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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.
R. Couture and P. L’Ecuyer [24] Mersenne Twister (MT) 1998 M. Matsumoto and T. Nishimura [25] Closely related with LFSRs. In its MT19937 implementation is probably the most commonly used modern PRNG. Default generator in R and the Python language starting from version 2.3. Xorshift: 2003 G. Marsaglia [26] It is a very fast sub-type of LFSR ...
A singly-linked list structure, implementing a list with three integer elements. The term list is also used for several concrete data structures that can be used to implement abstract lists, especially linked lists and arrays. In some contexts, such as in Lisp programming, the term list may refer specifically to a linked list rather than an array.
initial_ds is the seed data set; current_ds is the latest version of the data set; fit() is a function used to check whether moving the points gets closer to the desired shape; temp is the temperature of the simulated annealing algorithm; similar_enough() is a function that checks whether the statistics for the two given data sets are similar ...
Noam Nisan (1992) showed that this derandomization can actually be achieved with a pseudorandom generator of seed length () that fools all ()-space machines. Nisan's generator has been used by Saks and Zhou (1999) to show that probabilistic log-space computation can be simulated deterministically in space O ( log 1.5 n ...
A random seed (or seed state, or just seed) is a number (or vector) used to initialize a pseudorandom number generator. A pseudorandom number generator's number sequence is completely determined by the seed: thus, if a pseudorandom number generator is later reinitialized with the same seed, it will produce the same sequence of numbers.
Each step, x n−r ·(ab r −1) is added to this integer. This is done in two parts: −1·x n−r is added to x n−r, resulting in a least significant word of zero. And second, a·x n−r is added to the carry. This makes the integer one word longer, producing two new most significant words x n and c n.
In Python, a generator can be thought of as an iterator that contains a frozen stack frame. Whenever next() is called on the iterator, Python resumes the frozen frame, which executes normally until the next yield statement is reached. The generator's frame is then frozen again, and the yielded value is returned to the caller.