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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.
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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
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shell> python ./put_ids_array.py
shell> python ./put_ids_slices.py |
4. Open example file
Handling IDSes: put() vs. putSlice() |
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language | py |
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title | $TUTORIAL_DIR/ids_basics/python/put_ids_array.py |
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linenumbers | true |
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| 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 |
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language | py |
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title | $TUTORIAL_DIR/ids_basics/python/put_ids_slices.py |
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linenumbers | true |
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| import sys
from pylab import *
import ual
ids = ual.itm(14,4)
ids.create()
if not ids.isConnected():
print 'error during itmdb entry creation'
sys.exit(1)
equi = ids.equilibrium
#First fill fields which are not time-dependent.
equi.datainfo.dataprovider = 'MKO'
equi.datainfo.putdate = '20/09/2016'
equi.codeparam.parameters = 'param'
#Save time independent fields
equi.putNonTimed()
# ---- a loop ----
for i in range(0, 10):
#Fill time-dependent fields
equi.eqgeometry.boundary.resize(1)
equi.eqgeometry.boundary[0].r = sin(arange(0,2*pi,2*pi/100)) + (1/float(100-i))
equi.eqgeometry.boundary[0].z = cos(arange(0,2*pi,2*pi/100)) + (1/float(100-i))
#Do not forget time!!
equi.time = i
#Append this slice in the database
equi.putSlice() # <= Called inside the loop
# ---- a loop ----
#close the pulse file
ids.close() |
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Info |
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Official manual for IMAS installation on Gateway - link to pdf version |
CHEAT SHEET |
ITM | IMAS |
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$UAL | $IMAS_PREFIX |
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root | 3. Accessing IDS data |
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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() |
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Code Block |
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title | $TUTORIAL_DIR/ids_basics/fortran/get_ids_array.f90 |
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linenumbers | true |
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| program diagnostic
use imas_schemas
use imas_routines
implicit none
integer :: idx, i, arraySize
type (type_equilibrium), pointer :: eqArray(:) ! <= Array !!!
call imas_open('IDS', 14, 4, idx)
call imas_get(idx, 'equilibrium', eqArray)
arraySize = size(eqArray)
write (*,*) "Number of slices: ", arraySize
do i=1, arraySize
write (*,*) "Time: ", eqArray(i)%time
write (*,*) "Value of r: ", eqArray(i)%eqgeometry%boundary(1)%r(1)
write (*,*) "Value of z: ", eqArray(i)%eqgeometry%boundary(1)%z(1)
enddo
call imas_close(idx)
end program |
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title | $TUTORIAL_DIR/ids_basics/fortran/get_ids_slices.f90 |
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linenumbers | true |
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| program diagnostic
use imas_schemas
use imas_routines
implicit none
integer :: idx, i, arraySize
type (type_equilibrium) :: equilibrium
real(IMAS_R8), pointer :: timeVector(:)
real(IMAS_R8) :: time
call imas_open('IDS', 14, 4, idx)
call imas_get_times(idx, 'equilibrium',timeVector)
arraySize = size(timeVector)
write (*,*) "Number of slices: ", arraySize
write (*,*) "Time vector: ", timeVector
do i = 1, arraySize
time = timeVector(i)
call imas_get_slice(idx, 'equilibrium', equilibrium, time, 1)
write (*,*) "Time [", time, "]: ", equilibrium%time
write (*,*) "Value of r: ", equilibrium%eqgeometry%boundary(1)%r(1)
write (*,*) "Value of z: ", equilibrium%eqgeometry%boundary(1)%z(1)
enddo
call imas_close(idx)
end program |
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4. Compile the code
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shell> make clean
shell> make |
5. Run the code
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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