Make thermo output accessable through PyLammps

            self.lmp.eval("fy[%d]" % self.index))

def get_thermo_data(output):

    """ traverse output of runs and extract thermo data columns """

    if isinstance(output, str):

        lines = output.splitlines()

    else:

        lines = output

    runs = []

    columns = []

    in_run = False

    for line in lines:

        if line.startswith("Memory usage per processor"):

            in_run = True

        elif in_run and len(columns) == 0:

            # first line after memory usage are column names

            columns = line.split()

            current_run = {}

            for col in columns:

                current_run[col] = []

        elif line.startswith("Loop time of "):

            in_run = False

            columns = None

            thermo_data = namedtuple('ThermoData', list(current_run.keys()))(*list(current_run.values()))

            r = {'thermo' : thermo_data }

            runs.append(namedtuple('Run', list(r.keys()))(*list(r.values())))

        elif in_run and len(columns) > 0:

            values = [float(x) for x in line.split()]

            for i, col in enumerate(columns):

                current_run[col].append(values[i])

    return runs

class PyLammps(object):

  """

  More Python-like wrapper for LAMMPS (e.g., for iPython)

      self.lmp = lammps(name=name,cmdargs=cmdargs,ptr=None,comm=comm)

    print("LAMMPS output is captured by PyLammps wrapper")

    self._cmd_history = []

    self.runs = []

  def __del__(self):

    if self.lmp: self.lmp.close()

    self.lmp.command(cmd)

    self._cmd_history.append(cmd)

  def run(self, *args, **kwargs):

    output = self.__getattr__('run')(*args, **kwargs)

    self.runs += get_thermo_data(output)

    return output

  @property

  def last_run(self):

    if len(self.runs) > 0:

        return self.runs[-1]

    return None

  @property

  def atoms(self):

    return AtomList(self)