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 NaN and Inf values correctly.
- Fixed flushing/closing of compressed serialized models (SerializationHelper class).
- The CheckVariableUsage flow processor now excludes system-supplied variables like flow_dir and flow_id from 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 BatchUpdateException exceptions.
- 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.
- Dependency changes
- Weka 3.9.0 (with patched FilteredClassifier)
- Apache CXF 3.1.9
- LIRE 1.0b2
- deeplearning4j 0.7.2
- CUDA 8.0 libraries for deeplearning4j
- ImageJ 1.51h
- BoofCV 0.26
- 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.