16463103768

Committed 23 Jul 2025 06:19AM UTC coverage: 34.05% (-2.6%) from 36.605%

Build # 16463103768

Build Type

Pull #125

github

Committed by

web-flow

Commit Message

Merge dab4d24cf into b5a0f599e

Pull Request Pull Request #125: Start q loop

Run Details

3 of 70 branches covered (4.29%)

Branch coverage included in aggregate %.

85 of 221 new or added lines in 8 files covered. (38.46%)

40 existing lines in 4 files now uncovered.

203 of 535 relevant lines covered (37.94%)

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33.33

/src/quant_met/cli/q_analysis.py

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

import logging
from pathlib import Path

import h5py
import pandas as pd
import sisl

from quant_met import routines
from quant_met.parameters import Parameters
from quant_met.parameters.control import QAnalysis

logger = logging.getLogger(__name__)


def q_analysis(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, QAnalysis):
        raise ValueError("Wrong parameters for q-loop.")

    q_data = {}
    with h5py.File(f"{parameters.control.q_data}") as f:
        for key in f.keys():
            q_data.update({key: None})

    for key in q_data:
        q_data[key] = pd.read_hdf(f"{parameters.control.q_data}", key=key)

    hamiltonian = sisl.get_sile(parameters.control.hamiltonian_file).read_hamiltonian()

    (
        lengths_vs_temp,
        gap_and_current_fig,
    ) = routines.get_lengths_vs_temp(q_data=q_data, hamiltonian=hamiltonian)

    result_file = Path(f"{parameters.control.outdir}/{parameters.control.prefix}_sc_lengths.hdf5")
    result_file.unlink()
    lengths_vs_temp.to_hdf(result_file, key="lengths_vs_temp")
    gap_and_current_fig.savefig(
        f"{parameters.control.outdir}/{parameters.control.prefix}_gap_and_current_vs_q.pdf"
    )

    zero_temp_lengths, length_vs_temp_fig = routines.get_zero_temperature_values(
        hamiltonian=hamiltonian, lengths_vs_temp=lengths_vs_temp
    )
    zero_temp_lengths.to_hdf(result_file, key="zero_temp_lengths")
    length_vs_temp_fig.savefig(
        f"{parameters.control.outdir}/{parameters.control.prefix}_lengths_vs_temperature.pdf"
    )

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 pandas as pd	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 QAnalysis	3✔
13
14	logger = logging.getLogger(__name__)	3✔
15
16
17	def q_analysis(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, QAnalysis):	×
NEW 27	raise ValueError("Wrong parameters for q-loop.")	×
28
NEW 29	q_data = {}	×
NEW 30	with h5py.File(f"{parameters.control.q_data}") as f:	×
NEW 31	for key in f.keys():	×
NEW 32	q_data.update({key: None})	×
33
NEW 34	for key in q_data:	×
NEW 35	q_data[key] = pd.read_hdf(f"{parameters.control.q_data}", key=key)	×
36
NEW 37	hamiltonian = sisl.get_sile(parameters.control.hamiltonian_file).read_hamiltonian()	×
38
NEW 39	(	×
40	lengths_vs_temp,
41	gap_and_current_fig,
42	) = routines.get_lengths_vs_temp(q_data=q_data, hamiltonian=hamiltonian)
43
NEW 44	result_file = Path(f"{parameters.control.outdir}/{parameters.control.prefix}_sc_lengths.hdf5")	×
NEW 45	result_file.unlink()	×
NEW 46	lengths_vs_temp.to_hdf(result_file, key="lengths_vs_temp")	×
NEW 47	gap_and_current_fig.savefig(	×
48	f"{parameters.control.outdir}/{parameters.control.prefix}_gap_and_current_vs_q.pdf"
49	)
50
NEW 51	zero_temp_lengths, length_vs_temp_fig = routines.get_zero_temperature_values(	×
52	hamiltonian=hamiltonian, lengths_vs_temp=lengths_vs_temp
53	)
NEW 54	zero_temp_lengths.to_hdf(result_file, key="zero_temp_lengths")	×
NEW 55	length_vs_temp_fig.savefig(	×
56	f"{parameters.control.outdir}/{parameters.control.prefix}_lengths_vs_temperature.pdf"
57	)

Ruberhauptmann / quant-met / 16463103768

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