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Patch v1.2.0 (#62)
* Explicitly copying positions when building Cython CGF objects from Python variant * Adding example for symmetry adapted bases * Implementing MOPA and fixing Blender implementation for latest LTS version * Small tweaks * Adding nuclei to FB dic * Adding meson * Updating meson * Updating meson.build * Updating meson.build * Updating meson.build * Fixing source files * Fixing source files * Fixing meson.build * Changing build procedure * Removing manifest * Adding M_PI * Another try for M_PI support * Adding settings for Windows compilation * Adding M_PI * Changing extension name * Changing extension name * Another attempt * Renaming once more * Changing init procedure * Changing Windows compiler * Changing instructions * Changing instructions * Changing instructions * Updating version * Changing instructions * Changing instructions * Changing instructions * Changing instructions * Changing instructions * Changing instructions * Changing instructions * Another attempt * Another attempt * Another attempt * Another attempt * Another attempt * Another attempt * Another attempt * Another attempt * Another attempt * Another attempt * Another attempt * Another attempt * Another attempt * Another attempt * Adding comments * Removing universal2 * Adding contour plotter * Improving Geometry Optimization class and adding molecules * Fix version retrieval for pyqint package * Remove Windows compiler from build workflow Remove CIBW_WINDOWS_COMPILER environment variable. * Adding more molecules and propagating camera scale * Adding camera features for BlenderRender * Adding default camera position and improving TEI evaluation * Tuning settings * Migrating sources * Fixing build system * Changing function name * Adding molecules * Refactoring API to make input more consistent * Population analysis (#61) * Add Mulliken and Löwdin population analysis * remove debug print * Adding unit tests and integrating all population analysis techniques into one class * Updating manual * Fixing unit test --------- Co-authored-by: ifilot <ivo@ivofilot.nl> * Adding contour plot visualization to manuaL * Adding PyMoDia to manual * Adding matrix visualization class * Adding symmetry adaptation to the manual --------- Co-authored-by: Joeri van Limpt <114054404+joerivan@users.noreply.github.com>
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‎.github/workflows/build_wheels.yml‎

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types: [published]
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env:
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# macOS universal and arm64 wheels build on Intel
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CIBW_ARCHS_MACOS: "x86_64 universal2 arm64"
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CIBW_ARCHS_MACOS: "x86_64 arm64"
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CIBW_ARCHS_WINDOWS: "AMD64"
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CIBW_SKIP: "cp36-* cp37-* cp38-*"
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CIBW_SKIP: "cp38-*"
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CIBW_BUILD_VERBOSITY: 1
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jobs:
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- uses: actions/checkout@v4
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- name: Build wheels
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uses: pypa/cibuildwheel@v3.2.1
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uses: pypa/cibuildwheel@v3.3.0
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- uses: actions/upload-artifact@v4
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with:

‎.github/workflows/paper.yml‎

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name: paper
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on: [push]
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on:
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push:
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branches:
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- master
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- paper
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jobs:
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paper:

‎.gitignore‎

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# Cython debug symbols
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cython_debug/
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*.xyz
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!src/pyqint/molecules/*.xyz
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# Spynx documentation
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docs/build/*
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# managlyph .abo files
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*.abo
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.vscode
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.vscode
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*.jpg
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*.png

‎COMPILATION.md‎

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```bash
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python -m twine upload wheelhouse/*
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```
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## Editable install
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Make sure `methon-python` is installed:
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```
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pip install meson-python
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```
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```bash
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pip install -e .
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```

‎MANIFEST.in‎

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‎docs/_static/img/mo_co_canonical.svg‎

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‎docs/_static/img/mo_co_localized.svg‎

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‎docs/basis_functions.rst‎

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.. index:: basis-functions
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Basis functions
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###############
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.. contents:: Table of Contents
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:depth: 3
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Gaussian type orbitals (GTO)
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============================
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:program:`PyQInt` uses cartesian Gaussian type orbitals as given by
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.. math::
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\Phi(\alpha,l,m,n,\vec{R}) = N (x - X)^{l} (y - Y)^{m} (z - Z)^{n} \exp \left(- \alpha |\vec{r} - \vec{R}|^{2} \right)
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wherein :math:`\alpha` is the exponent, :math:`\vec{R} = \left(X,Y,Z\right)` the
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position of the orbital, :math:`(l,m,n)` the orders of the pre-exponential
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polynomial, and :math:`N` a normalization constant such that
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.. math::
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\left< \Phi | \Phi \right> = 1
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GTOs are a fundamental building block of CGF (see below) and typically a user
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would not directly work with them (a notable exception is provided below).
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Nevertheless, GTO objects can be constructed as follows::
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from pyqint import PyQInt, CGF, GTO
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coeff = 1.0 # coefficients only have meaning for GTOs within a CGF
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alpha = 0.5
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l,m,n = 0,0,0
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p = (0,0,0)
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G = GTO(coeff, p, alpha, l, m, n)
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.. note::
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* The normalization constant is automatically calculated by `PyQInt` based
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on the value of :math:`\alpha` and :math:`(l,m,n)` and does not have
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to be supplied by the user.
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* If you work with individual GTOs, the first parameter to construct the GTO
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should have a value of 1.0. This first parameter corresponds to the linear
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expansion coefficient used in the formulation of Contracted Gaussian Functions
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(see below).
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Contracted Gaussian Functions (CGF)
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===================================
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Several GTOs can be combined to produce a so-called Contracted Gaussian Functional which
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is esentially a linear combination of GTOs as given by
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.. math::
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\phi = \sum_{i} c_{i} \Phi_{i}(\alpha,l,m,n,\vec{R})
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To build a CGF, we first have to produce the CGF object and then
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add GTOs to it::
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from pyqint import PyQInt, CGF
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cgf = CGF([0.0, 0.0, 0.0])
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cgf.add_gto(0.154329, 3.425251, 0, 0, 0)
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cgf.add_gto(0.535328, 0.623914, 0, 0, 0)
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cgf.add_gto(0.444635, 0.168855, 0, 0, 0)
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.. note::
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The first argument of the :code:`add_gto` function is the linear expansion coefficient
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:math:`c_{i}` and the second argument is :math:`\alpha`.
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Position Handling and Advanced Usage
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************************************
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A :code:`CGF` object carries an explicit spatial position :math:`\vec{R}`,
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which is specified when the object is constructed. This position is used as
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the *default center* for all Gaussian Type Orbitals (GTOs) added to the CGF via
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the standard :code:`add_gto` method.
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When using
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.. code-block:: python
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cgf.add_gto(c, alpha, l, m, n)
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the position of the CGF itself is implicitly copied to the newly created GTO.
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This is the typical and intended usage pattern for atom-centered basis sets,
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where all primitive Gaussians contributing to a contracted function are located
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on the same atomic center. Under this assumption, the CGF represents a single
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atomic basis function composed of multiple primitives sharing a common center.
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Non-Atom-Centered GTOs and Mixed-Center CGFs
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********************************************
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In more advanced scenarios, it may be desirable to construct contracted
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functions composed of GTOs located at *different spatial positions*. This can
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arise, for example, when building symmetry-adapted basis functions or other
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non-standard orbital constructions.
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For such cases, the :code:`CGF` class provides the method
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:code:`add_gto_with_position`, which allows explicit specification of the GTO
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center:
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.. code-block:: python
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cgf.add_gto_with_position(c, p, alpha, l, m, n)
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where :code:`p` is a three-component array specifying the Cartesian coordinates
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of the GTO center.
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When this method is used, the position stored in the CGF object itself is
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*ignored* for that particular GTO, and the explicitly provided position is
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stored with the primitive instead.
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Integral Evaluation and Position Resolution
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*******************************************
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It is important to emphasize that **all integral evaluations are performed using
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the positions of the individual GTOs**, not the position stored in the CGF
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object. The CGF position serves only as a convenient default when adding
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atom-centered primitives via :code:`add_gto`. Consequently, CGFs containing GTOs
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at mixed centers are handled correctly by the integral engine, provided that
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:code:`add_gto_with_position` is used where appropriate.
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Users are therefore encouraged to:
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- Use :code:`add_gto` for standard atom-centered basis functions
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- Use :code:`add_gto_with_position` when constructing non-standard or
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symmetry-adapted contracted functions
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- Rely on GTO positions - **not CGF positions** — when reasoning about integral
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evaluation

‎docs/basis_sets_and_molecules.rst‎

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.. index:: basis-sets-and-molecules
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Basis sets and molecules
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========================
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.. contents:: Table of Contents
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:depth: 3
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Building molecules
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------------------
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Molecules can be efficiently built from the :code:`Molecule` class. For example,
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to build the H\ :sub:`2` molecule, one can run the script below.
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.. code-block:: python
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from pyqint import PyQInt, Molecule
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import numpy as np
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# construct integrator object
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integrator = PyQInt()
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# build hydrogen molecule
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mol = Molecule('H2')
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mol.add_atom('H', 0.0, 0.0, 0.0)
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mol.add_atom('H', 0.0, 0.0, 1.4)
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print(mol)
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The output of the above script is::
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Molecule: H2
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H (0.000000,0.000000,0.000000)
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H (0.000000,0.000000,1.400000)
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Using the MoleculeBuilder class
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-------------------------------
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Next to constructing molecules from scratch, one can also use the
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:code:`MoleculeBuilder` class which contains a number of pre-generated molecules.
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To see which molecules are available in the MoleculeBuilder class, run
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.. code-block:: python
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from pyqint import MoleculeBuilder
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mol = MoleculeBuilder.print_list_molecules()
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To load any of these molecules, one uses the :code:`from_name` function
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as shown in the script below
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.. code-block:: python
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from pyqint import MoleculeBuilder
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mol = MoleculeBuilder.from_name('ch4')
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print(mol)
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The output of the above script shows the elements and the atom positions::
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Molecule: methane
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C 0.000000 0.000000 0.000000
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H 1.195756 1.195756 1.195756
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H -1.195756 -1.195756 1.195756
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H -1.195756 1.195756 -1.195756
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H 1.195756 -1.195756 -1.195756
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.. note::
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Naming a molecule is completely optional and has no further implications
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on any of the calculations. To name a molecule, populate the :code:`name`
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member of the :code:`Molecule` class.
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Alternatively, one can load molecules from a :code:`.xyz` file via the
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:code:`from_file` routine.
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.. code-block:: python
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mol = MoleculeBuilder.from_file('ch4.xyz')
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.. warning::
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It is assumed that the positions inside the `.xyz` file are stored in
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**angstroms**. Internally, :program:`PyQInt` uses Bohr distances and the
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distances as reported in the :code:`.xyz` file are automatically converted.
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Constructing basis functions for a molecule
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-------------------------------------------
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To construct the basis functions for a given molecule, one first needs to
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construct the molecule after which the :code:`build_basis` function can be used
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to construct a basis.
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The following basis sets are supported. For each basis set, the range of atoms
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that are supported are given:
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* :code:`sto3g` (H-I)
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* :code:`sto6g` (H-Kr)
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* :code:`p321` (H-Cs)
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* :code:`p631` (H-Zn)
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The example code below builds the basis functions for the H\ :sub:`2` molecule:
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.. code-block:: python
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from pyqint import PyQInt, Molecule
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import numpy as np
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# construct integrator object
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integrator = PyQInt()
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# build hydrogen molecule
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mol = Molecule('H2')
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mol.add_atom('H', 0.0, 0.0, 0.0)
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mol.add_atom('H', 0.0, 0.0, 1.4)
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cgfs, nuclei = mol.build_basis('sto3g')
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for cgf in cgfs:
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print(cgfs)
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for nucleus in nuclei:
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print(nucleus)
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The output of the above script is::
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[CGF; R=(0.000000,0.000000,0.000000)
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01 | GTO : c=0.154329, alpha=3.425251, l=0, m=0, n=0, R=(0.000000,0.000000,0.000000)
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02 | GTO : c=0.535328, alpha=0.623914, l=0, m=0, n=0, R=(0.000000,0.000000,0.000000)
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03 | GTO : c=0.444635, alpha=0.168855, l=0, m=0, n=0, R=(0.000000,0.000000,0.000000)
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, CGF; R=(0.000000,0.000000,1.400000)
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01 | GTO : c=0.154329, alpha=3.425251, l=0, m=0, n=0, R=(0.000000,0.000000,1.400000)
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02 | GTO : c=0.535328, alpha=0.623914, l=0, m=0, n=0, R=(0.000000,0.000000,1.400000)
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03 | GTO : c=0.444635, alpha=0.168855, l=0, m=0, n=0, R=(0.000000,0.000000,1.400000)
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]
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[CGF; R=(0.000000,0.000000,0.000000)
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01 | GTO : c=0.154329, alpha=3.425251, l=0, m=0, n=0, R=(0.000000,0.000000,0.000000)
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02 | GTO : c=0.535328, alpha=0.623914, l=0, m=0, n=0, R=(0.000000,0.000000,0.000000)
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03 | GTO : c=0.444635, alpha=0.168855, l=0, m=0, n=0, R=(0.000000,0.000000,0.000000)
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, CGF; R=(0.000000,0.000000,1.400000)
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01 | GTO : c=0.154329, alpha=3.425251, l=0, m=0, n=0, R=(0.000000,0.000000,1.400000)
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02 | GTO : c=0.535328, alpha=0.623914, l=0, m=0, n=0, R=(0.000000,0.000000,1.400000)
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03 | GTO : c=0.444635, alpha=0.168855, l=0, m=0, n=0, R=(0.000000,0.000000,1.400000)
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]
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(array([0., 0., 0.]), 1)
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(array([0. , 0. , 1.4]), 1)
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Parallel evaluation of integrals
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--------------------------------
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From a collection of Contracted Gaussian Functions, the complete set of overlap,
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kinetic, nuclear attraction and two-electron integrals can be quickly evaluated
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using the `build_integrals_openmp` function. The function will automatically determine
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the number of available cores to allocate for this process.
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.. code-block:: python
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from pyqint import PyQInt, Molecule
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import numpy as np
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# construct integrator object
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integrator = PyQInt()
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# build hydrogen molecule
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mol = Molecule()
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mol.add_atom('H', 0.0, 0.0, 0.0)
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mol.add_atom('H', 0.0, 0.0, 1.4)
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cgfs, nuclei = mol.build_basis('sto3g')
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# evaluate all integrals
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S, T, V, teint = integrator.build_integrals_openmp(cgfs, nuclei)
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print(S)
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print(T)
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print(V)
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print(teint)
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The output of the above script is given by::
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[[1.00000011 0.6593185 ]
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[0.6593185 1.00000011]]
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[[0.76003161 0.23645446]
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[0.23645446 0.76003161]]
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[[-1.88044067 -1.19483464]
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[-1.19483464 -1.88044067]]
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[0.7746057639733748, 0.4441076656879813, 0.29702859983423036, 0.5696758530951017, 0.44410766568798105, 0.7746057639733748]

‎docs/community_guidelines.rst‎

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.. _community_guidelines:
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.. index:: Community Guidelines
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Community guidelines

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