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A K4-free near-triangulation is 3-colourable if and only if it is word-representable; [17] this result generalises studies in. [18] [19] Word-representability of face subdivisions of triangular grid graphs is studied in [20] and word-representability of triangulations of grid-covered cylinder graphs is studied in. [21]
In science the term is used in both ways. For example, Anderson (1997) stated more generally: "diagrams are pictorial, yet abstract, representations of information, and maps, line graphs, bar charts, engineering blueprints, and architects' sketches are all examples of diagrams, whereas photographs and video are not". [2]
Included are diagram techniques, chart techniques, plot techniques, and other forms of visualization. There is also a list of computer graphics and descriptive geometry topics . Simple displays
If a chart plots 10 colors or fewer, then by default it uses every other one: The colors can be manually set in a graph by adding them to the 'colors' parameter. For example, for two pie charts, the first of which is default and the second of which omits some colors in the first, you would manually enter your selections from the default 20:
IPE Graphics with LaTeX equations or notations can be stored as PDF files (not only exported to PDF) and be included in LaTeX documents. pdftoipe allows any PDF graph to be edited in Ipe. JFreeChart: GUI, Java, Groovy: LGPL: Yes 2000: November 5, 2017 / 1.5.0: Any : JMP: GUI, scripting: proprietary: No 1989: March 9, 2021 / 16.0: Mac, Windows
In the mathematical discipline of graph theory, a graph labeling is the assignment of labels, traditionally represented by integers, to edges and/or vertices of a graph. [1] Formally, given a graph G = (V, E), a vertex labeling is a function of V to a set of labels; a graph with such a function defined is called a vertex-labeled graph.
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In natural language processing (NLP), a text graph is a graph representation of a text item (document, passage or sentence). It is typically created as a preprocessing step to support NLP tasks such as text condensation [ 1 ] term disambiguation [ 2 ] (topic-based) text summarization , [ 3 ] relation extraction [ 4 ] and textual entailment .