment, which can be tricky for those not well versed in programming. We’ve tried to be as descriptive as possible in our installation guide for both Windows [1] , Linux and Mac users. If you have any questions or trouble installing VOCAL, feel free to ask for help from the support page and describe your issue to us.


Please read our developer documentation before developing yourself!

Windows [1]

  1. Download Python Anaconda 2.7
  2. Open a terminal, navigate to the Anaconda installation directory and type conda install numpy , y
  3. Grab the basemap package conda install basemap, y
  4. install pillow conda install pillow, y
    • Ensure you have pillow, rather than PIL. Pillow is a newer and updated version of PIL
  5. To install CCPLOT:
  6. Optional:
    • If using Eclipse [2]:
      • within Eclipse, go to help –> Install New Software
      • under Windows –> Preferences –> PyDev –> Interpreters –> Python
        • “Advanced Auto Config” or manually find Anaconda
      • import the existing “CALIPSO_Visualizer” package under the file menu
    • If using PyCharm: Simply set the python interpreter to the one supplied by anaconda.
  7. Download the zip from the GitHub or use Git (see cloning the repository <dev/startdev#Clone-the-Repository>)
  8. Using command prompt or bash, cd into the VOCAL/calipso folder and use python
    • If using Eclipse or Pycharm, use their built-in tools to clone the repository from GitHub

Linux [3]


At this time, Linux and OS X have not been tested with the current version of VOCAL. Installation may not work

  1. start off by grabbing the SciPy Stack
    • sudo apt-get install python-numpy python-scipy python-matplotlib
  2. install basemap
    • sudo apt-get install python-mpltoolkits.basemap
  3. installing CCPLOT
    • CCPLOT has quite a bit of dependencies, so run
      • sudo apt-get install --no-intall-recommends cython libhdf4-dev libhdfeos-dev python-imaging ttf-bitstream-vera
    • now CCPLOT needs to be built on Linux, so grab the source
    • extract the source anywhere you’d like, the directory does not matter
    • cd into the CCPLOT folder you just extracted
    • run python build
    • note if python cannot find HdfEosDef.h
      • run dpkg -L
      • search for the location of HdfEosDef.h, it is commonly found in usr/include/x86_64-linux-gnu/hdf/
      • open in the CCPLOT folder, and change line 24 to include your path
      • the new line would like similar to hdf_include_dirs = ['/usr/include/x86_64-linux-gnu/hdf', '/usr/include/hdf', '/usr/local/include/hdf/', '/opt/local/include']
      • rerun python build
    • run python install , sudo may be required as well
    • CCPLOT should be installed
  4. install bokeh.color
    • sudo pip install bokeh
  5. run the application with python

OS X [4]

  1. install XCode

    • if using OS 10.9, install xcode 6.2
  2. install macport

    • if port command not found in terminal, edit paths by

      • sudo vi /etc/paths
      • add the following lines:
        • /opt/local/bin
        • /opt/local/sbin
      • restart terminal
    • do port selfupdate

      • if you receive the error *‘rsync: failed to connect to <address> : connection

        refused (61) ...’*

        • it is likely your firewall is preventing access to the address ref
        • navigate to /opt/local/etc/macports in your terminal
        • open sources.config with admin access sudo vim sources.conf
        • comment out the last line, replace it with [default] ref
        • run port -v -d sync
        • run port search hdf4
        • you should have queries show up, meaning ports it working!
  3. run sudo port install hdf4 hdfeos py27-cython py27-numpy py27-matplotlib py27-matplotlib-basemap

  4. as root, do the following commands

    • mv /usr/bin/python /usr/bin/python.orig
    • ln -s /opt/local/bin/python /usr/bin/python
    • run port select --set python python27
  5. download ccplot-1.5.tar.gz from here

    • run tar xzf ccplot-1.5.tar.gz
    • cd ccplot-1.5.tar.gz
    • python build
    • python install --user
    • ccplot -v
    • and ccplot should be a recgonizable command!
  6. Install bokeh port install py27-bokeh

  7. Install sqlalchemy port install py27-sqlalchemy

  8. download the IDE of your choice, or run python


[1](1, 2) x86 (32bit) is currently the only supported architecture for windows
[2]Eclipse and Pycharm are not mandatory, but a development environment is recommended. Both are good options
[3]The packages specified in the instructions may not be comprehensive, if additional packages are required please inform the team so they can correctly add them to the docs
[4]Tested on OS X 9.5