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In this tutorial

how can you integrate your code with UAL
how can you access data via UAL

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 IDS via UAL.

Warning

Warning

Stop here for a moment. Make sure you have followed the configuration setup before proceeding any further!

Configuration related tutorial is here -> Click me! <-

3.1 Accessing data using Python

Exercise no. 3 - After this exercise you will:

know how to access UAL using Python
know how to retrieve IDS from UAL
know how to access IDS data

Exercise no. 3 (approx. 15 min)

1. source ITMv1 script by invoking

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

2. Go to example directory

cd $TUTORIAL_DIR/ids_basics/python/

3. Execute sample code

Code Block

language	bash

shell> python ./put_ids_array.py
shell> python ./put_ids_slices.py

4. Open example file

Handling IDSes: put() vs. putSlice()

Code Block

language	py
title	$TUTORIAL_DIR/ids_basics/python/put_ids_array.py
linenumbers	true

import sys
from pylab import * 
import ual

ids = ual.itm(13,3)
ids.create()

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

ids.equilibriumArray.resize(10)
equi = ids.equilibriumArray

#First fill fields which are not time-dependent.
equi.array[0].datainfo.dataprovider = 'MKO'
equi.array[0].datainfo.putdate = '20/09/2016'
equi.array[0].codeparam.parameters = 'param'



# ---- a loop ----
for i in range(0, 10):
    #Fill time-dependent fields 
    equi.array[i].eqgeometry.boundary.resize(1)
    equi.array[i].eqgeometry.boundary[0].r = sin(arange(0,2*pi,2*pi/100)) + (1/float(100-i))
    equi.array[i].eqgeometry.boundary[0].z = cos(arange(0,2*pi,2*pi/100)) + (1/float(100-i))
    
	#Do not forget time!!
    equi.array[i].time = i
# ---- a loop ----

#Save data in the database
equi.put() # <= Called outside the loop

#close the pulse file
ids.close()

Code Block

language	py
title	$TUTORIAL_DIR/ids_basics/python/put_ids_slices.py
linenumbers	true

import sys
from pylab import * 
import ual

ids = ual.itm(14,4)
ids.create()

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

equi = ids.equilibrium


#First fill fields which are not time-dependent.
equi.datainfo.dataprovider = 'MKO'
equi.datainfo.putdate = '20/09/2016'
equi.codeparam.parameters = 'param'

#Save time independent fields
equi.putNonTimed()
# ---- a loop ----
for i in range(0, 10):
	#Fill time-dependent fields 
	equi.eqgeometry.boundary.resize(1)
    equi.eqgeometry.boundary[0].r = sin(arange(0,2*pi,2*pi/100)) + (1/float(100-i))
    equi.eqgeometry.boundary[0].z = cos(arange(0,2*pi,2*pi/100)) + (1/float(100-i))
    
    #Do not forget time!!
    equi.time = i 
    
    #Append this slice in the database
    equi.putSlice() # <= Called inside the loop
# ---- a loop ----

#close the pulse file
ids.close()

...

3.2.1 Changes

ITM	IMAS
CHEAT SHEET
use euitm_schemas	use ids_schemas
use euitm_routines	use ids_routines
type (type_<cpo_name>) :: cpo	type (ids_<ids_name>) :: ids
type (type_<cpo_name>), pointer :: cpoArray(:) ! <= Array !!!	type (ids_<ids_name>) :: ids <== SINGLE OBJ !!!
call euitm_create('euitm', shot, run, refShot, refRun, idx)	call imas_create('ids', shot, run, refShot, refRun, idx)
call euitm_open('euitm', shot, run, idx)	call imas_open('ids', shot, run, idx)
call euitm_put(idx, '<cpo_name>', cpoArray) <== ARRAY!	call ids_put(idx, '<ids_name>', ids) <== SINGLE OBJ
call euitm_put_non_timed(idx,"<cpo_name>", cpo)	call ids_put_non_timed(idx,"<ids_name>",ids)
call euitm_put_slice(idx, '<cpo_name>', cpo)	call ids_put_slice(idx, '<ids_name>', ids)
call euitm_deallocate(cpoArray)	call ids_deallocate(ids)
call euitm_close(idx)	call imas_close(idx)
call euitm_enable_mem_cache(idx)	call imas_enable_mem_cache(idx)
call euitm_disable_mem_cache(idx)	call imas_disable_mem_cache(idx)
call euitm_flush_all(idx)	call imas_flush_all(idx)

3.2.2 CPO/IDS put

put() CPO vs IDS

Code Block

title	ITM
linenumbers	true

program diagnostic
    use euitm_schemas
    use euitm_routines
    implicit none

    integer :: idx, i, arraySize
    type (type_equilibrium), pointer::cpoArray(:)<= ARRAY!

	! Open a database
    call euitm_create('euitm', 11, 22, -1, -1, idx)





	! CPO structure allocation
	allocate(cpoArray(10))

!SCALARS (!)
	do i=1, 10
    	cpoArray(i)%time = VALUE
        cpoArray(i)%x%y = VALUE
    enddo
    




call euitm_put(idx, 'equilibrium', cpoArray)
call euitm_deallocate(cpoArray)
    ! Close a pulse file
    call euitm_close(idx)
end program

Code Block

title	IMAS
linenumbers	true

program diagnostic
    use ids_schemas
    use ids_routines
    implicit none

    integer :: idx, i
    type (ids_core_profiles): ids <= Single object !!

	! Open a database
    call imas_create('ids', 11, 22, -1, -1, idx)
  
   ! Mandatory to define this property
    ids%ids_properties%homogeneous_time = 1 

! IDS structure allocation
allocate(ids%time(10))
allocate(ids%x%y(10))

 !SCALARS (!)
	do i=1, 10
    	ids%time(i) = VALUE
        ids%x%y(i) = VALUE
    enddo
! VECTORS
    	ids%time = timeVector
        ids%x%y  = valueVector

call ids_put(idx, 'core_profiles', ids)
	call ids_deallocate(ids)
! Close a pulse file
    call imas_close(idx)
end program

3.2.3 CPO/IDS putSlice

putSlice() CPO vs IDS

Code Block

title	ITM
linenumbers	true

program diagnostic
    use euitm_schemas
    use euitm_routines
    implicit none

    integer :: idx, i
    type (type_equilibrium) :: cpo ! <= Single object !!!

	! Open a database
    call euitm_create('euitm', 11, 22, -1, -1, idx)





	! Time NOT dependent data
	allocate(cpo%datainfo%dataprovider(1))  
 	cpo%datainfo%dataprovider="FI"
	call euitm_put_non_timed(idx, 'equilibrium', cpo)





	cpo%time = VALUE
    cpo%x%y = VALUE
   
    call euitm_put_slice(idx, 'equilibrium', cpo)	
	
	call euitm_deallocate(cpoArray)
    
	! Close a pulse file
    call euitm_close(idx)
end program

Code Block

title	IMAS
linenumbers	true

program diagnostic
    use ids_schemas
    use ids_routines
    implicit none

    integer :: idx, i
    type (ids_core_profiles) :: ids ! <= Single object !

	! Open a database
    call imas_create('ids', 11, 22, -1, -1, idx)
  
   	! Mandatory to define this property
   	ids%ids_properties%homogeneous_time = 1 

	! Time NOT dependent data
	allocate(ids%ids_properties%comment(1))
 	ids%ids_properties%comment(1) = 'IDS put by put_slice'
 	call ids_put_non_timed(idx,"core_profiles",ids)

 	! IDS structure allocation
	allocate(ids%time(1))
	allocate(ids%x%y(1))   
 
    ids%time(1) = VALUE
    ids%x%y(1) = VALUE


	call ids_put_slice(idx, 'core_profiles', ids)
	
	call ids_deallocate(ids)
	
	! Close a pulse file
    call imas_close(idx)
end program

3.2.4 CPO/IDS get

get() CPO vs IDS

Code Block

title	ITM

vi $TUTORIAL_DIR/ids_basics/python/put_ids.py

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

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

3.2 Accessing data using Fortran

Exercise no. 4 - After this exercise you will:

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

Exercise no. 4 (approx. 15 min)

In this exercise you will read IDS 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 $TUTORIAL_DIR/ids_basics/fortran

Handling IDSes: get() vs. getSlice()

Code Block

title	$TUTORIAL_DIR/ids_basics/fortran/get_ids_array.f90
linenumbers	true

program diagnostic
    use imaseuitm_schemas
    use imaseuitm_routines
    implicit none

    integer :: idx, i, arraySize
    type (type_equilibrium), pointer :: eqArraycpoArray(:) ! <= Array !!!


	! Open a database
    call imaseuitm_open('IDSeuitm', 14, 4, idx)
  
    ! Get data
    call imaseuitm_get(idx, 'equilibrium', eqArraycpoArray)
   
	! Check array size
	arraySize = size(eqArraycpoArray)
   ! write (*,*) "Number of slices: ", arraySize<= array of CPOs
   
    
	! SCALARS (!)
	do i=1, arraySize
    	write (*,*) "Time : ", eqArraycpoArray(i)%time
        write (*,*) "Value of r: ", eqArraycpoArray(i)%eqgeometry%boundary(1)%r(1)%x%y
    enddo
    write (*,*) "Value of z: ", eqArray(i)%eqgeometry%boundary(1)%z(1)
    enddo




    ! Close a pulse file
    call call imaseuitm_close(idx)
end program

Code Block

title	$TUTORIAL_DIR/ids_basics/fortran/get_ids_slices.f90IMAS
linenumbers	true

program diagnostic
    use imasids_schemas
    use imasids_routines  
    implicit none

    integer :: idx, i, arraySize 
    type (typeids_core_equilibriumprofiles) :: equilibrium
ids ! <=  real(IMAS_R8), pointer :: timeVector(:)
    real(IMAS_R8) :: time

Single object !!


	! Open a database
    call imas_open('IDSids', 14, 4, idx)
  
    ! Get data
    call imasids_get_times(idx, 'equilibrium',timeVector)core_profiles', ids)

	! Check array size
    arraySize = size(ids%time)  ! <= time vector
    
    arraySize
	! =SCALARS size(timeVector!)
	do i=1, arraySize
    	write (*,*) "Number of slicesTime : ", ids%time(i)
        write (*,*) "Value: ", arraySizeids%x%y(i)
    enddo

	! VECTORS
    write (*,*) "Time vector: ", timeVector: ", ids%time
    write (*,*) "Value: ", ids%x%y
	
	! Close a pulse file
    call imas_close(idx)
end program

3.2.5 CPO/IDS getSlice

getSlice() CPO vs IDS

Code Block

language	cpp
title	ITM
linenumbers	true

program diagnostic
   ! UAL library
    use euitm_schemas
    
	do i = 1, arraySizeuse euitm_routines  
	implicit none
 
    integer :: idx 
    type (type_equilibrium) :: cpo
    
    ! Open a database
 time   =call timeVector(ieuitm_open('euitm', 11, 4, idx)
    
    ! Get data
    call imaseuitm_get_slice(idx, 'equilibrium', equilibriumcpo, time4.0, 1)
             
    	write (*,*) "Time  : [", time,cpo%time
    write (*,*) "]Value : ", cpo%x%y
     
	! Memory  equilibrium%time
clean-up
	call euitm_deallocate(cpo)

    ! Close a pulse file 
    writecall euitm_close(idx)
end program

Code Block

title	IMAS
linenumbers	true

program diagnostic
    ! UAL library
    use ids_schemas
    use ids_routines  
    implicit none

    integer :: idx 
    type (ids_core_profiles) :: ids
    
    ! Open a database
    call imas_open('ids', 11, 22, idx)
    
    ! Get data
    call ids_get_slice(idx, 'core_profiles', ids, 4.0, 1)
   (*,*) "Value of r: ", equilibrium%eqgeometry%boundary(1)%r(1)
         
    write (*,*) "ValueTime of z: ", equilibrium%eqgeometry%boundary(1)%z(1)
    enddoids%time
    write (*,*) "Value : ", ids%x%y

	! Memory clean-up
    
	call imasids_closedeallocate(idxids)
end program

4. Compile the code

Code Block
shell> make clean shell> make

5. Run the code

Code Block
shell> ./get_ids_array.exe shell> ./get_ids_slices.exe

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

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:

Prepare Fortran code that has a subroutine to be called and is compiled as a library
Prepare FC2K based description of the actor
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

...


    ! Close a pulse file
    call imas_close(idx)
end program

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Key

3.1 Accessing data using Python

3.2.1 Changes

3.2.2 CPO/IDS put

3.2.3 CPO/IDS putSlice

3.2.4 CPO/IDS get

3.2 Accessing data using Fortran

3.2.5 CPO/IDS getSlice

4. FC2K - Fortran Code to Kepler