forked from 3rdparty/wrf-python
Kevin Hallock
6 years ago
2 changed files with 413 additions and 0 deletions
@ -0,0 +1,412 @@
@@ -0,0 +1,412 @@
|
||||
WRF Users' Workshop 2019 |
||||
========================= |
||||
|
||||
Welcome WRF-Python Tutorial attendees! |
||||
|
||||
If you wish to actively participate in the tutorial, please bring your own |
||||
laptop. **Due to limited time constraints, the instructions below should be |
||||
completed prior to arriving at the tutorial**. |
||||
|
||||
I will be executing the same cells as the student workbook, so if you prefer |
||||
to sit and watch, that's OK too. Following the tutorial, I will upload |
||||
the instructor slides in to the same GitHub location as the student workbook if |
||||
you want to try it out later. |
||||
|
||||
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*. |
||||
|
||||
Regarding Python, to understand the examples in this tutorial, you |
||||
should have some experience with Python basics. 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. |
||||
|
||||
If you are completely new to Python, that shouldn't be a problem, since |
||||
most of the examples consist of basic container types and function calls. It |
||||
would be helpful to look at some introductory material before arriving at the |
||||
tutorial. If you've programmed before, picking up Python isn't too difficult. |
||||
|
||||
Here are some links: |
||||
|
||||
https://www.learnpython.org/ |
||||
|
||||
https://developers.google.com/edu/python/ |
||||
|
||||
|
||||
Step 1: Open a Command Terminal |
||||
-------------------------------- |
||||
|
||||
To begin, you will first need to know how to open a command line terminal for |
||||
your operating system. |
||||
|
||||
For Windows: |
||||
|
||||
.. code-block:: none |
||||
|
||||
WINDOWS + r |
||||
type cmd in the run window |
||||
|
||||
For Mac: |
||||
|
||||
.. code-block:: none |
||||
|
||||
Finder -> Applications -> Utilities -> Terminal |
||||
|
||||
For Linux: |
||||
|
||||
.. code-block:: none |
||||
|
||||
Try one of the following: |
||||
|
||||
CTRL + ALT + T |
||||
CTRL + ALT + F2 |
||||
|
||||
|
||||
Step 2: Download Miniconda |
||||
---------------------------- |
||||
|
||||
For this tutorial, you will need to download and install Miniconda. We are |
||||
going to use Python 3.7, but it will also work with Python 2.7. |
||||
|
||||
Please use the appropriate link below to download Miniconda for your operating |
||||
system. |
||||
|
||||
.. note:: |
||||
|
||||
64-bit OS recommended |
||||
|
||||
`Win64 <https://repo.continuum.io/miniconda/Miniconda3-latest-Windows-x86_64.exe>`_ |
||||
|
||||
`Mac <https://repo.continuum.io/miniconda/Miniconda3-latest-MacOSX-x86_64.sh>`_ |
||||
|
||||
`Linux <https://repo.continuum.io/miniconda/Miniconda3-latest-Linux-x86_64.sh>`_ |
||||
|
||||
For more information, see: https://conda.io/miniconda.html |
||||
|
||||
.. note:: |
||||
|
||||
**What is Miniconda?** |
||||
|
||||
If you have used the Anaconda distribution for Python before, then you will |
||||
be familiar with Miniconda. The Anaconda Python distribution includes numerous |
||||
scientific packages out of the box, which can be difficult for users to build and |
||||
install. More importantly, Anaconda includes the conda package manager. |
||||
|
||||
The conda package manager is a utility (similar to yum or apt-get) that installs |
||||
packages from a repository of pre-compiled Python packages. These repositories |
||||
are called channels. Conda makes it easy for Python users to install and |
||||
uninstall packages, and also can be used to create isolated Python environments |
||||
(more on that later). |
||||
|
||||
Miniconda is a bare bones implementation of Anaconda and only includes the |
||||
conda package manager. Since we are going to use the conda-forge channel to |
||||
install our scientific packages, Miniconda avoids any complications between |
||||
packages provided by Anaconda and conda-forge. |
||||
|
||||
|
||||
Step 3: Install Miniconda |
||||
---------------------------- |
||||
|
||||
Windows: |
||||
|
||||
1. Browse to the directory where you downloaded Miniconda3-latest-Windows-x86_64.exe. |
||||
|
||||
2. Double click on Miniconda3-latest-Windows-x86_64.exe. |
||||
|
||||
3. Follow the instructions. |
||||
|
||||
4. Restart your command terminal. |
||||
|
||||
Mac and Linux: |
||||
|
||||
For Mac and Linux, the installer is a bash script. |
||||
|
||||
1. Using a terminal, you need to execute the bash shell script that you downloaded by |
||||
doing:: |
||||
|
||||
bash /path/to/Miniconda3-latest-MacOSX-x86_64.sh [Mac] |
||||
|
||||
bash /path/to/Miniconda3-latest-Linux-x86_64.sh [Linux] |
||||
|
||||
2. Follow the instructions. |
||||
|
||||
3. At the end of the installation, it will ask if you want to add the |
||||
miniconda3 path to your bash environment. If you are unsure what to do, |
||||
you should say "yes". If you say "no", we're going to assume you know |
||||
what you are doing. |
||||
|
||||
If you said "yes", then once you restart your shell, the miniconda3 Python |
||||
will be found instead of the system Python when you type the "python" |
||||
command. If you want to undo this later, then you can edit |
||||
either ~/.bash_profile or ~/.bashrc (depending on OS used) and |
||||
comment out the line that looks similar to:: |
||||
|
||||
# added by Miniconda3 x.x.x installer |
||||
export PATH="/path/to/miniconda3/bin:$PATH" |
||||
|
||||
4. Restart your command terminal. |
||||
|
||||
5. [Linux and Mac Users Only] Miniconda only works with bash. If bash is |
||||
not your default shell, then you need to activate the bash shell by typing |
||||
the following in to your command terminal:: |
||||
|
||||
bash |
||||
|
||||
6. Verify that your system is using the correct Python interpreter by typing |
||||
the following in to your command terminal:: |
||||
|
||||
which python |
||||
|
||||
You should see the path to your miniconda installation. If not, see the |
||||
note below. |
||||
|
||||
.. note:: |
||||
|
||||
If you have already installed another Python distribution, like Enthought |
||||
Canopy, you will need to comment out any PATH entries for that distribution |
||||
in your .bashrc or .bash_profile. Otherwise, your shell environment may |
||||
pick the wrong Python installation. |
||||
|
||||
If bash is not your default shell type, and the PATH variable has been |
||||
set in .bash_profile by the miniconda installer, try executing |
||||
"bash -l" instead of the "bash" command in step 5. |
||||
|
||||
|
||||
Step 4: Set Up the Conda Environment |
||||
-------------------------------------- |
||||
|
||||
If you are new to the conda package manager, one of the nice features of conda |
||||
is that you can create isolated Python environments that prevent package |
||||
incompatibilities. This is similar to the *virtualenv* package that some |
||||
Python users may be familiar with. However, conda is not compatible with |
||||
virtualenv, so only use conda environments when working with conda. |
||||
|
||||
The name of our conda environment for this tutorial is: **tutorial_2019**. |
||||
|
||||
Follow the instructions below to create the tutorial_2019 environment. |
||||
|
||||
1. Open a command terminal if you haven't done so. |
||||
|
||||
2. [Linux and Mac Users Only] The conda package manager only works with bash, |
||||
so if bash is not your current shell, type:: |
||||
|
||||
bash |
||||
|
||||
3. Add the conda-forge channel to your conda package manager. |
||||
|
||||
Type or copy the command below in to your command terminal. You should |
||||
run this command even if you have already done it in the past. |
||||
This will ensure that conda-forge is set as the highest priority channel. |
||||
|
||||
:: |
||||
|
||||
conda config --add channels conda-forge |
||||
|
||||
.. note:: |
||||
|
||||
Conda-forge is a community driven collection of packages that are |
||||
continually tested to ensure compatibility. We highly recommend using |
||||
conda-forge when working with conda. See https://conda-forge.github.io/ |
||||
for more details on this excellent project. |
||||
|
||||
4. Create the conda environment for the tutorial. |
||||
|
||||
Type or copy this command in to your command terminal:: |
||||
|
||||
conda create -n tutorial_2019 python=3.7 matplotlib cartopy netcdf4 jupyter git ffmpeg wrf-python |
||||
|
||||
Type "y" when prompted. It will take several minutes to install everything. |
||||
|
||||
This command creates an isolated Python environment named *tutorial_2019*, and installs |
||||
the python interpreter, matplotlib, cartopy, netcdf4, jupyter, git, ffmpeg, and wrf-python |
||||
packages. |
||||
|
||||
.. note:: |
||||
|
||||
When the installation completes, your command terminal might post a message similar to: |
||||
|
||||
.. code-block:: none |
||||
|
||||
If this is your first install of dbus, automatically load on login with: |
||||
|
||||
mkdir -p ~/Library/LaunchAgents |
||||
cp /path/to/miniconda3/envs/tutorial_test/org.freedesktop.dbus-session.plist ~/Library/LaunchAgents/ |
||||
launchctl load -w ~/Library/LaunchAgents/org.freedesktop.dbus-session.plist |
||||
|
||||
This is indicating that the dbus package can be set up to automatically load on login. You |
||||
can either ignore this message or type in the commands as indicated on your command terminal. |
||||
The tutorial should work fine in either case. |
||||
|
||||
5. Activate the conda environment. |
||||
|
||||
To activate the tutorial_2019 Python environment, type the following |
||||
in to the command terminal: |
||||
|
||||
For Linux and Mac (using bash):: |
||||
|
||||
conda activate tutorial_2019 |
||||
|
||||
For Windows:: |
||||
|
||||
activate tutorial_2019 |
||||
|
||||
You should see (tutorial_2019) on your command prompt. |
||||
|
||||
To deactivate your conda environment, type the following in to the |
||||
command terminal: |
||||
|
||||
For Linux and Mac:: |
||||
|
||||
conda deactivate |
||||
|
||||
For Windows:: |
||||
|
||||
deactivate tutorial_2019 |
||||
|
||||
|
||||
Step 5: Download the Student Workbook |
||||
--------------------------------------- |
||||
|
||||
The student workbook for the tutorial is available on GitHub. The tutorial_2019 |
||||
conda environment includes the git application needed to download the repository. |
||||
|
||||
These instructions download the tutorial in to your home directory. If you want |
||||
to place the tutorial in to another directory, we're going to assume you know |
||||
how to do this yourself. |
||||
|
||||
To download the student workbook, follow these instructions: |
||||
|
||||
1. Activate the tutorial_2019 conda environment following the instructions |
||||
in the previous step (*conda activate tutorial_2019* or |
||||
*activate tutorial_2019*). |
||||
|
||||
2. Change your working directory to the home directory by typing the |
||||
following command in to the command terminal: |
||||
|
||||
For Linux and Mac:: |
||||
|
||||
cd ~ |
||||
|
||||
For Windows:: |
||||
|
||||
cd %HOMEPATH% |
||||
|
||||
3. Download the git repository for the tutorial by typing the following |
||||
in to the command terminal:: |
||||
|
||||
git clone --recursive https://github.com/NCAR/wrf_python_tutorial.git |
||||
|
||||
4. There may be additional changes to the tutorial after you have downloaded |
||||
it. To pull down the latest changes, type the following in to the |
||||
command terminal: |
||||
|
||||
For Linux and Mac:: |
||||
|
||||
conda activate tutorial_2019 |
||||
|
||||
cd ~/wrf_python_tutorial/wrf_workshop_2019 |
||||
|
||||
git pull |
||||
|
||||
For Windows:: |
||||
|
||||
activate tutorial_2019 |
||||
|
||||
cd %HOMEPATH%\wrf_python_tutorial\wrf_workshop_2019 |
||||
|
||||
git pull |
||||
|
||||
.. note:: |
||||
|
||||
If you try the "git pull" command and it returns an error indicating |
||||
that you have made changes to the workbook, this is probably because |
||||
you ran the workbook and it contains the cell output. To fix this, |
||||
first do a checkout of the workbook, then do the pull. |
||||
|
||||
.. code-block:: none |
||||
|
||||
git checkout -- . |
||||
git pull |
||||
|
||||
|
||||
Step 6: Verify Your Environment |
||||
---------------------------------- |
||||
|
||||
Verifying that your environment is correct involves importing a few |
||||
packages and checking for errors (you may see some warnings for matplotlib |
||||
or xarray, but you can safely ignore these). |
||||
|
||||
1. Activate the tutorial_2019 conda environment if it isn't already active |
||||
(see instructions above). |
||||
|
||||
2. Open a python terminal by typing the following in to the command |
||||
terminal:: |
||||
|
||||
python |
||||
|
||||
3. Now type the following in to the Python interpreter:: |
||||
|
||||
>>> import netCDF4 |
||||
>>> import matplotlib |
||||
>>> import xarray |
||||
>>> import wrf |
||||
|
||||
4. You can exit the Python interpreter using **CTRL + D** |
||||
|
||||
|
||||
Step 7: Obtain WRF Output Files |
||||
---------------------------------- |
||||
|
||||
A link will be provided in an email prior to the tutorial for the WRF-ARW |
||||
data files used for the examples. If you did not receive this email, the link |
||||
will also be provided at the tutorial itself. |
||||
|
||||
You also have the option of using your own data files for the tutorial by |
||||
modifying the first Jupyter Notebook cell to point to your data set. |
||||
However, there is no guarantee that every cell in your workbook will work |
||||
without some modifications (e.g. cross section lines will be drawn outside of |
||||
your domain). |
||||
|
||||
1. The link in the email should take you to a location on an Amazon cloud |
||||
drive. |
||||
|
||||
2. If you hover your mouse over the wrf_tutorial_data.zip file, you'll see |
||||
an empty check box appear next to the file name. Click this check |
||||
box. |
||||
|
||||
3. At the bottom of the screen, you'll see a Download button next to a |
||||
cloud icon. Click this button to start the download. |
||||
|
||||
4. The download was most likely placed in to your ~/Downloads folder |
||||
[%HOMEPATH%\\Downloads for Windows]. Using your preferred method of choice |
||||
for unzipping files, unzip this file in to your home directory. Your data |
||||
should now be in ~/wrf_tutorial_data |
||||
[%HOMEPATH%\\wrf_tutorial_data for Windows]. |
||||
|
||||
5. Verify that you have three WRF output files in that directory. |
||||
|
||||
|
||||
Getting Help |
||||
---------------- |
||||
|
||||
If you experience problems during this installation, please send a question |
||||
to the :ref:`google-group` support mailing list. |
||||
|
||||
|
||||
We look forward to seeing you at the tutorial! |
||||
Loading…
Reference in new issue