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 mtpa(pmrel, i1max, title='', projection='', ax=0):
    """create a line or surface plot with torque and mtpa curve"""
    nsamples = 10
    i1 = np.linspace(0, i1max, nsamples)
    iopt = np.array([pmrel.mtpa(x) for x in i1]).T

    iqmax, idmax = pmrel.iqdmax(i1max)
    iqmin, idmin = pmrel.iqdmin(i1max)

    if projection == '3d':
        nsamples = 50
    else:
        if iqmin == 0:
            iqmin = 0.1*iqmax
    id = np.linspace(idmin, idmax, nsamples)
    iq = np.linspace(iqmin, iqmax, nsamples)

    torque_iqd = np.array(
        [[pmrel.torque_iqd(x, y)
          for y in id] for x in iq])
    if projection == '3d':
        ax = idq_torque(id, iq, torque_iqd, ax)
        ax.plot(iopt[1], iopt[0], iopt[2],
                color='red', linewidth=2, label='MTPA: {0:5.0f} Nm'.format(
                    np.max(iopt[2][-1])))
    else:
        if ax == 0:
            ax = plt.gca()

        ax.set_aspect('equal')
        x, y = np.meshgrid(id, iq)
        CS = ax.contour(x, y, torque_iqd, 6, colors='k')
        ax.clabel(CS, fmt='%d', inline=1)

        ax.set_xlabel('Id/A')
        ax.set_ylabel('Iq/A')
        ax.plot(iopt[1], iopt[0],
                color='red', linewidth=2, label='MTPA: {0:5.0f} Nm'.format(
                    np.max(iopt[2][-1])))
        ax.grid()

    if title:
        ax.set_title(title)
    ax.legend()