If you are running your own EDEX and have a shapefile that you use consistently, instead of having to manually import it in CAVE, we'll show you how to import it into the maps database and then add it to the Maps menu.
AWIPS 20.3.2-0.2 is a beta release of CAVE. Great news, we've added installers for MacOS and Windows as well as made updates to the Linux and virtual machine option.
Today we're going back to CAVE and look at the purpose of different pane displays. The Unidata distribution of CAVE is defaulted to the 1-Pane layout, and the National Weather Service (NWS) version defaults to the 5-pane layout. We will also go over the differences between panes, panels, and editors.
Version 1.4.1 of MetPy, a collection of tools in Python for reading, visualizing, and performing calculations with weather data, has been released. The project aims to mesh well with the rest of the scientific Python ecosystem, including the Numpy, Scipy, and Matplotlib projects, adding functionality specific to meteorology. This is a bug fix release for MetPy v1.4.0.
Today we're going to talk a little bit about python-awips! However, unlike our previous python-awips blogs, where we talk about one of our example notebooks, today we're going to walk you through how to actually open up Jupyter and run those notebooks!
In this blog we are going to show you how to create a new projection and add it to the drop down scales menu in CAVE. For this scenario, we are assuming you have access to both CAVE and EDEX servers (ex. running your own EDEX).
With this edition of AWIPS Tips we're excited to highlight one of our power user Universities. The Unidata AWIPS team has had the pleasure of working with the Texas A&M (TAMU) Atmospheric Sciences department for the last several years.
If you have a lab of students who've made procedures, colormaps, displays, etc. (user configurations) but want to upgrade your EDEX without losing those configurations, it is possible!
Version 1.4.0 of MetPy, a collection of tools in Python for reading, visualizing, and performing calculations with weather data, has been released. The project aims to mesh well with the rest of the scientific Python ecosystem, including the Numpy, Scipy, and Matplotlib projects, adding functionality specific to meteorology. This release includes a variety of new features and enhancements, as well a variety of fixes for issues encountered by users.
