ANU Inversion Course Package
Project description
ANU Inversion Course Package
This package contains resources to be used in the inversion course practicals.
Table of contents
Getting started
1. Pre-requisites
Before installing the ANU-inversion-course
package, make sure you have the following ready:
- A computer with a recent OS.
- OS-specific dependencies including a system package manager:
- For Linux users:
- Familiarise yourself with the linux system package manager
apt
/dnf
/pacman
/yast
etc.
- Familiarise yourself with the linux system package manager
- For MacOS users:
- Download and install
Xcode
from "App Store" (you'll need to create an Apple account if not already done) - Install the Xcode command line tools by typing this in "Terminal":
xcode-select --install; sudo xcodebuild -license; sudo softwareinstall -i -a
- Install a recent package manager e.g. one of
Anaconda
(https://www.anaconda.com/),MacPorts
(https://www.macports.org/),HomeBrew
(https://brew.sh/)
- Download and install
- For Windows users:
- Install the
Cygwin
package manager (https://www.cygwin.com/)
- Install the
- For Linux users:
- Install git, gcc, g++, gfortran and python (3.6+) using the package manager. Use the package manager search facility to find options.
- Install any other software development tools you want using the package manager.
- If necessary add your package manager installation directory to the system PATH environment variable so installed programs can/will be found.
These tools can usually be downloaded in source form and compiled however this should only be necessary if you have an unusual setup. Don't be tempted by web sites that claim easy one step package installs, install a package manager. Package managers are far superior in almost every way.
2. Set up a python virtual environment [optional]
It's recommended to use a python virtual environment (e.g. venv
, virtualenv
, mamba
or conda
) so that ANU-Inversion-Course doesn't conflict with your other Python projects.
Open a terminal (or a Cygwin shell for Windows users) and refer to the cheat sheet below for how to create, activate, exit and remove a virtual environment. $
is the system prompt.
venv
Ensure you have and are using python >= 3.6. It may not be called python
but something like python3
, python3.10
etc.
Use the first two lines below to create and activate the new virtual environment. The other lines are for your future reference.
$ python -m venv <path-to-new-env>/inversion_course # to create
$ source <path-to-new-env>/inversion_course/bin/activate # to activate
$ deactivate # to exit
$ rm -rf <path-to-new-env>/inversion_course # to remove
virtualenv
Use the first two lines below to create and activate the new virtual environment. The other lines are for your future reference.
$ virtualenv <path-to-new-env>/inversion_course -p=3.10 # to create
$ source <path-to-new-env>/inversion_course/bin/activate # to activate
$ deactivate # to exit
$ rm -rf <path-to-new-env>/inversion_course # to remove
mamba
Use the first two lines below to create and activate the new virtual environment. The other lines are for your future reference.
$ mamba create -n inversion_course python=3.10 # to create
$ mamba activate inversion_course # to activate
$ mamba deactivate # to exit
$ mamba env remove -n inversion_course # to remove
conda
Use the first two lines below to create and activate the new virtual environment. The other lines are for your future reference.
$ conda create -n inversion_course python=3.10 # to create
$ conda activate inversion_course # to activate
$ conda deactivate # to exit
$ conda env remove -n inversion_course # to remove
3. Installation
Type the following in your terminal (or Cygwin shell for Windows users):
$ pip install jupyterlab matplotlib anu-inversion-course
4. Check
And when you run jupyter-lab
to do the practicals, make sure you are in the same environment as where your anu-inversion-course
was installed. You can try to test this by checking if the following commands give you similar result:
$ which pip
<some-path>/bin/pip
$ which jupyter-lab
<same-path>/bin/jupyter-lab
$ pip list | grep ANU-inversion-course
ANU-inversion-course 0.1.0
Troubleshooting
If you find problems importing anu_inversion_course.rf
, try to search for the error message you get. Here contains a nice explanation for one possible cause. And here is how to locate libgfortran
:
gfortran --print-file-name libgfortran.5.dylib # macOS
Developer Notes
Check out NOTES.md if you'd like to contribute to this package.
Project details
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