 | This article relies largely or entirely on a single source .(March 2024) |
An Aggregate pattern can refer to concepts in either statistics or computer programming. Both uses deal with considering a large case as composed of smaller, simpler, pieces.
| | This article relies largely or entirely on a single source .(March 2024) |
An Aggregate pattern can refer to concepts in either statistics or computer programming. Both uses deal with considering a large case as composed of smaller, simpler, pieces.
An aggregate pattern is an important statistical concept in many fields that rely on statistics to predict the behavior of large groups, based on the tendencies of subgroups to consistently behave in a certain way. It is particularly useful in sociology, economics, psychology, and criminology.
In Design Patterns , an aggregate is not a design pattern but rather refers to an object such as a list, vector, or generator which provides an interface for creating iterators. The following example code is in Python.
deffibonacci(n:int):a,b=0,1count=0whilecount<n:count+=1a,b=b,a+byieldaforxinfibonacci(10):print(x)deffibsum(n:int)->int:total=0forxinfibonacci(n):total+=xreturntotaldeffibsum_alt(n:int)->int:""" Alternate implementation. demonstration that Python's built-in function sum() works with arbitrary iterators. """returnsum(fibonacci(n))myNumbers=[1,7,4,3,22]defaverage(g)->float:returnfloat(sum(g))/len(g)# In Python 3 the cast to float is no longer be necessaryPython hides essentially all of the details using the iterator protocol. Confusingly, Design Patterns uses "aggregate" to refer to the blank in the code for x in ___: which is unrelated to the term "aggregation". [1] Neither of these terms refer to the statistical aggregation of data such as the act of adding up the Fibonacci sequence or taking the average of a list of numbers.
In programming language theory, lazy evaluation, or call-by-need, is an evaluation strategy which delays the evaluation of an expression until its value is needed and which also avoids repeated evaluations.
In object-oriented programming, the iterator pattern is a design pattern in which an iterator is used to traverse a container and access the container's elements. The iterator pattern decouples algorithms from containers; in some cases, algorithms are necessarily container-specific and thus cannot be decoupled.
In computer programming, an iterator is an object that enables a programmer to traverse a container, particularly lists. Various types of iterators are often provided via a container's interface. Though the interface and semantics of a given iterator are fixed, iterators are often implemented in terms of the structures underlying a container implementation and are often tightly coupled to the container to enable the operational semantics of the iterator. An iterator performs traversal and also gives access to data elements in a container, but does not itself perform iteration.
F# is a general-purpose, strongly typed, multi-paradigm programming language that encompasses functional, imperative, and object-oriented programming methods. It is most often used as a cross-platform Common Language Infrastructure (CLI) language on .NET, but can also generate JavaScript and graphics processing unit (GPU) code.
In computer programming, a function object is a construct allowing an object to be invoked or called as if it were an ordinary function, usually with the same syntax. In some languages, particularly C++, function objects are often called functors.
In computer science, a generator is a routine that can be used to control the iteration behaviour of a loop. All generators are also iterators. A generator is very similar to a function that returns an array, in that a generator has parameters, can be called, and generates a sequence of values. However, instead of building an array containing all the values and returning them all at once, a generator yields the values one at a time, which requires less memory and allows the caller to get started processing the first few values immediately. In short, a generator looks like a function but behaves like an iterator.
In computer programming, a callback or callback function is any reference to executable code that is passed as an argument to another piece of code; that code is expected to call back (execute) the callback function as part of its job. This execution may be immediate as in a synchronous callback, or it might happen at a later point in time as in an asynchronous callback. They are also called blocking and non-blocking.
In computer science, corecursion is a type of operation that is dual to recursion. Whereas recursion works analytically, starting on data further from a base case and breaking it down into smaller data and repeating until one reaches a base case, corecursion works synthetically, starting from a base case and building it up, iteratively producing data further removed from a base case. Put simply, corecursive algorithms use the data that they themselves produce, bit by bit, as they become available, and needed, to produce further bits of data. A similar but distinct concept is generative recursion, which may lack a definite "direction" inherent in corecursion and recursion.
In mathematics and in computer programming, a variadic function is a function of indefinite arity, i.e., one which accepts a variable number of arguments. Support for variadic functions differs widely among programming languages.
In computer science, object composition and object aggregation are closely related ways to combine objects or data types into more complex ones. In conversation the distinction between composition and aggregation is often ignored. Common kinds of compositions are objects used in object-oriented programming, tagged unions, sets, sequences, and various graph structures. Object compositions relate to, but are not the same as, data structures.
In number theory, a Dudeney number in a given number base is a natural number equal to the perfect cube of another natural number such that the digit sum of the first natural number is equal to the second. The name derives from Henry Dudeney, who noted the existence of these numbers in one of his puzzles, Root Extraction, where a professor in retirement at Colney Hatch postulates this as a general method for root extraction.
In number theory, a narcissistic number in a given number base is a number that is the sum of its own digits each raised to the power of the number of digits.
In computer science, recursion is a method of solving a computational problem where the solution depends on solutions to smaller instances of the same problem. Recursion solves such recursive problems by using functions that call themselves from within their own code. The approach can be applied to many types of problems, and recursion is one of the central ideas of computer science.
The power of recursion evidently lies in the possibility of defining an infinite set of objects by a finite statement. In the same manner, an infinite number of computations can be described by a finite recursive program, even if this program contains no explicit repetitions.
Tacit programming, also called point-free style, is a programming paradigm in which function definitions do not identify the arguments on which they operate. Instead the definitions merely compose other functions, among which are combinators that manipulate the arguments. Tacit programming is of theoretical interest, because the strict use of composition results in programs that are well adapted for equational reasoning. It is also the natural style of certain programming languages, including APL and its derivatives, and concatenative languages such as Forth. The lack of argument naming gives point-free style a reputation of being unnecessarily obscure, hence the epithet "pointless style".
The syntax of the Python programming language is the set of rules that defines how a Python program will be written and interpreted. The Python language has many similarities to Perl, C, and Java. However, there are some definite differences between the languages. It supports multiple programming paradigms, including structured, object-oriented programming, and functional programming, and boasts a dynamic type system and automatic memory management.
RDFLib is a Python library for working with RDF, a simple yet powerful language for representing information. This library contains parsers/serializers for almost all of the known RDF serializations, such as RDF/XML, Turtle, N-Triples, & JSON-LD, many of which are now supported in their updated form. The library also contains both in-memory and persistent Graph back-ends for storing RDF information and numerous convenience functions for declaring graph namespaces, lodging SPARQL queries and so on. It is in continuous development with the most recent stable release, rdflib 6.1.1 having been released on 20 December 2021. It was originally created by Daniel Krech with the first release in November, 2002.
In computer programming, an anonymous function is a function definition that is not bound to an identifier. Anonymous functions are often arguments being passed to higher-order functions or used for constructing the result of a higher-order function that needs to return a function. If the function is only used once, or a limited number of times, an anonymous function may be syntactically lighter than using a named function. Anonymous functions are ubiquitous in functional programming languages and other languages with first-class functions, where they fulfil the same role for the function type as literals do for other data types.
In number theory, a perfect digit-to-digit invariant is a natural number in a given number base that is equal to the sum of its digits each raised to the power of itself. An example in base 10 is 3435, because . The term "Munchausen number" was coined by Dutch mathematician and software engineer Daan van Berkel in 2009, as this evokes the story of Baron Munchausen raising himself up by his own ponytail because each digit is raised to the power of itself.
Nemerle is a general-purpose, high-level, statically typed programming language designed for platforms using the Common Language Infrastructure (.NET/Mono). It offers functional, object-oriented, aspect-oriented, reflective and imperative features. It has a simple C#-like syntax and a powerful metaprogramming system.
Nim is a general-purpose, multi-paradigm, statically typed, compiled high-level systems programming language, designed and developed by a team around Andreas Rumpf. Nim is designed to be "efficient, expressive, and elegant", supporting metaprogramming, functional, message passing, procedural, and object-oriented programming styles by providing several features such as compile time code generation, algebraic data types, a foreign function interface (FFI) with C, C++, Objective-C, and JavaScript, and supporting compiling to those same languages as intermediate representations.
 | This statistics-related article is a stub. You can help Wikipedia by expanding it. |
 | This computer-programming-related article is a stub. You can help Wikipedia by expanding it. |