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Merge pull request #131 from sunqm/2.6
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Update for 2.6 release
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tberkel authored Jun 18, 2024
2 parents 3a90fcd + 9a18b8b commit 0f1ac8e
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19 changes: 13 additions & 6 deletions source/install.rst
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Expand Up @@ -3,8 +3,8 @@
Install PySCF
*************

1) Install with `pip` (easiest method)
======================================
1) Install with `pip`
=====================
This is the recommended way to install PySCF for non-developers::

$ pip install --prefer-binary pyscf
Expand All @@ -16,8 +16,15 @@ PySCF via pip, you can upgrade it to the new version with::

$ pip install --upgrade pyscf

.. note::
Since PySCF version 2.1, the Linux wheels require manylinux2010 (for x86_64) or manylinux2014 (for aarch64). So the pip version should >= 19.3 for installing on Linux.
Some theoretical models developed in recent years are only available in the
pyscf-forge package. To access these modules, you can install the pyscf-forge package::

$ pip install pyscf-forge

Certain modules are maintained as extensions of PySCF (see also `Install extensions`_).
To install all PySCF functionalities, you can execute the command::

$ pip install pyscf[all]


2) Build from source with `pip`
Expand All @@ -38,7 +45,7 @@ list of prerequisites. If you would like to tune the CMake compilation
parameters, you can set them with the environment variable `CMAKE_CONFIGURE_ARGS`,
for example::

$ export CMAKE_CONFIGURE_ARGS="-DBUILD_MARCH_NATIVE=ON"
$ export CMAKE_CONFIGURE_ARGS="-DBUILD_MARCH_NATIVE=ON -DBLA_VENDOR=Intel10_64lp_seq"

See :ref:`cmake_options` for more details about CMake configuration.

Expand All @@ -56,7 +63,7 @@ Prerequisites for manual install are
* CMake >= 3.10
* Python >= 3.7
* Numpy >= 1.13
* Scipy >= 0.19
* Scipy >= 1.3
* h5py >= 2.7

You can download the latest version of PySCF (or the development
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2 changes: 1 addition & 1 deletion source/interface/geomopt.rst
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Expand Up @@ -17,7 +17,7 @@ The following example shows how to optimize the structure of the N\ :sub:`2`\ m
mol = gto.M(atom='N 0 0 0; N 0 0 1.2', basis='ccpvdz')
mf = scf.RHF(mol)
mol_eq = optimize(mf)
print(mol_eq.atom_coords())
print(mol_eq.tostring())

Examples
========
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8 changes: 4 additions & 4 deletions source/user/geomopt.rst
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Expand Up @@ -26,23 +26,23 @@ and :mod:`pyscf.geomopt.berny_solver`::
# geometric
from pyscf.geomopt.geometric_solver import optimize
mol_eq = optimize(mf, maxsteps=100)
print(mol_eq.atom_coords())
print(mol_eq.tostring())

# pyberny
from pyscf.geomopt.berny_solver import optimize
mol_eq = optimize(mf, maxsteps=100)
print(mol_eq.atom_coords())
print(mol_eq.tostring())


The second way is to create an :func:`optimizer` from the :class:`Gradients` class::

# geometric
mol_eq = mf.Gradients().optimizer(solver='geomeTRIC').kernel()
print(mol_eq.atom_coords())
print(mol_eq.tostring())

# pyberny
mol_eq = mf.Gradients().optimizer(solver='berny').kernel()
print(mol_eq.atom_coords())
print(mol_eq.tostring())

For the ``geomeTRIC`` backend, the convergence criteria are
controlled by the following parameters::
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2 changes: 2 additions & 0 deletions source/user/gto.rst
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Expand Up @@ -166,6 +166,8 @@ This function returns a (N,3) array for the coordinates of each atom::
[0. 1. 0.]
[0. 0. 1.]]

Please note the unit is Bohr by default. You can assign the keyword argument
`unit='Ang'` to change the unit to Angstrom.
Ghost atoms can also be specified when inputting the geometry.
See :source:`examples/gto/03-ghost_atom.py` for examples.

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4 changes: 4 additions & 0 deletions source/version.rst
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Expand Up @@ -7,6 +7,8 @@ Version history
=============== ============
Version Release date
=============== ============
2.6.0_ 2024-06-01
2.5.0_ 2024-02-03
2.4.0_ 2023-10-16
2.3.0_ 2023-07-04
2.2.0_ 2023-03-09
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1.0 alpha 1 2015-04-07
=============== ============

.. _2.6.0: https://github.com/pyscf/pyscf/releases/tag/v2.6.0
.. _2.5.0: https://github.com/pyscf/pyscf/releases/tag/v2.5.0
.. _2.4.0: https://github.com/pyscf/pyscf/releases/tag/v2.4.0
.. _2.3.0: https://github.com/pyscf/pyscf/releases/tag/v2.3.0
.. _2.2.0: https://github.com/pyscf/pyscf/releases/tag/v2.2.0
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