Collect data from BOUT++ runs in python using xarray
Project description
xBOUT
Documentation: https://xbout.readthedocs.io
Examples: https://github.com/boutproject/xBOUT-examples
xBOUT provides an interface for collecting the output data from a BOUT++ simulation into an xarray dataset in an efficient and scalable way, as well as accessor methods for common BOUT++ analysis and plotting tasks.
Currently only in alpha (until 1.0 released) so please report any bugs, and feel free to raise issues asking questions or making suggestions.
Installation
With pip:
pip install --user xbout
With conda:
conda install -c conda-forge xbout
You can test your installation of xBOUT
by running pytest --pyargs xbout
.
xBOUT requires other python packages, which will be installed when you run one of the above install commands if they are not already installed on your system.
Loading your data
The function open_boutdataset()
uses xarray & dask to collect BOUT++
data spread across multiple NetCDF files into one contiguous xarray
dataset.
The data from a BOUT++ run can be loaded with just
bd = open_boutdataset('./run_dir*/BOUT.dmp.*.nc', inputfilepath='./BOUT.inp')
open_boutdataset()
returns an instance of an xarray.Dataset
which
contains BOUT-specific information in the attrs
, so represents a
general structure for storing all of the output of a simulation,
including data, input options and (soon) grid data.
BoutDataset Accessor Methods
xBOUT defines a set of
accessor
methods on the loaded Datasets and DataArrays, which are called by
ds.bout.method()
.
This is where BOUT-specific data manipulation, analysis and plotting functionality is stored, for example
ds['n'].bout.animate2D(animate_over='t', x='x', y='z')
or
ds.bout.create_restarts(savepath='.', nxpe=4, nype=4)
Extending xBOUT for your BOUT module
The accessor classes BoutDatasetAccessor
and BoutDataArrayAccessor
are intended to be subclassed for specific BOUT++ modules. The subclass
accessor will then inherit all the .bout
accessor methods, but you
will also be able to override these and define your own methods within
your new accessor.
For example to add an extra method specific to the STORM
BOUT++
module:
from xarray import register_dataset_accessor
from xbout.boutdataset import BoutDatasetAccessor
@register_dataset_accessor('storm')
class StormAccessor(BoutAccessor):
def __init__(self, ds_object):
super().__init__(ds_object)
def special_method(self):
print("Do something only STORM users would want to do")
ds.storm.special_method()
Out [1]: Do something only STORM users would want to do
There is included an example of a
StormDataset
which contains all the data from a
STORM simulation, as well as
extra calculated quantities which are specific to the STORM module.
Contributing
Feel free to raise issues about anything, or submit pull requests, though I would encourage you to submit an issue before writing a pull request. For a general guide on how to contribute to an open-source python project see xarray's guide for contributors.
The existing code was written using Test-Driven Development, and I would
like to continue this, so please include pytest
tests with any pull
requests.
If you write a new accessor, then this should really live with the code for your BOUT module, but it could potentially be added as an example to this repository too.
Developers
Clone the repository with:
git clone git@github.com:boutproject/xBOUT.git
The recommended way to work with xBOUT
from the git repo is to do an editable
install with pip. Run this command from the xBOUT/
directory:
pip install --user -e .
which will also install all the required dependencies. Dependencies can also be installed using pip
pip install --user -r requirements.txt
or conda
conda install --file requirements.txt
It is possible to use xBOUT
by adding the xBOUT/
directory to your
$PYTHONPATH
.
Test by running pytest
in the xBOUT/
directory.
Development plan
Things which definitely need to be included (see the 1.0 milestone):
- More tests, both with
and against the original
boutdata.collect()
- Speed test against old collect
Things which would be nice and I plan to do:
- Infer concatenation order from global indexes (see issue)
- Real-space coordinates
- Variable names and units (following CF conventions)
- Unit-aware arrays
- Variable normalisations
Things which might require a fair amount of effort by another developer but could be very powerful:
- Using real-space coordinates to create tokamak-shaped plots
- Support for staggered grids using xgcm
- Support for encoding topology using xgcm
- API for applying BoutCore operations (hopefully using
xr.apply_ufunc
)
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