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Poetry version

* Moved from anaconda-compatible setup.py setuptools-based approach to
    Poetry-based builds.
* Implemented multi-dataset plotting using the quickslicer
* Safeguarded some script files with __name__ boilerplate
* Improved committee nets

edgerun10 version

Updated CI to use python3.8 by default
Added "edgerun10" reference script for filtering QLK data
Updated dataslicer to allow to optionally connect to NNDB
Increase testing surface

Improved CI for QLKNN version

Edgy-Camille version

Big improvements again on the EdgeSets, HornNets, MarionNets, megarun3, and pipeline side of things. Notably:
- HornNet
  * Quickslicer and training improvements
    https://gitlab.com/qualikiz-group/QLKNN-develop/-/merge_requests/24
    - quickslicer now also outputs abs abs thresh mismatch and the mean of all measures
    - target data for multi-output NNs can be scaled with mean of stds
    - hyperparameters can be tracked in TensorBoard for hyperparameter scans
    - load_from_store without columns (columns=False)
    - repeating feature_names in megaHornNet
- Test and build pipeline
  https://gitlab.com/qualikiz-group/QLKNN-develop/-/merge_requests/26
  https://gitlab.com/qualikiz-group/QLKNN-develop/-/merge_requests/33
  https://gitlab.com/qualikiz-group/QLKNN-develop/-/merge_requests/35
  https://gitlab.com/qualikiz-group/QLKNN-develop/-/merge_requests/36
  https://gitlab.com/qualikiz-group/QLKNN-develop/-/merge_requests/37
  * Add full CI test pipeline for Python3.6 and Python3.8. Target Python is
  * Python 3.7. (999737d4, dc0a4876, 534366c5, da6bad29, 5eb17813)
  * Use conda-friendly packaging using .txt files (b13f7218)
  * Use setuptools_scm to set the version of the package (e6ab479c)
  * Do not upload full venv as job artifact (586d99e8) [thanks Francis noticing file system explosion]
  * Require at least TensorFlow 2.2.0 to run Dan Nieuwenhuizens workflows on m100 (b13f7218)
  * Replaced ye olde mega_nn.py and replaces it with a new and shiny qlknn_hyper_10D.py. See a7070727
    - More flexible clipping (e104fc52, c73798d4)
    - Allow momentum filter to allow for negative values (a6adefee)
  * Drops support for Python 2.7 (f8bb4cff)
  * Blackify.py files:
    - setup.py (e0537d6b)
    - All python files (c4277fd8, a6adefee)
    - All python scripts (35a9019c, 90338421)
  * Blackify ignore list can be found in .git-blame-ignore-revs, see (01bb3a72, 1c990405)
  * Upgrades Black to use pyproject.toml and use python 3.7 syntax
  * Creates a new global fixture store_path build from
  * qlk_h5_gen5_4D_dataset for testing of gen5-aware code
  * Moves the existing tests to use above fixture
  * Adds a silly echo function to qlknn/training/keras_models.py:QLKNet to
  * test partial initialization of Keras classes
  * Adds initial mostly empty tests for Camille's edgerun code
  * Adds fallbacks to outlier dropping
  * Build packages on every tag
- Implement Sphinx documentation and CI for qlknn package
  https://gitlab.com/qualikiz-group/QLKNN-develop/-/merge_requests/27
  * Autoparse requirements*.txt (1d26f946)
  * Clean up package dependencies (1d26f946, 1ecf2b71)
  * Use scripting over YAML constructs (1ecf2b71, 1ecf2b71)
  * Use Sphinx instead of Doxygen (126880b9)
- Add workaround for pip install bug
  https://gitlab.com/qualikiz-group/QLKNN-develop/-/merge_requests/29
  * See https://github.com/pypa/pip/issues/7953 relating to editable installs
- Quickslicer cleanup
  https://gitlab.com/qualikiz-group/QLKNN-develop/-/merge_requests/30
  * Move CLI interface from docopt to argparse (88615aee, dc5f6dd1)
  * Make qlknn_hyper_10D.py usable in the quickslicer (c3445450)
  * Allow slicing with the "wrong" dataset {e.g. 9D and 4D for 7D networks} (7decf15b, 127ac2e2)
  * Add quickslicer as console script (5a30f06a)
  * Reduce reliance on global variables (9e2403be)
  * Move testdata to dedicated folder (4ef94768)
  * Disable luigi tests (7d378723)
  * Add tests and testdata for
    - quickslicer (3d459e7b, 090aa7dd, 7ae1e47a)
    - committees (d8bee41a)
    - FFNNs (08d7031e, 9aa23dee)
  * Shuffle the dataset is now the default (1d31cfb2)
- Clustering scripts by @BartKremers and @aaronkho
  https://gitlab.com/qualikiz-group/QLKNN-develop/-/merge_requests/28
- MarionNets
  https://gitlab.com/qualikiz-group/QLKNN-develop/-/merge_requests/31
  https://gitlab.com/qualikiz-group/QLKNN-develop/-/merge_requests/32
  preparing for divnet training for QLKNN-11D and MarionNets:
  * pytest test suite improvements
    - General cleanup (c0cd2481)
    - Add tests for divsum variables in dataset (fcd5f92e, bdd19f19, 7622d5bb)
    - Removal of unused tests (7c5b6ad9, 6df4b1b7)
    - Add new "CLI-like python code" tester (9e8db883, 928c511c, 0ed9c395)
  * qlknn refactor
    - Move all code to Black codestyle (4f43f45c, 60451e24), see https://black.readthedocs.io
    - Tiny internal syntax improvements (c822debe)
    - WIP code to misc (4eeb8283)
  * Add more entry points for CLI tools (7002755b, a74bbeb2)
  * Allow generating divsum variables on the fly for QLKNN training (9359d21b, ce1c14b2, 1792a38b, d3b63ed1, c9b35831)
  * Improvements to docs (d7d30297)
  * Karel-style linter settings (d60d4fd1)
  * Improved indexing and low/high bounds for get_output (6d1de645), thanks @MESmedberg
- CamilleNets
  https://gitlab.com/qualikiz-group/QLKNN-develop/-/merge_requests/34
  * Implements all contributed CamilleNet scripts. Thanks @cambouvy

Keras-enabled version

Big improvement on usability in the glorious post-paper time.
Most notably, training loop finally uses TF2.0/keras! Not much loss in performance.

- Main training loop now uses TensorFlow>=2.0, and can use Keras features
  * https://gitlab.com/Karel-van-de-Plassche/QLKNN-develop/-/merge_requests/17
- Improvement to quickslicer
  * https://gitlab.com/Karel-van-de-Plassche/QLKNN-develop/-/merge_requests/20
- Improved debugging
  * https://gitlab.com/Karel-van-de-Plassche/QLKNN-develop/-/merge_requests/23
- Committee nets with multiple outputs A. Ho, publication in preparation.
  * https://gitlab.com/Karel-van-de-Plassche/QLKNN-develop/-/merge_requests/12
- Add CMGnets (later dubbed HornNets), see P. Horn MSc thesis. Publication in preparation
  * https://gitlab.com/Karel-van-de-Plassche/QLKNN-develop/-/merge_requests/18
  * https://gitlab.com/Karel-van-de-Plassche/QLKNN-develop/-/merge_requests/19
  * https://gitlab.com/Karel-van-de-Plassche/QLKNN-develop/-/merge_requests/22
- Improve filtering for committee nets A. Ho, publication in preparation.
  * https://gitlab.com/Karel-van-de-Plassche/QLKNN-develop/-/merge_requests/16
  * https://gitlab.com/Karel-van-de-Plassche/QLKNN-develop/-/merge_requests/15
- Allow loading parts of Kerasnets
  * https://gitlab.com/Karel-van-de-Plassche/QLKNN-develop/-/merge_requests/13
- Allow not shuffling every epoch, saves time in large-dataset, small-network cases. See R. Winkler MSc thesis
  * https://gitlab.com/Karel-van-de-Plassche/QLKNN-develop/-/merge_requests/14

PoP submitted version