Giter Club home page Giter Club logo

ivert's Introduction

IVERT

The ICESat-2 Validation of Elevations Reporting Tool

This code is currently in active development by the CIRES Coastal DEM Team. Primary authors are Mike MacFerrin (developing the IVERT code) and Matthew Love (developing the CUDEM modules underpinning various aspects of IVERT's functionality). Some modules may have broken dependencies or other shortfalls, bugs are being worked out as we migrate to a cloud computing environment. This code is not yet considered stable.

Primary modules for DEM validation are:

  • validate_dem.py -- Code for performing ICESat-2 validations--with masking and vertical datum conversions--on a single DEM.
  • validate_dem_collection.py -- Code for performing ICESat-2 validations on a group or directory of DEMs. A wrapper for looped execution and gathering summary results from looped calls of validate_dem.py

Both the scripts can be run independently as Python scripts with the "-h" or "--help" flags to see a complete list of command-line options.

Code to execute IVERT in a client-server setting in an AWS environment is currently underway. This README will be updated when that is completed.

ivert's People

Contributors

mmacferrin avatar

Watchers

Lucian avatar  avatar Shiva Khanal avatar

Forkers

whigg

ivert's Issues

Convert IVERT client install to setuptools

Currently, the IVERT client is installed on a user's machine with the src/ivert_new_user_setup.py script. There are a few issues with this:

  • The current setup script makes several assumptions about dependencies, etc, that are not checked.
  • It's a multistep process and could be simplified. Users (who may or may-not be familiar with git) have to clone the repository, then run the "src/ivert.py setup" script.
  • After install, it currently requires users to run "src/ivert.py", but it is not in a user's "path" directory.

Python Setuptools can help with that, requiring a user to do just one (maybe two) to install and being using IVERT from anywhere in their environment.

Recommend Projects

  • React photo React

    A declarative, efficient, and flexible JavaScript library for building user interfaces.

  • Vue.js photo Vue.js

    ๐Ÿ–– Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.

  • Typescript photo Typescript

    TypeScript is a superset of JavaScript that compiles to clean JavaScript output.

  • TensorFlow photo TensorFlow

    An Open Source Machine Learning Framework for Everyone

  • Django photo Django

    The Web framework for perfectionists with deadlines.

  • D3 photo D3

    Bring data to life with SVG, Canvas and HTML. ๐Ÿ“Š๐Ÿ“ˆ๐ŸŽ‰

Recommend Topics

  • javascript

    JavaScript (JS) is a lightweight interpreted programming language with first-class functions.

  • web

    Some thing interesting about web. New door for the world.

  • server

    A server is a program made to process requests and deliver data to clients.

  • Machine learning

    Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.

  • Game

    Some thing interesting about game, make everyone happy.

Recommend Org

  • Facebook photo Facebook

    We are working to build community through open source technology. NB: members must have two-factor auth.

  • Microsoft photo Microsoft

    Open source projects and samples from Microsoft.

  • Google photo Google

    Google โค๏ธ Open Source for everyone.

  • D3 photo D3

    Data-Driven Documents codes.