Notebooks
---------

The notebooks in this repository serve as descriptions of the pipeline design, motivation, and implementation, while also presenting key results and providing brief commentary on the research decisions made.

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   :widths: 35 80
   :header-rows: 1

   * - Notebook
     - Description
   * - ``0_data_preprocessing.ipynb``
     - Overview of the preprocessing and filtering pipelines, including data querying and the motivation behind the cuts used to obtain a usable dataset for analysis.
   * - ``1_apogee_scaled_pipeline.ipynb``
     - A full run-through of the Extreme Deconvolution (GMM) pipeline applied to the 6-dimensional APOGEE dataset (with normalisation), describing the analysis and providing visualisation and discussion of results.
   * - ``2_galah_scaled_pipeline.ipynb``
     - A similar pipeline applied to the 12-dimensional GALAH data.
   * - ``3_apogee_unscaled_pipeline.ipynb``
     - A demonstration of the XD pipeline’s handling of manually adjusted or unscaled energy dimensions.
   * - ``4_dimreduction_investigate.ipynb``
     - Uses dimensionality reduction to explore structure stability and investigate clustering performance in low-dimensional space.
   * - ``5_apogee_assignment_statistic.ipynb``
     - A Notebook demonstrating the cluster assignment analysis pipeline and investigating the Aurora Population.
   * - ``[6_galah_reconstruction.ipynb``
     - Overview of the pipeline that automates robust dimensionality mapping, clustering, and analysis on GALAH data, along with visualised results.
   * - ``7_6D_galah_reconstruction.ipynb``
     - Here we investigate the success of GALAH at resolving these structures and whether this is simply attributed to the Higher Dimensionality of Chemical Abundances or the dataset itself.
   * - ``8_computational_cost_compare.ipynb``
     - Here we explicity compare the computational costs of the low dimensional and high dimensional pipelines to show the significant speed up across all models