| """Crystal structure representation and Elk input parsing.""" |
|
|
| from __future__ import annotations |
|
|
| from dataclasses import dataclass |
| from pathlib import Path |
|
|
| import numpy as np |
|
|
| from .constants import BOHR_TO_ANGSTROM |
|
|
|
|
| @dataclass(frozen=True) |
| class CrystalStructure: |
| """Crystal structure as parsed from an Elk input file. |
| |
| Attributes: |
| scale: Elk lattice scale in Bohr. |
| avec: Lattice vectors before applying `scale`, row-wise. |
| species: Species names from the Elk `atoms` block. |
| positions: Fractional atomic coordinates. |
| species_numbers: Integer species labels suitable for spglib. |
| """ |
|
|
| scale: float |
| avec: np.ndarray |
| species: list[str] |
| positions: np.ndarray |
| species_numbers: np.ndarray |
|
|
| @property |
| def lattice_bohr(self) -> np.ndarray: |
| return self.scale * self.avec |
|
|
| @property |
| def lattice_angstrom(self) -> np.ndarray: |
| return BOHR_TO_ANGSTROM * self.lattice_bohr |
|
|
| @property |
| def spglib_cell(self) -> tuple[np.ndarray, np.ndarray, np.ndarray]: |
| return self.lattice_angstrom, self.positions, self.species_numbers |
|
|
|
|
| def strip_comment(line: str) -> str: |
| return line.split(":", 1)[0].split("!", 1)[0].strip() |
|
|
|
|
| def _read_numeric_block(lines: list[str], start: int, nrows: int) -> np.ndarray: |
| rows = [] |
| for idx in range(start, start + nrows): |
| text = strip_comment(lines[idx]) |
| if not text: |
| raise ValueError(f"Expected numeric row at line {idx + 1}") |
| rows.append([float(x) for x in text.split()[:3]]) |
| return np.asarray(rows, dtype=float) |
|
|
|
|
| class ElkInputParser: |
| """Parse the subset of Elk input needed for fourj analysis.""" |
|
|
| def parse(self, path: Path) -> CrystalStructure: |
| """Parse `scale`, `avec`, and `atoms` from an Elk file. |
| |
| Args: |
| path: Elk input or temporary file. |
| |
| Returns: |
| Parsed crystal structure. |
| """ |
| lines = path.read_text().splitlines() |
| scale = None |
| avec = None |
| species: list[str] = [] |
| positions: list[list[float]] = [] |
| species_numbers: list[int] = [] |
|
|
| i = 0 |
| while i < len(lines): |
| key = strip_comment(lines[i]).lower() |
| if key == "scale": |
| i += 1 |
| while i < len(lines) and not strip_comment(lines[i]): |
| i += 1 |
| scale = float(strip_comment(lines[i]).split()[0]) |
| elif key == "avec": |
| avec = _read_numeric_block(lines, i + 1, 3) |
| i += 3 |
| elif key == "atoms": |
| i += 1 |
| while i < len(lines) and not strip_comment(lines[i]): |
| i += 1 |
| nspecies = int(strip_comment(lines[i]).split()[0]) |
| for ispecies in range(1, nspecies + 1): |
| i += 1 |
| while i < len(lines) and not strip_comment(lines[i]): |
| i += 1 |
| species.append(Path(strip_comment(lines[i]).strip("'\"")).stem) |
| i += 1 |
| while i < len(lines) and not strip_comment(lines[i]): |
| i += 1 |
| natoms = int(strip_comment(lines[i]).split()[0]) |
| for _ in range(natoms): |
| i += 1 |
| while i < len(lines) and not strip_comment(lines[i]): |
| i += 1 |
| positions.append([float(x) for x in strip_comment(lines[i]).split()[:3]]) |
| species_numbers.append(ispecies) |
| i += 1 |
|
|
| if scale is None: |
| raise ValueError(f"Could not find 'scale' in {path}") |
| if avec is None: |
| raise ValueError(f"Could not find 'avec' in {path}") |
| if not positions: |
| raise ValueError(f"Could not find 'atoms' block in {path}") |
|
|
| return CrystalStructure( |
| scale=scale, |
| avec=avec, |
| species=species, |
| positions=np.asarray(positions, dtype=float), |
| species_numbers=np.asarray(species_numbers, dtype=int), |
| ) |
|
|
