"test_consistency" test cases failing on servers

[ggand0]

def test_consistency(self):
    # Ensure that returned values stay the same when setting a fixed seed.
    mu, beta = 0, 1
    gumbel_sample = Gumbel_sample(temp=0.01, seed=1234567890)
    actual = TestGumbelSample.get_sample(mu, beta, gumbel_sample, 5)
    desired = [
        1.7462246417999268,
        0.2874840497970581,
        0.9974965453147888,
        0.3290553689002991,
        -1.0215276479721069
    ]
    assert_array_almost_equal(actual, desired, decimal=15)

Added test cases ensuring the consistency of sampling methods, and they all passed on the local environment.
However, if we set the decimals more than 6 or 7, test cases other than Gaussian and Gumbel distributions will fail when run on other machines including servers.

Example log on travis ci:

_____________________ TestBernoulliSample.test_consistency _____________________
self = <Tars.tests.test_distribution_samples.TestBernoulliSample testMethod=test_consistency>
    def test_consistency(self):
        # Ensure that returned values stay the same when setting a fixed seed.
        mean = 0.5
        bernoulli_sample = Bernoulli_sample(temp=0.1, seed=1234567890)
        actual = TestBernoulliSample.get_sample(mean, bernoulli_sample, 5)
        desired = [
            0.9999971508356551,
            0.9101269246280252,
            0.0248156363467501,
            0.3538078165724645,
            0.1615775890919983
        ]
>       assert_array_almost_equal(actual, desired, decimal=15)
E       AssertionError: 
E       Arrays are not almost equal to 15 decimals
E       
E       (mismatch 20.0%)
E        x: array([ 0.999997150839051,  0.910126924628025,  0.02481563634675 ,
E               0.353807816572465,  0.161577589091998])
E        y: array([ 0.999997150835655,  0.910126924628025,  0.02481563634675 ,
E               0.353807816572465,  0.161577589091998])
Tars/tests/test_distribution_samples.py:97: AssertionError