Principia Materia v0

We are in the process of doing a major rewrite of our entire software suite, which for now is being called Principia Materia. It will be at least several months before we get to the point of producing tutorials for the new code. In the meatime, this sphinx site provides tutorials for the current version of the code, which I am simply referring to as version 0. This is the version that you should be using for now, and it can be found in the following repo on the development branch:

git@github.com:marianettigroup/Principia.git

Most of the tutorials are simply composed of Jupyter notebooks that sphinx then uses to compile into webpages. This git repository for these tutorials are located here:

ssh://grandcentral/home/cam1/git_repos/principia_materia_doc_v0.git

If you would rather play around with the Jupyter notebooks directly, you can simply clone the above repository and directly access the notebooks.

Contents:

• Data Input (enhance_argparse)
  • General Background and Instantiation
  • Organizing Parser Data
  • Argument Data and Methods
  • Methods for Handling Input Files
  • Typical Main Program Example
• Finite Difference (finite_difference)
  • General Background
  • Single Variable
  • Multiple Variables
  • Defining Deltas
  • Performing Finite Difference with Data
• Extracting Error Tails (fit_quadratic)
  • Introduction
  • Fitting over subsets of data
  • Using code from command line
• Strain Derivatives (strain_derivative)
  • Background and Basic Usage
  • Examples
  • NaCl
  • ThO2
• Irreducible K-Points N
  • get_tpoints
  • Irreducible K-Points at arbitrary order with symmetry
• KMesh
  • class KMesh(supa, pgn=“C1”, lattice_vecs=np.eye(3), strict_symmetry=True, decimal=6)
  • class DiagKMesh(supa, pgn, lattice_vecs)
  • class Tetrahedra(DiagKMesh):
• Arbirary Order Frozen Phonon
  • method make_runs(delta,dft_io_interface=None,overide_naming_scheme=None,renorm_delta=False,sequence=False,defaults={},dry_run=False,skip_delta_check=False)
• Analytic Dynamic Tensor
  • Little group approach
  • Full group approach
• DqN analysis
  • class Abstract_Dqn_Analysis(pos=None, supa=None, pgn=None, pg_loc=None, order=2, D=None, tensor_vec_indices=None, known_tensor_vec_indices=None, nocache=False, parallel=False, tol=1.0E-8, use_star=False, symadt=False, quiet=False)
• Array Parser and Formatter
• Unit Testing
  • Creating a test
  • Running tests
• LID Phonon (lid_phonon.py)
  • Background
• BID and HS-BID
  • BID
  • HS-BID
• Thermal Conductivity
  • Examples:
• Dipole-Dipole effect at second order
  • class DipoleDipole(struct, zeu=None, epsilon=None, dataset=None, G_ran=5, Lambda=0.20, factor=1.0, tol=1.0E-6)
• Including LO-TO from command line
• Order N Fourier Interpolation
• DqN analysis
  • class Abstract_Dqn_Analysis(pos=None, supa=None, pgn=None, pg_loc=None, order=2, D=None, tensor_vec_indices=None, known_tensor_vec_indices=None, nocache=False, parallel=False, tol=1.0E-8, use_star=False, symadt=False, quiet=False)
• Minimum supercell problem
• Symmetric product of irreps associated with qvectors
  • Product representation of irreps associated with q-vectors.
  • Symmetric product representation of irreps associated with q-vectors.

Indices and tables

• Index
• Module Index
• Search Page