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nirvana-psp

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    Simon Schleich authored and GitHub committed
    00b955b0
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    Name Last commit Last update
    MODULES
    TESTING
    README.md
    binned_stats.py
    main.py

    PSP SWEAP (and FIELDS?) data analysis

    PSEUDOCODE

    BACKGROUND

    • Collect data for one Encounter in folder

      • Variable name of folder to handle different encounters In total, evaluate the last few encounters
      • Perihelia of ~0.064 au (ENCOUNTER 10)
      • Perihelia of ~0.074 au (ENCOUNTER 8 and 9)
      • Perihelia of ~0.090 au (ENCOUNTER 6 and 7)
    • SWEAP provides (all with uncertainties)

      • Date and time of observation
      • Cartesian position (x, y, z)
      • RTN frame velocity
      • Thermal velocity w
      • Density of protons (majority of wind)
    • Collect all measurements (after reduction) into singular arrays?

      • Could then be split by minimum distance for perihelion

    OPERATIONS

    • Sort through "general flag" (only use where set to 0)
      • Also sort through each array to find entries with -1e30, which marks failed measurements
    • Calculate spherical heliocentric coordinates (HIC)
    • Transform to usable data parameters (vr, log_T, log_rho)
    • Generate log-file with important information
      • Total number of data points
      • Reduced number of data points
      • Epoch from start to finish
    • If mean/median + std is desired, I need to bin the data appropriately
      • Loop over multiple files, collect data in bins, do evaluation at end.
      • Generate a plot (Bar Chart) displaying each bin at the end, to have quick reference.
    • Radial data binning: Find appropriate bin size (maybe 0.5 R_sol)
    • After radial sorting is done:
      • Take all indices for each bin and treat the data bin by bin

    SINGLE ENCOUNTER SEQUENCE -For File in encounter - Fill encounter dictionary with reduced values

    • Find index of minimum distance-value
      • Split total data into approach and recession

    Files

    • test.py: Testing data operations on data files.

    NIROperations

    Python modules necessary in the processing of measurement data.