This repository contains a python package hilbert_modgroup
that implements algorithms
for Hilbert modular groups, in particular a reduction algorithm.
The implementation is written in Python using classes and libraries from SageMath.
- SageMath v9.6 - 10.5 (https://www.sagemath.org/)
- passagemath 10.5.22 (https://github.com/passagemath/passagemath)
The package can be installed using pip using the modularized passagemath fork of SageMath (https://github.com/passagemath/passagemath).
The following will install the hilbert-modular-group package together with necessary dependencies from passagemath.
$ python -m venv hilbertmodgroup
$ source hilbertmodgroup/bin/activate
$ pip install hilbert-modular-group
If SageMath is already installed:
$ sage -pip install hilbert-modular-group
You can of course also download and install from source using e.g.:
$ git clone https://github.com/fredstro/hilbertmodgroup.git
$ cd hilbertmodgrup
$ pip install .
If you have docker installed you can use install this package
in a docker container built and executed using e.g. make docker-sage
or make docker-examples
The package can be imported and used as any other package. For example, to find the reduction of the point given by [1+i,1+i] in H^2 with respect to the Hilbert modular group of Q joint by square-root of 5 write:
sage: from hilbert_modgroup.all import *
sage: H1=HilbertModularGroup(5)
sage: P1=HilbertPullback(H1)
sage: z = UpperHalfPlaneProductElement([1+I,1+I])
sage: P1.reduce(z)
[1.00000000000000*I, 1.00000000000000*I]
sage: z = UpperHalfPlaneProductElement([0.25+I/2,1+I])
sage: P1.reduce(z) # abs tol 1e-10
[0.694427190999916 + 0.611145618000168*I, -0.309016994374947 + 1.30901699437495*I]
sage: P1.reduce(z, return_map=True)[1]
[-1/2*a + 1/2 1/2*a + 1/2]
[-1/2*a + 1/2 0]
For more examples see the embedded doctests (search for EXAMPLES
) as well as
the /examples
directory which contains Jupyter notebook with more extensive
examples corresponding to the paper
"Reduction Algorithms for Hilbert Modular Groups" by F. Stromberg. (Reference to appear)
The directory /examples
contains Jupyter notebooks with example code to illustrate the interface and functionality of this package.
You can either open them manually from SageMath or run one of the following commands:
make examples
make docker-examples
which will start up a Jupyter notebook server from sagemath either locally or in a docker container.
- Open an issue on GitHub and create a pull / merge request against the
develop
branch.
- First check if the issue is resolved in the
develop
branch. If not, open an issue on GitHub.
- Contact the maintainer, Fredrik Stromberg, at: [email protected] (alternatively at [email protected])
The make file Makefile
contains a number of useful commands that you can run using
$ make <command>
The following commands are run in your local SageMath environment:
sage-build
-- builds the package, including wheel and source distributionsage-sdist
-- build source distribution onlysage-install
-- build and install the packagetest
-- run sage's doctests (same assage -t src/*
)tox
-- runsage -tox
with all environments:doctest
,coverage
,pycodestyle
,relint
,codespell
( Note: If your local SageMath installation does not contain tox this will runsage -pip install tox
.)sage-examples
-- runsage --notebook=jupyterlab
initialised at the/examples
directory.
The following commands are run in the current virtual environment (an error is raised if you are not in a virtual environment so for global installation please just run python -m build .
etc.)
build
-- builds the package, including wheel and source distributionsdist
-- build source distribution onlyinstall
-- build and install the packageexamples
-- installsjupyterlab
and runsjupyter lab
with the SageMath kernel installed and initialised at the/examples
directory.
The following commands are run in an isolated docker container and requires docker to be installed and running:
docker-build
-- build a docker container with the taghilbertmodgroup-{GIT_BRANCH}
docker-rebuild
-- rebuild the docker container without cachedocker-test
-- run SageMath's doctests in the docker containerdocker-examples
-- run a Jupyter notebook with the SageMath kernel initialised at the/examples
directory and exposing the notebook at http://127.0.0.1:8888. The port used can be modified bydocker-tox
-- run tox with all environments:doctest
,coverage
,pycodestyle
,relint
,codespell
.docker-shell
-- run a shell in a docker containerdocker-sage
-- run a sage interactive shell in a docker container
General commands:
clean
-- remove all build and temporary files
The following command-line parameters are available
NBPORT
-- set the port of the notebook forexamples
anddocker-examples
(default is 8888)TOX_ARGS
-- can be used to select one or more of the tox environments (default is all)REMOTE_SRC
-- set to 0 if you want to use the local source instead of pulling from gitHub (default 1)GIT_BRANCH
-- the branch to pull from gitHub (used if REMOTE_SRC=1)
Run tox coverage on the branch main
from gitHub:
make docker-tox REMOTE_SRC=1 GIT_BRANCH=main TOX_ARGS=coverage
Run doctests on the local source with local version of sage:
make tox TOX_ARGS=doctest
Run relint on the local source with docker version of sage:
make docker-tox REMOTE_SRC=0 TOX_ARGS=relint
- There are two long-lived branches
main
anddevelop
. - The
develop
branch is used for development and can contain new / experimental features. - Pull-requests should be based on
develop
. - Releases should be based on
main
. - The
main
branch should always be as stable and functional as possible. In particular, merges should always happen fromdevelop
intomain
. - Git-Flow is enabled (and encouraged) with feature branches based on
develop
and hotfixes based onmain
.
Each commit is tested and checked using gitHub actions with tox running:
doctest
-- run all doctestscoverage
-- ensure that all functions and classes are documentedpycodestyle-minimal
-- ensure PEP8 style guide is followed (except we allow max line length 99)relint
-- relint against some patterns taken from the SageMath source (config file .relint.yaml)codespell
-- spellchecker
To make sure that your commit passes all tests you should make tox
or make docker-tox REMOTE_SRC=0
on the command line.
Versioning of this project is managed by setuptools_scm.
To bump the version create a git tag x.y.z
and the file
src/hilbert_modgroup/version.py
will then be automatically updated to contain
version = 'x.y.z.???'
version_tuple = (x, y, z, '???')
where ??? depends on the state of the current directory. If you are creating a new version to release the source directory should be clean.
To upload new versions to PyPi:
- Install twine:
pip install twine
make sdist
-- creates a source distributiondist/hilbert_modular_group-x.y.z
twine check dist/hilbert_modular_group-x.y.z
twine upload --repository pypi dist/hilbert_modular_group-z.y.z