CHANGELOG

Changelog
=========

All notable changes to this project will be documented in this file.

The format is based on `Keep a Changelog <http://keepachangelog.com/>`_
and this project adheres to `Semantic Versioning <http://semver.org/>`_

3.6.3 - 2023-08-15
------------------

Fixed
~~~~~
- Bug in computing confidence intervals when performance was always the same,
  results now in a np.nan confidence interval.
- Error catched and message added when you provide images and/or features in the
  test set, but not labels.
- SimpleWORC and BasicWORC now detect whether user has provided a separate training
  and test set and thus bootstrapping should be used.
- Bug in PREDICT was fixed that mixed up the mode in shape feature extraction (2D / 2.5D)
- Bug in performance calculation of multiclass classification.
- Bugs in statistical feature testing.

Changed
~~~~~~~
- Statistical test feature selection before PCA: otherwise when combined,
  it will select PCA components, not features.

Added
~~~~~
- Histogram equalization to preprocessing.
- Recursive feature elimination (RFE) feature selection.
- Workflow to provide evaluate a trained model on new data
- Option to set a fixed random seed in the hyperoptimization
  for reproducibility.
- Various FAQs
- Updated user manual with more extensive debugging guide.
- Thoroughly updated user manual documentation on different data flows, e.g.
  train-test setups, multiple segmentations per patient.
- function in SimpleWORC to add parameter files for elastix.


3.6.2 - 2023-03-14
------------------

Fixed
~~~~~
- Bug when using statisticaltestthreshold in multiclass classification,
  see Github Issue #73.


3.6.1 - 2023-02-15
------------------

Fixed
~~~~~
- Bug when using elastix, dimensionality got wrong name in fastr network.
- Bug in BasicWORC when starting from features
- For statistical test thresholding, if refit does not work during ensembling, skip this method
  instead of returning NaN.
- Createfixedsplits function was outdated, updates to newest conventions and added
  to documentation.
- When using Dummy's, segmentix now still copies metadata information from image
  to segmentation when required.

Changed
~~~~~~~
- When part of fiting and scoring a workflow fails, during optimization return NaN as performance,
  but during refitting skip that step. During optimization, if we skip it, the relation between
  the hyperparameter and performance gets disturbed. During refitting, we need to have a model,
  so best option is to skip the step. Previously, there was only skipping.
- Set default of XGB estimator parallelization to single job.

Added
~~~~~
- Documentation updates
- Option to save the workflows trained on the train-validation training datasets, besides the option to save workflows
  trained on the full training dataset. Not an option for SMAC due to implementation of SMAC.
- Validate function for fastr HDF5 datatype, as previously fastr deemed empty hdf5 types as valid.
- Option to eliminate features which are all NaN during imputation.
- Preflightcheck on number of image types provided.


3.6.0 - 2022-04-05
------------------

Added
~~~~~~~
- Bayesian optimization through SMAC as alternative to random search. Due
  to specific requirements for SMAC, this is not by default installed.
  Instructions to install this component are provided in the documentation.
- Besides Top_N ensembling, various other methods are added:
  'ForwardSelection', 'Caruana', and 'Bagging'
- LightGBM classifier
- Light fingerprinting approach to adjust config based on dataset.

Fixed
~~~~~
- When none of the workflows to be included in the workflow converges during
  retraining, add the next best performing workflows.

3.5.0 - 2021-08-18
------------------

Fixed
~~~~~
- Bug in plotting 2D images when ranking the posteriors or percentages.
- Bug in Evaluate for Regression.
- Bug in BasicWORC for supplying label files.
- There is a bug in SimpleITK 2.1.0, which leads it to not be able
  to read certain NIFTI files. See: https://github.com/InsightSoftwareConsortium/ITK/issues/2674
  Reverting to SimpleITK 2.0.2 for now

Changed
~~~~~~~
- Defaults for splitting jobs in hyperoptimization: now more parallelized.

Added
~~~~~~~
- Documentation on additional functionality.

3.4.5 - 2021-07-09
------------------
 Unit tests moved from Travis to Github Workflow from this verion on.

Fixed
~~~~~
- Bug in plotting images when ranking the posteriors or percentages.
- Linting issues.

Changed
~~~~~~~
- Removed deprecated scatterplot, RankedSVM functions.

3.4.4 - 2021-07-01
------------------

Fixed
~~~~~
- Bug where most recent added estimators were not valid in SimpleWORC.
- SelectorMixin is now imported directly from sklearn.feature_selection,
  as sklearn.feature_selection.base is deprecated and will be removed.

Changed
~~~~~~~
- Apply variance threshold selection before feature scaling, otherwise
  variance is always the same for all features.
- RELIEF, selection using a model, PCA, and univariate testing default
  use changed from 0.20 to 0.275.

Added
~~~~~~~
- Functionality in plotting images functions.
- Documentation on how to use your own features.

3.4.3 - 2021-06-02
------------------

Fixed
~~~~~
- SimpleWORC and BasicWORC now support multilabel workflows.
- SimpleWORC and BasicWORC now support use of masks.

Added
~~~~~~~
- Unit testing for multilabel workflows.

3.4.2 - 2021-05-27
------------------

Fixed
~~~~~
- Bug in flattening of plot_ranked_posteriors function.
- Bug in plot_images: could not handle 2D images when applying slicing.
- Bug in precision-recall curve.
- Bug in performance estimation plotting.
- Preflighcheck now also accepts labels from txt or XNAT.

Added
~~~~~~~
- Label file can now also be separated by semicolons.

3.4.1 - 2021-05-18
------------------

Fixed
~~~~~
- Bugfix when PCA cannot be fitted.
- Bugfix when using LOO cross-validation in performance evaluation.
- Fix XGboost verson, as newest version automatically uses multihreading,
  which is unsuitable for clusters.
- Bug in decomposition for Evaluation.
- RankedPosteriors naming of images was rounded to an integer, now unrounded
- Several fixes for regression.
- Regression in unit test.
- Several fixes for using 2D images.

Changed
~~~~~~~
- Reverted back to weighted f1-score without predictproba for optimization,
  more stable.
- Updated regressors in SimpleWORC.

Added
~~~~~~~
- Option to combine features from a varying number of objects per patient,
  e.g. by averaging or taking the maximum.
- Logarithmic z-score scaler to be more robust to non-normal distributions
  and outliers.
- Linear and Ridge regression.
- Precision-recall curves.

3.4.0 - 2021-02-02
------------------

Fixed
~~~~~
- MAJOR: Bug in SearchCV sorting of output files.
- Bug in StatisticalTest for Manhattan plot.
- Bug in evaluate when using a test set.
- Bug in SearchCV for fitting preprocessing.
- Fix random states in boosting estimators.

Changed
~~~~~~~
- IMPORTANT: previously, used f1_score based on estimator.predict function.
  Now, use predict_proba.
- New defaults for random-search and ensemble.

Added
~~~~~~~
- All performances to output statistics.
- Script for plotting of errors in classification. Not embedded yet.
- Option to refit top performing workflows and save them.
- Part to conduct experiment with varying random search and ensemble sizes.

3.3.5 - 2020-10-21
------------------

Fixed
~~~~~
- Some function cleaning: removing redundant parts / variables.

Changed
~~~~~~~
- Part of developper documentation for addinf methods to hyperoptimization.
- Default config: SelectFromModel incorporated, so now also use
  that in feature selection step.

Added
~~~~~~~
- OneHotEncoder to workflows / HyperOptimization.
- Documentation updates.
- SelectFromModel expanded and properly integrated in workflow.
- AdaBoost as classifier and regressor.
- XGDBoost as classifier and regressor.
- Plotting of hyperparameters of best workflows in Evaluate network.
- Plotting of p-values of features.

3.3.4 - 2020-10-06
------------------

Fixed
~~~~~
- Bugfixes in some error messages.
- If a classifier cannot give a score, use the prediction instead.
- Bugfix in bootstrapping.
- Bugfix: use f1-weighted score in SimpleWORC binary classification.

Changed
~~~~~~~
- There are no longer ''patient_features'' in PREDICT: these are extracted
  from the DICOM tags and are thus now called ''dicom_features.
- As bootstrapping is now more efficient, increase default to 1000 iterations.

Added
~~~~~~~
- Option to transpose all images and segmentations to a default orientation.
  Currently only supports axial.
- Support for PREDICT DICOM features.
- Memory of single optimization job to general config.
- Catch when imputation completely removes a feature.
- Clipping as preprocessing option
- Function to show which hyperparameters were used in the best workflows.

3.3.3 - 2020-09-11
------------------

Fixed
~~~~~
- In the RobustStandardScaler, if less than two values for a feature are left,
  use the original set inset of the ``robust'' reduced set.

Changed
~~~~~~~
- By default, semantic features are skipped in scaling, as the robust scaler
  cannot deal well with categorical variables.
- Wrapped scalers in single WORC scaler object to allow above for all scalers.

Added
~~~~~~~
- Leave-One-Out (LOO) cross-validation.
- Option to skip features in scaling.
- Bias correction in preprocessing.
- Option to check whether Nifti spacing seems incorrect and correct
  with DICOM metadata.
- ElasticNet as classifier through LogisticRegression penalty.

3.3.2 - 2020-08-19
------------------

Fixed
~~~~~
- Bug in fit and score when using scaling: was incorrectly parsed as string
  and always set to None.
- Catch exception in ADASYN sampling.
- Typo in configuration documentation.

Added
~~~~~~~
- New type of scaler (robust z-scoring)
- Resampling of image and mask in preprocessing (preprocessing and segmentix
  nodes)

Changed
~~~~~~~
- Newly added scaler is now also the default to use, instead of the search
  over the older included scalers.
- Evaluation of estimator is now separate from training it.

3.3.1 - 2020-07-31
------------------

Changed
~~~~~~~
- Updated to using tikzplotlib for conversion of figures to LaTeX instead
  of deprecated matplotlib2tikz.
- Output of evaluation pipeline now in separate subfolder.
- KNNImputer now also in sklearn, missingpy deprecated, so switched to
  sklearn KNNImputer.

Fixed
~~~~~
- Bug in fixandscore when using resampling.


3.3.0 - 2020-07-28
------------------

Added
~~~~~~~
- Graphviz vizualization of network is now nicely grouped.
- Properly integrated ObjectSampler: various resampling options now available.
- Verbose option to fit and score tool
- Validator for PyRadiomics output.
- FAQ version to documentation

Changed
~~~~~~~
- Upgraded to new versions of sklearn (0.23.1) and imbalanced learn (0.7.0)
- Some defaults, based on computation time.
- Do not skip workflow if feature selection selects zero features,
  but disable the feature selection.
- Do not skip workflow if resampling is unsuccesfull,
  but disable the resampling.
- Default scaling is now not only Z-score, but also MinMax and Robust
- Renamed plot SVM function and all functions using it, as now
  we use all kinds of estimators.
- L1 penalty does not work with new standard LR solver. Removed L1 penalty.

Fixed
~~~~~
- Bug when using both elastix and segmentix.
- Bug when using elastix in train-test workflow.
- IMPORTANT: Previously, all methods except the machine learning where fit on
  both the training and validation set together in fitandscore. This led
  to overfitting on the validation set. Now, these are properly split.
- Bugfix in Evaluate standalone for decompositon tool.
- Applied imputation in decomposition if NaNs are detected.
- In the facade ConfigBuilder, an error is raised when incorrect
  overrides are given.
- Bugfix in statistical feature test plotting.
- Bugfix in Evaluate when using ComBat
- Bugfix in feature converter of PyRadiomics when using 2D images.
- Catch Graphviz error.
- Bug in ICC.


3.2.2 - 2020-07-14
------------------

Added
~~~~~~~
- In classify node, when using temporary saves, start from where
  the process previously stopped instead of from the beginning.
- Imputation to ComBat.

Changed
~~~~~~~
- Imputation is now the first step in the workflows. More logical as
  scaler and variance threshold can crash on missing values.
- In config, preprocessing fields are now actually called preprocessing and
  not normalize.

Fixed
~~~~~
- Preflightcheck now also compatible with BasicWORC.
- Bugfix in ComBat when not using mod variable and skipping patients.
- Bug in PyRadiomics feature converter: can now handle 2D images.
- ReliefSampleSize parameter is now a uniform distribution, which it should be.
- Gabor features now actually used in model instead of only computing them.


3.2.1 - 2020-07-02
------------------

Added
~~~~~~~
- Major documentation update.

Changed
~~~~~~~
- PyRadiomics setup not dependent on pre-install of numpy anymore, so altered
  travis, yml, setup, and documentation.
- PREDICT updated, change dependencies.
- Defaults are now a bit different: see argumentation in the documentation.
  Main thing is that PyRadiomics and PREDICT both compute certain features,
  so it's redundant to use both. Additionally, the wavelet features
  from PyRadiomics add +1000 features, which did not seem to help in many
  experiments while majorly slowing down the computation.

Fixed
~~~~~
- Catch error when PCA does not converge in fit and score function.

3.2.0 - 2020-06-26
------------------

Added
~~~~~~~
- Labelprocessing can now also handle having patient ID in the feature files.
  Was required for ComBat.

Changed
~~~~~~~
- Output of plot_SVM function is better ordered.
- Several defaults, as we now have PyRadiomics fully embedded, resulting in
  a large increase in features.
- No more overrides for the full config, as the default now is the full config.

Fixed
~~~~~
- Cardinality of decomposition tool was incorrect.
- ComBat integration in WORC network now works properly.
- Documentation didn't build due to C-extension dependencies of PyRadiomics,
  and thus therefore also PREDICT. Fixed in setup.py and readthedocs files.
- Documentation building.
- Bugfix in segmentix test output url.
- Bugfix in SimpleWORC facade when using features.
- Warning when using Evaluation pipeline without images.


3.1.4 - 2020-05-26
------------------

Added
~~~~~~~
- Catch error if number of segmentations supplied does not match number of
  images.
- Add support in SimpleWORC and BasicWORC for multiple segmentations per
  patient.
- Chi2 test in statistical testing.
- fastr tool to make boxplots of all features, overall and per class.
- Added this boxplot tool to the evaluate workflow.
- Option in evaluation to overfit feature scaling to test set: should only
  be used to assess differences between the training and test sets, not
  in an actual model.
- Option to delete small objects in segmentation.
- Option to within the preprocessing, use a dilated ROI.
- Otsu thresholding as mask for preprocessing.
- Memory for each fastr node is now in a dictionary of the WORC object and can
  be easily changed.
- PyRadiomics now fully embedded and configurable.
- ComBat harmonization: currently as separate tool on full dataset,
  not in cross-validation.
- Computation of ICC, and thresholding object to use ICC for feature selection.
- Added groupwise feature selection per feature extraction toolbox.
- Feature converter tool, to convert features from a toolbox to WORC compatible
  format.
- RobustScaler for feature scaling.
- Decomposition to evaluate network.
- Combat: in WORK workflow.

Changed
~~~~~~~
- Resampling of objects is now after feature selection.
- Made plot_SVM function more memory efficient.
- For PCA, Relief, VarianceThreshold, and SelectFromModel feature selection,
  you can now simply supply a float to determine the percentage of times
  this method is used in the created workflows.
- Moved load_features from trainclassifier to file_io.
- Matching of PID from labels from label file to other objects is now all
  converted to lower case.
- Refactoring of WORC network building.
- Segmentix tool is cleaned up. Segmentix script is moved to processing.

Fixed
~~~~~
- Order of methods in preprocessing function of SearchCV did not correspond
  with that in fitandscore.
- Replace spaces in uri conversion of sources in SimpleWORC.
- Check whether all fitandscore jobs succeeded, otherwise throw error.
- Bug in PCA when n_components > min(n_samples, n_features)
- Random seed is now set and passed to PCA, Relief and all classifiers
  for reproducability of the results.
- Evaluate can now also accept multiple feature toolboxes.


3.1.3 - 2020-01-24
------------------

Added
~~~~~~~
- Some options for the plot_images slicer function.
- Validators to check your inputs before executing experiment.
- Timer in classification log.
- Backwards compatibility in fastr config.
- Option for fixed seed in cross-validation.
- BasicWORC Facade.
- Support for computing confidence intervals on differences between models.
- Error when config file cannot be found.

Changed
~~~~~~~
- Preprocessor slows down progress and is not always neccesary. Made it optional.
- Moved the preprocessor to the SearchCV script to do once on the training set,
  not in within the algorithm optimization.
- Ensembling during training is turned-of, as it takes to much time. Only
  used when plotting the performance.
- Debug flag includes fixed seed in cross-validation.
- Joblib now uses by default only 1 core and threading backend.

Fixed
~~~~~
- Bug in patient naming of plotting function: if ensembling was done in training,
  do not re-ensemble.


3.1.2 - 2019-12-09
------------------

Added
~~~~~~~
- Support for Oncoradiomics RadiomiX tool
- Groupwise Search includes GLDZM, Fractal, location, NGTDM, NGLDM, wavelet,
  and rgrd features
- SimpleWORC now also accepts features instead of images and segs as input
- Preprocessor object to preprocess the features before any fitting algorithms
  are ran. Mostly to detect possible faults/errors in the data.

Changed
~~~~~~~
- On runtime, copy config.d file if it does not exist yet.

Fixed
~~~~~
- KNN imputation gave an error if >80% of the feature values were missing.
  Added preprocessing function to remove these features.

3.1.1 - 2019-11-28
------------------

Added
~~~~~~~
- Travis continuous integration for Windows.
- Removed RT Struct Reader, as it was buggy and not used.

Changed
~~~~~~~
- SimpleWORC now properly uses the fastr FileSystem plugin, instead
  of supplying the absolute filepaths.

Fixed
~~~~~
- Under Windows, creation of the fastr home folder if it did not exist
  did not work when using pip for installing. We now use a new feature
  of fastr to simply add the WORC folder to the fastr config
  at WORC import time.
- When debugging, override manual tempdir setting and always use default. On
  Windows, Travis gives errors if the tempdir is not in a vfs mount.
- Use shutil.move in the datadownloader, as os.rename could not overwrite files.

3.1.0 - 2019-10-16
------------------

Added
~~~~~~~
- Thresholding option in plot_SVM.
- NPV (Negative Preditive Value) to classification metrics.
- Facade for easier interaction with WORC.
- Thresholding option in plot_SVM.
- Function to create fixed splits for cross validation.
- n_splits parameter for train-test cross validation.
- Added generalization score.
- Parameter to choose how many of the optimal settings to save (maxlen).
- Option to combine multiple onevsrest models in plot_SVM.
- StatsticalTestThreshold feature selection for multilabel problems.
- Support for test sets in which only one class is present in various
  plotting functions and the metrics.
- Installation: create fastr home if it does not exist yet.
- Boostrapping as performance evaluation in plot_SVM.
- Confidence intervals for boostrapping based on percentile.
- Catch for if patient is in the test set, but not the overall label set.
- Downloader for downloading example datasets.
- ReadTheDocs.yml for configuration of documentation.
- Unit test included in Travis.
- Various detectors.

Changed
~~~~~~~
- Plot_SVR is removed: it's now embedded in plot_SVM.
- Moved statistical feature selection to last step in fit and score.
- Also the minimum train and validation score are now saved.
- Put scaler at top of fitandscore function.
- Make link in file conversion if output is same format as input.
- Sort keys in performance output JSON.
- VarianceThreshold features selection on by default.
- Removed grid_scores from SearchCV as support is dropped in sklearn > 0.20
- Renamed IntermediateFacade to SimpleWORC
- Use inspect to find packagedir

Fixed
~~~~~
- Metric computation can now handle it when both the truth and the predicted
  labels are from a single class.
- Plotting module now correctly initialized.
- Plot_SVM now also works properly for regression.
- Masks for ROI normalization now properly added.
- Preprocessing: mask needed to be cast to binary.
- Failed workflows now return nan instead of zero for performance.
- Several bugs in multilabel performance evaluation
- Ring in segmentix was in sagital instead of axial direction.
- Added replacenan in features before applying SMOTE.
- Metadata test was not passed to calcfeatures: bugfix.
- Bugfix: overide labels in facade when predict_labels is called.
- Several bugfixes in the overrides in the facade configbuilder.
- Various print commands converted to Python3: .format prints were still
  left and sometimes buggy.
- StatisticalTestFeatures and PlotRankedScores tools only accepted cardinality
  of 1.
- Bugfixes in many plotting functions: opening files with 'w' instead of 'wb'
  due to python3 conversion, Compatibility issues with plot_SVM due to
  conversion.
- Except error when Grahpviz is not installed.
- Symlinking in worccastcovert not supported by Windows, reverted to copying.
- Bugfix in create_ensemble in SearchCV when using ensemble = 1.


3.0.0 - 2019-05-08
------------------

Added
~~~~~~~
- Now ported to Python3.6+ (Python 2 is no longer supported!). Thereby also
  to fastr3.
- Compatibility for Windows. Some small changes in functions, as some packages
  behaviour differently under Windows. Also, adjusted sink and source paths
  to use OS file separator.
- Config is now also a sink.


Changed
~~~~~~~
- PCE and DTI node removed, as they were not open source.
- Pinfo file can now also be a csv. Txt is still supported.
- Use fastr as default for hyperparameter search parallelization instead
  of Joblib, as this is much more flexible.
- When the conffidence interval cannot be computed, just use the mean.


Fixed
~~~~~
- WORC_config.py was not correctly copied in Windows due to incorrect path separation.
- Source creation for the config was only for Linux.
- In numpy 1.15>, booleans cannot be subtracted. Fixed an error due to this in
  segmentix by using bitwise_xor instead.
- Bug when using masks, but not for all images, and segmentix.
- Cardinality of classify node was incorrect.


2.1.3 - 2019-04-08
------------------

Changed
~~~~~~~
- PREDICT was updated, so had to update the requirements. Changed it
  to a minimum of PREDICT to prevent these issues in the future.


2.1.2 - 2019-04-02
------------------

Added
~~~~~~~
- Dummy workflow in segmentix and calcfeatures PREDICT tools.
- Added several new PREDICT parameters.
- Slicer tool.


Changed
~~~~~~~
- Memory for elastix tool is now larger.

Fixed
~~~~~
-Evaluate framework now correctly adopts the name you give it.


2.1.1 - 2019-02-15
------------------

Added
~~~~~~~
- Several new PREDICT variables to the config.
- Multilabel classification workflow.
- New oversampling strategy.
- RankedSVM multilabel classification and Relief feature selection.


Changed
~~~~~~~
- Major reduction in memory usage, especially due to PREDICT updates.
- Only use first configuration in the classify config.
- Outputs are now in multiple subfolders instead of one big folder.


Fixed
~~~~~
- Minor bug in test workflow: needed str of label in appending to classify.
- There was a bug in using a .ini file as a config.


2.1.0 - 2018-08-09
------------------

Added
~~~~~~~
- Feature imputation settings in WORC config.
- PCA settings in WORC config.
- Dummy file, which can generally be accepted by WORC.
- Preprocessing is now a separate node before the calcfeatures node.
- Started working on a RTStructReader tool.
- Added EditElastixTransformFile node to set FinalBSplineInterpolationOrder to 0
  in Elastix. Neccesary for transforming segmentations.
- Registred image is also saved as a sink.
- Tex, Zip and PNG Datatypes
- Plot ROC tool for PREDICT
- Plot SVM tool for PREDICT
- Plot Barchart tool for PREDICT
- Plot Ranked Scores tool for PREDICT
- Plot statistical test tool for PREDICT
- Tools: Evaluation network. Can currently be run only serparately: future
  work includes the optional addition of the Evaluate network to the WORC network.
- Settings for PREDICT General, which contains the joblib Parallel settings and
  whether a temporary save will be made after each cross validation.


Changed
~~~~~~~
- Separate sinks for the output segmentations of the elastix and segmentix
  nodes.
- Switched from using PXCastConvert to WORCCastConvert, hence ITK is not
  anymore required as well as ITK tools.

Fixed
~~~~~
- Patientclass ID was used for both test and training. Now given separate names.
- When elastix is used but segmentix isn't, there was a bug.
- DataFile dataype is now a TypeGroup instead of an URLType.
- Last transformation output from elastix is passed further to the network.
- Set FinalBSplineInterpolationOrder to 0 before transforming segmentation with
  transformix.
- Bug: when giving multiple feature sources, only the first was used.


2.0.0 - 2018-02-13
------------------

Added
~~~~~~~
- Elastix and transformix as separate workflow in the tools folder. Can be used
  through the WORC.Tools attribute.
- Example data for elastix and transformix tool.
- Workflow for separate training and testing set
- FASTR tool for applying ttest to all features. Works similar to the
  trainclassifier tool in terms of inputs and outputs.


Changed
~~~~~~~
- Option for multiple modalities. Supports infinitely many inputs per object.
- Moved many PREDICT parameters to the configuration file.
- When using a multimodal workflow with only a single segmentation,
  Elastix will automatically be used for registration. Note that you have to
  put the reference segmentation on the first modality!

Fixed
~~~~~
- Proper combining of features from multiple modalities to classify tool.
- Minor bugs in segmentix tool.
- For multiple modalities, add only optional sources like metadata when present.

1.0.0rc1 - 2017-05-08
---------------------

First release