16553145710

Committed 27 Jul 2025 04:20PM UTC coverage: 41.213% (-0.3%) from 41.536%

Build # 16553145710

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push

github

Committed by

web-flow

Commit Message

Bugfixes (#127)

Run Details

10 of 74 branches covered (13.51%)

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0 of 4 new or added lines in 1 file covered. (0.0%)

255 of 569 relevant lines covered (44.82%)

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18.18

/src/quant_met/cli/q_loop.py

"""Functions to run self-consistent calculation for the order parameter."""

import logging
from pathlib import Path

import h5py
import numpy as np
import sisl

from quant_met import routines
from quant_met.parameters import Parameters
from quant_met.parameters.control import CritTemp, QLoop

logger = logging.getLogger(__name__)


def q_loop(parameters: Parameters) -> None:
    """Self-consistent calculation for the order parameter.

    Parameters
    ----------
    parameters: Parameters
        An instance of Parameters containing control settings, the model,
        and k-point specifications for the T_C calculation.
    """
    if not isinstance(parameters.control, QLoop):
        err_msg = "Wrong parameters for q-loop."
        raise TypeError(err_msg)

    result_path = Path(parameters.control.outdir)
    result_path.mkdir(exist_ok=True, parents=True)

    hamiltonian = sisl.get_sile(parameters.control.hamiltonian_file).read_hamiltonian()
    k_grid_obj = sisl.MonkhorstPack(
        hamiltonian.geometry,
        [parameters.k_points.nk1, parameters.k_points.nk2, 1],
    )

    if isinstance(parameters.control.crit_temp, CritTemp):
        delta_vs_temp, critical_temperatures, fit_fig = routines.search_crit_temp(
            hamiltonian=hamiltonian,
            kgrid=k_grid_obj,
            hubbard_int_orbital_basis=np.array(parameters.control.crit_temp.hubbard_int_orbital_basis),
            epsilon=parameters.control.crit_temp.conv_treshold,
            max_iter=parameters.control.crit_temp.max_iter,
            n_temp_points=20,
        )
        logger.info("Search for T_C completed successfully.")
        logger.info("Obtained T_Cs: %s", critical_temperatures)

        fit_fig.savefig(
            result_path / f"{parameters.control.crit_temp.prefix}_critical_temperatures_fit.pdf",
            bbox_inches="tight",
        )

        result_file_crit_temp = (
            result_path / f"{parameters.control.crit_temp.prefix}_critical_temperatures.hdf5"
        )
        if result_file_crit_temp.exists():
            result_file_crit_temp.exists()
        delta_vs_temp.to_hdf(result_file_crit_temp, key="delta_vs_temp")
        with h5py.File(result_file_crit_temp, mode="a") as file:
            for orbital, crit_temp_orbital in enumerate(critical_temperatures):
                file.attrs[f"T_C_{orbital}"] = crit_temp_orbital

        logger.info("Results saved to %s", result_file_crit_temp)
    else:
        critical_temperatures = []
        with h5py.File(f"{parameters.control.crit_temp}", mode="r") as file:
            for key, critical_temperature in file.attrs.items():
                if key.startswith("T_C"):
                    critical_temperatures.append(critical_temperature)
        logger.info("Read critical temperatures from file.")
        logger.info("Obtained T_Cs: %s", critical_temperatures)

    delta_vs_q = routines.loop_over_q(
        hamiltonian=hamiltonian,
        kgrid=k_grid_obj,
        hubbard_int_orbital_basis=np.array(parameters.control.hubbard_int_orbital_basis),
        epsilon=parameters.control.conv_treshold,
        max_iter=parameters.control.max_iter,
        n_q_points=parameters.control.n_q_points,
        crit_temps=np.array(critical_temperatures),
    )

    result_file_q = result_path / f"{parameters.control.prefix}_q.hdf5"

    if result_file_q.exists():
        result_file_q.unlink()
    for key, df in delta_vs_q.items():
        df.to_hdf(result_file_q, key=f"temp_{float(key):.6f}")
        with h5py.File(result_file_q, "a") as f:
            grp = f[f"temp_{float(key):.6f}"]
            grp.attrs["crit_temp"] = critical_temperatures
            grp.attrs["temp"] = float(key)

1	"""Functions to run self-consistent calculation for the order parameter."""
2
3	import logging	3✔
4	from pathlib import Path	3✔
5
6	import h5py	3✔
7	import numpy as np	3✔
8	import sisl	3✔
9
10	from quant_met import routines	3✔
11	from quant_met.parameters import Parameters	3✔
12	from quant_met.parameters.control import CritTemp, QLoop	3✔
13
14	logger = logging.getLogger(__name__)	3✔
15
16
17	def q_loop(parameters: Parameters) -> None:	3✔
18	"""Self-consistent calculation for the order parameter.
19
20	Parameters
21	----------
22	parameters: Parameters
23	An instance of Parameters containing control settings, the model,
24	and k-point specifications for the T_C calculation.
25	"""
26	if not isinstance(parameters.control, QLoop):	×
27	err_msg = "Wrong parameters for q-loop."	×
28	raise TypeError(err_msg)	×
29
30	result_path = Path(parameters.control.outdir)	×
31	result_path.mkdir(exist_ok=True, parents=True)	×
32
33	hamiltonian = sisl.get_sile(parameters.control.hamiltonian_file).read_hamiltonian()	×
34	k_grid_obj = sisl.MonkhorstPack(	×
35	hamiltonian.geometry,
36	[parameters.k_points.nk1, parameters.k_points.nk2, 1],
37	)
38
39	if isinstance(parameters.control.crit_temp, CritTemp):	×
40	delta_vs_temp, critical_temperatures, fit_fig = routines.search_crit_temp(	×
41	hamiltonian=hamiltonian,
42	kgrid=k_grid_obj,
43	hubbard_int_orbital_basis=np.array(parameters.control.crit_temp.hubbard_int_orbital_basis),
44	epsilon=parameters.control.crit_temp.conv_treshold,
45	max_iter=parameters.control.crit_temp.max_iter,
46	n_temp_points=20,
47	)
48	logger.info("Search for T_C completed successfully.")	×
49	logger.info("Obtained T_Cs: %s", critical_temperatures)	×
50
51	fit_fig.savefig(	×
52	result_path / f"{parameters.control.crit_temp.prefix}_critical_temperatures_fit.pdf",
53	bbox_inches="tight",
54	)
55
56	result_file_crit_temp = (	×
57	result_path / f"{parameters.control.crit_temp.prefix}_critical_temperatures.hdf5"
58	)
NEW 59	if result_file_crit_temp.exists():	×
NEW 60	result_file_crit_temp.exists()	×
61	delta_vs_temp.to_hdf(result_file_crit_temp, key="delta_vs_temp")	×
62	with h5py.File(result_file_crit_temp, mode="a") as file:	×
63	for orbital, crit_temp_orbital in enumerate(critical_temperatures):	×
64	file.attrs[f"T_C_{orbital}"] = crit_temp_orbital	×
65
66	logger.info("Results saved to %s", result_file_crit_temp)	×
67	else:
68	critical_temperatures = []	×
69	with h5py.File(f"{parameters.control.crit_temp}", mode="r") as file:	×
70	for key, critical_temperature in file.attrs.items():	×
71	if key.startswith("T_C"):	×
72	critical_temperatures.append(critical_temperature)	×
73	logger.info("Read critical temperatures from file.")	×
74	logger.info("Obtained T_Cs: %s", critical_temperatures)	×
75
76	delta_vs_q = routines.loop_over_q(	×
77	hamiltonian=hamiltonian,
78	kgrid=k_grid_obj,
79	hubbard_int_orbital_basis=np.array(parameters.control.hubbard_int_orbital_basis),
80	epsilon=parameters.control.conv_treshold,
81	max_iter=parameters.control.max_iter,
82	n_q_points=parameters.control.n_q_points,
83	crit_temps=np.array(critical_temperatures),
84	)
85
86	result_file_q = result_path / f"{parameters.control.prefix}_q.hdf5"	×
87
NEW 88	if result_file_q.exists():	×
NEW 89	result_file_q.unlink()	×
90	for key, df in delta_vs_q.items():	×
91	df.to_hdf(result_file_q, key=f"temp_{float(key):.6f}")	×
92	with h5py.File(result_file_q, "a") as f:	×
93	grp = f[f"temp_{float(key):.6f}"]	×
94	grp.attrs["crit_temp"] = critical_temperatures	×
95	grp.attrs["temp"] = float(key)	×

Ruberhauptmann / quant-met / 16553145710

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