TECA
stable

Contents:

  • Installation
  • Command Line Applications
  • Python
  • Development
  • Bibliography
TECA
  • Docs »
  • The TECA User’s Guide
  • Edit on GitHub

_images/tracks_crop_2.gif

Fig. 1 Storm Tracks Generated by TECA¶

The TECA User’s Guide¶

TECA is a framework for parallel data analytics on large scale systems built by the DOE. TECA has algorithms for extreme event detection and post detection analysis. Written in C++, TECA uses MPI + X , where X is one of threads, OpenMP, or GPUs, to deliver state of the art performance and scaling. It’s Python bindings provide an easy way to script analysis suitable to any need and to develop new diagnostics.

Contents:

  • Installation
    • On a Cray Supercomputer
    • On a laptop or desktop
    • Python only
  • Command Line Applications
    • Applying the Command Line Applications at Scale
    • Considerations When Running at NERSC
    • Common Command Line Options
    • teca_metadata_probe
    • teca_bayesian_ar_detect
    • teca_integrated_vapor_transport
    • teca_integrated_water_vapor
    • teca_tc_detect
    • teca_tc_trajectory
    • teca_tc_wind_radii
    • teca_potential_intensity
    • teca_tc_stats
    • teca_tc_trajectory_scalars
    • teca_tc_wind_radii_stats
    • teca_event_filter
    • teca_temporal_reduction
    • teca_deeplab_ar_detect
    • teca_convert_table
    • teca_cf_restripe
    • teca_lapse_rate
  • Python
    • Pipeline Construction, Configuration and Execution
    • Algorithm Development
  • Development
    • Online Source Code Documentation
    • Class Indices
    • Environment Variables
    • Testing
    • Timing and Profiling
    • Creating PyPi Packages
    • Python Coding Standard
    • C++ Coding Standard
  • Bibliography
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© Copyright 2021, Burlen Loring, Travis O'Brien & Abdelrahman Elbashandy Revision 9358a992.

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