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Thus an element in row i and column j of an array A would be accessed by double indexing (A[i][j] in typical notation). This way of emulating multi-dimensional arrays allows the creation of jagged arrays, where each row may have a different size – or, in general, where the valid range of each index depends on the values of all preceding indices.
To use column-major order in a row-major environment, or vice versa, for whatever reason, one workaround is to assign non-conventional roles to the indexes (using the first index for the column and the second index for the row), and another is to bypass language syntax by explicitly computing positions in a one-dimensional array.
The following Python implementation [1] [circular reference] performs cycle sort on an array, counting the number of writes to that array that were needed to sort it. Python def cycle_sort ( array ) -> int : """Sort an array in place and return the number of writes.""" writes = 0 # Loop through the array to find cycles to rotate.
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 .
First, divide the list into equal-sized sublists // consisting of the first half and second half of the list. // This assumes lists start at index 0. var left := empty list var right := empty list for each x with index i in m do if i < (length of m)/2 then add x to left else add x to right // Recursively sort both sublists. left := merge_sort ...
Timsort is a hybrid, stable sorting algorithm, derived from merge sort and insertion sort, designed to perform well on many kinds of real-world data. It was implemented by Tim Peters in 2002 for use in the Python programming language. The algorithm finds subsequences of the data that are already ordered (runs) and uses them to sort the ...
Bucket sort can be seen as a generalization of counting sort; in fact, if each bucket has size 1 then bucket sort degenerates to counting sort. The variable bucket size of bucket sort allows it to use O( n ) memory instead of O( M ) memory, where M is the number of distinct values; in exchange, it gives up counting sort's O( n + M ) worst-case ...
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.