Difference between revisions of "Getting Started with pySPEDAS"
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== pySPEDAS releases == | == pySPEDAS releases == | ||
− | * [https://github.com/spedas/pyspedas | + | * [https://github.com/spedas/pyspedas GitHub] |
* [https://pypi.org/project/pyspedas/ PyPI] | * [https://pypi.org/project/pyspedas/ PyPI] | ||
Revision as of 22:57, 18 May 2021
Contents
Welcome to pySPEDAS
pySPEDAS is an implementation of the SPEDAS framework in Python.
Requirements
- Python 3.7 and later (as of pySPEDAS v1.2)
pySPEDAS releases
Installing Python
We suggest that you install Python using the Anaconda distribution; step-by-step instructions for installing Anaconda can be found at:
- macOS: https://docs.anaconda.com/anaconda/install/mac-os/
- Windows: https://docs.anaconda.com/anaconda/install/windows/
- Linux: https://docs.anaconda.com/anaconda/install/linux/
Once Anaconda is installed, you should be able to open Python in your terminal window by typing "python". Note: your Python version will be the first line displayed; Python 3.7 or later is required.
Creating a virtual environment
To avoid potential dependency issues with other Python packages, it’s best to create a virtual environment in Python
You can create a virtual environment in your terminal with:
python -m venv pyspedas
And enter into that virtual environment by running the 'activate' script with:
macOS and Linux
source environment-name/bin/activate
Windows
.\environment-name\Scripts\activate
Installing pySPEDAS
The first time you enter your virtual environment, you’ll have to install pyspedas; this is as simple as:
pip install pyspedas
This should go out and find all of the required libraries and install them inside the virtual environment.
If you would like to upgrade your copy of the pySPEDAS libraries inside of your virtual environment, use:
pip install pyspedas --upgrade
Setting your local data directory
The recommended way of setting your local data directory is to set the 'SPEDAS_DATA_DIR' environment variable. 'SPEDAS_DATA_DIR' acts as a root data directory for all missions, and will also be used by IDL (if you’re running a recent copy of the bleeding edge).
Mission specific data directories (e.g., 'MMS_DATA_DIR') can also be set, and these will override 'SPEDAS_DATA_DIR'
Checking that everything is working
The quickest way to check if everything is working is to load some data; once you’re inside Python in your virtual environment, try:
import pyspedas
pyspedas.mms.fgm()
This should load some default data (srvy mode, probe 1) for Oct 16, 2015. You can then plot the FGM data with:
from pytplot import tplot
tplot('mms1_fgm_b_gse_srvy_l2')
Using Jupyter notebooks with your virtual environment
To get virtual environments working with Jupyter, there are a few extra steps:
in the virtual environment, type:
pip install ipykernel
python -m ipykernel install --user --name pyspedas --display-name "Python (pySPEDAS)"
(note: "pyspedas" is the name of your virtual environment)
Then once you open the notebook, go to "Kernel" then "Change kernel" and select the one named "Python (pySPEDAS)"
Examples
There are two projects that contain examples of using pyspedas:
MMS Examples
Examples for other missions and general webinars
Comparison of pySPEDAS to SPEDAS
Some examples that demonstrate how to achieve the same results using either IDL SPEDAS or python pySPEDAS.