Color sequences, ordered sets of colors for data visualization, that balance aesthetics with accessibility considerations are presented. In order to model aesthetic preference, data were collected with an online survey, and the results were used to train a machine-learning model. To ensure accessibility, this model was combined with minimum-perceptual-distance constraints, including for simulated color-vision deficiencies, as well as with minimum-lightness-distance constraints for grayscale printing, maximum-lightness constraints for maintaining contrast with a white background, and scores from a color-saliency model for ease of use of the colors in verbal and written descriptions. Optimal color sequences containing six, eight, and ten colors were generated using the data-driven aesthetic-preference model and accessibility constraints. Due to the balance of aesthetics and accessibility considerations, the resulting color sequences can serve as reasonable defaults in data-plotting codes, e.g., for use in scatter plots and line plots.
翻译:为了模拟美学偏好,通过在线调查收集数据,并用结果培训机器学习模型。为了确保无障碍,该模型与最低感知距离限制相结合,包括模拟色视缺陷,以及灰度印刷的最小亮度-距离限制,保持与白背景对比的最大亮度限制,以及便于在口头和书面描述中使用颜色的色调模型的分数。使用数据驱动的美学偏好模型和无障碍限制,生成了包含6、8和10种色的优化颜色序列。由于美观和无障碍考虑的平衡,由此产生的颜色序列可以作为数据绘图代码的合理默认,例如用于散落地和线块。