Search results
Results From The WOW.Com Content Network
The JS++ programming language is able to analyze if an array index or map key is out-of-bounds at compile time using existent types, which is a nominal type describing whether the index or key is within-bounds or out-of-bounds and guides code generation. Existent types have been shown to add only 1ms overhead to compile times.
When one has an associative array (mapping, hash map) whose keys are (references to) objects, for example to hold auxiliary data about objects, using weak references for the keys avoids keeping the objects alive just because of their use as keys. When one has an object where other objects are registered, such as in the observer pattern ...
In mathematical terms, an associative array is a function with finite domain. [1] It supports 'lookup', 'remove', and 'insert' operations. The dictionary problem is the classic problem of designing efficient data structures that implement associative arrays. [2] The two major solutions to the dictionary problem are hash tables and search trees.
For example, to perform an element by element sum of two arrays, a and b to produce a third c, it is only necessary to write c = a + b In addition to support for vectorized arithmetic and relational operations, these languages also vectorize common mathematical functions such as sine.
The cross product operation is an example of a vector rank function because it operates on vectors, not scalars. Matrix multiplication is an example of a 2-rank function, because it operates on 2-dimensional objects (matrices). Collapse operators reduce the dimensionality of an input data array by one or more dimensions. For example, summing ...
So, PHP can have non-consecutively numerically indexed arrays. The keys have to be of integer (floating point numbers are truncated to integer) or string type, while values can be of arbitrary types, including other arrays and objects. The arrays are heterogeneous: a single array can have keys of different types.
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]
This is a generalization of single-dispatch polymorphism where a function or method call is dynamically dispatched based on the derived type of the object on which the method has been called. Multiple dispatch routes the dynamic dispatch to the implementing function or method using the combined characteristics of one or more arguments.