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Here, the list [0..] represents , x^2>3 represents the predicate, and 2*x represents the output expression.. List comprehensions give results in a defined order (unlike the members of sets); and list comprehensions may generate the members of a list in order, rather than produce the entirety of the list thus allowing, for example, the previous Haskell definition of the members of an infinite list.
The mode of a sample is the element that occurs most often in the collection. For example, the mode of the sample [1, 3, 6, 6, 6, 6, 7, 7, 12, 12, 17] is 6. Given the list of data [1, 1, 2, 4, 4] its mode is not unique. A dataset, in such a case, is said to be bimodal, while a set with more than two modes may be described as multimodal.
In computer programming, indentation style is a convention, a.k.a. style, governing the indentation of blocks of source code.An indentation style generally involves consistent width of whitespace (indentation size) before each line of a block, so that the lines of code appear to be related, and dictates whether to use space or tab characters for the indentation whitespace.
Numeric literals in Python are of the normal sort, e.g. 0, -1, 3.4, 3.5e-8. Python has arbitrary-length integers and automatically increases their storage size as necessary. Prior to Python 3, there were two kinds of integral numbers: traditional fixed size integers and "long" integers of arbitrary size.
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It is also possible to present short lists using very basic formatting, such as: ''Title of list:'' example 1, example 2, example 3 Title of list: example 1, example 2, example 3 This style requires less space on the page, and is preferred if there are only a few entries in the list, it can be read easily, and a direct edit point is not required.
Alternatively, there is also an output mode that generates a cross reference file, listing information about various names found in a set of language files in human-readable form. The original Ctags was introduced in BSD Unix 2.0 [ 1 ] [ 2 ] and was written by Ken Arnold , with Fortran support by Jim Kleckner and Pascal support by Bill Joy .
In data science, dynamic mode decomposition (DMD) is a dimensionality reduction algorithm developed by Peter J. Schmid and Joern Sesterhenn in 2008. [ 1 ] [ 2 ] Given a time series of data, DMD computes a set of modes, each of which is associated with a fixed oscillation frequency and decay/growth rate.