def deploy_service_registry_and_set_urls(
    private_keys, web3, contract_manager, service_registry_address
) -> Tuple[ServiceRegistry, List[str]]:
    urls = ["http://foo", "http://boo", "http://coo"]
    c1_client = JSONRPCClient(web3, private_keys[0])
    c1_service_proxy = ServiceRegistry(
        jsonrpc_client=c1_client,
        service_registry_address=service_registry_address,
        contract_manager=contract_manager,
    )
    c2_client = JSONRPCClient(web3, private_keys[1])
    c2_service_proxy = ServiceRegistry(
        jsonrpc_client=c2_client,
        service_registry_address=service_registry_address,
        contract_manager=contract_manager,
    )
    c3_client = JSONRPCClient(web3, private_keys[2])
    c3_service_proxy = ServiceRegistry(
        jsonrpc_client=c3_client,
        service_registry_address=service_registry_address,
        contract_manager=contract_manager,
    )

    # Test that getting a random service for an empty registry returns None
    pfs_address = get_random_service(c1_service_proxy, "latest")
    assert pfs_address is None

    # Test that setting the urls works
    c1_service_proxy.set_url(urls[0])
    c2_service_proxy.set_url(urls[1])
    c3_service_proxy.set_url(urls[2])

    return c1_service_proxy, urls
def gerrity_score(self):
        """
        Gerrity Score, which weights each cell in the contingency table by its observed relative frequency.
        :return:
        """
        k = self.table.shape[0]
        n = float(self.table.sum())
        p_o = self.table.sum(axis=0) / n
        p_sum = np.cumsum(p_o)[:-1]
        a = (1.0 - p_sum) / p_sum
        s = np.zeros(self.table.shape, dtype=float)
        for (i, j) in np.ndindex(*s.shape):
            if i == j:
                s[i, j] = 1.0 / (k - 1.0) * (np.sum(1.0 / a[0:j]) + np.sum(a[j:k - 1]))
            elif i < j:
                s[i, j] = 1.0 / (k - 1.0) * (np.sum(1.0 / a[0:i]) - (j - i) + np.sum(a[j:k - 1]))
            else:
                s[i, j] = s[j, i]
        return np.sum(self.table / float(self.table.sum()) * s)