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Date table sorting is used to correctly sort and display dates in a sortable table (see Help:Sortable tables). What it solves Dates in their customary formats, if simply treated as alphanumeric text strings, sort in nonsensical ways:
Shuffling can also be implemented by a sorting algorithm, namely by a random sort: assigning a random number to each element of the list and then sorting based on the random numbers. This is generally not done in practice, however, and there is a well-known simple and efficient algorithm for shuffling: the Fisher–Yates shuffle .
Timsort is a stable sorting algorithm (order of elements with same key is kept) and strives to perform balanced merges (a merge thus merges runs of similar sizes). In order to achieve sorting stability, only consecutive runs are merged. Between two non-consecutive runs, there can be an element with the same key inside the runs.
returns a calendar time based on a time base Format conversions asctime: converts a struct tm object to a textual representation (deprecated) ctime: converts a time_t value to a textual representation strftime: converts a struct tm object to custom textual representation strptime: converts a string with time information to a struct tm: wcsftime
sort is a generic function in the C++ Standard Library for doing comparison sorting.The function originated in the Standard Template Library (STL).. The specific sorting algorithm is not mandated by the language standard and may vary across implementations, but the worst-case asymptotic complexity of the function is specified: a call to sort must perform no more than O(N log N) comparisons ...
Methods of cell sorting fall into two major categories: fluorescence-activated cell sorting (FACS) and immunomagnetic cell sorting. [2] Due to many years of refinement and increased demand for cell separation however, researchers are working to develop microfluidic sorting devices that have many benefits in comparison to the main types of fluorescence-activated cell sorting and immunomagnetic ...
Arora et al. (2016) [25] explain word2vec and related algorithms as performing inference for a simple generative model for text, which involves a random walk generation process based upon loglinear topic model. They use this to explain some properties of word embeddings, including their use to solve analogies.