File size: 14,233 Bytes
bc2957c | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 187 188 189 190 191 192 193 194 195 196 197 198 199 200 201 202 203 204 205 206 207 208 209 210 211 212 213 214 215 216 217 218 219 220 221 222 223 224 225 226 227 228 229 230 231 232 233 234 235 236 237 238 239 240 241 242 243 244 245 246 247 248 249 250 251 252 253 254 255 256 257 258 259 260 261 262 263 264 265 266 267 268 269 270 271 272 273 274 275 276 277 278 279 280 281 282 283 284 285 286 287 288 289 290 291 292 293 | """Visualization utilities for fourj spectra."""
from __future__ import annotations
import math
import os
from pathlib import Path
import numpy as np
from .constants import HARTREE_TO_MRY, MRY_TO_MEV
from .lsq import LSQFitResult
from .structure import CrystalStructure
from .transforms import ExchangeSpectrum, FrozenMagnonTransformer
def reciprocal_lattice_rows(lattice_rows: np.ndarray) -> np.ndarray:
return 2.0 * np.pi * np.linalg.inv(lattice_rows).T
def seekpath_labels(label: str) -> str:
replacements = {
"GAMMA": r"$\Gamma$",
"SIGMA": r"$\Sigma$",
"DELTA": r"$\Delta$",
"LAMBDA": r"$\Lambda$",
}
return replacements.get(label, label.replace("_", r"\_"))
class SeekPath:
"""Wrapper around Seekpath for original-cell high-symmetry paths."""
def __init__(self, structure: CrystalStructure, symprec: float = 1e-5) -> None:
self.structure = structure
self.symprec = symprec
def get(self) -> tuple[dict[str, np.ndarray], list[tuple[str, str]], str]:
"""Return point coordinates, path segments, and Bravais label."""
try:
import seekpath # type: ignore
except Exception as exc:
raise RuntimeError("Plotting along symmetry paths requires seekpath in the active Python environment") from exc
path_data = seekpath.get_path_orig_cell(self.structure.spglib_cell, symprec=self.symprec)
points = {label: np.asarray(coords, dtype=float) for label, coords in path_data["point_coords"].items()}
bravais = str(path_data.get("bravais_lattice_extended", path_data.get("bravais_lattice", "unknown")))
return points, list(path_data["path"]), bravais
def point_on_segment(q: np.ndarray, start: np.ndarray, end: np.ndarray, tol: float) -> tuple[bool, float]:
direction = end - start
denom = float(np.dot(direction, direction))
if denom <= tol * tol:
return np.linalg.norm(q - start) <= tol, 0.0
t = float(np.dot(q - start, direction) / denom)
if t < -tol or t > 1.0 + tol:
return False, t
return np.linalg.norm(q - (start + t * direction)) <= tol, min(1.0, max(0.0, t))
def find_existing_points_on_segment(q: np.ndarray, values: np.ndarray, start: np.ndarray, end: np.ndarray, tol: float) -> list[tuple[float, np.ndarray, float]]:
points = []
seen = set()
for qq, value in zip(q, values):
on_segment, t = point_on_segment(qq, start, end, tol)
if not on_segment:
continue
key = tuple(np.round(qq, 10))
if key in seen:
continue
seen.add(key)
points.append((t, qq, float(value)))
points.sort(key=lambda item: item[0])
return points
def make_seekpath_line(start: np.ndarray, end: np.ndarray, npoints: int) -> list[tuple[float, np.ndarray]]:
if npoints < 2:
raise ValueError("--lswt-path-points must be at least 2")
return [(float(t), start + float(t) * (end - start)) for t in np.linspace(0.0, 1.0, npoints)]
class SeekPathPlotter:
"""Matplotlib plots for DFT, full-FT, and LSQ spectra along Seekpath lines."""
def __init__(self, structure: CrystalStructure, output_prefix: Path, symprec: float = 1e-5) -> None:
self.structure = structure
self.output_prefix = output_prefix
self.symprec = symprec
def plot(
self,
q_raw: np.ndarray,
energy_raw_hartree: np.ndarray,
transformer: FrozenMagnonTransformer,
plot_kind: str = "magnon",
vectors: np.ndarray | None = None,
jij_mry: np.ndarray | None = None,
lsq_result: LSQFitResult | None = None,
plot_lswt: bool = False,
lswt_moment: float | None = None,
dense_path: bool = False,
path_points: int = 202,
tol: float = 1e-7,
min_points: int = 2,
) -> tuple[Path, Path, list[str]]:
"""Create a Seekpath spectrum plot.
Args:
q_raw: Raw DFT q-points from the energy table.
energy_raw_hartree: Raw DFT energies in Hartree.
transformer: FourJ transformer defining theta and E0.
plot_kind: `magnon` or `energy`.
vectors: Real-space vectors for full-FT spectrum reconstruction.
jij_mry: Exchange constants for full-FT spectrum reconstruction.
lsq_result: Optional LSQ shell fit to overlay.
plot_lswt: Overlay the full-FT reconstructed spectrum.
lswt_moment: Optional moment for `4/M` meV scaling.
dense_path: Evaluate reconstructed curves on a dense Seekpath mesh.
path_points: Points per dense path segment.
tol: q-point matching tolerance for raw DFT points.
min_points: Minimum raw DFT points required for a segment.
Returns:
Plot path, sparse path-data path, and skipped segment names.
"""
sin2 = math.sin(math.radians(transformer.theta_degrees)) ** 2
if sin2 <= 1e-14:
raise ValueError("theta gives sin(theta)^2 too close to zero")
if plot_kind == "energy":
e0 = transformer.reference_energy(q_raw, energy_raw_hartree)
plot_values = (energy_raw_hartree - e0) * HARTREE_TO_MRY
ylabel = r"$E(q)-E_0$ (mRy)"
dft_column = "dft_value_mRy"
elif plot_kind == "magnon":
plot_values = transformer.dft_spectrum_mry(q_raw, energy_raw_hartree)
ylabel = r"$(E(q)-E_0)//\sin^2\theta$ (mRy)"
dft_column = "dft_magnon_mRy"
else:
raise ValueError(f"Unknown plot kind: {plot_kind}")
if plot_lswt:
if vectors is None or jij_mry is None:
raise ValueError("LSWT/exchange overlay requires extracted J_ij values")
if plot_kind != "magnon":
raise ValueError("--plot-lswt is only meaningful with --plot-kind magnon")
if lswt_moment is not None:
if lswt_moment <= 0.0:
raise ValueError("--lswt-moment must be positive")
plot_values = (4.0 / lswt_moment) * plot_values * MRY_TO_MEV
ylabel = rf"$4[J(0)-J(q)]/{lswt_moment:g}$ (meV)"
dft_column = "dft_lswt_meV"
_lswt_values, lswt_label, lswt_column = ExchangeSpectrum.scale(
ExchangeSpectrum.from_jij(q_raw, vectors, jij_mry),
lswt_moment,
)
else:
lswt_label = None
lswt_column = None
if lsq_result is not None and plot_kind != "magnon":
raise ValueError("LSQ plot overlay is only meaningful with --plot-kind magnon")
points, path_segments, bravais = SeekPath(self.structure, self.symprec).get()
recip = reciprocal_lattice_rows(self.structure.lattice_angstrom)
x_offset = 0.0
tick_positions = []
tick_labels = []
rows = []
plotted_segments = []
skipped_segments = []
mpl_config_dir = Path("/private/tmp/matplotlib")
mpl_config_dir.mkdir(parents=True, exist_ok=True)
os.environ.setdefault("MPLBACKEND", "Agg")
os.environ.setdefault("MPLCONFIGDIR", str(mpl_config_dir))
import matplotlib.pyplot as plt # type: ignore
fig, ax = plt.subplots(figsize=(8.0, 4.8))
for start_label, end_label in path_segments:
start = points[start_label]
end = points[end_label]
segment_points = find_existing_points_on_segment(q_raw, plot_values, start, end, tol)
if len(segment_points) < min_points:
skipped_segments.append(f"{start_label}-{end_label}")
continue
segment_length = float(np.linalg.norm((end - start) @ recip))
x = np.asarray([x_offset + t * segment_length for t, _, _ in segment_points], dtype=float)
y = np.asarray([value for _, _, value in segment_points], dtype=float)
dft_line = ax.plot(x, y, marker="o", markersize=3.5, linewidth=1.2, alpha=0.5, label="DFT frozen magnon")
y_secondary = None
if plot_lswt:
q_existing = np.asarray([qq for _, qq, _ in segment_points], dtype=float)
y_secondary = ExchangeSpectrum.scale(ExchangeSpectrum.from_jij(q_existing, vectors, jij_mry), lswt_moment)[0]
if dense_path:
line = make_seekpath_line(start, end, path_points)
q_line = np.asarray([qq for _, qq in line], dtype=float)
y_line = ExchangeSpectrum.scale(ExchangeSpectrum.from_jij(q_line, vectors, jij_mry), lswt_moment)[0]
x_line = np.asarray([x_offset + t * segment_length for t, _ in line], dtype=float)
else:
y_line = y_secondary
x_line = x
ax.plot(x_line, y_line, marker=None if dense_path else "s", markersize=3.0, linewidth=1.5 if dense_path else 1.1, linestyle="--", color=dft_line[0].get_color(), label=lswt_label)
if lsq_result is not None:
q_existing = np.asarray([qq for _, qq, _ in segment_points], dtype=float)
y_lsq_existing = ExchangeSpectrum.scale(lsq_result.spectrum(q_existing), lswt_moment if plot_lswt else None)[0]
if y_secondary is None:
y_secondary = y_lsq_existing
if dense_path:
line = make_seekpath_line(start, end, path_points)
q_line = np.asarray([qq for _, qq in line], dtype=float)
y_lsq = ExchangeSpectrum.scale(lsq_result.spectrum(q_line), lswt_moment if plot_lswt else None)[0]
x_lsq = np.asarray([x_offset + t * segment_length for t, _ in line], dtype=float)
else:
y_lsq = y_lsq_existing
x_lsq = x
ax.plot(x_lsq, y_lsq, marker=None, linewidth=1.4, linestyle=":", color=dft_line[0].get_color(), label=f"LSQ shell fit ({len(lsq_result.shells)} shells)")
tick_positions.append(x_offset)
tick_labels.append(seekpath_labels(start_label))
tick_positions.append(x_offset + segment_length)
tick_labels.append(seekpath_labels(end_label))
plotted_segments.append(f"{start_label}-{end_label}")
if y_secondary is None:
for xx, (t, qq, value) in zip(x, segment_points):
rows.append((start_label, end_label, xx, t, qq[0], qq[1], qq[2], value, None))
else:
for xx, (t, qq, value), secondary_value in zip(x, segment_points, y_secondary):
rows.append((start_label, end_label, xx, t, qq[0], qq[1], qq[2], value, secondary_value))
x_offset += segment_length
if not plotted_segments:
raise ValueError("No Seekpath segment had enough existing q points")
for xpos in tick_positions:
ax.axvline(xpos, color="0.85", linewidth=0.8, zorder=0)
ax.set_xlim(min(tick_positions), max(tick_positions))
ax.set_xticks(tick_positions)
ax.set_xticklabels(tick_labels)
ax.set_ylabel(ylabel)
ax.set_xlabel(r"Wave-vector distance ($\mathrm{\AA}^{-1}$)")
ax.set_title(f"Seekpath {bravais}; existing input q-points only")
ax.grid(axis="y", color="0.9", linewidth=0.8)
if plot_lswt or lsq_result is not None:
handles, labels = ax.get_legend_handles_labels()
unique = {}
for handle, label in zip(handles, labels):
unique.setdefault(label, handle)
ax.legend(unique.values(), unique.keys(), frameon=False, fontsize=8)
fig.tight_layout()
plot_path = self.output_prefix.with_suffix(f".seekpath_{plot_kind}.png")
data_path = self.output_prefix.with_suffix(f".seekpath_{plot_kind}.dat")
fig.savefig(plot_path, dpi=200)
plt.close(fig)
with data_path.open("w") as handle:
if lswt_column is None:
handle.write(f"# start_label end_label path_distance_1_per_A segment_fraction q1 q2 q3 {dft_column}\n")
else:
handle.write("# start_label end_label path_distance_1_per_A segment_fraction q1 q2 q3 " f"{dft_column} {lswt_column}\n")
handle.write("# plotted_segments " + " ".join(plotted_segments) + "\n")
if skipped_segments:
handle.write("# skipped_segments " + " ".join(skipped_segments) + "\n")
for row in rows:
if row[8] is None:
handle.write(f"{row[0]:>8s} {row[1]:>8s} {row[2]:16.8f} {row[3]:12.8f} {row[4]:12.8f} {row[5]:12.8f} {row[6]:12.8f} {row[7]:16.8f}\n")
else:
handle.write(f"{row[0]:>8s} {row[1]:>8s} {row[2]:16.8f} {row[3]:12.8f} {row[4]:12.8f} {row[5]:12.8f} {row[6]:12.8f} {row[7]:16.8f} {row[8]:16.8f}\n")
if plot_lswt and dense_path:
dense_path_file = self.output_prefix.with_suffix(f".seekpath_{plot_kind}_lswt_dense.dat")
with dense_path_file.open("w") as handle:
handle.write("# start_label end_label path_distance_1_per_A segment_fraction q1 q2 q3 " f"{lswt_column}\n")
x_offset = 0.0
for start_label, end_label in path_segments:
if f"{start_label}-{end_label}" in skipped_segments:
continue
start = points[start_label]
end = points[end_label]
segment_length = float(np.linalg.norm((end - start) @ recip))
line = make_seekpath_line(start, end, path_points)
q_line = np.asarray([qq for _, qq in line], dtype=float)
values = ExchangeSpectrum.scale(ExchangeSpectrum.from_jij(q_line, vectors, jij_mry), lswt_moment)[0]
for (t, qq), value in zip(line, values):
handle.write(f"{start_label:>8s} {end_label:>8s} {x_offset + t * segment_length:16.8f} {t:12.8f} {qq[0]:12.8f} {qq[1]:12.8f} {qq[2]:12.8f} {value:16.8f}\n")
x_offset += segment_length
return plot_path, data_path, skipped_segments
|