/membership

Primary LanguageTeX

Description of all the files/folders here

Folders

  • input/ This folder contains the 600 (compressed) synthetic files used for the validation process.

  • metrics/ Contains the output from the getMetrics script.

  • old/ Old not-used scripts.

  • OLD_modules Early iterations of the code.

  • output/ This folder contains the output files with the probabilities assigned by pyUPMASK/UPMASK.

  • plots/ Where all the generated plots are stored.

  • synth_clusts Stores the synthetic clusters generated by the generate_synth_clust script.

  • UPMASK_convergence/ Files used by the UP-convergence.py script.

Scripts

  • auxFuncs Contains the parameters tie_min, tie_max, and the functions of general use: WinTieLoss(), readTables().

  • cantat_gaudin.py Cantat-Gaudin code modified to run on the cluster.

  • CI_metrics pyUPMASK minus UPMASK versus CI for each metric, one file per clustering method. Also plots, optionally, the raw metric for pyUPMASK.

  • CI_UP-PYUP pyUPMASK minus UPMASK versus CI for all the combined metric, for each clustering method.

  • CMD_results_plot Plot the three worst performers for each set (PHOT, PM) for a selected clustering method, versus UPMASK.

  • combined_summary Make the full summary plot that compares pyUPMASK versus UPMASK combining all the configurations, the PM & PHOT clusters, and all the metrics, into a single 'WIN vs LOSS' plots.

  • generate_synth_clust Script to generate synthetic clusters with proper motions, based on the template synth_clust_input.dat synthetic cluster.

  • getMetrics Takes the output files from pyUPMASK/UPMASK (from output/) and generates the metrics files. Files are stored in the metrics/ folder.

  • matrix Matrix plot for PM, PHoT, and combined sets showing the (WIN-LOSS)% delta for each metric and each configuration.

  • metrics_hbars Horizontal bar for the combined PHOT+PM sets for all the metrics for each clustering method in pyUPMASK versus UPMASK.

  • metrics_hbars_split Horizontal bar plots for PHOT, PM, and PHOT+PM, for all the metrics, for each clustering method in pyUPMASK versus UPMASK.

  • met_vs_ci_nstUP ???? TODO

  • MST_vs_RK Compare the results of a pyUPMASK run using Kmeans with the results from UPMASK-MST (Cantat-Gaudin modification). The output data files for the "KMS_clean" run are in the output/KMS_clean/.

  • PPV_TPR PPV vs the TPR (90%) plot for each pyUPMASK configuration, and for UPMASK results.

  • summary_metrics Win vs loss for PM & PHOT, and bar plots for each metric showing how many were won/lost.

  • times Generates the final vertical bar plot showing the time performance for each method in pyUPMASK + UPMASK + MST.

  • UPMASK_code UPMASK code in R and Python function to call it.

  • UP_convergence Analysis of the required number of outer loop runs for UPMASK to converge. Uses the files in the UPMASK_convergence/ folder, which were pre-processed with the XXXX script to obtain their metrics. TODO