User Guide

Getting started

This guide is for people who want to use FDP on the PPPL Linux cluster. If you wish to contribute to the FDP project as a developer, see the developer guide.

To use FDP on the PPPL Linux cluster, load the module nstx/fdp (you may need to unload other nstx modules):

[sunfire06:~] % module load nstx/fdp

[sunfire06:~] % module list
Currently Loaded Modulefiles:
1) torque/2.5.2      5) idl/8.2           9) java/v1.6
2) moab/5.4.0        6) nstx/treedefs    10) nstx/mdsplus5
3) ppplcluster/1.1   7) nstx/epics       11) nstx/fdp
4) freetds/0.91      8) nstx/idldirs

Verify that python points to /p/fdp/anaconda/bin/python:

[sunfire06:~] % which python
/p/fdp/anaconda/bin/python

If python does not point to /p/fdp/anaconda/bin/python, then PATH contains to a different python distribution. In this case, you need to modify PATH so /p/fdp/anaconda/bin is the first python distribution in PATH.

Finally, you can launch python and import the FDP package:

[sunfire06:~] % python
Python 2.7.10 |Anaconda 2.3.0 (64-bit)| (default, Sep 15 2015, 14:50:01)
[GCC 4.4.7 20120313 (Red Hat 4.4.7-1)] on linux2
Type "help", "copyright", "credits" or "license" for more information.
Anaconda is brought to you by Continuum Analytics.
Please check out: http://continuum.io/thanks and https://anaconda.org
>>> import fdp
>>>

See Usage Examples to learn about the capabilities of FDP.

Usage examples

First, import the FDP module:

>>> import fdp

Initiate a machine instance

Define a NSTX machine instance:

>>> nstxu = fdp.nstxu

Shots are added as referenced. For instance, without previous reference to 139980, you can enter:

>>> nstxu.s139980.chers.plot()

Add shots to the NSTX instance:

>>> nstxu.addshot(140000)

or a shotlist:

>>> nstxu.addshot([141400, 141401, 141402])

or by XP:

>>> nstxu.addshot(xp=1048)

or by date (string or int YYYYMMDD):

>>> nstxu.addshot(date=20100817)

List shots presently loaded:

>>> dir(nstxu)

or:

>>> nstxu.listshot()

Get a custom shotlist:

>>> my_shotlist = nstxu.get_shotlist(xp=1032)  # returns numpy.ndarray