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If you are using a version prior to the 3.8 update, follow these steps to integrate the Shared Data Access System in your Octave code. All the examples were successfully tested in MS Windows and Linux distributions like Fedora, Gentoo and Debian.
Installation of Java support
Although no issues with OpenJDK have been reportd, it is recommended to use the last version (at least 1.5) of the Oracle Java Development Kit (JDK).
Linux
Many Linux distros offer java-octave on their repositories. Since the exact name of the package varies and in some cases it comes bundled with other packages, you should refer to the documentation of the distro you are using. If you weren't able to install the Java support from a repository, please follow these instructions.
First you have to find out where is your java home located. To avoid errors, download and run this utility. The value returned by the utility is the JAVA_JRE value.
Now you have to set JAVA_HOME as a system variable:
/opt/jdk1.6.0_18/jre: export JAVA_HOME="/opt/jdk1.6.0_18/"
Download and install the Octave JAVA support. Packages installation instructions can be found on this Octave documentation page.
Windows
First you have to find out where is your java home located. To avoid errors, download and run this utility. The value returned by the utility is the JAVA_JRE value.
Now you have to set JAVA_HOME as a system variable:
Select the tab Advanced
Click on Environment Variables...
In the system variables click New...
The Variable name is: JAVA_HOME
In the value field (supposing the value of JAVA_JRE is C:\java\jdk1.6.0_18\jre) enter the following value: C:/java/jdk1.6.0_18 (notice that it uses / instead of \).
Attention: Try avoiding paths with spaces. If you already have Java installed on your machine, one solution is to create a symbolic link to your installation and set the variable to it. The build architecture of Octave and Java must match (32 bits with 32 bits, 64 bits with 64 bits).
After this is done, follow the instructions on the SourceForge download page, to load the Java support package. More information can be found here.
Download the libraries
Download the following libraries into a folder of your system:
Apache XML-RPC
Apache Jakarta Commons
Since the server at baco computer uses an older version, if you are planing on accessing it server, you should download this version of SDAS Core Libraries and Client:
SDAS Core Libraries
SDAS Client
If you are using a different server, download these instead:
SDAS Core Libraries
SDAS Client
Add the SDAS libraries to the octave classpath
These example assume that you have saved all the jar files in the folder /home/user/sdas/
javaaddpath("/home/user/sdas/SDAS.jar")
javaaddpath("/home/user/sdas/SDASClient.jar")
javaaddpath("/home/user/sdas/commons-codec-1.3.jar")
javaaddpath("/home/user/sdas/xmlrpc-2.0.jar") Beware that on Windows you must use / instead of the regular \. If you have saved all the jar files in the folder C:\sdas\, for example:
javaaddpath("C:/sdas/SDAS.jar")
javaaddpath("C:/sdas/SDASClient.jar")
javaaddpath("C:/sdas/commons-codec-1.3.jar")
javaaddpath("C:/sdas/xmlrpc-2.0.jar")
Get a connection to the sdas server
client = java_new("org.sdas.core.client.SDASClient", "baco.ipfn.ist.utl.pt", 8888); Search events
found = client.searchDeclaredEventsByName('S');
found = client.searchDeclaredEventsByName('S');
found = client.searchDeclaredEventsByName('SHOT', 'en');
found = client.searchDeclaredEventsByUniqueID('SHOT', 'en');
found = client.searchDeclaredEventsByDescription('SHOT');
found = client.searchDeclaredEventsByDescription('SHOT', 'en');
for i=1:1:size(found)
found(i).toString
end
max = client.searchMaxEventNumber('0x0000')
min = client.searchMinEventNumber('0x0000')
Search events in a time window
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 = java_new("org.sdas.core.time.Date", 2005, 11, 1);
date_end = java_new("org.sdas.core.time.Date", 2005, 11, 31);
tstart = java_new("org.sdas.core.time.TimeStamp", date_start);
tend = java_new("org.sdas.core.time.TimeStamp", date_end);
eventsFound = client.searchEventsByEventTimeWindow(tstart, tend);
for i = 1:1:size(eventsFound)
eventsFound(i).toString
end
Search events in the 22 December 2005 between 5pm and 6pm:
date_start = java_new("org.sdas.core.time.Date", 2005, 11, 22);
date_end = java_new("org.sdas.core.time.Date", 2005,11,22);
time_start = java_new("org.sdas.core.time.Time", 17, 0, 0);
time_end = java_new("org.sdas.core.time.Time", 18, 0, 0);
tstart = java_new("org.sdas.core.time.TimeStamp", date_start, time_start);
tend = java_new("org.sdas.core.time.TimeStamp", date_end, time_end);
eventsFound = client.searchEventsByEventTimeWindow(tstart, tend);
for i = 1:1:size(eventsFound)
eventsFound(i).toString
end Search parameters
parametersFound = client.searchParametersByName('DENS');
parametersFound = client.searchParametersByName('DENS', 'pt');
parametersFound = client.searchParametersByUniqueID('DENS');
parametersFound = client.searchParametersByDescription('current');
for i = 1:1:size(parametersFound)
parametersFound(i).toString
end
Search data
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
Get data
NOTE: The unique identifiers are CASE-SENSITIVE
NOTE2: Some java types like float and long are not automatically recognised by octave. A transformation must be manually performed using the intValue and doubleValue methods
The returned data structure gives you information about:
- start time
- end time
- time of the event
- mime_type
- the parameter unique identifier
Data for only one parameter
dataStructArray=client.getData('POST.PROCESSED.DENSITY','0x0000', 17898)
dataStruct=dataStructArray(1);
dens=dataStruct.getData;
for i=1:length(dens)
density(i)=dens(i).doubleValue;
end
tstart = dataStruct.getTStart;
tend = dataStruct.getTEnd;
Calculate the time between samples
tbs= (tend.getTimeInMicros.intValue - tstart.getTimeInMicros.intValue)/length(density); Get the events associated with this data
events = dataStruct.getEvents;
The event time (I’m assuming the event I want is at the index 0, but I should check first...)
tevent = events(1).getTimeStamp;
The delay of the start time relative to the event time
delay = tstart.getTimeInMicros.intValue - tevent.getTimeInMicros.intValue
Finally create the time array
times = delay:tbs:delay+tbs*(length(density)-1);
And plot the data
plot(times, density);
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])
More example code is available on the Octave Code page.
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