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Matplotlib-animation [11] capabilities are intended for visualizing how certain data changes. However, one can use the functionality in any way required. These animations are defined as a function of frame number (or time). In other words, one defines a function that takes a frame number as input and defines/updates the matplotlib-figure based ...
UpSet plots are a data visualization method for showing set data with more than three intersecting sets. UpSet shows intersections in a matrix, with the rows of the matrix corresponding to the sets, and the columns to the intersections between these sets (or vice versa). The size of the sets and of the intersections are shown as bar charts.
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Julia has the vec(A) function as well. In Python NumPy arrays implement the flatten method, [ note 1 ] while in R the desired effect can be achieved via the c() or as.vector() functions. In R , function vec() of package 'ks' allows vectorization and function vech() implemented in both packages 'ks' and 'sn' allows half-vectorization.
In size theory, the size function (,): + = {(,): <} associated with the size pair (,:) is defined in the following way. For every (,) +, (,) (,) is equal to the number of connected components of the set {: ()} that contain at least one point at which the measuring function (a continuous function from a topological space to [1] [2]) takes a value smaller than or equal to . [3]
The shape of a distribution will fall somewhere in a continuum where a flat distribution might be considered central and where types of departure from this include: mounded (or unimodal), U-shaped, J-shaped, reverse-J shaped and multi-modal. [1]
A popular window function, the Hann window. Most popular window functions are similar bell-shaped curves. In signal processing and statistics, a window function (also known as an apodization function or tapering function [1]) is a mathematical function that is zero-valued outside of some chosen interval. Typically, window functions are ...
The lower contour set of is the set of all such that is related to them: { y ∍ x ≽ y } {\displaystyle \left\{y~\backepsilon ~x\succcurlyeq y\right\}} The strict upper contour set of x {\displaystyle x} is the set of all y {\displaystyle y} that are related to x {\displaystyle x} without x {\displaystyle x} being in this way related to any ...