14759532904

Committed 30 Apr 2025 04:31PM UTC coverage: 35.932% (-64.1%) from 100.0%

Build # 14759532904

Build Type

Pull #121

github

Committed by

web-flow

Commit Message

Merge 885831614 into df44f68e5

Pull Request Pull Request #121: Start implementing sisl

Run Details

4 of 44 branches covered (9.09%)

Branch coverage included in aggregate %.

61 of 166 new or added lines in 12 files covered. (36.75%)

31 existing lines in 3 files now uncovered.

102 of 251 relevant lines covered (40.64%)

1.22 hits per line

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0.0

/src/quant_met/utils.py

"""
Utility functions (:mod:`quant_met.utils`)
==========================================

.. currentmodule:: quant_met.utils

Functions
---------

.. autosummary::
   :toctree: generated/

    generate_uniform_grid
"""  # noqa: D205, D400

import numpy as np
import numpy.typing as npt
from numba import jit


def generate_uniform_grid(
    ncols: int,
    nrows: int,
    corner_1: npt.NDArray[np.floating],
    corner_2: npt.NDArray[np.floating],
    origin: npt.NDArray[np.floating],
) -> npt.NDArray[np.floating]:
    """
    Generate a uniform grid of points in 2D.

    Parameters
    ----------
        ncols : int
            Number of columns
        nrows : int
            Number of rows
        corner_1 : :py:class:`numpy.ndarray`
            First corner vector
        corner_2 : :py:class:`numpy.ndarray`
            Second corner vector
        origin : :py:class:`numpy.ndarray`
            Origin point

    Returns
    -------
        :py:class:`numpy.ndarray`
            Grid

    """
    if ncols <= 1 or nrows <= 1:
        msg = "Number of columns and rows must be greater than 1."
        raise ValueError(msg)
    if np.linalg.norm(corner_1) == 0 or np.linalg.norm(corner_2) == 0:
        msg = "Vectors to the corners cannot be zero."
        raise ValueError(msg)

    grid: npt.NDArray[np.floating] = np.concatenate(
        [
            np.linspace(
                origin[0] + i / (nrows - 1) * corner_2,
                origin[1] + corner_1 + i / (nrows - 1) * corner_2,
                num=ncols,
            )
            for i in range(nrows)
        ]
    )

    return grid


@jit
def fermi_dirac(energy: npt.NDArray[np.floating], beta: float) -> npt.NDArray[np.floating]:
    """Fermi dirac distribution.

    Parameters
    ----------
    energy
    beta

    Returns
    -------
    fermi_dirac

    """
    return (
        np.where(energy < 0, 1.0, 0.0)
        if np.isinf(beta)
        else np.asarray(1 / (1 + np.exp(beta * energy)))
    )

1	"""
2	Utility functions (:mod:`quant_met.utils`)
3	==========================================
4
5	.. currentmodule:: quant_met.utils
6
7	Functions
8	---------
9
10	.. autosummary::
11	:toctree: generated/
12
13	generate_uniform_grid
14	""" # noqa: D205, D400
15
UNCOV 16	import numpy as np	×
UNCOV 17	import numpy.typing as npt	×
UNCOV 18	from numba import jit	×
19
20
UNCOV 21	def generate_uniform_grid(	×
22	ncols: int,
23	nrows: int,
24	corner_1: npt.NDArray[np.floating],
25	corner_2: npt.NDArray[np.floating],
26	origin: npt.NDArray[np.floating],
27	) -> npt.NDArray[np.floating]:
28	"""
29	Generate a uniform grid of points in 2D.
30
31	Parameters
32	----------
33	ncols : int
34	Number of columns
35	nrows : int
36	Number of rows
37	corner_1 : :py:class:`numpy.ndarray`
38	First corner vector
39	corner_2 : :py:class:`numpy.ndarray`
40	Second corner vector
41	origin : :py:class:`numpy.ndarray`
42	Origin point
43
44	Returns
45	-------
46	:py:class:`numpy.ndarray`
47	Grid
48
49	"""
UNCOV 50	if ncols <= 1 or nrows <= 1:	×
UNCOV 51	msg = "Number of columns and rows must be greater than 1."	×
UNCOV 52	raise ValueError(msg)	×
UNCOV 53	if np.linalg.norm(corner_1) == 0 or np.linalg.norm(corner_2) == 0:	×
UNCOV 54	msg = "Vectors to the corners cannot be zero."	×
UNCOV 55	raise ValueError(msg)	×
56
UNCOV 57	grid: npt.NDArray[np.floating] = np.concatenate(	×
58	[
59	np.linspace(
60	origin[0] + i / (nrows - 1) * corner_2,
61	origin[1] + corner_1 + i / (nrows - 1) * corner_2,
62	num=ncols,
63	)
64	for i in range(nrows)
65	]
66	)
67
UNCOV 68	return grid	×
69
70
UNCOV 71	@jit	×
UNCOV 72	def fermi_dirac(energy: npt.NDArray[np.floating], beta: float) -> npt.NDArray[np.floating]:	×
73	"""Fermi dirac distribution.
74
75	Parameters
76	----------
77	energy
78	beta
79
80	Returns
81	-------
82	fermi_dirac
83
84	"""
UNCOV 85	return (	×
86	np.where(energy < 0, 1.0, 0.0)
87	if np.isinf(beta)
88	else np.asarray(1 / (1 + np.exp(beta * energy)))
89	)

Ruberhauptmann / quant-met / 14759532904

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