Source code for colour.plotting.common

"""
Common Plotting
===============

Defines the common plotting objects:

-   :func:`colour.plotting.colour_style`
-   :func:`colour.plotting.override_style`
-   :func:`colour.plotting.colour_cycle`
-   :func:`colour.plotting.artist`
-   :func:`colour.plotting.camera`
-   :func:`colour.plotting.decorate`
-   :func:`colour.plotting.boundaries`
-   :func:`colour.plotting.display`
-   :func:`colour.plotting.render`
-   :func:`colour.plotting.label_rectangles`
-   :func:`colour.plotting.uniform_axes3d`
-   :func:`colour.plotting.plot_single_colour_swatch`
-   :func:`colour.plotting.plot_multi_colour_swatches`
-   :func:`colour.plotting.plot_single_function`
-   :func:`colour.plotting.plot_multi_functions`
-   :func:`colour.plotting.plot_image`
"""

from __future__ import annotations

import functools
import itertools
import matplotlib
import matplotlib.cm
import matplotlib.patches as Patch
import matplotlib.pyplot as plt
import matplotlib.ticker
import numpy as np
import re
from dataclasses import dataclass, field
from functools import partial
from matplotlib.colors import LinearSegmentedColormap

from colour.characterisation import CCS_COLOURCHECKERS, ColourChecker
from colour.colorimetry import (
    MultiSpectralDistributions,
    MSDS_CMFS,
    SDS_ILLUMINANTS,
    SDS_LIGHT_SOURCES,
    SpectralDistribution,
)
from colour.hints import (
    Any,
    ArrayLike,
    Boolean,
    Callable,
    Dict,
    Floating,
    Integer,
    List,
    Literal,
    Mapping,
    NDArray,
    Optional,
    RegexFlag,
    Sequence,
    Tuple,
    TypedDict,
    Union,
    cast,
)
from colour.models import RGB_COLOURSPACES, RGB_Colourspace, XYZ_to_RGB
from colour.utilities import (
    CanonicalMapping,
    Structure,
    as_float_array,
    attest,
    first_item,
    is_sibling,
    is_string,
    filter_mapping,
    optional,
    runtime_warning,
    validate_method,
)

__author__ = "Colour Developers"
__copyright__ = "Copyright 2013 Colour Developers"
__license__ = "New BSD License - https://opensource.org/licenses/BSD-3-Clause"
__maintainer__ = "Colour Developers"
__email__ = "colour-developers@colour-science.org"
__status__ = "Production"

__all__ = [
    "CONSTANTS_COLOUR_STYLE",
    "CONSTANTS_ARROW_STYLE",
    "colour_style",
    "override_style",
    "XYZ_to_plotting_colourspace",
    "ColourSwatch",
    "colour_cycle",
    "KwargsArtist",
    "artist",
    "KwargsCamera",
    "camera",
    "KwargsRender",
    "render",
    "label_rectangles",
    "uniform_axes3d",
    "filter_passthrough",
    "filter_RGB_colourspaces",
    "filter_cmfs",
    "filter_illuminants",
    "filter_colour_checkers",
    "update_settings_collection",
    "plot_single_colour_swatch",
    "plot_multi_colour_swatches",
    "plot_single_function",
    "plot_multi_functions",
    "plot_image",
]

CONSTANTS_COLOUR_STYLE: Structure = Structure(
    **{
        "colour": Structure(
            **{
                "darkest": "#111111",
                "darker": "#222222",
                "dark": "#333333",
                "dim": "#505050",
                "average": "#808080",
                "light": "#D5D5D5",
                "bright": "#EEEEEE",
                "brighter": "#F0F0F0",
                "brightest": "#F5F5F5",
                "cycle": (
                    "#F44336",
                    "#9C27B0",
                    "#3F51B5",
                    "#03A9F4",
                    "#009688",
                    "#8BC34A",
                    "#FFEB3B",
                    "#FF9800",
                    "#795548",
                    "#607D8B",
                ),
                "map": LinearSegmentedColormap.from_list(
                    "colour",
                    (
                        "#F44336",
                        "#9C27B0",
                        "#3F51B5",
                        "#03A9F4",
                        "#009688",
                        "#8BC34A",
                        "#FFEB3B",
                        "#FF9800",
                        "#795548",
                        "#607D8B",
                    ),
                ),
                "colourspace": RGB_COLOURSPACES["sRGB"],
            }
        ),
        "opacity": Structure(**{"high": 0.75, "medium": 0.5, "low": 0.25}),
        "geometry": Structure(**{"long": 5, "medium": 2.5, "short": 1}),
        "hatch": Structure(
            **{
                "patterns": (
                    "\\\\",
                    "o",
                    "x",
                    ".",
                    "*",
                    "//",
                )
            }
        ),
        "zorder": Structure(
            {
                "background_polygon": -140,
                "background_scatter": -130,
                "background_line": -120,
                "background_annotation": -110,
                "background_label": -100,
                "midground_polygon": -90,
                "midground_scatter": -80,
                "midground_line": -70,
                "midground_annotation": -60,
                "midground_label": -50,
                "foreground_polygon": -40,
                "foreground_scatter": -30,
                "foreground_line": -20,
                "foreground_annotation": -10,
                "foreground_label": 0,
            }
        ),
    }
)
"""Various defaults settings used across the plotting sub-package."""

CONSTANTS_ARROW_STYLE: Structure = Structure(
    **{
        "color": CONSTANTS_COLOUR_STYLE.colour.dark,
        "headwidth": CONSTANTS_COLOUR_STYLE.geometry.short * 4,
        "headlength": CONSTANTS_COLOUR_STYLE.geometry.long,
        "width": CONSTANTS_COLOUR_STYLE.geometry.short * 0.5,
        "shrink": CONSTANTS_COLOUR_STYLE.geometry.short * 0.1,
        "connectionstyle": "arc3,rad=-0.2",
    }
)
"""Annotation arrow settings used across the plotting sub-package."""


[docs]def colour_style(use_style: Boolean = True) -> Dict: """ Return *Colour* plotting style. Parameters ---------- use_style Whether to use the style and load it into *Matplotlib*. Returns ------- :class:`dict` *Colour* style. """ constants = CONSTANTS_COLOUR_STYLE style = { # Figure Size Settings "figure.figsize": (12.80, 7.20), "figure.dpi": 100, "savefig.dpi": 100, "savefig.bbox": "standard", # Font Settings # 'font.size': 12, "axes.titlesize": "x-large", "axes.labelsize": "larger", "legend.fontsize": "small", "xtick.labelsize": "medium", "ytick.labelsize": "medium", # Text Settings "text.color": constants.colour.darkest, # Tick Settings "xtick.top": False, "xtick.bottom": True, "ytick.right": False, "ytick.left": True, "xtick.minor.visible": True, "ytick.minor.visible": True, "xtick.direction": "out", "ytick.direction": "out", "xtick.major.size": constants.geometry.long * 1.25, "xtick.minor.size": constants.geometry.long * 0.75, "ytick.major.size": constants.geometry.long * 1.25, "ytick.minor.size": constants.geometry.long * 0.75, "xtick.major.width": constants.geometry.short, "xtick.minor.width": constants.geometry.short, "ytick.major.width": constants.geometry.short, "ytick.minor.width": constants.geometry.short, # Spine Settings "axes.linewidth": constants.geometry.short, "axes.edgecolor": constants.colour.dark, # Title Settings "axes.titlepad": plt.rcParams["font.size"] * 0.75, # Axes Settings "axes.facecolor": constants.colour.brightest, "axes.grid": True, "axes.grid.which": "major", "axes.grid.axis": "both", # Grid Settings "axes.axisbelow": True, "grid.linewidth": constants.geometry.short * 0.5, "grid.linestyle": "--", "grid.color": constants.colour.light, # Legend "legend.frameon": True, "legend.framealpha": constants.opacity.high, "legend.fancybox": False, "legend.facecolor": constants.colour.brighter, "legend.borderpad": constants.geometry.short * 0.5, # Lines "lines.linewidth": constants.geometry.short, "lines.markersize": constants.geometry.short * 3, "lines.markeredgewidth": constants.geometry.short * 0.75, # Cycle "axes.prop_cycle": matplotlib.cycler(color=constants.colour.cycle), } if use_style: plt.rcParams.update(style) return style
def override_style(**kwargs: Any) -> Callable: """ Decorate a function to override *Matplotlib* style. Other Parameters ---------------- kwargs Keywords arguments. Returns ------- Callable Examples -------- >>> @override_style(**{'text.color': 'red'}) ... def f(): ... plt.text(0.5, 0.5, 'This is a text!') ... plt.show() >>> f() # doctest: +SKIP """ keywords = dict(kwargs) def wrapper(function: Callable) -> Callable: """Wrap given function wrapper.""" @functools.wraps(function) def wrapped(*args: Any, **kwargs: Any) -> Any: """Wrap given function.""" keywords.update(kwargs) style_overrides = { key: value for key, value in keywords.items() if key in plt.rcParams.keys() } with plt.style.context(style_overrides): return function(*args, **kwargs) return wrapped return wrapper def XYZ_to_plotting_colourspace( XYZ: ArrayLike, illuminant: ArrayLike = RGB_COLOURSPACES["sRGB"].whitepoint, chromatic_adaptation_transform: Optional[ Union[ Literal[ "Bianco 2010", "Bianco PC 2010", "Bradford", "CAT02 Brill 2008", "CAT02", "CAT16", "CMCCAT2000", "CMCCAT97", "Fairchild", "Sharp", "Von Kries", "XYZ Scaling", ], str, ] ] = "CAT02", apply_cctf_encoding: Boolean = True, ) -> NDArray: """ Convert from *CIE XYZ* tristimulus values to the default plotting colourspace. Parameters ---------- XYZ *CIE XYZ* tristimulus values. illuminant Source illuminant chromaticity coordinates. chromatic_adaptation_transform *Chromatic adaptation* transform. apply_cctf_encoding Apply the default plotting colourspace encoding colour component transfer function / opto-electronic transfer function. Returns ------- :class:`numpy.ndarray` Default plotting colourspace colour array. Examples -------- >>> import numpy as np >>> XYZ = np.array([0.20654008, 0.12197225, 0.05136952]) >>> XYZ_to_plotting_colourspace(XYZ) # doctest: +ELLIPSIS array([ 0.7057393..., 0.1924826..., 0.2235416...]) """ return XYZ_to_RGB( XYZ, illuminant, CONSTANTS_COLOUR_STYLE.colour.colourspace.whitepoint, CONSTANTS_COLOUR_STYLE.colour.colourspace.matrix_XYZ_to_RGB, chromatic_adaptation_transform, CONSTANTS_COLOUR_STYLE.colour.colourspace.cctf_encoding if apply_cctf_encoding else None, ) @dataclass class ColourSwatch: """ Define a data structure for a colour swatch. Parameters ---------- RGB RGB Colour. name Colour name. """ RGB: ArrayLike name: Optional[str] = field(default_factory=lambda: None)
[docs]def colour_cycle(**kwargs: Any) -> itertools.cycle: """ Return a colour cycle iterator using given colour map. Other Parameters ---------------- colour_cycle_map Matplotlib colourmap name. colour_cycle_count Colours count to pick in the colourmap. Returns ------- :class:`itertools.cycle` Colour cycle iterator. """ settings = Structure( **{ "colour_cycle_map": CONSTANTS_COLOUR_STYLE.colour.map, "colour_cycle_count": len(CONSTANTS_COLOUR_STYLE.colour.cycle), } ) settings.update(kwargs) samples = np.linspace(0, 1, settings.colour_cycle_count) if isinstance(settings.colour_cycle_map, LinearSegmentedColormap): cycle = settings.colour_cycle_map(samples) else: cycle = getattr(plt.cm, settings.colour_cycle_map)(samples) return itertools.cycle(cycle)
[docs]class KwargsArtist(TypedDict): """ Define the keyword argument types for the :func:`colour.plotting.artist` definition. Parameters ---------- axes Axes that will be passed through without creating a new figure. uniform Whether to create the figure with an equal aspect ratio. """ axes: plt.Axes uniform: Boolean
[docs]def artist(**kwargs: Union[KwargsArtist, Any]) -> Tuple[plt.Figure, plt.Axes]: """ Return the current figure and its axes or creates a new one. Other Parameters ---------------- kwargs {:func:`colour.plotting.common.KwargsArtist`}, See the documentation of the previously listed class. Returns ------- :class:`tuple` Current figure and axes. """ width, height = plt.rcParams["figure.figsize"] figure_size = (width, width) if kwargs.get("uniform") else (width, height) axes = kwargs.get("axes") if axes is None: figure = plt.figure(figsize=figure_size) return figure, figure.gca() else: return plt.gcf(), axes
[docs]class KwargsCamera(TypedDict): """ Define the keyword argument types for the :func:`colour.plotting.camera` definition. Parameters ---------- figure Figure to apply the render elements onto. axes Axes to apply the render elements onto. azimuth Camera azimuth. elevation Camera elevation. camera_aspect Matplotlib axes aspect. Default is *equal*. """ figure: plt.Figure axes: plt.Axes azimuth: Optional[Floating] elevation: Optional[Floating] camera_aspect: Union[Literal["equal"], str]
[docs]def camera(**kwargs: Union[KwargsCamera, Any]) -> Tuple[plt.Figure, plt.Axes]: """ Set the camera settings. Other Parameters ---------------- kwargs {:func:`colour.plotting.common.KwargsCamera`}, See the documentation of the previously listed class. Returns ------- :class:`tuple` Current figure and axes. """ figure = cast(plt.Figure, kwargs.get("figure", plt.gcf())) axes = cast(plt.Axes, kwargs.get("axes", plt.gca())) settings = Structure( **{"camera_aspect": "equal", "elevation": None, "azimuth": None} ) settings.update(kwargs) if settings.camera_aspect == "equal": uniform_axes3d(axes=axes) axes.view_init(elev=settings.elevation, azim=settings.azimuth) return figure, axes
[docs]class KwargsRender(TypedDict): """ Define the keyword argument types for the :func:`colour.plotting.render` definition. Parameters ---------- figure Figure to apply the render elements onto. axes Axes to apply the render elements onto. filename Figure will be saved using given ``filename`` argument. standalone Whether to show the figure and call :func:`matplotlib.pyplot.show` definition. aspect Matplotlib axes aspect. axes_visible Whether the axes are visible. Default is *True*. bounding_box Array defining current axes limits such `bounding_box = (x min, x max, y min, y max)`. tight_layout Whether to invoke the :func:`matplotlib.pyplot.tight_layout` definition. legend Whether to display the legend. Default is *False*. legend_columns Number of columns in the legend. Default is *1*. transparent_background Whether to turn off the background patch. Default is *True*. title Figure title. wrap_title Whether to wrap the figure title. Default is *True*. x_label *X* axis label. y_label *Y* axis label. x_ticker Whether to display the *X* axis ticker. Default is *True*. y_ticker Whether to display the *Y* axis ticker. Default is *True*. """ figure: plt.Figure axes: plt.Axes filename: str standalone: Boolean aspect: Union[Literal["auto", "equal"], Floating] axes_visible: Boolean bounding_box: ArrayLike tight_layout: Boolean legend: Boolean legend_columns: Integer transparent_background: Boolean title: str wrap_title: Boolean x_label: str y_label: str x_ticker: Boolean y_ticker: Boolean
[docs]def render(**kwargs: Union[KwargsRender, Any]) -> Tuple[plt.Figure, plt.Axes]: """ Render the current figure while adjusting various settings such as the bounding box, the title or background transparency. Other Parameters ---------------- kwargs {:func:`colour.plotting.common.KwargsRender`}, See the documentation of the previously listed class. Returns ------- :class:`tuple` Current figure and axes. """ figure = cast(plt.Figure, kwargs.get("figure", plt.gcf())) axes = cast(plt.Axes, kwargs.get("axes", plt.gca())) settings = Structure( **{ "filename": None, "standalone": True, "aspect": None, "axes_visible": True, "bounding_box": None, "tight_layout": True, "legend": False, "legend_columns": 1, "transparent_background": True, "title": None, "wrap_title": True, "x_label": None, "y_label": None, "x_ticker": True, "y_ticker": True, } ) settings.update(kwargs) if settings.aspect: axes.set_aspect(settings.aspect) if not settings.axes_visible: axes.set_axis_off() if settings.bounding_box: axes.set_xlim(settings.bounding_box[0], settings.bounding_box[1]) axes.set_ylim(settings.bounding_box[2], settings.bounding_box[3]) if settings.title: axes.set_title(settings.title, wrap=settings.wrap_title) if settings.x_label: axes.set_xlabel(settings.x_label) if settings.y_label: axes.set_ylabel(settings.y_label) if not settings.x_ticker: axes.set_xticks([]) if not settings.y_ticker: axes.set_yticks([]) if settings.legend: axes.legend(ncol=settings.legend_columns) if settings.tight_layout: figure.tight_layout() if settings.transparent_background: figure.patch.set_alpha(0) if settings.standalone: if settings.filename is not None: figure.savefig(settings.filename) else: plt.show() return figure, axes
[docs]def label_rectangles( labels: Sequence[str], rectangles: Sequence[Patch], rotation: Union[Literal["horizontal", "vertical"], str] = "vertical", text_size: Floating = 10, offset: Optional[ArrayLike] = None, **kwargs: Any, ) -> Tuple[plt.Figure, plt.Axes]: """ Add labels above given rectangles. Parameters ---------- labels Labels to display. rectangles Rectangles to used to set the labels value and position. rotation Labels orientation. text_size Labels text size. offset Labels offset as percentages of the largest rectangle dimensions. Other Parameters ---------------- figure Figure to apply the render elements onto. axes Axes to apply the render elements onto. Returns ------- :class:`tuple` Current figure and axes. """ rotation = validate_method( rotation, ["horizontal", "vertical"], '"{0}" rotation is invalid, it must be one of {1}!', ) figure = kwargs.get("figure", plt.gcf()) axes = kwargs.get("axes", plt.gca()) offset = as_float_array(cast(ArrayLike, optional(offset, (0.0, 0.025)))) x_m, y_m = 0, 0 for rectangle in rectangles: x_m = max(x_m, rectangle.get_width()) y_m = max(y_m, rectangle.get_height()) for i, rectangle in enumerate(rectangles): x = rectangle.get_x() height = rectangle.get_height() width = rectangle.get_width() ha = "center" va = "bottom" axes.text( x + width / 2 + offset[0] * width, height + offset[1] * y_m, labels[i], ha=ha, va=va, rotation=rotation, fontsize=text_size, clip_on=True, zorder=CONSTANTS_COLOUR_STYLE.zorder.midground_label, ) return figure, axes
[docs]def uniform_axes3d(**kwargs: Any) -> Tuple[plt.Figure, plt.Axes]: """ Set equal aspect ratio to given 3d axes. Other Parameters ---------------- figure Figure to apply the render elements onto. axes Axes to apply the render elements onto. Returns ------- :class:`tuple` Current figure and axes. """ figure = kwargs.get("figure", plt.gcf()) axes = kwargs.get("axes", plt.gca()) try: # pragma: no cover # TODO: Reassess according to # https://github.com/matplotlib/matplotlib/issues/1077 axes.set_aspect("equal") except NotImplementedError: # pragma: no cover pass extents = np.array([getattr(axes, f"get_{axis}lim")() for axis in "xyz"]) centers = np.mean(extents, axis=1) extent = np.max(np.abs(extents[..., 1] - extents[..., 0])) for center, axis in zip(centers, "xyz"): getattr(axes, f"set_{axis}lim")( center - extent / 2, center + extent / 2 ) return figure, axes
def filter_passthrough( mapping: Mapping, filterers: Union[Any, str, Sequence[Union[Any, str]]], anchors: Boolean = True, allow_non_siblings: Boolean = True, flags: Union[Integer, RegexFlag] = re.IGNORECASE, ) -> Dict: """ Return mapping objects matching given filterers while passing through class instances whose type is one of the mapping element types. This definition allows passing custom but compatible objects to the various plotting definitions that by default expect the key from a dataset element. For example, a typical call to :func:`colour.plotting.\ plot_multi_illuminant_sds` definition with a regex pattern automatically anchored at boundaries by default is as follows: >>> import colour >>> colour.plotting.plot_multi_illuminant_sds(['A']) ... # doctest: +SKIP Here, `'A'` is by default anchored at boundaries and transformed into `'^A$'`. Note that because it is a regex pattern, special characters such as parenthesis must be escaped: `'Adobe RGB (1998)'` must be written `'Adobe RGB \\(1998\\)'` instead. With the previous example, t is also possible to pass a custom spectral distribution as follows: >>> data = { ... 500: 0.0651, ... 520: 0.0705, ... 540: 0.0772, ... 560: 0.0870, ... 580: 0.1128, ... 600: 0.1360 ... } >>> colour.plotting.plot_multi_illuminant_sds( ... ['A', colour.SpectralDistribution(data)]) ... # doctest: +SKIP Similarly, a typical call to :func:`colour.plotting.\ plot_planckian_locus_in_chromaticity_diagram_CIE1931` definition is as follows: >>> colour.plotting.plot_planckian_locus_in_chromaticity_diagram_CIE1931( ... ['A']) ... # doctest: +SKIP But it is also possible to pass a custom whitepoint as follows: >>> colour.plotting.plot_planckian_locus_in_chromaticity_diagram_CIE1931( ... ['A', {'Custom': np.array([1 / 3 + 0.05, 1 / 3 + 0.05])}]) ... # doctest: +SKIP Parameters ---------- mapping Mapping to filter. filterers Filterer or object class instance (which is passed through directly if its type is one of the mapping element types) or list of filterers. anchors Whether to use Regex line anchors, i.e. *^* and *$* are added, surrounding the filterers patterns. allow_non_siblings Whether to allow non-siblings to be also passed through. flags Regex flags. Returns ------- :class:`dict` Filtered mapping. """ if is_string(filterers): filterers = [filterers] elif not isinstance(filterers, (list, tuple)): filterers = [filterers] string_filterers: List[str] = [ cast(str, filterer) for filterer in filterers if is_string(filterer) ] object_filterers: List[Any] = [ filterer for filterer in filterers if is_sibling(filterer, mapping) ] if allow_non_siblings: non_siblings = [ filterer for filterer in filterers if filterer not in string_filterers and filterer not in object_filterers ] if non_siblings: runtime_warning( f'Non-sibling elements are passed-through: "{non_siblings}"' ) object_filterers.extend(non_siblings) filtered_mapping = filter_mapping( mapping, string_filterers, anchors, flags ) for filterer in object_filterers: # TODO: Consider using "MutableMapping" here. if isinstance(filterer, (dict, CanonicalMapping)): for key, value in filterer.items(): filtered_mapping[key] = value else: try: name = filterer.name except AttributeError: try: name = filterer.__name__ except AttributeError: name = str(id(filterer)) filtered_mapping[name] = filterer return filtered_mapping def filter_RGB_colourspaces( filterers: Union[ RGB_Colourspace, str, Sequence[Union[RGB_Colourspace, str]] ], anchors: Boolean = True, allow_non_siblings: Boolean = True, flags: Union[Integer, RegexFlag] = re.IGNORECASE, ) -> Dict[str, RGB_Colourspace]: """ Return the *RGB* colourspaces matching given filterers. Parameters ---------- filterers Filterer or :class:`colour.RGB_Colourspace` class instance (which is passed through directly if its type is one of the mapping element types) or list of filterers. ``filterers`` elements can also be of any form supported by the :func:`colour.plotting.filter_passthrough` definition. anchors Whether to use Regex line anchors, i.e. *^* and *$* are added, surrounding the filterers patterns. allow_non_siblings Whether to allow non-siblings to be also passed through. flags Regex flags. Returns ------- :class:`dict` Filtered *RGB* colourspaces. """ return filter_passthrough( RGB_COLOURSPACES, filterers, anchors, allow_non_siblings, flags ) def filter_cmfs( filterers: Union[ MultiSpectralDistributions, str, Sequence[Union[MultiSpectralDistributions, str]], ], anchors: Boolean = True, allow_non_siblings: Boolean = True, flags: Union[Integer, RegexFlag] = re.IGNORECASE, ) -> Dict[str, MultiSpectralDistributions]: """ Return the colour matching functions matching given filterers. Parameters ---------- filterers Filterer or :class:`colour.LMS_ConeFundamentals`, :class:`colour.RGB_ColourMatchingFunctions` or :class:`colour.XYZ_ColourMatchingFunctions` class instance (which is passed through directly if its type is one of the mapping element types) or list of filterers. ``filterers`` elements can also be of any form supported by the :func:`colour.plotting.filter_passthrough` definition. anchors Whether to use Regex line anchors, i.e. *^* and *$* are added, surrounding the filterers patterns. allow_non_siblings Whether to allow non-siblings to be also passed through. flags Regex flags. Returns ------- :class:`dict` Filtered colour matching functions. """ return filter_passthrough( MSDS_CMFS, filterers, anchors, allow_non_siblings, flags ) def filter_illuminants( filterers: Union[ SpectralDistribution, str, Sequence[Union[SpectralDistribution, str]] ], anchors: Boolean = True, allow_non_siblings: Boolean = True, flags: Union[Integer, RegexFlag] = re.IGNORECASE, ) -> Dict[str, SpectralDistribution]: """ Return the illuminants matching given filterers. Parameters ---------- filterers Filterer or :class:`colour.SpectralDistribution` class instance (which is passed through directly if its type is one of the mapping element types) or list of filterers. ``filterers`` elements can also be of any form supported by the :func:`colour.plotting.filter_passthrough` definition. anchors Whether to use Regex line anchors, i.e. *^* and *$* are added, surrounding the filterers patterns. allow_non_siblings Whether to allow non-siblings to be also passed through. flags Regex flags. Returns ------- :class:`dict` Filtered illuminants. """ illuminants = {} illuminants.update( filter_passthrough( SDS_ILLUMINANTS, filterers, anchors, allow_non_siblings, flags ) ) illuminants.update( filter_passthrough( SDS_LIGHT_SOURCES, filterers, anchors, allow_non_siblings, flags ) ) return illuminants def filter_colour_checkers( filterers: Union[ColourChecker, str, Sequence[Union[ColourChecker, str]]], anchors: Boolean = True, allow_non_siblings: Boolean = True, flags: Union[Integer, RegexFlag] = re.IGNORECASE, ) -> Dict[str, ColourChecker]: """ Return the colour checkers matching given filterers. Parameters ---------- filterers Filterer or :class:`colour.characterisation.ColourChecker` class instance (which is passed through directly if its type is one of the mapping element types) or list of filterers. ``filterers`` elements can also be of any form supported by the :func:`colour.plotting.filter_passthrough` definition. anchors Whether to use Regex line anchors, i.e. *^* and *$* are added, surrounding the filterers patterns. allow_non_siblings Whether to allow non-siblings to be also passed through. flags Regex flags. Returns ------- :class:`dict` Filtered colour checkers. """ return filter_passthrough( CCS_COLOURCHECKERS, filterers, anchors, allow_non_siblings, flags ) def update_settings_collection( settings_collection: Union[Dict, List[Dict]], keyword_arguments: Union[Dict, List[Dict]], expected_count: Integer, ): """ Update given settings collection, *in-place*, with given keyword arguments and expected count of settings collection elements. Parameters ---------- settings_collection Settings collection to update. keyword_arguments Keyword arguments to update the settings collection. expected_count Expected count of settings collection elements. Examples -------- >>> settings_collection = [{1: 2}, {3: 4}] >>> keyword_arguments = {5 : 6} >>> update_settings_collection(settings_collection, keyword_arguments, 2) >>> print(settings_collection) [{1: 2, 5: 6}, {3: 4, 5: 6}] >>> settings_collection = [{1: 2}, {3: 4}] >>> keyword_arguments = [{5 : 6}, {7: 8}] >>> update_settings_collection(settings_collection, keyword_arguments, 2) >>> print(settings_collection) [{1: 2, 5: 6}, {3: 4, 7: 8}] """ if not isinstance(keyword_arguments, dict): attest( len(keyword_arguments) == expected_count, "Multiple keyword arguments defined, but they do not " "match the expected count!", ) for i, settings in enumerate(settings_collection): if isinstance(keyword_arguments, dict): settings.update(keyword_arguments) else: settings.update(keyword_arguments[i])
[docs]@override_style( **{ "axes.grid": False, "xtick.bottom": False, "ytick.left": False, "xtick.labelbottom": False, "ytick.labelleft": False, } ) def plot_single_colour_swatch( colour_swatch: Union[ArrayLike, ColourSwatch], **kwargs: Any ) -> Tuple[plt.Figure, plt.Axes]: """ Plot given colour swatch. Parameters ---------- colour_swatch Colour swatch, either a regular `ArrayLike` or a :class:`colour.plotting.ColourSwatch` class instance. Other Parameters ---------------- kwargs {:func:`colour.plotting.artist`, :func:`colour.plotting.plot_multi_colour_swatches`, :func:`colour.plotting.render`}, See the documentation of the previously listed definitions. Returns ------- :class:`tuple` Current figure and axes. Examples -------- >>> RGB = ColourSwatch((0.45620519, 0.03081071, 0.04091952)) >>> plot_single_colour_swatch(RGB) # doctest: +ELLIPSIS (<Figure size ... with 1 Axes>, <...AxesSubplot...>) .. image:: ../_static/Plotting_Plot_Single_Colour_Swatch.png :align: center :alt: plot_single_colour_swatch """ return plot_multi_colour_swatches((colour_swatch,), **kwargs)
[docs]@override_style( **{ "axes.grid": False, "xtick.bottom": False, "ytick.left": False, "xtick.labelbottom": False, "ytick.labelleft": False, } ) def plot_multi_colour_swatches( colour_swatches: Sequence[Union[ArrayLike, ColourSwatch]], width: Floating = 1, height: Floating = 1, spacing: Floating = 0, columns: Optional[Integer] = None, direction: Union[Literal["+y", "-y"], str] = "+y", text_kwargs: Optional[Dict] = None, background_colour: ArrayLike = (1.0, 1.0, 1.0), compare_swatches: Optional[ Union[Literal["Diagonal", "Stacked"], str] ] = None, **kwargs: Any, ) -> Tuple[plt.Figure, plt.Axes]: """ Plot given colours swatches. Parameters ---------- colour_swatches Colour swatch sequence, either a regular `ArrayLike` or a sequence of :class:`colour.plotting.ColourSwatch` class instances. width Colour swatch width. height Colour swatch height. spacing Colour swatches spacing. columns Colour swatches columns count, defaults to the colour swatch count or half of it if comparing. direction Row stacking direction. text_kwargs Keyword arguments for the :func:`matplotlib.pyplot.text` definition. The following special keywords can also be used: - ``offset``: Sets the text offset. - ``visible``: Sets the text visibility. background_colour Background colour. compare_swatches Whether to compare the swatches, in which case the colour swatch count must be an even number with alternating reference colour swatches and test colour swatches. *Stacked* will draw the test colour swatch in the center of the reference colour swatch, *Diagonal* will draw the reference colour swatch in the upper left diagonal area and the test colour swatch in the bottom right diagonal area. Other Parameters ---------------- kwargs {:func:`colour.plotting.artist`, :func:`colour.plotting.render`}, See the documentation of the previously listed definitions. Returns ------- :class:`tuple` Current figure and axes. Examples -------- >>> RGB_1 = ColourSwatch((0.45293517, 0.31732158, 0.26414773)) >>> RGB_2 = ColourSwatch((0.77875824, 0.57726450, 0.50453169)) >>> plot_multi_colour_swatches([RGB_1, RGB_2]) # doctest: +ELLIPSIS (<Figure size ... with 1 Axes>, <...AxesSubplot...>) .. image:: ../_static/Plotting_Plot_Multi_Colour_Swatches.png :align: center :alt: plot_multi_colour_swatches """ direction = validate_method( direction, ["+y", "-y"], '"{0}" direction is invalid, it must be one of {1}!', ) if compare_swatches is not None: compare_swatches = validate_method( compare_swatches, ["Diagonal", "Stacked"], '"{0}" compare swatches method is invalid, it must be one of {1}!', ) _figure, axes = artist(**kwargs) # Handling case where `colour_swatches` is a regular *ArrayLike*. colour_swatches = list(colour_swatches) colour_swatches_converted = [] if not isinstance(first_item(colour_swatches), ColourSwatch): for i, colour_swatch in enumerate( as_float_array(cast(ArrayLike, colour_swatches)).reshape([-1, 3]) ): colour_swatches_converted.append(ColourSwatch(colour_swatch)) else: colour_swatches_converted = cast(List[ColourSwatch], colour_swatches) colour_swatches = colour_swatches_converted if compare_swatches is not None: attest( len(colour_swatches) % 2 == 0, "Cannot compare an odd number of colour swatches!", ) colour_swatches_reference = colour_swatches[0::2] colour_swatches_test = colour_swatches[1::2] else: colour_swatches_reference = colour_swatches_test = colour_swatches columns = optional(columns, len(colour_swatches_reference)) text_settings = { "offset": 0.05, "visible": True, "zorder": CONSTANTS_COLOUR_STYLE.zorder.midground_label, } if text_kwargs is not None: text_settings.update(text_kwargs) text_offset = text_settings.pop("offset") offset_X: Floating = 0 offset_Y: Floating = 0 x_min, x_max, y_min, y_max = 0, width, 0, height y = 1 if direction == "+y" else -1 for i, colour_swatch in enumerate(colour_swatches_reference): if i % columns == 0 and i != 0: offset_X = 0 offset_Y += (height + spacing) * y x_0, x_1 = offset_X, offset_X + width y_0, y_1 = offset_Y, offset_Y + height * y axes.fill( (x_0, x_1, x_1, x_0), (y_0, y_0, y_1, y_1), color=np.clip(colour_swatches_reference[i].RGB, 0, 1), zorder=CONSTANTS_COLOUR_STYLE.zorder.midground_polygon, ) if compare_swatches == "stacked": margin_X = width * 0.25 margin_Y = height * 0.25 axes.fill( ( x_0 + margin_X, x_1 - margin_X, x_1 - margin_X, x_0 + margin_X, ), ( y_0 + margin_Y * y, y_0 + margin_Y * y, y_1 - margin_Y * y, y_1 - margin_Y * y, ), color=np.clip(colour_swatches_test[i].RGB, 0, 1), zorder=CONSTANTS_COLOUR_STYLE.zorder.midground_polygon, ) else: axes.fill( (x_0, x_1, x_1), (y_0, y_0, y_1), color=np.clip(colour_swatches_test[i].RGB, 0, 1), zorder=CONSTANTS_COLOUR_STYLE.zorder.midground_polygon, ) if colour_swatch.name is not None and text_settings["visible"]: axes.text( x_0 + text_offset, y_0 + text_offset * y, colour_swatch.name, verticalalignment="bottom" if y == 1 else "top", clip_on=True, **text_settings, ) offset_X += width + spacing x_max = min(len(colour_swatches), int(columns)) x_max = x_max * width + x_max * spacing - spacing y_max = offset_Y axes.patch.set_facecolor(background_colour) if y == 1: bounding_box = [ x_min - spacing, x_max + spacing, y_min - spacing, y_max + spacing + height, ] else: bounding_box = [ x_min - spacing, x_max + spacing, y_max - spacing - height, y_min + spacing, ] settings: Dict[str, Any] = { "axes": axes, "bounding_box": bounding_box, "aspect": "equal", } settings.update(kwargs) return render(**settings)
[docs]@override_style() def plot_single_function( function: Callable, samples: Optional[ArrayLike] = None, log_x: Optional[Integer] = None, log_y: Optional[Integer] = None, plot_kwargs: Optional[Union[Dict, List[Dict]]] = None, **kwargs: Any, ) -> Tuple[plt.Figure, plt.Axes]: """ Plot given function. Parameters ---------- function Function to plot. samples Samples to evaluate the functions with. log_x Log base to use for the *x* axis scale, if *None*, the *x* axis scale will be linear. log_y Log base to use for the *y* axis scale, if *None*, the *y* axis scale will be linear. plot_kwargs Keyword arguments for the :func:`matplotlib.pyplot.plot` definition, used to control the style of the plotted function. Other Parameters ---------------- kwargs {:func:`colour.plotting.artist`, :func:`colour.plotting.plot_multi_functions`, :func:`colour.plotting.render`}, See the documentation of the previously listed definitions. Returns ------- :class:`tuple` Current figure and axes. Examples -------- >>> from colour.models import gamma_function >>> plot_single_function(partial(gamma_function, exponent=1 / 2.2)) ... # doctest: +ELLIPSIS (<Figure size ... with 1 Axes>, <...AxesSubplot...>) .. image:: ../_static/Plotting_Plot_Single_Function.png :align: center :alt: plot_single_function """ try: name = function.__name__ except AttributeError: name = "Unnamed" settings: Dict[str, Any] = { "title": f"{name} - Function", "legend": False, } settings.update(kwargs) return plot_multi_functions( {name: function}, samples, log_x, log_y, plot_kwargs, **settings )
[docs]@override_style() def plot_multi_functions( functions: Dict[str, Callable], samples: Optional[ArrayLike] = None, log_x: Optional[Integer] = None, log_y: Optional[Integer] = None, plot_kwargs: Optional[Union[Dict, List[Dict]]] = None, **kwargs: Any, ) -> Tuple[plt.Figure, plt.Axes]: """ Plot given functions. Parameters ---------- functions Functions to plot. samples Samples to evaluate the functions with. log_x Log base to use for the *x* axis scale, if *None*, the *x* axis scale will be linear. log_y Log base to use for the *y* axis scale, if *None*, the *y* axis scale will be linear. plot_kwargs Keyword arguments for the :func:`matplotlib.pyplot.plot` definition, used to control the style of the plotted functions. ``plot_kwargs`` can be either a single dictionary applied to all the plotted functions with the same settings or a sequence of dictionaries with different settings for each plotted function. Other Parameters ---------------- kwargs {:func:`colour.plotting.artist`, :func:`colour.plotting.render`}, See the documentation of the previously listed definitions. Returns ------- :class:`tuple` Current figure and axes. Examples -------- >>> functions = { ... 'Gamma 2.2' : lambda x: x ** (1 / 2.2), ... 'Gamma 2.4' : lambda x: x ** (1 / 2.4), ... 'Gamma 2.6' : lambda x: x ** (1 / 2.6), ... } >>> plot_multi_functions(functions) ... # doctest: +ELLIPSIS (<Figure size ... with 1 Axes>, <...AxesSubplot...>) .. image:: ../_static/Plotting_Plot_Multi_Functions.png :align: center :alt: plot_multi_functions """ settings: Dict[str, Any] = dict(kwargs) _figure, axes = artist(**settings) plot_settings_collection = [ { "label": f"{name}", "zorder": CONSTANTS_COLOUR_STYLE.zorder.midground_label, } for name in functions.keys() ] if plot_kwargs is not None: update_settings_collection( plot_settings_collection, plot_kwargs, len(functions) ) # TODO: Remove when "Matplotlib" minimum version can be set to 3.5.0. matplotlib_3_5 = tuple( int(token) for token in matplotlib.__version__.split(".")[:2] ) >= (3, 5) if log_x is not None and log_y is not None: attest( log_x >= 2 and log_y >= 2, "Log base must be equal or greater than 2.", ) plotting_function = axes.loglog axes.set_xscale("log", base=log_x) axes.set_yscale("log", base=log_y) elif log_x is not None: attest(log_x >= 2, "Log base must be equal or greater than 2.") if matplotlib_3_5: # pragma: no cover plotting_function = partial(axes.semilogx, base=log_x) else: # pragma: no cover plotting_function = partial(axes.semilogx, basex=log_x) elif log_y is not None: attest(log_y >= 2, "Log base must be equal or greater than 2.") if matplotlib_3_5: # pragma: no cover plotting_function = partial(axes.semilogy, base=log_y) else: # pragma: no cover plotting_function = partial(axes.semilogy, basey=log_y) else: plotting_function = axes.plot samples = cast(ArrayLike, optional(samples, np.linspace(0, 1, 1000))) for i, (_name, function) in enumerate(functions.items()): plotting_function( samples, function(samples), **plot_settings_collection[i] ) x_label = ( f"x - Log Base {log_x} Scale" if log_x is not None else "x - Linear Scale" ) y_label = ( f"y - Log Base {log_y} Scale" if log_y is not None else "y - Linear Scale" ) settings = { "axes": axes, "legend": True, "title": f"{', '.join(functions)} - Functions", "x_label": x_label, "y_label": y_label, } settings.update(kwargs) return render(**settings)
[docs]@override_style() def plot_image( image: ArrayLike, imshow_kwargs: Optional[Dict] = None, text_kwargs: Optional[Dict] = None, **kwargs: Any, ) -> Tuple[plt.Figure, plt.Axes]: """ Plot given image. Parameters ---------- image Image to plot. imshow_kwargs Keyword arguments for the :func:`matplotlib.pyplot.imshow` definition. text_kwargs Keyword arguments for the :func:`matplotlib.pyplot.text` definition. The following special keyword arguments can also be used: - ``offset`` : Sets the text offset. Other Parameters ---------------- kwargs {:func:`colour.plotting.artist`, :func:`colour.plotting.render`}, See the documentation of the previously listed definitions. Returns ------- :class:`tuple` Current figure and axes. Examples -------- >>> import os >>> import colour >>> from colour import read_image >>> path = os.path.join( ... colour.__path__[0], 'examples', 'plotting', 'resources', ... 'Ishihara_Colour_Blindness_Test_Plate_3.png') >>> plot_image(read_image(path)) # doctest: +ELLIPSIS (<Figure size ... with 1 Axes>, <...AxesSubplot...>) .. image:: ../_static/Plotting_Plot_Image.png :align: center :alt: plot_image """ _figure, axes = artist(**kwargs) imshow_settings = { "interpolation": "nearest", "cmap": matplotlib.cm.Greys_r, "zorder": CONSTANTS_COLOUR_STYLE.zorder.background_polygon, } if imshow_kwargs is not None: imshow_settings.update(imshow_kwargs) text_settings = { "text": None, "offset": 0.005, "color": CONSTANTS_COLOUR_STYLE.colour.brightest, "alpha": CONSTANTS_COLOUR_STYLE.opacity.high, "zorder": CONSTANTS_COLOUR_STYLE.zorder.midground_label, } if text_kwargs is not None: text_settings.update(text_kwargs) text_offset = text_settings.pop("offset") image = as_float_array(image) axes.imshow(np.clip(image, 0, 1), **imshow_settings) if text_settings["text"] is not None: text = text_settings.pop("text") axes.text( text_offset, text_offset, text, transform=axes.transAxes, ha="left", va="bottom", **text_settings, ) settings: Dict[str, Any] = { "axes": axes, "axes_visible": False, } settings.update(kwargs) return render(**settings)