Matlab

Before starting to use the system check if JAVA is well configured in MatLab, type in the matlab console:

version -java

If you get an answer like: Java 1.5.0_04 with Sun Microsystems Inc. Java HotSpot(TM) Server VM, then you’re ready to start.

If your version of MatLab has an older version of Java, then you will need to install a newer version and set the MATLAB_JAVA enviroment variable, as described next.

Add all of the downloaded libraries to your system classpath.
Use the matlab static path. More information at the matlab documentation site.

If your are unable to set the static path on your computer you can use the dynamic path.

import org.sdas.core.client.*;
client = SDASClient('baco.ipfn.tecnico.ulisboa.pt', 8890);

If you get an error check the classpath.

found = client.searchDeclaredEventsByName('S');

found = client.searchDeclaredEventsByName('S');

found = client.searchDeclaredEventsByName('SHOT', 'pt');

found = client.searchDeclaredEventsByUniqueID('SHOT', 'pt');

found = client.searchDeclaredEventsByDescription('SHOT');

found = client.searchDeclaredEventsByDescription('SHOT', 'pt');

for i=1:1:size(found)
    found(i)
end

max = client.searchMaxEventNumber('0x0000')

min = client.searchMinEventNumber('0x0000')

NOTE: You can construct time with a resolution of picosseconds, just add to the example values for millis, micros, nanos and picos
NOTE 2: Date constructors have the months index to 0 (January is 0 and December is 11)

Search events in December 2005:

date_start = Date(2005, 11, 1);
date_end = Date(2005, 11, 31);
tstart = TimeStamp(date_start);
tend = TimeStamp(date_end);
eventsFound = client.searchEventsByEventTimeWindow(tstart, tend);
for i = 1:1:size(eventsFound)
    eventsFound(i)
end

Search events in the 22 December 2005 between 5pm and 6pm:

date_start = Date(2005, 11, 22);
date_end = Date(2005,11,22);
time_start = Time(17, 0, 0);
time_end = Time(18, 0, 0);
tstart = TimeStamp(date_start, time_start);
tend = TimeStamp(date_end, time_end);
eventsFound = client.searchEventsByEventTimeWindow(tstart, tend);
for i = 1:1:size(eventsFound)
    eventsFound(i)
end

parametersFound = client.searchParametersByName('DENS');

parametersFound = client.searchParametersByName('DENS', 'pt');

parametersFound = client.searchParametersByUniqueID('DENS');

parametersFound = client.searchParametersByDescription('current');

parametersFound = client.searchParametersByDescription('corrente', 'pt');

for i = 1:1:size(parametersFound)
    parametersFound(i)
end

This function returns the parameters unique identifiers where the data isn’t null for the selected event:

dataFound = client.searchDataByEvent('0x0000', 17898);
for i = 1:1:size(dataFound)
    dataFound (i)
end

NOTE: The unique identifiers are CASE-SENSITIVE

Data for only one parameter

dataStruct=client.getData('POST.PROCESSED.DENSITY','0x0000', 17898)
dataStruct=dataStruct(1);

Data for several parameters in the same event

dataStruct=client.getMultipleData({'POST.PROCESSED.DENSITY', 'POST.PROCESSED.IPLASMA'},'0x0000', 17898)
dataStructDens=dataStruct(1,1);
dataStructIP=dataStruct(2,1);
dens=dataStructDens.getData(); 
ip=dataStructIP.getData(); 

Data for several parameters in different events

dataStruct=client.getMultipleData({'POST.PROCESSED.DENSITY', 'POST.PROCESSED.IPLASMA'},{'0x0000','0x0000'}, [17898,17899])
dataStructDens=dataStruct(1,1);
dataStructIP=dataStruct(2,1);
dens=dataStructDens.getData(); 
ip=dataStructIP.getData(); 

Data for the same parameter in different events

dataStruct=client.getMultipleData('POST.PROCESSED.DENSITY',{'0x0000','0x0000'}, [17898,17899])
dataStructDens=dataStruct(1,1);
dataStructIP=dataStruct(2,1);
dens=dataStructDens.getData(); 
ip=dataStructIP.getData(); 

Data for the same parameter in different event numbers

dataStruct=client.getMultipleData('POST.PROCESSED.DENSITY', '0x0000', [17898,17899])

This data structure gives you information about:

• start time
• end time
• time of the event
• mime_type
• the parameter unique identifier

The following example shows how to calculate and plot the density at ISTTOK:
1. The data

dataStruct=client.getMultipleData({'CENTRAL.OS9_ADC_VME_I8.IF0CS',
'CENTRAL.OS9_ADC_VME_I8.IF0SN'},'0x0000', 11244);
cosine = dataStruct(1,1).getData;
isine = dataStruct(2,1).getData;

2. Calculate the phase

len = length(cosine)
cosavg = cosine - max(movavg(cosine, 10, 10))/2 - min(movavg(cosine, 10, 10))/2;
sinavg = isine - max(movavg(isine, 10, 10))/2 - min(movavg(isine, 10, 10))/2;
for j = 1:len
  phase(j) = atan2(double(sinavg(j)), double(cosavg(j)));
end

3. Unwrap

unwraped = unwrap(phase);

4. The start time

tstart = dataStruct(1,1).getTStart

5. The end time

tend = dataStruct(1,1).getTEnd

6. The time between samples is:

tbs= (tend.getTimeInMicros - tstart.getTimeInMicros)/len

7. The events

events = dataStruct(1,1).getEvents;

8. The event time (I’m assuming the event I want is at the index 0, but I should check first...)

tevent = events(1,1).getTimeStamp

9. The delay of the start time relative to the event time

delay = tstart.getTimeInMicros - tevent.getTimeInMicros

10. Create the time array

times = delay:tbs:delay+tbs*(len-1);

11. Normalize the data

dens = -7e17 * unwraped;
thold = dens(len-100:len);
density = dens-mean(thold);

11. Plot the chart

plot(times, density)