![]() The bright, high-contrast, vibrant, muted and medium-contrast schemes work well for plot lines and map regions, but the colours are too strong to use for backgrounds to mark (black) text, typically in a table. It is designed for situations needing colour pairs, shown by the three rectangles, with the lower half in the greyscale equivalent. It is also optimized for contrast to work in a monochrome printout, but the differences are inevitably smaller. Figure 5: Medium-contrast qualitative colour scheme, an alternative to the high-contrast scheme of Fig. 2 that is colour-blind safe with more colours. Figure 4: Muted qualitative colour scheme, an alternative to the bright scheme of Fig. 1 that is equally colour-blind safe with more colours, but lacking a clear red or medium blue. It has been designed for data visualization framework TensorBoard, built around their signature orange FF7043. Figure 3: Vibrant qualitative colour scheme, an alternative to the bright scheme of Fig. 1 that is equally colour-blind safe. The samples underneath are shades of grey with the same luminance this scheme also works well for people with monochrome vision and in a monochrome printout.Ĭolours in default order: '#EE7733', '#0077BB', '#33BBEE', '#EE3377', '#CC3311', '#009988', '#BBBBBB'. Figure 2: High-contrast qualitative colour scheme, an alternative to the bright scheme of Fig. 1 that is colour-blind safe and optimized for contrast. The main scheme for lines and their labels.Ĭolours in default order: '#004488', '#DDAA33', '#BB5566'. Figure 1: Bright qualitative colour scheme that is colour-blind safe. If more than nine colours are really needed, a sequential colour scheme can be (mis)used: the discrete rainbow colour scheme ( Fig. 21), skipping the lightest colours for lines on a white background, or the smooth rainbow colour scheme ( Fig. 20) starting at purple, interpolated in large equal steps.Ĭolours in default order: '#4477AA', '#EE6677', '#228833', '#CCBB44', '#66CCEE', '#AA3377', '#BBBBBB'. A fourth alternative is the medium-contrast scheme in Fig. 5 with three colour pairs that can work in greyscale, but not as well as the high-contrast scheme. A third alternative is the muted scheme in Fig. 4, which has more colours, but lacks a clear red or medium blue. A second alternative is the vibrant scheme in Fig. 3, designed for data visualization framework TensorBoard. An alternative when fewer colours are enough is the high-contrast scheme in Fig. 2, which also works when converted to greyscale. ![]() ![]() Click on this and other defining figures for the hexadecimal values as text. Colour coordinates ( R,G,B) are given in the RGB colour system (red R, green G and blue B), decimal at the top and hexadecimal below. My default colour scheme for qualitative data is the bright scheme in Fig. 1. SRON specific: templates for PowerPoint and LaTeX.A way of splitting the data analysis and the production of maps.A look at a traditional, bad rainbow scheme and how a scheme with fewer colours can be better.A very specific colour scheme for the AVHRR global land cover classification.The schemes that work well in a monochrome display or printout are highlighted, with tips on how to use them best.Info on simulating approximately how any colour is seen if you are colour-blind.The following three sections describe colour schemes for these types of data. Sequential data – data ordered from low to high.positive and negative deviations from zero or a mean. Diverging data – data ordered between two extremes where the midpoint is important, e.g. ![]() This includes lines in plots and text in presentations. Qualitative data – nominal or categorical data, where magnitude differences are not relevant.A colour scheme should reflect the type of data shown. ![]() This site shows such schemes, developed with the help of mathematical descriptions of colour differences and the two main types of colour-blind vision.
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