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Code: Alles auswählen

# Prozess 0
import random
random.seed()
random_state = random.getstate()
# Nun random_state an Prozesse verteilen und je 100000 Zahlen generieren

# Prozess 1
random.setstate(random_state)
random.jumpahead(0)
return [random.random() for i in xrange(100000)]

# Prozess 2
random.setstate(random_state)
random.jumpahead(100000)
return [random.random() for i in xrange(100000)]

# Prozess 3
random.setstate(random_state)
random.jumpahead(200000)
return [random.random() for i in xrange(100000)]

# und so weiter

Code: Alles auswählen

def jumpahead(n):
    x = 100000
    # For Loop über Ganzahldivision von n/x wegen Speicherverbrauch
    for i in xrange(n/x):
        numpy.random.rand(x)
    # Nun noch der Rest
    numpy.random.rand(n%x)

Code: Alles auswählen

def jumpahead(self, n):
        """Act as if n calls to random() were made, but quickly.

        n is an int, greater than or equal to 0.

        Example use:  If you have 2 threads and know that each will
        consume no more than a million random numbers, create two Random
        objects r1 and r2, then do
            r2.setstate(r1.getstate())
            r2.jumpahead(1000000)
        Then r1 and r2 will use guaranteed-disjoint segments of the full
        period.
        """

        if not n >= 0:
            raise ValueError("n must be >= 0")
        x, y, z = self._seed
        x = int(x * pow(171, n, 30269)) % 30269
        y = int(y * pow(172, n, 30307)) % 30307
        z = int(z * pow(170, n, 30323)) % 30323
        self._seed = x, y, z