#!/usr/bin/python
# -*- coding: utf-8 -*-

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# Copyright (c) 2012 Michael Hull.
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import numpy
import random


[docs]class MFRandom(object):

    """ A class to centralise random numbers.

    This is centralised so that a seed can be set in a single place in order
    to make simulations repeatable. This is particularly relevant in the case
    of NEURON simulations, which are saved and spawned in another process.
    """

    _seed = None

    @classmethod
[docs]    def seed(cls, seed):
        """ Seed the random number generator

        This method simply calls 'random.seed()' and 'numpy.random.seed()'
        """

        MFRandom._seed = seed
        cls._reseed()

    @classmethod
[docs]    def get_seed(cls):
        """ Returns the current seed used"""

        return cls._seed

    @classmethod
[docs]    def _reseed(cls):
        random.seed(cls._seed)
        numpy.random.seed(cls._seed)


import os
if not os.environ.get('READTHEDOCS', None) == 'True':
    # Randomly initialise the seed:
    MFRandom.seed(random.randint(0, 100000))