Coverage for colour/plotting/corresponding.py: 100%

1""" 

2Corresponding Chromaticities Prediction Plotting 

3================================================ 

4 

5Define the corresponding chromaticities prediction plotting objects. 

6 

7- :func:`colour.plotting.plot_corresponding_chromaticities_prediction` 

8""" 

9 

10from __future__ import annotations 

11 

12import typing 

13 

14if typing.TYPE_CHECKING: 

15 from matplotlib.figure import Figure 

16 from matplotlib.axes import Axes 

17 

18from colour.corresponding import ( 

19 CorrespondingColourDataset, 

20 corresponding_chromaticities_prediction, 

21) 

22 

23if typing.TYPE_CHECKING: 

24 from colour.hints import Any, Dict, Literal, Tuple 

25 

26from colour.hints import cast 

27from colour.plotting import ( 

28 CONSTANTS_COLOUR_STYLE, 

29 artist, 

30 override_style, 

31 plot_chromaticity_diagram_CIE1976UCS, 

32 render, 

33) 

34from colour.utilities import is_numeric 

35 

36__author__ = "Colour Developers" 

37__copyright__ = "Copyright 2013 Colour Developers" 

38__license__ = "BSD-3-Clause - https://opensource.org/licenses/BSD-3-Clause" 

39__maintainer__ = "Colour Developers" 

40__email__ = "colour-developers@colour-science.org" 

41__status__ = "Production" 

42 

43__all__ = [ 

44 "plot_corresponding_chromaticities_prediction", 

45] 

46 

47 

48@override_style() 

49def plot_corresponding_chromaticities_prediction( 

50 experiment: (Literal[1, 2, 3, 4, 6, 8, 9, 11, 12] | CorrespondingColourDataset) = 1, 

51 model: ( 

52 Literal[ 

53 "CIE 1994", 

54 "CMCCAT2000", 

55 "Fairchild 1990", 

56 "Von Kries", 

57 "Zhai 2018", 

58 ] 

59 | str 

60 ) = "Von Kries", 

61 corresponding_chromaticities_prediction_kwargs: dict | None = None, 

62 **kwargs: Any, 

63) -> Tuple[Figure, Axes]: 

64 """ 

65 Plot the corresponding chromaticities prediction for the specified 

66 chromatic adaptation model. 

67 

68 Parameters 

69 ---------- 

70 experiment 

71 *Breneman (1987)* experiment number or 

72 :class:`colour.CorrespondingColourDataset` class instance. 

73 model 

74 Corresponding chromaticities prediction model name. 

75 corresponding_chromaticities_prediction_kwargs 

76 Keyword arguments for the 

77 :func:`colour.corresponding_chromaticities_prediction` definition. 

78 

79 Other Parameters 

80 ---------------- 

81 kwargs 

82 {:func:`colour.plotting.artist`, 

83 :func:`colour.plotting.diagrams.plot_chromaticity_diagram`, 

84 :func:`colour.plotting.render`}, 

85 See the documentation of the previously listed definitions. 

86 

87 Returns 

88 ------- 

89 :class:`tuple` 

90 Current figure and axes. 

91 

92 Examples 

93 -------- 

94 >>> plot_corresponding_chromaticities_prediction(1, "Von Kries") 

95 ... # doctest: +ELLIPSIS 

96 (<Figure size ... with 1 Axes>, <...Axes...>) 

97 

98 .. image:: ../_static/Plotting_\ 

99Plot_Corresponding_Chromaticities_Prediction.png 

100 :align: center 

101 :alt: plot_corresponding_chromaticities_prediction 

102 """ 

103 

104 if corresponding_chromaticities_prediction_kwargs is None: 

105 corresponding_chromaticities_prediction_kwargs = {} 

106 

107 settings: Dict[str, Any] = {"uniform": True} 

108 settings.update(kwargs) 

109 

110 _figure, axes = artist(**settings) 

111 

112 name = ( 

113 f"Experiment {experiment}" 

114 if is_numeric(experiment) 

115 else cast("CorrespondingColourDataset", experiment).name 

116 ) 

117 title = ( 

118 f"Corresponding Chromaticities Prediction - {model} - {name} - " 

119 "CIE 1976 UCS Chromaticity Diagram" 

120 ) 

121 

122 settings = {"axes": axes, "title": title} 

123 settings.update(kwargs) 

124 settings["show"] = False 

125 

126 plot_chromaticity_diagram_CIE1976UCS(**settings) 

127 

128 results = corresponding_chromaticities_prediction( 

129 experiment, model, **corresponding_chromaticities_prediction_kwargs 

130 ) 

131 

132 for result in results: 

133 _name, uv_t, uv_m, uv_p = result.values 

134 axes.arrow( 

135 uv_t[0], 

136 uv_t[1], 

137 uv_p[0] - uv_t[0] - 0.1 * (uv_p[0] - uv_t[0]), 

138 uv_p[1] - uv_t[1] - 0.1 * (uv_p[1] - uv_t[1]), 

139 color=CONSTANTS_COLOUR_STYLE.colour.dark, 

140 head_width=0.005, 

141 head_length=0.005, 

142 zorder=CONSTANTS_COLOUR_STYLE.zorder.midground_annotation, 

143 ) 

144 axes.plot( 

145 uv_t[0], 

146 uv_t[1], 

147 "o", 

148 color=CONSTANTS_COLOUR_STYLE.colour.brightest, 

149 markeredgecolor=CONSTANTS_COLOUR_STYLE.colour.dark, 

150 markersize=( 

151 CONSTANTS_COLOUR_STYLE.geometry.short * 6 

152 + CONSTANTS_COLOUR_STYLE.geometry.short * 0.75 

153 ), 

154 markeredgewidth=CONSTANTS_COLOUR_STYLE.geometry.short * 0.75, 

155 zorder=CONSTANTS_COLOUR_STYLE.zorder.foreground_line, 

156 ) 

157 axes.plot( 

158 uv_m[0], 

159 uv_m[1], 

160 "^", 

161 color=CONSTANTS_COLOUR_STYLE.colour.brightest, 

162 markeredgecolor=CONSTANTS_COLOUR_STYLE.colour.dark, 

163 markersize=( 

164 CONSTANTS_COLOUR_STYLE.geometry.short * 6 

165 + CONSTANTS_COLOUR_STYLE.geometry.short * 0.75 

166 ), 

167 markeredgewidth=CONSTANTS_COLOUR_STYLE.geometry.short * 0.75, 

168 zorder=CONSTANTS_COLOUR_STYLE.zorder.foreground_line, 

169 ) 

170 axes.plot( 

171 uv_p[0], 

172 uv_p[1], 

173 "^", 

174 color=CONSTANTS_COLOUR_STYLE.colour.dark, 

175 zorder=CONSTANTS_COLOUR_STYLE.zorder.foreground_line, 

176 ) 

177 

178 settings.update( 

179 { 

180 "show": True, 

181 "bounding_box": (-0.1, 0.7, -0.1, 0.7), 

182 } 

183 ) 

184 settings.update(kwargs) 

185 

186 return render(**settings)