The new year started mainly with a lot of work and, whenever I had time, with the upgrade of some libraries, like Weka and deeplearning4j.
The Utils.doubleToStringFixed method now handles
Fixed flushing/closing of compressed serialized models (SerializationHelper class).
The CheckVariableUsage flow processor now excludes system-supplied variables like
flow_idfrom the check.
Added icon for DL4JModelReader transformer.
RecordReaderDataSetIteratorConfigurator now allows using 0 as minimum for the 0-based indices.
adams-weka: The WekaFileReader transformer now handles filenames without extension as long as there is a custom loader defined.
The Display and HistoryPanel sinks now have options for line-wrap and wrap-style-word.
The GridView standalone and the DisplayPanelGrid sink now allow the user to change the grid layout at runtime.
added example flows/scripts for configuring deeplearning4j networks using Groovy and Jython.
added adams-imaging dependency to have basic image processing capability
adams-spreadsheet: batch import of spreadsheets now output a more detailed error message in case of
adams-weka: Added a popup menu to the dataset table of the Investigator's Preprocess panel and added the Clear action to the menu for removing all datasets at once.
Weka 3.9.0 (with patched FilteredClassifier)
Apache CXF 3.1.9
CUDA 8.0 libraries for deeplearning4j
DL4JDatasetIterator source now has option to output full dataset instead of batches.
Added regexp option to CALSpectrumLoader Weka file loader to allow loading of only specific reference value(s).
Added ConditionalSequence control actor, the conditional version of the default Sequence actor.
adams-imaging: With the updated version of LIRE, additional feature generators are now available:
Added DL4JModelParamsToSpreadSheet conversion for extracting the parameters.
Added DL4JModelParamsToSpreadString conversion for extracting the parameters as simple string.
Added ImageScaler dataset preprocessor.
Added DL4JCrossValidationSplit transformer to generate sequence of train/test set containers.
The DL4JCrossValidationEvaluator transformer performs cross-validation on a referenced model using the incoming dataset.
The SpreadSheetRecordReaderConfigurator allows to read any spreadsheet that ADAMS can read. However, textual cells get converted to NULLs and date/time ones to their Java epoch equivalent.
The DL4JDatasetAppend transformer combines multiple datasets into a single dataset, one after the other
Added the Storage and Variable rat inputs, for getting access to the specified storage item/variable.
Added SpreadSheetToNumeric conversion for turning non-numeric cells in a spreadsheet into numeric ones.
Added Unique values column action to the SpreadSheetTable column popup menu to display the unique values of the selected column.
Condition for checking whether spectrum already in database: HasSpectrum.
Spectra are now rendered in the Breakpoint and can be exported as well.