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In terms of a merge-base theory of language acquisition, complements and specifiers are simply notations for first-merge (read as "complement-of" [head-complement]), and later second-merge (read as "specifier-of" [specifier-head]), with merge always forming to a head. First-merge establishes only a set {a, b} and is not an ordered pair.
In the merge sort algorithm, this subroutine is typically used to merge two sub-arrays A[lo..mid], A[mid+1..hi] of a single array A. This can be done by copying the sub-arrays into a temporary array, then applying the merge algorithm above. [1] The allocation of a temporary array can be avoided, but at the expense of speed and programming ease.
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.
Analogously, TreeMap, and other sorted data structures, require that an ordering be defined on the data type. Either the data type must already have defined its own ordering, by implementing the Comparable interface; or a custom Comparator must be provided at the time the map is constructed. As with HashMap above, the relative ordering of keys ...
algorithm nested_loop_join is for each tuple r in R do for each tuple s in S do if r and s satisfy the join condition then yield tuple <r,s> This algorithm will involve n r *b s + b r block transfers and n r +b r seeks, where b r and b s are number of blocks in relations R and S respectively, and n r is the number of tuples in relation R.
Merge. Merge uses a local function loop for efficiency. The inner loop is defined in terms of cases: when both lists are non-empty (x:: xs) and when one list is empty ([]). This function merges two sorted lists into one sorted list. Note how the accumulator acc is built backwards, then reversed before being returned.
The recipe, the user explains, only requires three things — a two-liter bottle of Dr Pepper, a fresh lemon and a slow cooker. "This is soda on a whole 'nother level," she said.
Introduced in Python 2.2 as an optional feature and finalized in version 2.3, generators are Python's mechanism for lazy evaluation of a function that would otherwise return a space-prohibitive or computationally intensive list. This is an example to lazily generate the prime numbers: