<!-- # CPPE -->
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CPPE is an open-source, light-weight C++ and Python library for Polarizable Embedding (PE)<sup>1,2</sup>
calculations.
It provides an easy-to-use API to implement PE for ground-state self-consistent field (SCF)
calculations and post-SCF methods. A convenient Python interface is also available.

CPPE enables PE calculations in the following programs:
- [PySCF](https://github.com/pyscf/pyscf)
- [Psi4](https://github.com/psi4/psi4)
- [Q-Chem](https://www.q-chem.com)
- [VeloxChem](https://veloxchem.org)

Linear scaling electric field computations in CPPE are achieved through autogenerated code
by the `fmmgen` library.<sup>3</sup>

__Examples__ for the open-source Python-driven programs can be found [here](https://github.com/maxscheurer/cppe_examples).

## Installation
### Conda
The easiest way to install CPPE is via `conda`:
```
conda install cppe -c conda-forge
```

### Build from Source
Manual builds can be done using CMake by running
```
git clone https://github.com/maxscheurer/cppe
cd cppe; mkdir build; cd build
cmake ..
make
```

### pip/setuptools
Another way to install CPPE is via `pip`:
```
pip install cppe
```
Note that CPPE will be built from source and a C++14 compatible compiler is required (see below), and OpenMP parallelization is **disabled** in the `setup.py`/`pip` installation.
Alternatively, CPPE can be built from source using the `setup.py` script with
```
git clone https://github.com/maxscheurer/cppe
cd cppe
python setup.py install
```

### Python interface
If the Python interface should be built, specify the CMake option
`-DENABLE_PYTHON_INTERFACE=ON`. If `pybind11` is not installed, CMake
will automatically download `pybind11` and install it locally.
Installing through `setup.py` will always build the Python interface.

### Dependencies
- C++ 14 compiler
- Python >= 3.6 (interpreter and development packages)

### Tests
The tests can be run with
```
python setup.py build_ext -i; python setup.py test
```
for the `setup.py` build, or
```
source setup_environment.sh; py.test
```
for the CMake build.


## Citation

**Papers:** | [![](https://img.shields.io/badge/DOI-10.1021/acs.jctc.9b00758-blue)](https://doi.org/10.1021/acs.jctc.9b00758) [![](https://img.shields.io/badge/DOI-10.1021/acs.jctc.1c00225-blue)](https://pubs.acs.org/doi/10.1021/acs.jctc.1c00225)
-----------| --------------------------------------------------------------------------------------------------------------------------------------
**Code:**  | [![DOI](https://zenodo.org/badge/DOI/10.5281/zenodo.3345696.svg)](https://doi.org/10.5281/zenodo.3345696)


**CPPE: An Open-Source C++ and Python Library for Polarizable Embedding**</br>
Maximilian Scheurer, Peter Reinholdt, Erik Rosendahl Kjellgren, Jógvan Magnus Haugaard Olsen, Andreas Dreuw, and Jacob Kongsted;
_Journal of Chemical Theory and Computation_ 2019 15 (11), 6154-6163,
DOI: 10.1021/acs.jctc.9b00758

If you use the linear-scaling FMM implementation, please also cite:

**Efficient Open-Source Implementations of Linear-Scaling Polarizable Embedding: Use Octrees to Save the Trees**</br>
Maximilian Scheurer, Peter Reinholdt, Jógvan Magnus Haugaard Olsen, Andreas Dreuw, and Jacob Kongsted;
_Journal of Chemical Theory and Computation_ 2021,
DOI: 10.1021/acs.jctc.1c00225


## Literature
<sup>1</sup> Olsen, J. M. H.; Aidas, K.; Kongsted, J. (2010). Excited States in Solution through Polarizable Embedding. _J. Chem. Theory Comput._, **6** (12), 3721–3734. https://doi.org/10.1021/ct1003803

<sup>2</sup> Olsen, J. M. H.; Kongsted, J. (2011). Molecular Properties through Polarizable Embedding. _Advances in Quantum Chemistry_ (Vol. 61). https://doi.org/10.1016/B978-0-12-386013-2.00003-6

<sup>3</sup> Pepper, R.; Fangohr, H. (2020). fmmgen: Automatic Code Generation of Operators for Cartesian Fast Multipole and Barnes-Hut Methods. [arXiv:2005.12351](https://arxiv.org/abs/2005.12351)