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This can only be done for a variadic parameter. It is not possible to apply an array of arguments to non-variadic parameter without using reflection. An ambiguous case arises should the caller want to pass an array itself as one of the arguments rather than using the array as a list of arguments.
In functional programming languages, variadics can be considered complementary to the apply function, which takes a function and a list/sequence/array as arguments, and calls the function with the arguments supplied in that list, thus passing a variable number of arguments to the function.
A function call using named parameters differs from a regular function call in that the arguments are passed by associating each one with a parameter name, instead of providing an ordered list of arguments. For example, consider this Java or C# method call that doesn't use named parameters:
In addition to support for vectorized arithmetic and relational operations, these languages also vectorize common mathematical functions such as sine. For example, if x is an array, then y = sin (x) will result in an array y whose elements are sine of the corresponding elements of the array x. Vectorized index operations are also supported.
A recursive function named foo, which is passed a single parameter, x, and if the parameter is 0 will call a different function named bar and otherwise will call baz, passing x, and also call itself recursively, passing x-1 as the parameter, could be implemented like this in Python:
Folds can be regarded as consistently replacing the structural components of a data structure with functions and values. Lists, for example, are built up in many functional languages from two primitives: any list is either an empty list, commonly called nil ([]), or is constructed by prefixing an element in front of another list, creating what is called a cons node ( Cons(X1,Cons(X2,Cons ...
Array#map passes 3 arguments to func: the element, the index of the element, and the array. Unused arguments can be omitted. Unused arguments can be omitted. Stops at the end of List1 , extending the shorter arrays with undefined items if needed.
NumPy (pronounced / ˈ n ʌ m p aɪ / NUM-py) is a library for the Python programming language, adding support for large, multi-dimensional arrays and matrices, along with a large collection of high-level mathematical functions to operate on these arrays. [3]