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. Set up virtual environment
(optional) It's recommended to use a virtual environment (using conda
or venv
, etc.) so that it doesn't conflict with your other Python projects. Create a new environment with
conda create -n inversion_course python=3.10 scipy
and enter that environment with
conda activate inversion_course
and if you are on MacOS M1 chip:
conda install -c conda-forge gfortran
2. Dependency
If you are on Linux/Windows and have followed above step to install
scipy
usingconda
, then feel free to skip this step.
This package requires you to have gfortran
(or at least libgfortran
on Linux/Windows) installed. Check this page (and notes below for MacOS) for instructions on how to install gfortran
.
Notes for installing gfortran
on MacOS
- Install
XCode
(from App Store) - Install command line tools
xcode-select --install
- For M1 chip: if you've set up a conda environment, then
conda install -c conda-forge gfortran
will work - If step 3 doesn't suit you: follow the instructions in this page about how to install
gfortran
Reasons for why we need `gfortran` (only) on MacOS
- A Fortran compiler is needed for MacOS to build C/Fortran libraries from source, as wheels are not provided for MacOS due to a problem described here.
- Fortran libraries (
libgfortran.5.dylib
) is also needed for other operating systems. Otherwiseanu_inversion_course.rf
will fail to import. If you've followed step one above to installscipy
viaconda
, thenlibgfortran5
is downloaded so no further action is needed. - The issue on MacOS is possible to fix, but with some effort of uploading the package to
conda
, so this will be in future work
3. Installation
Type the following in your terminal:
pip install 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 the error message you get. Here contains a nice explanation for the possible cause. And here is how to locate libgfortran
:
gfortran --print-file-name libgfortran.5.dylib
Developer Notes
Check out NOTES.md if you'd like to contribute to this package.
Project details
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