GUI updates

This release mostly features updates in the GUI:

• Added publish_data functionality which allows pushing data sources to client graphs
• Linking x-range of coverage and rates/protection factor figures is working again
• Coverage and rates/protection figures are now aligned by introducing left border space
• Different color maps for the coverage figure can be selected
• A color bar was added to the coverage control panel

Other changes:

• Added tests for the GUI
• Removed old code and comments, specifically RateFigureOld and CoverageFigureOld
• Added a script to run a cluster locally
• Added a new function for obtaining initial guesses (needs to be added to GUI)

Fixes

• Fixed thresholding values bug (#86)
• Fixed fit1 in initial guesses by default (#87)
• Fixed classification not working after second iteration of fitting (#71)
• Fixed not re-applying thresholds when threshold values are set (#88)
• Fixed mouse-over hovertools (#73)

Full protein tensorflow fit

The main new feature of this beta release is the change to fitting of the whole protein in one go rather than splitting it into sections and fitting one by one.

Advantages include:

• Significant speed increase
• Regularizer can propagate across gaps of no coverage
• Regularizer now propagates across prolines

Changelog:

• Default value for l1 regularizer is now 2000 because it was changed to average rather than sum
• Default value of epochs from 10000 to 100000
• Added method for getting intersections of KineticSeries
• Added method to get k_int structured array, k_int for prolines and no coverage is now 0.
• Updated internal intervals to [start, end) rather than [start, end]
• Added TFCoverage object to allow fitting over the whole protein, to be merged in future releases
• Added a 'uptake_corrected' field which is absolute D uptake but corrected by FD control
• Added 'half life' initial guesses to GUI
• Added full protein fit to GUI (replaced old fitting procedure)

First Beta Release

This is the first beta release of pyHDX

Main features:

• Weighted averaging of exchange rate
• Global fitting of exchange rate
• Global fitting of protection factors taking intrinsic rates into account

Changelog

• Version numbers by pbr
• Version numbers in exported data and web app title
• Global fit now combines sections with a gap of zero
• Added global PF fitting test
• Regularization is now calculated as the mean instead of the sum as the error function is MSE not total squared difference
• Updated Neural networks to Keras functional API to allow parallel fitting of multiple datasets

Version 0.0.1 alpha1

Early alpha before removal of expfact and deprecated code