Code examples for Nonlinear Algebra in Macaulay2.
To view the code and the LaTeX in the notebooks properly rendered, go to the following links:
We will be using the Macaulay2 Jupyter Kernel from here: https://github.com/radoslavraynov/Macaulay2-Jupyter-Kernel
You need a recent version of Python and pip. Python 3 is recommended for build installs and necessary for source installs. You can first install Python and pip through the miniconda package manager. First, to download miniconda, go to the installation site and download the installation corresponding to your machine. Then do
conda install python jupyter pipYou will also need an installation of Macaulay2, which can be found here.
Make sure that both M2 and M2-binary are in $PATH. Check by running
$ which M2
/Users/maximsmol/bin/M2
$ which M2-binary
/Users/maximsmol/bin/M2-binary
$ echo $PATH
/Users/maximsmol/M2:/Users/maximsmol/bin/M2-binary:...
See this answer if you need to add the binaries to your $PATH.
Finally, to finish the setup, run
$ pip install macaulay2-jupyter-kernel
$ python3 -m m2_kernel.install --sys-prefix
First clone the github repository.
$ git clone https://github.com/tyleryzhu/nonlinear-algebra-code.git
$ cd nonlinear-algebra-code
To start up a jupyter instance inside this directory, run
$ jupyter notebook
If you get an error with "Not a directory: 'xdg-settings'", you may need to pass the --no-browser flag (this is a current bug in Jupyter with Python3.7).
To present a notebook as a presentation, go to View > Cell Toolbar > Slideshow and identify each slide. Then run
jupyter nbconvert Chapter\ 1\,\ Polynomial\ Rings.ipynb --to slides --post serve
There are also pdfs for your viewing, but those are buggy right now and need to be worked out.
If you have any questions, feel free to open an issue/pull request or email any of the contributors.