WRF-Python Tutorial 2018 ========================= NCAR will be providing a four hour tutorial for wrf-python on Wednesday, March 7, 2018. The tutorial is free, but seating is limited to only 16 students, so registration is required. The tutorial will take place at NCAR's corporate training center in Boulder, Colorado. `Corporate Technical Training Center `_ 3085 Center Green Drive, Building CG-2, Room #3024 Boulder, Colorado Overview -------------- This tutorial provides an introduction to wrf-python. The tutorial is beginner friendly for new users of wrf-python, but this is not an introduction to the Python programming language (see :ref:`prereq`). Due to limited seating, if you do not have any previous experience with Python, please do not register for this tutorial. Students are encouraged to bring their own data sets, but data will be provided if this is not an option. Students will be provided a jupyter notebook workbook which can be modified to accommodate their data. Topics include: - How to install wrf-python via conda - A brief introduction to jupyter notebook - Overview of WRF data files - WRF-Python basics - Plotting with cartopy - Overview of OpenMP features and other performance tips - Open lab for students Registration --------------- The registration form is here: `Registration Form `_ Registration consists of a brief survey, which will help give the instructors a brief overview of your background and will help tailor the tutorial to your expectations. .. _prereq: Prerequisites --------------- This tutorial assumes that you have basic knowledge of how to type commands in to a command terminal using your preferred operating system. You should know some basic directory commands like *cd*, *mkdir*, *cp*, *mv*. This tutorial assumes that you have prior experience programming in Python. Below is a list of some Python concepts that you will see in the examples, but don't worry if you aren't familiar with everything. - Opening a Python interpreter and entering commands. - Importing packages via the import statement. - Familiarity with some of the basic Python types: str, list, tuple, dict, bool, float, int, None. - Creating a list, tuple, or dict with "[ ]", "( )", "{ }" syntax (e.g. my_list = [1,2,3,4,5]). - Accessing dict/list/tuple items with the "x[ ]" syntax (e.g. my_list_item = my_list[0]). - Slicing str/list/tuple with the ":" syntax (e.g. my_slice = my_list[1:3]). - Using object methods and attributes with the "x.y" syntax (e.g. my_list.append(6)). - Calling functions (e.g. result = some_function(x, y)) - Familiarity with numpy would be helpful, as only a very brief introduction is provided. - Familiarity with matplotlib would be helpful, as only a very brief introduction is provided.