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Flow diagram. In computing, serialization (or serialisation, also referred to as pickling in Python) is the process of translating a data structure or object state into a format that can be stored (e.g. files in secondary storage devices, data buffers in primary storage devices) or transmitted (e.g. data streams over computer networks) and reconstructed later (possibly in a different computer ...
^ Means that generic tools/libraries know how to encode, decode, and dereference a reference to another piece of data in the same document. A tool may require the IDL file, but no more. Excludes custom, non-standardized referencing techniques.
Unlike an if-then statement, the method of choice between these alternatives is not directly specified by the programmer; the program must decide at run time between the alternatives, via some general method applied to all choice points. A programmer specifies a limited number of alternatives, but the program must later choose between them ...
In Python, non-innermost-local and not-declared-global accessible names are all aliases. Among dynamically-typed languages, Python is moderately type-checked. Implicit conversion is defined for numeric types (as well as booleans), so one may validly multiply a complex number by an integer (for instance) without explicit casting.
To create a synthetic data point, take the vector between one of those k neighbors, and the current data point. Multiply this vector by a random number x which lies between 0, and 1. Add this to the current data point to create the new, synthetic data point.
A counterpart to /dev/random is /dev/urandom ("unlimited" [8] /non-blocking random source [7]) which reuses the internal pool to produce more pseudo-random bits. This means that the call will not block, but the output may contain less entropy than the corresponding read from /dev/random.
A USB-pluggable hardware true random number generator. In computing, a hardware random number generator (HRNG), true random number generator (TRNG), non-deterministic random bit generator (NRBG), [1] or physical random number generator [2] [3] is a device that generates random numbers from a physical process capable of producing entropy (in other words, the device always has access to a ...
The execution of random inputs is also called random testing or monkey testing. In 1981, Duran and Ntafos formally investigated the effectiveness of testing a program with random inputs. [ 23 ] [ 24 ] While random testing had been widely perceived to be the worst means of testing a program, the authors could show that it is a cost-effective ...