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In languages which support first-class functions and currying, map may be partially applied to lift a function that works on only one value to an element-wise equivalent that works on an entire container; for example, map square is a Haskell function which squares each element of a list.
Sets can be considered sub-cases of corresponding Maps in which the values are always a particular constant which can be ignored, although the Set API uses corresponding but differently named methods. At the bottom is the java.util.concurrent.ConcurrentNavigableMap, which is a multiple-inheritance. java.util.Collection. java.util.Map. java.util ...
The user can search for elements in an associative array, and delete elements from the array. The following shows how multi-dimensional associative arrays can be simulated in standard AWK using concatenation and the built-in string-separator variable SUBSEP:
This is the case for tree-based implementations, one representative being the <map> container of C++. [16] The order of enumeration is key-independent and is instead based on the order of insertion. This is the case for the "ordered dictionary" in .NET Framework, the LinkedHashMap of Java and Python. [17] [18] [19] The latter is more common.
Maps are data structures that associate a key with an element. This lets the map be very flexible. If the key is the hash code of the element, the Map is essentially a Set. If it's just an increasing number, it becomes a list. Examples of Map implementations include java.util.HashMap, java.util.LinkedHashMap, and java.util.TreeMap.
One subtlety is that the value of a method call ("message") in a cascade is still the ordinary value of the message, not the receiver. This is a problem when you do want the value of the receiver, for example when building up a complex value. This can be worked around by using the special yourself method that simply returns the receiver: [2]
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.
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.