16489119678

Committed 24 Jul 2025 06:05AM UTC coverage: 34.768% (-1.8%) from 36.605%

Build # 16489119678

Build Type

Pull #125

github

Committed by

web-flow

Commit Message

Merge b4aa50e23 into b5a0f599e

Pull Request Pull Request #125: Start q loop

Run Details

3 of 67 branches covered (4.48%)

Branch coverage included in aggregate %.

92 of 226 new or added lines in 11 files covered. (40.71%)

23 existing lines in 2 files now uncovered.

207 of 537 relevant lines covered (38.55%)

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20.0

/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.hubbard_int_orbital_basis),
            epsilon=parameters.control.conv_treshold,
            max_iter=parameters.control.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.prefix}_critical_temperatures_fit.pdf",
            bbox_inches="tight",
        )

        result_file_crit_temp = (
            result_path / f"{parameters.control.prefix}_critical_temperatures.hdf5"
        )
        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"
    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	"""
NEW 26	if not isinstance(parameters.control, QLoop):	×
NEW 27	err_msg = "Wrong parameters for q-loop."	×
NEW 28	raise TypeError(err_msg)	×
29
NEW 30	result_path = Path(parameters.control.outdir)	×
NEW 31	result_path.mkdir(exist_ok=True, parents=True)	×
32
NEW 33	hamiltonian = sisl.get_sile(parameters.control.hamiltonian_file).read_hamiltonian()	×
NEW 34	k_grid_obj = sisl.MonkhorstPack(	×
35	hamiltonian.geometry,
36	[parameters.k_points.nk1, parameters.k_points.nk2, 1],
37	)
38
NEW 39	if isinstance(parameters.control.crit_temp, CritTemp):	×
NEW 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.hubbard_int_orbital_basis),
44	epsilon=parameters.control.conv_treshold,
45	max_iter=parameters.control.max_iter,
46	n_temp_points=20,
47	)
NEW 48	logger.info("Search for T_C completed successfully.")	×
NEW 49	logger.info("Obtained T_Cs: %s", critical_temperatures)	×
50
NEW 51	fit_fig.savefig(	×
52	result_path / f"{parameters.control.prefix}_critical_temperatures_fit.pdf",
53	bbox_inches="tight",
54	)
55
NEW 56	result_file_crit_temp = (	×
57	result_path / f"{parameters.control.prefix}_critical_temperatures.hdf5"
58	)
NEW 59	delta_vs_temp.to_hdf(result_file_crit_temp, key="delta_vs_temp")	×
NEW 60	with h5py.File(result_file_crit_temp, mode="a") as file:	×
NEW 61	for orbital, crit_temp_orbital in enumerate(critical_temperatures):	×
NEW 62	file.attrs[f"T_C_{orbital}"] = crit_temp_orbital	×
63
NEW 64	logger.info("Results saved to %s", result_file_crit_temp)	×
65	else:
NEW 66	critical_temperatures = []	×
NEW 67	with h5py.File(f"{parameters.control.crit_temp}", mode="r") as file:	×
NEW 68	for key, critical_temperature in file.attrs.items():	×
NEW 69	if key.startswith("T_C"):	×
NEW 70	critical_temperatures.append(critical_temperature)	×
NEW 71	logger.info("Read critical temperatures from file.")	×
NEW 72	logger.info("Obtained T_Cs: %s", critical_temperatures)	×
73
NEW 74	delta_vs_q = routines.loop_over_q(	×
75	hamiltonian=hamiltonian,
76	kgrid=k_grid_obj,
77	hubbard_int_orbital_basis=np.array(parameters.control.hubbard_int_orbital_basis),
78	epsilon=parameters.control.conv_treshold,
79	max_iter=parameters.control.max_iter,
80	n_q_points=parameters.control.n_q_points,
81	crit_temps=np.array(critical_temperatures),
82	)
83
NEW 84	result_file_q = result_path / f"{parameters.control.prefix}_q.hdf5"	×
NEW 85	result_file_q.unlink()	×
NEW 86	for key, df in delta_vs_q.items():	×
NEW 87	df.to_hdf(result_file_q, key=f"temp_{float(key):.6f}")	×
NEW 88	with h5py.File(result_file_q, "a") as f:	×
NEW 89	grp = f[f"temp_{float(key):.6f}"]	×
NEW 90	grp.attrs["crit_temp"] = critical_temperatures	×
NEW 91	grp.attrs["temp"] = float(key)	×

Ruberhauptmann / quant-met / 16489119678

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