History

v1.1 series

v1.1.0 (xx xxx 20xx)

New features:
  • Added models : ApogeeKplerEchelle

  • Input data can now be a dict, such as nn.train({'input': input_data, 'input': aux_input_data}, {'output': labels, 'output_aux': aux_labels})

  • Added numerical integrator for NeuralODE

Improvement:
Breaking Changes:
  • Deprecated support for all Tensorflow 1.x

  • Dropped optional Keras support, now depends on Tensorflow only

  • Tested with Tensorflow 2.2.x

  • Incompatible to Tensorflow 1.x and <=2.2 due to necessary changes for Tensorflow eager execution API

v1.0 series

v1.0.1 (5 March 2019)

This release mainly targeted to the paper Simultaneous calibration of spectro-photometric distances and the Gaia DR2 parallax zero-point offset with deep learning available at [arXiv:1902.08634] [ADS]

Documentation for this version is available at https://astronn.readthedocs.io/en/v1.0.1/

New features:
  • Better and faster with IPython tab auto-completion

  • Added models : ApogeeDR14GaiaDR2BCNN

Improvement:
  • Improved data pipeline to generate data for NNs

Breaking Changes:
  • Tested with Tensorflow 1.11.0/1.12.0/1.13.1 and Keras 2.2.0/2.2.4

v1.0.0 (16 August 2018)

This is the first release of astroNN. This release mainly targeted to the paper Deep learning of multi-element abundances from high-resolution spectroscopic data available at [arXiv:1804.08622] [ADS]

Documentation for this version is available at https://astronn.readthedocs.io/en/v1.0.0/

New features:
  • Initial Release!!

Breaking Changes:
  • Tested with Tensorflow 1.8.0/1.9.0 and Keras 2.2.0/2.2.2

  • Python 3.6 or above only

v0.0 series

v0.0.0 (13 October 2017)

First commit of astroNN on Github!!!