Tutorials


Install ASTROMER

ASTROMER is tested and supported on the following 64-bit systems:

  • Python 3.8-3.10

    • Install our python library including all the functionalities:

    pip install ASTROMER

    Explore ASTROMER

    Learn to use ASTROMER following the tutorials stored in these Google Colaboratory notebooks.

    Tutorial 1: Prepare the data

    Here you will learn how to format our available data to fit ASTROMER's requirements.



    Tutorial 2: Classification using MACHO Catalog

    Use the pre-trained weights to classify light curves from the Massive Compact Halo Object survey with a Tensorflow model.



    Tutorial 3: Classification using ALeRCE broker

    Learn to extract the embeddings of ASTROMER to classify light curves from the Zwicky Transient Facility (ZTF) using a Random Forest classifier.