"""
Corresponding-Colour Datasets - Luo and Rhodes (1999)
=====================================================
Define the objects implementing support for *Luo and Rhodes (1999)*
*Corresponding-Colour Datasets* dataset loading:
- :class:`colour_datasets.loaders.DatasetLoader_Luo1999`
- :func:`colour_datasets.loaders.build_Luo1999`
References
----------
- :cite:`Breneman1987b` : Breneman, E. J. (1987). Corresponding
chromaticities for different states of adaptation to complex visual fields.
Journal of the Optical Society of America A, 4(6), 1115.
doi:10.1364/JOSAA.4.001115
- :cite:`Luo1999` : Luo, M. R., & Rhodes, P. A. (1999). Corresponding-colour
datasets. Color Research & Application, 24(4), 295-296.
doi:10.1002/(SICI)1520-6378(199908)24:4<295::AID-COL10>3.0.CO;2-K
- :cite:`McCann1976` : McCann, J. J., McKee, S. P., & Taylor, T. H. (1976).
Quantitative studies in retinex theory a comparison between theoretical
predictions and observer responses to the "color mondrian" experiments.
Vision Research, 16(5), 445-IN3. doi:10.1016/0042-6989(76)90020-1
"""
from __future__ import annotations
import codecs
import os
import typing
from dataclasses import dataclass
import numpy as np
if typing.TYPE_CHECKING:
from colour.hints import Dict, NDArrayFloat, Tuple
from colour.hints import cast
from colour.utilities import as_float_array
from colour_datasets.loaders import AbstractDatasetLoader
from colour_datasets.records import datasets
__author__ = "Colour Developers"
__copyright__ = "Copyright 2019 Colour Developers"
__license__ = "BSD-3-Clause - https://opensource.org/licenses/BSD-3-Clause"
__maintainer__ = "Colour Developers"
__email__ = "colour-developers@colour-science.org"
__status__ = "Production"
__all__ = [
"CorrespondingColourDataset_Luo1999",
"DatasetLoader_Luo1999",
"build_Luo1999",
]
@dataclass(frozen=True)
class CorrespondingColourDataset_Luo1999:
"""
Define a *Luo and Rhodes (1999)* *Corresponding-Colour Datasets* dataset.
Parameters
----------
name
*Luo and Rhodes (1999)* *Corresponding-Colour Datasets* dataset name.
XYZ_r
*CIE XYZ* tristimulus values of the reference illuminant.
XYZ_t
*CIE XYZ* tristimulus values of the test illuminant.
XYZ_cr
Corresponding *CIE XYZ* tristimulus values under the reference
illuminant.
XYZ_ct
Corresponding *CIE XYZ* tristimulus values under the test illuminant.
Y_r
Reference white luminance :math:`Y_r` in :math:`cd/m^2`.
Y_t
Test white luminance :math:`Y_t` in :math:`cd/m^2`.
B_r
Luminance factor :math:`B_r` of reference achromatic background as
percentage.
B_t
Luminance factor :math:`B_t` of test achromatic background as
percentage.
metadata
Dataset metadata.
"""
name: str
XYZ_r: NDArrayFloat
XYZ_t: NDArrayFloat
XYZ_cr: NDArrayFloat
XYZ_ct: NDArrayFloat
Y_r: float
Y_t: float
B_r: float
B_t: float
metadata: Dict
[docs]
class DatasetLoader_Luo1999(AbstractDatasetLoader):
"""
Define the *Luo and Rhodes (1999)* *Corresponding-Colour Datasets* dataset
loader.
Attributes
----------
- :attr:`colour_datasets.loaders.DatasetLoader_Luo1999.ID`
Methods
-------
- :meth:`colour_datasets.loaders.DatasetLoader_Luo1999.__init__`
- :meth:`colour_datasets.loaders.DatasetLoader_Luo1999.load`
References
----------
:cite:`Breneman1987b`, :cite:`Luo1999`, :cite:`McCann1976`
"""
ID: str = "3270903"
"""Dataset record id, i.e., the *Zenodo* record number."""
def __init__(self) -> None:
super().__init__(datasets()[DatasetLoader_Luo1999.ID])
[docs]
def load(self) -> Dict[str, CorrespondingColourDataset_Luo1999]:
"""
Sync, parse, convert and return the *Luo and Rhodes (1999)*
*Corresponding-Colour Datasets* dataset content.
Returns
-------
:class:`dict`
*Luo and Rhodes (1999)* *Corresponding-Colour Datasets* dataset
content.
Notes
-----
- *Brene.p6.dat* has only 11 samples while *Breneman (1987)* has 12
results.
- The illuminance in :math:`Lux` for *Breneman (1987)* datasets given
by *Luo and Rhodes (1999)* is in domain [50, 3870] while
*Breneman (1987)* reports luminance in :math:`cd/m^2` in domain
[15, 11100], i.e., [47, 34871.69] in :math:`Lux`. The metadata has
been corrected accordingly.
- The illuminance values, i.e., 14 and 40, for
*McCann, McKee and Taylor (1976)* datasets given by
*Luo and Rhodes (1999)* were not found in :cite:`McCann1976`. The
values in use are the average of both.
Examples
--------
>>> from colour_datasets.utilities import suppress_stdout
>>> dataset = DatasetLoader_Luo1999()
>>> with suppress_stdout():
... dataset.load()
>>> len(dataset.content.keys())
37
"""
super().sync()
metadata_headers = (
"No. of Phases",
"No. of Samples",
"Illuminant Test",
"Illuminant Ref.",
"Illuminance (lux)",
"Background (Y%)",
"Sample Size",
"Medium",
"Experimental Method",
)
corresponding_colour_datasets: Dict[str, Tuple] = {
"CSAJ-C": (
("CSAJ.da.dat",),
(
1,
87,
"D65",
"A",
np.tile(1000, [1, 2]),
np.tile(20, [1, 2]),
"S",
"Refl.",
"Haploscopic",
),
),
"CSAJ-Hunt": (
(
"CSAJ.10.dat",
"CSAJ.50.dat",
"CSAJ.1000.dat",
"CSAJ.3000.dat",
),
(
4,
20,
"D65",
"D65",
np.reshape(np.repeat([10, 50, 1000, 3000], 2, -1), (-1, 2)),
np.tile(20, [4, 2]),
"S",
"Refl.",
"Haploscopic",
),
),
"CSAJ-Stevens": (
(
"Steve.10.dat",
"Steve.50.dat",
"Steve.1000.dat",
"Steve.3000.dat",
),
(
4,
19,
"D65",
"D65",
np.reshape(np.repeat([10, 50, 1000, 3000], 2, -1), (-1, 2)),
np.tile(20, [4, 2]),
"S",
"Refl.",
"Haploscopic",
),
),
"Helson": (
("helson.ca.dat",),
(
1,
59,
"D65",
"A",
np.tile(1000, [1, 2]),
np.tile(20, [1, 2]),
"S",
"Refl.",
"Memory",
),
),
"Lam & Rigg": (
("lam.da.dat",),
(
1,
58,
"D65",
"A",
np.tile(1000, [1, 2]),
np.tile(20, [1, 2]),
"L",
"Refl.",
"Memory",
),
),
"Lutchi (A)": (
("lutchi.da.dat",),
(
1,
43,
"D65",
"A",
np.tile(1000, [1, 2]),
np.tile(20, [1, 2]),
"S",
"Refl.",
"Magnitude",
),
),
"Lutchi (D50)": (
("lutchi.dd.dat",),
(
1,
44,
"D65",
"D50",
np.tile(1000, [1, 2]),
np.tile(20, [1, 2]),
"S",
"Refl.",
"Magnitude",
),
),
"Lutchi (WF)": (
("lutchi.dw.dat",),
(
1,
41,
"D65",
"WF",
np.tile(1000, [1, 2]),
np.tile(20, [1, 2]),
"S",
"Refl.",
"Magnitude",
),
),
"Kuo & Luo (A)": (
("Kuo.da.dat",),
(
1,
40,
"D65",
"A",
np.tile(1000, [1, 2]),
np.tile(20, [1, 2]),
"L",
"Refl.",
"Magnitude",
),
),
"Kuo & Luo (TL84)": (
("Kuo.dt.dat",),
(
1,
41,
"D65",
"TL84",
np.tile(1000, [1, 2]),
np.tile(20, [1, 2]),
"S",
"Refl.",
"Magnitude",
),
),
"Breneman-C": (
(
"Brene.p1.dat",
"Brene.p2.dat",
"Brene.p3.dat",
"Brene.p4.dat",
"Brene.p6.dat",
"Brene.p8.dat",
"Brene.p9.dat",
"Brene.p11.dat",
"Brene.p12.dat",
),
(
9,
107,
"D65, 55",
"A, P, G",
np.reshape(
np.repeat(
[
1500,
1500,
75,
75,
11100,
350,
15,
1560,
75,
],
2,
-1,
),
(-1, 2),
),
np.tile(30, [9, 2]),
"S",
"Trans.",
"Magnitude",
),
),
"Breneman-L": (
(
"Brene.p5.dat",
"Brene.p7.dat",
"Brene.p10.dat",
),
(
3,
36,
"D55",
"D55",
np.array([[130, 2120], [850, 11100], [15, 270]]),
np.tile(30, [3, 2]),
"S",
"Trans.",
"Haploscopic",
),
),
"Braun & Fairchild": (
(
"RIT.1.dat",
"RIT.2.dat",
"RIT.3.dat",
"RIT.4.dat",
),
(
4,
66,
"D65",
"D30, 65, 95",
np.tile(129, [4, 2]),
np.tile(20, [4, 2]),
"S",
"Mon., Refl.",
"Matching",
),
),
"McCann": (
(
"mcan.b.dat",
"mcan.g.dat",
"mcan.grey.dat",
"mcan.r.dat",
"mcan.y.dat",
),
(
5,
85,
"D65",
"R, Y, G, B",
np.tile((14 + 40) / 2, [5, 2]),
np.tile(30, [5, 2]),
"S",
"Refl.",
"Haploscopic",
),
),
}
self._content = {}
for key, (
filenames,
metadata,
) in corresponding_colour_datasets.items():
for i, filename in enumerate(filenames):
path = os.path.join(self.record.repository, "dataset", filename)
XYZ_r, XYZ_t = [], []
XYZ_cr, XYZ_ct = [], []
with codecs.open(path, encoding="utf-8") as dat_file:
lines = filter(
None, (line.strip() for line in dat_file.readlines())
)
for j, line in enumerate(lines):
values = line.split()
if j == 0:
XYZ_r = list(map(float, values[:3]))
XYZ_t = list(map(float, values[3:]))
elif len(values) == 1:
continue
else:
XYZ_cr.append(list(map(float, values[:3])))
XYZ_ct.append(list(map(float, values[3:])))
name = f"{key} - {filename.split('.')[1]}"
dataset_metadata = dict(zip(metadata_headers, metadata, strict=False))
Y_r = dataset_metadata["Illuminance (lux)"][i][0]
Y_t = dataset_metadata["Illuminance (lux)"][i][1]
B_r = dataset_metadata["Background (Y%)"][i][0]
B_t = dataset_metadata["Background (Y%)"][i][1]
dataset_metadata["Illuminance (lux)"] = dataset_metadata[
"Illuminance (lux)"
][i]
dataset_metadata["Background (Y%)"] = dataset_metadata[
"Background (Y%)"
][i]
self._content[name] = CorrespondingColourDataset_Luo1999(
name,
as_float_array(XYZ_r) / 100,
as_float_array(XYZ_t) / 100,
as_float_array(XYZ_cr) / 100,
as_float_array(XYZ_ct) / 100,
cast(float, Y_r) * np.pi,
cast(float, Y_t) * np.pi,
B_r,
B_t,
dataset_metadata,
)
return self._content
_DATASET_LOADER_LUO1999: DatasetLoader_Luo1999 | None = None
"""
Singleton instance of the *Luo and Rhodes (1999)*
*Corresponding-Colour Datasets* dataset loader.
"""
[docs]
def build_Luo1999(load: bool = True) -> DatasetLoader_Luo1999:
"""
Singleton factory that the builds *Luo and Rhodes (1999)*
*Corresponding-Colour Datasets* dataset loader.
Parameters
----------
load
Whether to load the dataset upon instantiation.
Returns
-------
:class:`colour_datasets.loaders.DatasetLoader_Luo1999`
Singleton instance of the *Luo and Rhodes (1999)*
*Corresponding-Colour Datasets* dataset loader.
References
----------
:cite:`Breneman1987b`, :cite:`Luo1999`, :cite:`McCann1976`
"""
global _DATASET_LOADER_LUO1999 # noqa: PLW0603
if _DATASET_LOADER_LUO1999 is None:
_DATASET_LOADER_LUO1999 = DatasetLoader_Luo1999()
if load:
_DATASET_LOADER_LUO1999.load()
return _DATASET_LOADER_LUO1999
