ADD: GPM-API Tutorial (#84)

* Add intro tutorial to GPM-API
* Fix precommit issues
* tag docker

---------
Co-authored-by: Kai Mühlbauer <kai.muehlbauer@uni-bonn.de>

.github/workflows/build-book-pullrequest.yaml

@@ -28,7 +28,7 @@ permissions:
   contents: read
 
 env:
-  DOCKER_TAG: pr_83
+  DOCKER_TAG: pr_84
 
 jobs:
   build-book:

.github/workflows/build-book.yaml

@@ -25,7 +25,7 @@ on:
         type: string  # had a lot of trouble with boolean types, see https://github.com/actions/runner/issues/1483
 
 env:
-  DOCKER_TAG: pr_83
+  DOCKER_TAG: pr_84
 
 jobs:
   build-container:

README.md

@@ -1,6 +1,6 @@
 <img src="https://upload.wikimedia.org/wikipedia/commons/thumb/5/52/Norman_Doppler_Radar_-_NOAA.jpg/640px-Norman_Doppler_Radar_-_NOAA.jpg" alt="thumbnail" width="300"/>
 
-# ERAD 2024 Open Radar Science Shortcourse
+# ERAD2024 Open Radar Science Short Courses
 
 [![nightly-build](https://github.com/openradar/erad2024/actions/workflows/publish-book.yaml/badge.svg)](https://github.com/openradar/erad2024/actions/workflows/publish-book.yaml)
 [![Binder](https://binder.projectpythia.org/badge_logo.svg)](https://binder.projectpythia.org/v2/gh/openradar/erad2024/main?labpath=notebooks)
@@ -9,27 +9,39 @@ This tutorial covers how to get started with the Open Radar Science stack!
 
 ## Motivation
 
-The course will take place on 8 September 2024, the day before the [2024 ERAD Radar Conference](https://www.erad2024.it/). The course will discuss the principles of open science and provide an overview of the most mature and exciting software packages available for radar data processing (ex. LROSE, Py-ART, pyrad, BALTRAD, wradlib) and how they connect with the scientific software stack.
+The course will take place on 8 September 2024, the day before the [12th European Conference on RADar in meteorology and hydrology (ERAD2024)](https://www.erad2024.it/).
+The course will discuss the principles of open science and provide an overview of the most mature and exciting software packages available for radar data processing
+(ex.
+[LROSE](https://github.com/NCAR/lrose-core),
+[Py-ART](https://arm-doe.github.io/pyart/),
+[pyrad](https://meteoswiss.github.io/pyrad/),
+[BALTRAD](https://baltrad.github.io/),
+[wradlib](https://docs.wradlib.org/en/latest/)
+) and how they connect with the scientific software stack.
 
 The course will be built with Jupyter Notebooks as hands-on approach for interactive user experience. The main course programming language is Python, but also Command Line Tools are used.
 
-The course will also highlight the “xradar” package, implementing the newly adopted FM301/CfRadial2 WMO standard, as well as the gpm-api software, which facilitates the
-download and analysis of TRMM PR and GPM DPR spaceborne radars data. These two tools will be used to showcase how to harness the power of xarray and dask for efficient, distributed radar data processing.
+The course will also highlight the
+[xradar](https://docs.openradarscience.org/projects/xradar/en/stable/)
+package, implementing the newly adopted FM301/CfRadial2 WMO standard, as well as the
+[gpm-api](https://gpm-api.readthedocs.io/en/latest/) software, which facilitates the
+download and analysis of TRMM PR and GPM DPR spaceborne radars data. These two tools will be used to showcase how to harness the power of
+[xarray](https://docs.xarray.dev/en/stable/) and [dask](https://docs.dask.org/en/stable/array.html)
+for efficient, distributed radar data processing.
 
 The course will cover operational use (e.g. in HPC environments or Cloud Infrastructure) as well as algorithm development, enabling the participants to implement their own algorithms.
 
 The course will also show how to create workflows for different aspects of weather radar
-data processing, using open datasets relevant to the attendees and ERAD 2024.
-
+data processing, using open datasets relevant to the attendees and ERAD2024.
 
 ## List of Instructors
 
 - Alfonso Ladino, University of Illinois at Urbana-Champaign (UIUC)
 - Anna del Moral Méndez, National Center for Atmospheric Research (NCAR)
 - Brenda Javornik, National Center for Atmospheric Research (NCAR)
 - Daniel Michelson, Environment and Climate Change Canada (ECCC)
-- Daniel Wolfensberger, MeteoSwiss
-- Gionata Ghiggi, Ecole polytechnique fédérale de Lausanne (EPFL)
+- Daniel Wolfensberger, MeteoSwiss (MCH)
+- Gionata Ghiggi, Ecole Polytechnique Fédérale de Lausanne (EPFL)
 - Jen DeHart, Colorado State University (CSU)
 - Jordi Figueras i Ventura, independent radar scientist
 - Julian Giles, University of Bonn
@@ -40,7 +52,6 @@ data processing, using open datasets relevant to the attendees and ERAD 2024.
 - Scott Collis, Argonne National Laboratory
 - Ting-Yu Cha, National Center for Atmospheric Research (NCAR)
 
-
 ### Contributors
 
 <a href="https://github.com/openradar/erad2024/graphs/contributors">

binder/Dockerfile

@@ -1 +1 @@
-FROM ghcr.io/openradar/erad2024:pr_83
+FROM ghcr.io/openradar/erad2024:pr_84

binder/environment.yml

@@ -8,7 +8,6 @@ dependencies:
   - sphinx-pythia-theme
   - arm_pyart>=1.18.7
   - cartopy
-  - gpm-api>=0.2.15
   - matplotlib
   - numpy
   - pyrad_arm
@@ -19,6 +18,19 @@ dependencies:
   - xradar>=0.6.3
   - numpy<2.0
   - python<=3.11
+  # this is needed for gpm-api
+  - gpm-api>=0.2.15    # to update to 0.2.16 once released
+  - ximage>=0.0.5
+  - pycolorbar>=0.0.13 # to update to 0.0.14 once released
+  - shapely>=2.0.0
+  - geopandas
+  - xoak
+  - scikit-learn
+  # this is needed for gpm-api interactive 3D viz
+  # - pyvista
+  # - trame
+  # - trame-vuetify
+  # - trame-vtk
   # this is needed for baltrad compilation
   - compilers
   - make

myst.yml

@@ -70,6 +70,9 @@ project:
           children:
             - file: notebooks/xradar-pyart/pyart-basics.ipynb
             - file: notebooks/wradlib/wradlib_clutter_beamblockage.ipynb
+        - title: GPM-API
+          children:
+            - file: notebooks/gpm-api/gpm-api-intro.ipynb
         - title: BALTRAD
           children:
             - pattern: notebooks/baltrad/baltrad_short_course/*.ipynb