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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:
In Python 2.x is possible to use a function called xrange() which returns an object that generates the numbers in the range on demand. The advantage of xrange is that generated object will always take the same amount of memory.
Using a factory method to create instances of a class (factory method pattern) Storing the instances in a map, and returning the same instance to each request for an instance with same parameters (multiton pattern) Using lazy initialization to instantiate the object the first time it is requested (lazy initialization pattern)
The probability distribution of the sum of two or more independent random variables is the convolution of their individual distributions. The term is motivated by the fact that the probability mass function or probability density function of a sum of independent random variables is the convolution of their corresponding probability mass functions or probability density functions respectively.
If g is a general function, then the probability that g(X) is valued in a set of real numbers K equals the probability that X is valued in g −1 (K), which is given by (). Under various conditions on g , the change-of-variables formula for integration can be applied to relate this to an integral over K , and hence to identify the density of g ...
Starting with Python 3.12, the built-in "sum()" function uses the Neumaier summation. [ 25 ] In the Julia language, the default implementation of the sum function does pairwise summation for high accuracy with good performance, [ 26 ] but an external library provides an implementation of Neumaier's variant named sum_kbn for the cases when ...
We are given an instance of 3DM, where the vertex sets are W, X, Y. Each set has n vertices. There are m edges, where each edge contains exactly one vertex from each of W, X, Y. Denote L := ceiling(log 2 (m+1)), so that L is larger than the number of bits required to represent the number of edges. We construct an instance of SSP with m positive ...
The extraneous intermediate list structure can be eliminated with the continuation-passing style technique, foldr f z xs == foldl (\ k x-> k. f x) id xs z; similarly, foldl f z xs == foldr (\ x k-> k. flip f x) id xs z ( flip is only needed in languages like Haskell with its flipped order of arguments to the combining function of foldl unlike e ...