PyChemia is a python library for automatize atomistic simulations. PyChemia is build around a core module with two classes and a set of some other modules that offers a variety of operations in order to perform more complex operations.

The core is made of two classes ‘Structure’ and ‘Composition’. Other modules are:

  • analysis:
    Uses pure structure information for changing structures, matching atoms between two structures, create slabs, surfaces and some other geometrical operations on structures.
  • code:
    This module deals with creating inputs and reading outputs from several atomistic simulation codes. Right now, we support ABINIT, DFTB+, Fireball, an internal calculator for LennardJones Clusters, Octopus and VASP.
  • core:
    The core of PyChemia are two classes that are imported at the root level of the library: Structure and Composition. For PyChemia, Structure is a set of sites with one or more atoms located on each site with a probability associated to them. The Structure could be finite or periodic in one or more directions. In the case of a crystal the Structure will have also a lattice. Composition is a set o atoms of a define species. For crystals is the set of atoms on each unit cell. No geometry is store on a Composition object, and the order of atoms is irrelevant.
  • crystal:
    For the case of periodic structures in three directions, a set of modules is created for three basic properties of a crystal. The class ‘KPoints’ store the description a a k-point mesh, path, or direct list of points on the reciprocal lattice. The class ‘Lattice’ store and manipulate the cell vectors of a crystal. The third class is ‘CrystalSymmetry’ for computing the Space Group, getting structures on the Bravais cell and finding the primitive cell.
  • db:
    PyChemia uses MongoDB as Database for storing Structures and the properties computed by atomistic simulation codes. There are two classes defined, PyChemiaDB to store structures and properties and PyChemiaQueue to store a massive set of calculations and the status of those calculations.
  • dm:
    This is a module in development, it contains classes for DataMining PyChemia Databases and global searches. Right now it contains a class for Network analysis, but in the future will provide interfaces with some other libraries for machine learning.
  • evaluator:
    There are two circumstances where a atomistic simulation can be perform. If you have a machine without a queue system PyChemia will provide a very simplified queue for computing concurrent calculations under the constrains of your number of cores. If you use a queue system, the evaluator will setup the batch scripts, submit the jobs and monitor the status of those jobs, finally when the job is done, it will collect the final data and update the the databases.
  • external:
    There are some other packages for which PyChemia worth interact, ASE (Atomistic Simulation Environment) is a python package supporting a remarkable number of calculators. Findsym is a close software to compute spacegroups and computing the CIF file of a give structure. ‘pymatgen’ is python code behind ‘Materials Project’ and a outstanding piece of very well written code. Originally implemented for VASP only now includes support for ABINIT.
  • io:
    There are a pletora of formats for describing atomistic structures. We support three basic file-formats, ascii, CIF and XYZ. This module provides the classes for reading and writing them.
  • md:
    Molecular Dynamics is an important operation for atomistic simulations. This module provide a ‘in-house’ calculator for MD simulations, using the forces computed from static calculations from an external atomistic code.
  • population:
    A population is basically a collection of candidates collected somehow by a global searcher or from a DB query. PyChemia includes classes for populations of Lennard-Jones clusters, populations of vectors on a N-dimensional space.
  • runner:
    Controls the executions in cluster by creating batch scripts and checking the status of the queue. Right now only supports Torque
  • searcher:
    Global search operations, the prototypical case is structural search but any pychemia population could be use for searching. Several metaheuristic algorithms have been implemented
  • utils:
    Several small routines, like a periodic table, mathematical operations, conversions and serializers.
  • visual:
    PyChemia includes a set of classes and routines for interfacing with some other libraries and external software for data visualization, 3D plotting and graphic representation. pyprocar plots band-structures, LatticePlot and StructurePlot uses mayavi for visualizing atomic configurations and lattices. We have also interfaces for Povray and a developing interface to D3.js.
  • web:
    On development, creation of a web interface for looking into the pychemia databases and controling executions. The web interface is build on top of Python-Bottle and CherryPy to access the database.

PyChemia is a open-source Python library for High-throughput first-principles materials discovery. The focus of this library is on structural search and data analysis. The ultimate purpose of the code is to optimize the search of new materials using a variety of methods such as Minima hopping method (MHM), soft-computing-based methods and statistical methods.

The main objectives of the code are:

  1. Provide flexible classes for atomic structures such as molecules, clusters, thin films and crystals.
  2. Manipulate both input and output for DFT and Tight-binding codes such as VASP. ABINIT, Fireball and DFTB+
  3. Offer a robust architecture for storing a large collection of structures. Structural search methods generate many structures that are stored in repositories. Calculations done on those structures are also store in repositories.
  4. Similarity analysis based on fingerprints, pair correlation and comparators.
  5. Stability analysis for crystals. Including thermal analysis (Enthalpy) and dynamic stability (Phonons)
  6. Tools for producing comprehensive reports, convex hulls, band structures, density of states, etc
  7. Datamining tools to extract knowledge from the structures found, identify patterns in the data and identify suitable candidates for technological applications
  8. A web interface

This is a new project and many classes and methods are refactored frequently. This is and will be a work in progress. We hope to stabilize the most critical classes for the release 1.

This code is open-source. We also welcome extra hands to improve this library with your own contributions. At present only one developer has being in charge of the project. More hands and eyes are very welcomed.