def qloguniform(low, high, q, random_state):
    '''
    low: an float that represent an lower bound
    high: an float that represent an upper bound
    q: sample step
    random_state: an object of numpy.random.RandomState
    '''
    return np.round(loguniform(low, high, random_state) / q) * q
def qloguniform ( low , high , q , random_state ) : return np . round ( loguniform ( low , high , random_state ) / q ) * q
low: an float that represent an lower bound
    high: an float that represent an upper bound
    q: sample step
    random_state: an object of numpy.random.RandomState