An easy to use interface to gravitational wave surrogate models
Project description
# Welcome to GWSurrogate! #
GWSurrogate is an easy to use interface to gravitational wave surrogate models.
Surrogates provide a fast and accurate evaluation mechanism for gravitational
waveforms which would otherwise be found through solving differential
equations. These equations must be solved in the ``building" phase, which
was performed using other codes. For details see:
[1] Scott Field, Chad Galley, Jan Hesthaven, Jason Kaye, and Manuel Tiglio.
`"Fast prediction and evaluation of gravitational waveforms using surrogate
models". Phys. Rev. X 4, 031006 (2014). arXiv: gr-qc:1308.3565
If you find this package useful in your work, please cite reference [1] and,
if available, the relevant paper describing the specific surrogate used.
gwsurrogate is available at https://pypi-hypernode.com
# Installation #
gwsurrogate is a pure-Python module, thus installation is very easy.
## Dependency ##
gwsurrogate requires gwtools. If you are installing gwsurrogate with pip you
will automatically get gwtools. If you are installing gwsurrogate from
source, please see https://bitbucket.org/chadgalley/gwtools/
## From pip ##
The python package pip supports installing from PyPI (the Python Package
Index). gwsurrogate can be installed to the standard location
(e.g. /usr/local/lib/pythonX.X/dist-packages) with
```
>>> pip install gwsurrogate
```
## From source ##
Download and unpack gwsurrogate-X.X.tar.gz to any folder gws_folder of your
choosing. The gwsurrogate module can be used immediately by adding
```
import sys
sys.path.append('absolute_path_to_gws_folder')
```
at the beginning of any script/notebook which uses gwsurrogate.
Alternatively, if you are a bash or sh user, edit your .profile
(or .bash_profile) file and add the line
```
export PYTHONPATH=~absolute_path_to_gws_folder:$PYTHONPATH
```
For a "proper" installation
```
>>> python setup.py install # option 1
>>> pip install -e gwsurrogate # option 2
```
where the "-e" installs an editable (development) project with pip. This allows
your local code edits to be automatically seen by the system-wide installation.
# Getting Started #
Please read the gwsurrogate docstring found in the __init__.py file
or from ipython with
```
>>> import gwsurrogate as gws
>>> gws?
```
Additional examples can be found in the accompanying Jupyter notebooks
located in the 'tutorial' folder. To open a notebook, for example
basics.ipynb, do
```
>>> jupyter notebook basics.ipynb
```
from the directory 'notebooks'
# Where to find surrogates? #
Surrogates can be downloaded directly from gwsurrogate. For download
instructions, see the basics.ipynb Jupyter notebook.
# Tests #
If you have downloaded the entire project as a tar.gz file, its a good idea
to run some regression tests.
```
>>> py.test # run from the top folder (not the test folder)
```
Note that if you are running the model regression test, regression
data must be generated locally on your machine:
```
>>> cd test
>>> python test_model_regression.py
```
# NSF Support #
This package is based upon work supported by the National Science Foundation
under PHY-1316424 and PHY-1208861.
Any opinions, findings, and conclusions or recommendations expressed in
gwsurrogate are those of the authors and do not necessarily reflect the
views of the National Science Foundation.
GWSurrogate is an easy to use interface to gravitational wave surrogate models.
Surrogates provide a fast and accurate evaluation mechanism for gravitational
waveforms which would otherwise be found through solving differential
equations. These equations must be solved in the ``building" phase, which
was performed using other codes. For details see:
[1] Scott Field, Chad Galley, Jan Hesthaven, Jason Kaye, and Manuel Tiglio.
`"Fast prediction and evaluation of gravitational waveforms using surrogate
models". Phys. Rev. X 4, 031006 (2014). arXiv: gr-qc:1308.3565
If you find this package useful in your work, please cite reference [1] and,
if available, the relevant paper describing the specific surrogate used.
gwsurrogate is available at https://pypi-hypernode.com
# Installation #
gwsurrogate is a pure-Python module, thus installation is very easy.
## Dependency ##
gwsurrogate requires gwtools. If you are installing gwsurrogate with pip you
will automatically get gwtools. If you are installing gwsurrogate from
source, please see https://bitbucket.org/chadgalley/gwtools/
## From pip ##
The python package pip supports installing from PyPI (the Python Package
Index). gwsurrogate can be installed to the standard location
(e.g. /usr/local/lib/pythonX.X/dist-packages) with
```
>>> pip install gwsurrogate
```
## From source ##
Download and unpack gwsurrogate-X.X.tar.gz to any folder gws_folder of your
choosing. The gwsurrogate module can be used immediately by adding
```
import sys
sys.path.append('absolute_path_to_gws_folder')
```
at the beginning of any script/notebook which uses gwsurrogate.
Alternatively, if you are a bash or sh user, edit your .profile
(or .bash_profile) file and add the line
```
export PYTHONPATH=~absolute_path_to_gws_folder:$PYTHONPATH
```
For a "proper" installation
```
>>> python setup.py install # option 1
>>> pip install -e gwsurrogate # option 2
```
where the "-e" installs an editable (development) project with pip. This allows
your local code edits to be automatically seen by the system-wide installation.
# Getting Started #
Please read the gwsurrogate docstring found in the __init__.py file
or from ipython with
```
>>> import gwsurrogate as gws
>>> gws?
```
Additional examples can be found in the accompanying Jupyter notebooks
located in the 'tutorial' folder. To open a notebook, for example
basics.ipynb, do
```
>>> jupyter notebook basics.ipynb
```
from the directory 'notebooks'
# Where to find surrogates? #
Surrogates can be downloaded directly from gwsurrogate. For download
instructions, see the basics.ipynb Jupyter notebook.
# Tests #
If you have downloaded the entire project as a tar.gz file, its a good idea
to run some regression tests.
```
>>> py.test # run from the top folder (not the test folder)
```
Note that if you are running the model regression test, regression
data must be generated locally on your machine:
```
>>> cd test
>>> python test_model_regression.py
```
# NSF Support #
This package is based upon work supported by the National Science Foundation
under PHY-1316424 and PHY-1208861.
Any opinions, findings, and conclusions or recommendations expressed in
gwsurrogate are those of the authors and do not necessarily reflect the
views of the National Science Foundation.
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