Analyzing a dataset =================== This tutorial introduces the basic functionality of the package when applied to a real-world analysis of a dataset containing atomic structures. Lets start by loading a series of geometries as `ASE.Atoms `_ objects. In this case we have used a list of extended xyz-files to represent our dataset. But in general as long as the atomic positions, unit cell, periodic boundary conditions and chemical symbols for the atoms are available, any dataset can be turned into an ASE.Atoms object and analyzed by MatID. So let's start by loading a series of structures into a list: .. literalinclude:: ../../../examples/summary.py :lines: 1-22 With a list of geometries available, we can start analyzing them with MatID. Typically the first task is to get a generic classification for the structure. This is done with the Classifier-class: .. literalinclude:: ../../../examples/summary.py :lines: 24-33 Once we have determined the structural class of each geometry, we can further query for additional information that depends on the detected classification, and create a summary of the results: .. literalinclude:: ../../../examples/summary.py :lines: 35- You can find the full example in "examples/summary.py". Here are the results: .. raw:: html

Filename

Results

Image

C32Mo32+CO2.xyz

system_type: Surface
outlier_formula: CO2
outlier_indices: [64, 65, 66]
space_group_number: 225
crystal_system: cubic
bravais_lattice: cF

C49+N.xyz

system_type: Material2D
outlier_formula: N
outlier_indices: [49]

H2O.xyz

system_type: Class0D

Si8.xyz

system_type: Class3D
space_group_number: 227
crystal_system: cubic
bravais_lattice: cF

Mg61O62+CH4Ni.xyz

system_type: Surface
outlier_formula: CH4Ni
outlier_indices: [72, 124, 125,126, 127, 128]
space_group_number: 225
crystal_system: cubic
bravais_lattice: cF

C26H24N4O2.xyz

system_type: Class2D

Ru.xyz

system_type: Atom