Changelog

0.1.0 (2016-09-15)

First release on PyPI.

0.1.1 (2016-09-17)

Minor documentation changes
Renamed some internal variables

0.2.0 (2016-09-21)

Introduced new feature: regress_out_feat
Major renaming of variables for concistency

0.3.0 (2016-11-30)

Added L-BFGS optimizer in addition to Adam. Use optimizer="lbfgs" in Concise()

0.3.1 (2016-11-30)

New function: :code:best_kmers for motif efficient initialization

0.4.0 (2017-02-07)

refactor: Removed regress_out feature
feature: multi-task learning

0.4.1 (2017-02-09)

bugfix: multi-task learning

0.4.2 (2017-02-09)

same as 0.4.1 (pypi upload failed for 0.4.1)

0.4.3 (2017-02-09)

feat: added early_stop_patience argument

0.4.4 (2017-02-10)

fix: When X_feat had 0 columns, loading its weights from file was failing.
feat: When training the global model in ConciseCV, use the average number of epochs yielding the best validation-set accuracy.

0.4.5 SNAPSHOT

fix: Update tensorflow function (tf.op_scope -> tf.name_scope, initialize_all_variables -> tf.global_variables_initializer)

0.6.0 (2017-07-16)

Complete re-write. Now moved completely to Keras from pure TensorFlow.

0.6.1 (2017-07-16)

fix: required version keras>=2.0.2

0.6.2 (2017-08-17)

0.6.3 (2017-08-16)

added more documentation
ipynb -> docs compilation
hocomoco motif database added to concise.data.hocomoco
added utility function for position extraction
fix: hyopt and memoization of data() now works
implemented seqlogo plot

0.6.4 (2017-08-29)

Added more documentation
hyopt.CompileFN: loss_metric -> optim_metric
eval_metrics: y,z -> y_true, y_pred arguments
speedup encodeSequences by 4x