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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 IDSs: put() vs. putSlice() |
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| Code Block |
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| language | py |
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| title | $TUTORIAL_DIR/cpo_basics/python/put_cpo_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/cpo_basics/python/put_cpo_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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Downloading the user guide for the Data Model and Access Layer
Remember to set you IMAS environment via modules, for instance
module load imas/3.15.0
imasdb test
UAL interfaces
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| root | 3.Writing simple code for accessing IDS data |
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| Info |
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| title | Encapsulating user code within Kepler actor |
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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 IDSs: get() vs. getSlice() |
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| Code Block |
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| title | $TUTORIAL_DIR/cpo_basics/fortran/get_cpo_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 |
| | Code Block |
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| title | $TUTORIAL_DIR/cpo_basics/fortran/get_cpo_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.
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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. |
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- 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.
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This topics is covered in separate tutorial: |
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