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%global _empty_manifest_terminate_build 0
Name: python-pyberny
Version: 0.6.3
Release: 1
Summary: Molecular/crystal structure optimizer
License: MPL-2.0
URL: https://github.com/jhrmnn/pyberny
Source0: https://mirrors.aliyun.com/pypi/web/packages/48/22/fa2aa59c294449f13cbbbdc62c6e926bbd0379c6cf1a3d16e51e383f4316/pyberny-0.6.3.tar.gz
BuildArch: noarch
Requires: python3-numpy
Requires: python3-pytest
Requires: python3-coverage
Requires: python3-sphinx
Requires: python3-sphinxcontrib-katex
Requires: python3-toml
%description
# PyBerny
[](https://travis-ci.com/jhrmnn/pyberny)
[](https://codecov.io/gh/jhrmnn/pyberny)
[](https://pypi.org/project/pyberny/)
[](https://github.com/jhrmnn/pyberny/releases)
[](https://github.com/jhrmnn/pyberny/commits/master)
[](https://github.com/jhrmnn/pyberny/blob/master/LICENSE)
[](https://github.com/ambv/black)
[](http://doi.org/10.5281/zenodo.3695037)
PyBerny is an optimizer of molecular geometries with respect to the total energy, using nuclear gradient information.
In each step, it takes energy and Cartesian gradients as an input, and returns a new equilibrium structure estimate.
The package implements a single optimization algorithm, which is an amalgam of several techniques, comprising the quasi-Newton method, redundant internal coordinates, an iterative Hessian approximation, a trust region scheme, and linear search. The algorithm is described in more detailed in the [documentation](https://jhrmnn.github.io/pyberny/algorithm.html).
Several desirable features are missing at the moment but planned, some of them being actively worked on (help is always welcome): [crystal geometries](https://github.com/jhrmnn/pyberny/issues/5), [coordinate constraints](https://github.com/jhrmnn/pyberny/issues/14), [coordinate weighting](https://github.com/jhrmnn/pyberny/issues/32), [transition state search](https://github.com/jhrmnn/pyberny/issues/4).
PyBerny is available in [PySCF](https://sunqm.github.io/pyscf/geomopt.html#pyberny), [ASE](https://wiki.fysik.dtu.dk/ase/dev/ase/optimize.html?highlight=berny#pyberny), and [QCEngine](http://docs.qcarchive.molssi.org/projects/QCEngine/en/latest/index.html?highlight=pyberny#backends).
## Installing
Install and update using [Pip](https://pip.pypa.io/en/stable/quickstart/):
```
pip install -U pyberny
```
## Example
```python
from berny import Berny, geomlib
optimizer = Berny(geomlib.readfile('geom.xyz'))
for geom in optimizer:
# get energy and gradients for geom
optimizer.send((energy, gradients))
```
## Links
- Documentation: https://jhrmnn.github.io/pyberny
%package -n python3-pyberny
Summary: Molecular/crystal structure optimizer
Provides: python-pyberny
BuildRequires: python3-devel
BuildRequires: python3-setuptools
BuildRequires: python3-pip
%description -n python3-pyberny
# PyBerny
[](https://travis-ci.com/jhrmnn/pyberny)
[](https://codecov.io/gh/jhrmnn/pyberny)
[](https://pypi.org/project/pyberny/)
[](https://github.com/jhrmnn/pyberny/releases)
[](https://github.com/jhrmnn/pyberny/commits/master)
[](https://github.com/jhrmnn/pyberny/blob/master/LICENSE)
[](https://github.com/ambv/black)
[](http://doi.org/10.5281/zenodo.3695037)
PyBerny is an optimizer of molecular geometries with respect to the total energy, using nuclear gradient information.
In each step, it takes energy and Cartesian gradients as an input, and returns a new equilibrium structure estimate.
The package implements a single optimization algorithm, which is an amalgam of several techniques, comprising the quasi-Newton method, redundant internal coordinates, an iterative Hessian approximation, a trust region scheme, and linear search. The algorithm is described in more detailed in the [documentation](https://jhrmnn.github.io/pyberny/algorithm.html).
Several desirable features are missing at the moment but planned, some of them being actively worked on (help is always welcome): [crystal geometries](https://github.com/jhrmnn/pyberny/issues/5), [coordinate constraints](https://github.com/jhrmnn/pyberny/issues/14), [coordinate weighting](https://github.com/jhrmnn/pyberny/issues/32), [transition state search](https://github.com/jhrmnn/pyberny/issues/4).
PyBerny is available in [PySCF](https://sunqm.github.io/pyscf/geomopt.html#pyberny), [ASE](https://wiki.fysik.dtu.dk/ase/dev/ase/optimize.html?highlight=berny#pyberny), and [QCEngine](http://docs.qcarchive.molssi.org/projects/QCEngine/en/latest/index.html?highlight=pyberny#backends).
## Installing
Install and update using [Pip](https://pip.pypa.io/en/stable/quickstart/):
```
pip install -U pyberny
```
## Example
```python
from berny import Berny, geomlib
optimizer = Berny(geomlib.readfile('geom.xyz'))
for geom in optimizer:
# get energy and gradients for geom
optimizer.send((energy, gradients))
```
## Links
- Documentation: https://jhrmnn.github.io/pyberny
%package help
Summary: Development documents and examples for pyberny
Provides: python3-pyberny-doc
%description help
# PyBerny
[](https://travis-ci.com/jhrmnn/pyberny)
[](https://codecov.io/gh/jhrmnn/pyberny)
[](https://pypi.org/project/pyberny/)
[](https://github.com/jhrmnn/pyberny/releases)
[](https://github.com/jhrmnn/pyberny/commits/master)
[](https://github.com/jhrmnn/pyberny/blob/master/LICENSE)
[](https://github.com/ambv/black)
[](http://doi.org/10.5281/zenodo.3695037)
PyBerny is an optimizer of molecular geometries with respect to the total energy, using nuclear gradient information.
In each step, it takes energy and Cartesian gradients as an input, and returns a new equilibrium structure estimate.
The package implements a single optimization algorithm, which is an amalgam of several techniques, comprising the quasi-Newton method, redundant internal coordinates, an iterative Hessian approximation, a trust region scheme, and linear search. The algorithm is described in more detailed in the [documentation](https://jhrmnn.github.io/pyberny/algorithm.html).
Several desirable features are missing at the moment but planned, some of them being actively worked on (help is always welcome): [crystal geometries](https://github.com/jhrmnn/pyberny/issues/5), [coordinate constraints](https://github.com/jhrmnn/pyberny/issues/14), [coordinate weighting](https://github.com/jhrmnn/pyberny/issues/32), [transition state search](https://github.com/jhrmnn/pyberny/issues/4).
PyBerny is available in [PySCF](https://sunqm.github.io/pyscf/geomopt.html#pyberny), [ASE](https://wiki.fysik.dtu.dk/ase/dev/ase/optimize.html?highlight=berny#pyberny), and [QCEngine](http://docs.qcarchive.molssi.org/projects/QCEngine/en/latest/index.html?highlight=pyberny#backends).
## Installing
Install and update using [Pip](https://pip.pypa.io/en/stable/quickstart/):
```
pip install -U pyberny
```
## Example
```python
from berny import Berny, geomlib
optimizer = Berny(geomlib.readfile('geom.xyz'))
for geom in optimizer:
# get energy and gradients for geom
optimizer.send((energy, gradients))
```
## Links
- Documentation: https://jhrmnn.github.io/pyberny
%prep
%autosetup -n pyberny-0.6.3
%build
%py3_build
%install
%py3_install
install -d -m755 %{buildroot}/%{_pkgdocdir}
if [ -d doc ]; then cp -arf doc %{buildroot}/%{_pkgdocdir}; fi
if [ -d docs ]; then cp -arf docs %{buildroot}/%{_pkgdocdir}; fi
if [ -d example ]; then cp -arf example %{buildroot}/%{_pkgdocdir}; fi
if [ -d examples ]; then cp -arf examples %{buildroot}/%{_pkgdocdir}; fi
pushd %{buildroot}
if [ -d usr/lib ]; then
find usr/lib -type f -printf "\"/%h/%f\"\n" >> filelist.lst
fi
if [ -d usr/lib64 ]; then
find usr/lib64 -type f -printf "\"/%h/%f\"\n" >> filelist.lst
fi
if [ -d usr/bin ]; then
find usr/bin -type f -printf "\"/%h/%f\"\n" >> filelist.lst
fi
if [ -d usr/sbin ]; then
find usr/sbin -type f -printf "\"/%h/%f\"\n" >> filelist.lst
fi
touch doclist.lst
if [ -d usr/share/man ]; then
find usr/share/man -type f -printf "\"/%h/%f.gz\"\n" >> doclist.lst
fi
popd
mv %{buildroot}/filelist.lst .
mv %{buildroot}/doclist.lst .
%files -n python3-pyberny -f filelist.lst
%dir %{python3_sitelib}/*
%files help -f doclist.lst
%{_docdir}/*
%changelog
* Fri Jun 09 2023 Python_Bot <Python_Bot@openeuler.org> - 0.6.3-1
- Package Spec generated
|
