Move tensorflow_models/research/astronet to google-research/exoplanet-ml

research/astronet/README.md

@@ -1,75 +1,4 @@
-# Exoplanet ML
+# AstroNet has moved!
 
-Machine learning models and utilities for exoplanet science.
-
-## Code Author
-
-Chris Shallue: [@cshallue](https://github.com/cshallue)
-
-## Quick Start
-
-Jump to the [AstroNet walkthrough](astronet/README.md#walkthrough).
-
-## Citation
-
-If you find this code useful, please cite our paper:
-
-Shallue, C. J., & Vanderburg, A. (2018). Identifying Exoplanets with Deep
-Learning: A Five-planet Resonant Chain around Kepler-80 and an Eighth Planet
-around Kepler-90. *The Astronomical Journal*, 155(2), 94.
-
-Full text available at [*The Astronomical Journal*](http://iopscience.iop.org/article/10.3847/1538-3881/aa9e09/meta).
-
-## Directories
-
-[astronet/](astronet/)
-
-* A neural network for identifying exoplanets in light curves. Contains code for:
-  * Downloading and preprocessing Kepler light curves.
-  * Building different types of neural network classification models.
-  * Training and evaluating a new model.
-  * Using a trained model to generate new predictions.
-
-[astrowavenet/](astrowavenet/)
-
-* A generative model for light curves.
-
-[light_curve/](light_curve)
-
-* Utilities for operating on light curves. These include:
-  * Reading Kepler data from `.fits` files.
-  * Applying a median filter to smooth and normalize a light curve.
-  * Phase folding, splitting, removing periodic events, etc.
-* [light_curve/fast_ops/](light_curve/fast_ops) contains optimized C++ light
-curve operations.
-
-[tf_util/](tf_util)
-
-* Shared TensorFlow utilities.
-
-[third_party/](third_party/)
-
-* Utilities derived from third party code.
-
-
-# Setup
-
-## Required Packages
-
-* **TensorFlow** ([instructions](https://www.tensorflow.org/install/))
-* **Pandas** ([instructions](http://pandas.pydata.org/pandas-docs/stable/install.html))
-* **NumPy** ([instructions](https://docs.scipy.org/doc/numpy/user/install.html))
-* **SciPy** ([instructions](https://scipy.org/install.html))
-* **AstroPy** ([instructions](http://www.astropy.org/))
-* **PyDl** ([instructions](https://pypi.python.org/pypi/pydl))
-* **Bazel** ([instructions](https://docs.bazel.build/versions/master/install.html))
-* **Abseil Python Common Libraries** ([instructions](https://github.com/abseil/abseil-py))
-
-## Run Unit Tests
-
-Verify that all dependencies are satisfied by running the unit tests:
-
-```bash
-bazel test astronet/... astrowavenet/... light_curve/... tf_util/... third_party/...
-```
+The code is now located at https://github.com/google-research/exoplanet-ml