In this tutorial what CPOs are what UAL is how can you integrate your code with UAL how can you access data via UAL

 

1.1. 1. CPO - Consistent Physical Object

A Consistent Physical Object (CPO), is a data structure that contains the relevant information on a Physical Entity, e.g. the plasma equilibrium, the core plasma profiles (densities, temperature etc.), distribution functions, etc.

What is important from the user's perspective is the way CPO data are stored. Each CPO structure can be accessed via UAL documentation at the ITM portal ITM Portal.

Accessing documentation structure is fairly easy. Open ITM Portal web page in browser and navigate to ISIP related documentation.

ITM Portal page

After documentation is opened browse to: "Data structure" (it is located at the bottom of the picture)

ITM Portal - ISIP related section

You should see web page similar to the content of picture below

UAL documentation

After choosing "Browse" you will see the structure of the CPOs.

CPOs within data structure

What you can see at the picture above is collection of CPOs. All CPOs are bound to the top level element. After you expand particular CPO you can browse it's details. In this case magdiag (Magnetic diagnostics) was expanded.

 

Downloading structure If you plan to browse structure extensively, it is advised to download it to your local system.

 

• know how to find CPO related documentation
• know how to browse through the tree structure
• know how to access CPO details

In this exercise you will browse documentation of CPO elements.

1. Log in into ITM Portal link

2. Browse to Documentation -> ISIP -> Data structure

3. Choose "Browse" from "Data structure 4.10b (Browse) (Download)"

4. Check few CPOs to get familiar with documentation

1.1.1. 1.1 Structure of the CPO

In this section we will take a closer look at the data. After copying MDSPlus database files into your account's public area you can dump the data using cpodump script.

cpodump 13 3 equilibrium

1.1.1.1. 1.1.1 Time independent CPOs vs. time dependent CPOs

In general a CPO can contain both time-dependent and time-independent information. Typically, information related to the tokamak hardware will not be time-dependent, while the value of plasma physical quantities will likely be time dependent. Therefore the fields of a CPO can be either time- dependent or time-independent. The CPO itself will be time-independent if it contains only time- independent fields. It will be time-dependent otherwise. Only few CPOs in the ITM database will be time-independent (e.g. topinfo, summary, vessel), while the others will describe physical phenomena which vary over time.

Time-dependent CPOs are treated as arrays of the elementary CPO structure, i.e. in Fortran: equilibrium( : ) is a pointer and equilibrium( i ) is an equilibrium structure corresponding to time index i. Since many physics code manipulate only one time slice at a time, special UAL functions exist to extract a single time slice of the CPO : these are the GET_SLICE and PUT_SLICE functions.

source: UAL User Guide

1.1.1.2. 1.1.2 Time slice index

Each time slice is located at given index. When you are looking for a time slice, there are three possible ways of finding "correct" time slice.

• 1 : CLOSEST_SAMPLE
  the returned CPO is the stored CPO whose time is closest to the passed time;
• 2 : PREVIOUS_SAMPLE
  the CPO whose time is just before the passed time is returned.
• 3 : LINEAR INTERPOLATION
  the values of the time-dependent return CPO fields are computed according to a linear interpolation between the corresponding values of the CPOs just before and after the passed time;

1.2. 2. UAL - Universal Access Layer

In order to cope with multiple languages and maintaining at the same time a unique structure definition, the UAL architecture defines two layers. The top layer provides the external Application Programming Interface (API), and its code is automatically produced from the XML description of the ITM database structure. For each supported programming language, a high level layer is generated in the target language. The following sections will describe the language specific API, and they provide all the required information for simulation program developers.

The lower layer is implemented in C and provides unstructured data access to the underlying database. It defines an API which is used by all the high level layer implementations. Knowledge of this API (presented in a later section) is not necessary to end users, and is only required to the developers of new language specific high level implementations of the UAL as well as the developers of support tools for ITM management.

source: UAL User Guide

1.3. 3. Writing simple code for accessing CPO data

Accessing data from UAL requires some modification to your code. In this part of tutorial, we will take a closer look on how to access CPO via UAL.

1.3.1. 3.1 Accessing data using Python

• know how to access UAL using Python
• know how to retrieve CPO from UAL
• know how to access CPO data

In this exercise you will browse MDSPlus database using jTraverser application.

1. source ITMv1 script by invoking

source $ITMSCRIPTDIR/ITMv1 kepler test 4.10b > /dev/null

2. Go to example directory

cd $ITMWORK/tutorials/split-2014/cpo_basics/python

3. Execute sample code

python put_cpo.py

4. Open example file

 

VI related notice I will use VI in every place where text files are modified. If you have any other text file editor of your choice - fell free to use it instead.

 

vi $ITMWORK/tutorials/split-2014/cpo_basics/python/put_cpo.py

What you can see here is a simple code that stores particular CPO into MDSPlus database using UAL.

import sys
from pylab import *
import ual

cpo = ual.itm(12,2)
cpo.create()

if not cpo.isConnected():
    print 'error during itmdb entry creation'
    sys.exit(1)

cpo.equilibriumArray.resize(1)

equi = cpo.equilibriumArray
equi.array[0].time = 0.0

equi.array[0].datainfo.dataprovider = 'MKO'
equi.array[0].datainfo.putdate = '18/02/2013'
equi.array[0].codeparam.parameters = 'param'

equi.array[0].eqgeometry.boundary.resize(1)
equi.array[0].eqgeometry.boundary[0].r = sin(arange(0,2*pi,2*pi/100))
equi.array[0].eqgeometry.boundary[0].z = cos(arange(0,2*pi,2*pi/100))


print equi.array[0].eqgeometry.boundary[0].r
print equi.array[0].eqgeometry.boundary[0].z

equi.put()

cpo.close()

Let's check how to read these data in Fortran.

1.3.2. 3.2 Accessing data using Fortran

• know how to connect to UAL
• know how to retrieve data from UAL
• know how to prepare Makefile for your Fortran code

In this exercise you will read CPO and print some data stored inside.

1. source ITMv1 script by invoking

source $ITMSCRIPTDIR/ITMv1 kepler test 4.10b > /dev/null

2. Change directory to a demo location for this exercise

cd $ITMWORK/tutorials/split-2014/cpo_basics/fortran

3. Open GetSlice.f90 file

vi GetSlice.f90

 

How can I quit VI!? Quitting vi is fairly simple. Just use following command sequence by pressing characters listed below. Esc Esc : q ! Enter

 

4. You should see code similar to following one

program diagnostic
    use euitm_schemas
    use euitm_routines
    use write_structures
    implicit none

    integer :: idx
    type (type_equilibrium), pointer :: equilibrium(:)

    Integer x

    call euitm_open('euitm', 12, 2, idx)

    call euitm_get(idx, 'equilibrium', equilibrium)

    write (*,*) "Size of CPO: ", size(equilibrium)

    write (*,*) "Value of r: ", equilibrium(1)%eqgeometry%boundary(1)%r(1)
    write (*,*) "Value of z: ", equilibrium(1)%eqgeometry%boundary(1)%z(1)

    call euitm_close(idx)
    call euitm_disconnect()
end program

5. Run the code

make clean
make
./readEquilibrium

6. You should see values that we have stored using Python based code.

1.4. 4. FC2K - Fortran Code to Kepler

It is possible to encapsulate Fortran/C++ code with Java code that represents Kepler actor. This way, you can easily incorporate your Fortran code with existing Kepler workflow. In order to make it happen you will have to:

1. Prepare Fortran code that has a subroutine to be called and is compiled as a library
2. Prepare FC2K based description of the actor
3. Recompile Kepler with newly created actor

After these steps are performed, you will have an access to Kepler actor that encapsulates your Fortran code.

All these topics will be covered in separate tutorial: 1.4 Using FC2K for embedding Fortran code into Kepler