Merge pull request #24 from swagnercarena/readme

Readme

MANIFEST.in

@@ -1,3 +1,23 @@
 include *.rst
 include *.md
 include *.txt
+include datasets/hst_psf/emp_psf_f814w_*x.npy
+include paltax/TrainConfigs/train_config_500k.py
+include paltax/TrainConfigs/train_config_50k.py
+include paltax/TrainConfigs/train_config_5M.py
+include paltax/TrainConfigs/train_config_constant.py
+include paltax/TrainConfigs/train_config_exp_fast.py
+include paltax/TrainConfigs/train_config_exp_slow.py
+include paltax/TrainConfigs/train_config_linear.py
+include paltax/TrainConfigs/train_config_linear_0p001.py
+include paltax/TrainConfigs/train_config_npe_base.py
+include paltax/TrainConfigs/train_config_res_18.py
+include paltax/TrainConfigs/train_config_res_18_small.py
+include paltax/TrainConfigs/train_config_res_18_very_small.py
+include paltax/TrainConfigs/train_config_res_34.py
+include paltax/TrainConfigs/train_config_res_d.py
+include paltax/TrainConfigs/train_config_snpe_base.py
+include paltax/TrainConfigs/train_config_snpe_instant_avg.py
+include paltax/TrainConfigs/train_config_snpe_m_ad.py
+include paltax/InputConfigs/train_config_linear.py
+include paltax/test_files/*

README.rst

@@ -61,6 +61,6 @@ Code for generating the plots included in some of the publications using ``palta
 
 Attribution
 -----------
-If you use ``paltax`` for your own research, please cite the ``paltax`` package (`Wagner-Carena et al. 2024 <https://arxiv.org/abs/xxxx.yyyyy>`_)
+If you use ``paltax`` for your own research, please cite the ``paltax`` package (`Wagner-Carena et al. 2024 <https://arxiv.org/abs/2404.14487>`_)
 
 ``paltax`` builds off of the publically released Google DeepMind codebase `jaxstronomy <https://github.com/google-research/google-research/tree/master/jaxstronomy>`_.