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Instructor: Fernando Paolo (paolofer@jpl.nasa.gov)
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Institution: JPL/Caltech
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## Tutorials:
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Part 1: Introduction to HDF5 data model
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Part 2: Reduction of ICESat-2 data files
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## Goals:
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- Familiarize with HDF5 data model
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- Familiarize with HDF5 basic tools
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- Select IS2 files according region of interest
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- Extract variables of interest and filter in time and space
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- Prepare data for large-scale processing
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- Learn simple/generic data parallelization strategy
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- Inspect data files with plots (Histog, Maps, Time Series)
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## Libraries:
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- h5py (HDF5 handling)
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- numpy (numeric routines)
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- scipy (scientific routines)
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- astropy (extra scientific routines)
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- pyproj (map projection routines)
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- joblib (shared-memory parallelization)
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- matplotlib (visualization routines)
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- glob (pathname pattern expansion)
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- getpass (password management)
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- argparse (arguments parsing)
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## Credits
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*The algorithms used in this tutorial are downscaled versions of a Python altimetry package, currently being devloped at JPL/Caltech. This package provides a range of algorithms for common tasks in altimetry data processing. It will soon become avalibale on GitHub as the `captoolkit` for public usage.*
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