Custom Data Formats¶

BaderKit only provides convenience functions for loading VASP CHGCAR-like files or Gaussian cube-like files. However, as long as you can read in your charge density into a NumPy array, you can still use BaderKit by constructing the Structure, Grid, and Bader classes manually. This tutorial provides the outline for how to do this.

Import the required classes from BaderKit as well as numpy

from baderkit import Bader, Grid, Structure
import numpy as np

Create a PyMatGen Structure object. This is usually easiest to do from a file, but can also be made manually.
```
structure = Structure.from_file(filename = "mystructure.cif", fmt = "cif")
```
Load your data, however you can, into a numpy array. Here we manually construct a fake grid as the actual method will be specific to your use case.
```
charge_data = np.array([
[[1,2,3],[3,4,5],[6,7,8]],
[[1,2,3],[3,4,5],[6,7,8]],
[[1,2,3],[3,4,5],[6,7,8]],
])
```
Construct a data dictionary and then the Grid object.
```
data = {"total": charge_data}
charge_grid = Grid(structure=structure, data=data)
```
Note

Charge density data is assumed to be in VASP's default format i.e. it should be stored as

data(r) = n(r) x V_grid x V_cell

where
- n(r) = charge density in 1/Ang at point r
- V_grid = the total number of grid points
- V_cell = the volume of the simulation cell
See VASP's wiki for more details.
Construct a Bader class object.
```
bader = Bader(charge_grid=charge_grid)
```
From here you can use the Bader class as you wish.

Download Resources¶

Tutorial Script: other_formats.py