Currently, I'm working mainly on a commercial project that involves meta-flows, i.e., flows that use their parametrization to generate flows on the fly that do the actual work, aka worker-flows. Hence there being many tweaks and changes based around this approach, e.g., making it easier to load models into memory and use them directly from there.
The TryCatch control actor now works again as expected within Rat, LocalScopeTransformer and LocalScopeTrigger actors. It also now properly stops its try and catch branches.
Fixed rendering of arrays in the Preview browser, now each element has its own renderer determined. Necessary for mixed object arrays. The PlainText handler no longer crashes if it cannot read a file, one with binary content.
The BaseDirectoryChooser dialog now correctly retrieves the currently selected directory for adding bookmarks. Also displaying a text field with the currently selected directory, enabling fast copy/paste.
All help screens in the GUI have been centralized into a separate Help frame, which keeps a history of the screens.
Remote commands can be sent and received now in JSON as well, using the JsonProcessor instead of the DefaultProcessor.
The Serialize transformer and Deserialize sink now take advantage of the object writer/reader class hierarchies for more flexibility in output/input formats.
Updated processoutput4j to 0.0.6
The Command source actor now has a timeOut option, which kills the process once exceeded.
adams-event: added template support for cron schedules: adams/core/base/CronSchedule.props
The attribute index is now displayed in the table header of the WekaInstancesDisplay sink and the object renderer at debugging time.
Added support for updating properties via variables to: WekaAssociatorSetup, WekaClassifierSetup, WekaClustererSetup, WekaDataGenerator, WekaFilter, WekaStreamFilter
simplified model loading, centralizing it in the adams.flow.core.AbstractModelLoader class, now offering loading from file, source actor and internal storage: WekaFilter, WekaClassifying, WekaClustering
The evaluations of classifiers in the Weka Investigator no longer require class values to be present on data sets other than the training set. This allows to simply make predictions then.
adams-moa: simplified model loading, centralizing it in the adams.flow.core.AbstractModelLoader class, now offering loading from file, source actor and internal storage: MOAClassifying, MOAClustering, MOARegressing
adams-meka: simplified model loading, centralizing it in the adams.flow.core.AbstractModelLoader class, now offering loading from file, source actor and internal storage: MekaClassifying
The Cleaner transformer now adds the actual cleaner to the output container now as well.
The PostProcessor transformer can output a container now, which contains the input and output data, as well as the actual processor in use.
The spetrum's wave-numbers can be used as suffix now instead of the amplitude indices (affecting only the SimpleInstanceGenerator).
renamed IntensityImageSpectrumWriter to SpectrumImageWriter, uses new class hierarchy for image generators: adams.data.spectrumimage.AbstractSpectrumImageGenerator
updated rsync4j to 3.1.2-5.
added maxTime option to RSync and SimpleRSync sources, which kills the rsync process once exceeded.
- adams-cntk-weka: The CNTKSaver converter now turns a nominal class attribute
into CNTK's 1-hot encoding format (aka unsupervised NominalToBinary).
adams-imaging: The ImageAnnotator transformer now allows the manual selection of objects via a selection processor.
Added reader/writer for objects implementing adams.core.SerializableObject
The object export in the debug's object tree or the Flow editor's debug view now allows you to export any serializable object as well.
Added OutlierDetector transformer to directly tap into detection messages returned by detection scheme.
Added the SetManyVariables standalone and transformer, which allow to update multiple variables at the same time.
The DeserializeToStorage standalone simplifies loading serialized models into storage.
Added handler for CNTK models to the Preview browser
Added Weka loader for CNTK text files: CNTKLoader
Added Weka saver for CNTK text file format: CNTKSaver
Added classifier for building a CNTK using a Brainscript file and using the final model for making predictions: functions.CNTKBrainscriptModel
Have a good weekend!