def deploy_tokens_and_fund_accounts(
    token_amount: int,
    number_of_tokens: int,
    deploy_service: BlockChainService,
    participants: typing.List[typing.Address],
    contract_manager: ContractManager,
) -> typing.List[typing.TokenAddress]:
    """ Deploy `number_of_tokens` ERC20 token instances with `token_amount` minted and
    distributed among `blockchain_services`. Optionally the instances will be registered with
    the raiden registry.

    Args:
        token_amount (int): number of units that will be created per token
        number_of_tokens (int): number of token instances that will be created
        deploy_service (BlockChainService): the blockchain connection that will deploy
        participants (list(address)): participant addresses that will receive tokens
    """
    result = list()
    for _ in range(number_of_tokens):
        token_address = deploy_contract_web3(
            CONTRACT_HUMAN_STANDARD_TOKEN,
            deploy_service.client,
            contract_manager=contract_manager,
            constructor_arguments=(token_amount, 2, "raiden", "Rd"),
        )

        result.append(token_address)

        # only the creator of the token starts with a balance (deploy_service),
        # transfer from the creator to the other nodes
        for transfer_to in participants:
            deploy_service.token(token_address).transfer(
                to_address=transfer_to, amount=token_amount // len(participants)
            )

    return result
def _check_target_vars(target_names):
    """Error-checks list of target variables.

    Target variables must all have the same mean lead time (average of min and
    max lead times) and event type (tornado or wind).

    :param target_names: 1-D list with names of target variables.  Each must be
        accepted by `target_val_utils.target_name_to_params`.
    :return: mean_lead_time_seconds: Mean lead time (shared by all target
        variables).
    :return: event_type_string: Event type.
    :raises: ValueError: if target variables do not all have the same mean lead
        time or event type.
    """

    error_checking.assert_is_string_list(target_names)
    error_checking.assert_is_numpy_array(
        numpy.array(target_names), num_dimensions=1
    )

    num_target_vars = len(target_names)
    mean_lead_times = numpy.full(num_target_vars, -1, dtype=int)
    event_type_strings = numpy.full(num_target_vars, '', dtype=object)

    for k in range(num_target_vars):
        this_param_dict = target_val_utils.target_name_to_params(
            target_names[k]
        )

        event_type_strings[k] = this_param_dict[target_val_utils.EVENT_TYPE_KEY]

        mean_lead_times[k] = int(numpy.round(
            (this_param_dict[target_val_utils.MAX_LEAD_TIME_KEY] +
             this_param_dict[target_val_utils.MIN_LEAD_TIME_KEY])
            / 2
        ))

    if len(numpy.unique(mean_lead_times)) != 1:
        error_string = (
            'Target variables (listed below) have different mean lead times.'
            '\n{0:s}'
        ).format(str(target_names))

        raise ValueError(error_string)

    if len(numpy.unique(event_type_strings)) != 1:
        error_string = (
            'Target variables (listed below) have different event types.\n{0:s}'
        ).format(str(target_names))

        raise ValueError(error_string)

    return mean_lead_times[0], event_type_strings[0]