amd.utils module

General utility functions and classes.

amd.utils.cellpar_to_cell(a, b, c, alpha, beta, gamma)

Simplified version of function from ase.geometry.

Unit cell params a,b,c,α,β,γ –> cell as 3x3 ndarray.

amd.utils.cellpar_to_cell_2D(a, b, alpha)

amd.utils.random_cell(length_bounds=(1, 2), angle_bounds=(60, 120), dims=3)

class amd.utils.ETA(to_do, update_rate=100)

Bases: object

Pass total amount to do on construction, then call .update() on every loop. ETA will estimate an ETA and print it to the terminal.

update(): Call when one item is finished.

amd.utils.extract_tags(periodic_sets) → dict

Return dict with scalar data in the tags of PeriodicSets in the passed list.

Dict is in format passable to pandas.DataFrame, as in:

periodic_sets = list(amd.SetReader('periodic_sets.hdf5'))
names = [s.name for s in periodic_sets]
data = amd.utils.extract_tags(periodic_sets)
df = pd.DataFrame(data, index=names, columns=data.keys())

Format of returned dict is for example:

{
    'density': [1.231, 2.532, ...],
    'family':  ['CBMZPN', 'SEMFAU', ...],
    ...
}

where the inner lists have the same order as the items in periodic_sets.

amd.utils.neighbours_df_dict(n_neighbours, references, comparisons, invariant_key=None)

n, reference psets, comparison psets –> dict passable to DataFrame

Example::: data = amd.neighbours_df_dict(10, pdds, pdds_) df = pd.DataFrame(data, index=ref_names)