Installation

For running ADC calculations with adcc you will need two things: adcc itself and a host program (i.e. SCF code) of your choice.

We have some more detailed guides for installing adcc Using conda (on Debian/Ubuntu and macOS), Using pip (on Debian / Ubuntu) and Using pip (on macOS), where we know things should be working. If you encounter problems see Troubleshooting. Please get in touch by opening an issue if you cannot get adcc to work.

Some specialty features of adcc require extra dependencies (e.g., Pandas and Matplotlib), see Optional dependencies for analysis features for details.

Installing adcc

Using conda (on Debian/Ubuntu and macOS)

The conda binary packages can be installed using the conda-forge channel:

conda install -c conda-forge adcc

This should work on a recent Debian, Ubuntu or macOS and with python 3.7, 3.8 or 3.9.

Warning

As of version 0.15.13, adcc is deployed via conda-forge. Before that, we maintained our own Anaconda channel, which is now discontinued. Thus, we highly recommend you use the conda-forge version from now on.

Using pip (on Debian / Ubuntu)

For installing adcc from PyPi, using pip, the procedure for Debian / Ubuntu and macOS differs. For Debian and Ubuntu:

Install openblas: Make sure you have the openblas BLAS library installed. This library is reasonably wide-spread, so there is a good chance it may already be installed on your system. If not, you can easily install it using
```
sudo apt-get install libopenblas-base
```
Install compilation requirements: For compiling the Python extensions of adcc, you need to have the the python development headers and some essential build packages installed. This can be achieved via
```
sudo apt-get install python3-dev build-essential
```

Install adcc:

pip install pybind11     # Install pybind11 first to suppress some error messages
pip install adcc

Using pip (on macOS)

Attention

macOS support via pip covers Catalina (10.15) and Big Sur (11.0). For other macOS versions, please install adcc using conda.

The installation on macOS requires a clang compiler. Make sure to have XCode and the command line tools installed. Then install adcc using pip:

pip install pybind11     # Install pybind11 first to suppress some error messages
pip install adcc

Installing a host program

Since adcc does not contain a self-consistent field (SCF) code you should install one of the supported SCF programs needs as well. Without expressing any particular preference, this documentation will mostly focus on Psi4 and PySCF, since these are very easy to obtain, install and use. If you prefer, feel free to install molsturm or veloxchem instead. Also note, that connecting to further host programs is not too hard and can be achieved via a dictionary or an HDF5 file, see Connecting host programs to adcc for details.

Installing Psi4

Either use the conda binary distribution
```
conda install -c psi4 psi4
```
or use the version packaged in Debian or Ubuntu via
```
sudo apt-get install psi4
```

Installing PySCF

A PySCF installation can be achieved following the PySCF quickstart guide. E.g. if you are using pip this boils down to

pip install pyscf

Finishing the setup

Congratulations! With these packages installed you are all set to run ADC calculations. Feel free to take a look at the Performing calculations with adcc section for learning how to use adcc in practice or take a look at our examples folder on github.

Finally, if you are interested in developing or contributing to adcc, even the better! In this case we hope the Developer’s notes will provide you with some useful pointers to get started.

Optional dependencies for analysis features

Matplotlib: Plotting spectra with adcc.ElectronicTransition.plot_spectrum()
Pandas: Export to pandas.DataFrame via adcc.ExcitedStates.to_dataframe()

Installation of optional packages

Using pip: Either install optional dependencies directly with adcc via pip install adcc[analysis] or run manually for each package, e.g., pip install matplotlib
Using conda: Install each package manually, e.g., conda install matplotlib.

Note that all other core features of adcc still work without these packages installed.

Troubleshooting

If the installation of adcc fails due to an issue with compiling the python extension, check the following:

Make sure your pip uses the correct compiler. On Linux we only support gcc and not clang. On macOS we only support Apple clang and not gcc. To enforce a compiler, set the environment variables CC and CXX to the full path of your C and C++ compilers, respectively.