Search results
Results from the WOW.Com Content Network
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 ...
The flattening transformation is an algorithm that transforms nested data parallelism into flat data parallelism. It was pioneered by Guy Blelloch as part of the NESL programming language. [ 1 ] The flattening transformation is also sometimes called vectorization , but is completely unrelated to automatic vectorization .
Multidimensional scaling (MDS) is a means of visualizing the level of similarity of individual cases of a data set. MDS is used to translate distances between each pair of objects in a set into a configuration of points mapped into an abstract Cartesian space.
Plain text files usually contain one record per line. [2]Examples of flat files include /etc/passwd and /etc/group on Unix-like operating systems. Another example of a flat file is a name-and-address list with the fields Name, Address and Phone Number.
Flattening is a measure of the compression of a circle or sphere along a diameter to form an ellipse or an ellipsoid of revolution respectively. Other terms used are ellipticity , or oblateness . The usual notation for flattening is f {\displaystyle f} and its definition in terms of the semi-axes a {\displaystyle a} and b {\displaystyle b} of ...
Flattening the curve is a public health strategy to slow down the spread of an epidemic, used against the SARS-CoV-2 virus during the early stages of the COVID-19 pandemic. The curve being flattened is the epidemic curve , a visual representation of the number of infected people needing health care over time.
The average of these values is 18.05 and the excess kurtosis is thus 18.05 − 3 = 15.05. This example makes it clear that data near the "middle" or "peak" of the distribution do not contribute to the kurtosis statistic, hence kurtosis does not measure "peakedness". It is simply a measure of the outlier, 999 in this example.