# System properties Similar to what is described in [Library_properties]{.title-ref}, the instances of `lammps `{.interpreted-text role="py:class"}\_\_, `PyLammps `{.interpreted-text role="py:class"}\_\_, or `IPyLammps `{.interpreted-text role="py:class"}\_\_ can be used to extract different kinds of information about the active LAMMPS instance and also to modify some of it. The main difference between the interfaces is how the information is exposed. While the `lammps `{.interpreted-text role="py:class"}\_\_ is just a thin layer that wraps C API calls, `PyLammps `{.interpreted-text role="py:class"}\_\_ and `IPyLammps `{.interpreted-text role="py:class"}\_\_ expose information as objects and properties. In some cases the data returned is a direct reference to the original data inside LAMMPS cast to `ctypes` pointers. Where possible, the wrappers will determine the `ctypes` data type and cast pointers accordingly. If `numpy` is installed arrays can also be extracted as numpy arrays, which will access the C arrays directly and have the correct dimensions to protect against invalid accesses. :::: warning ::: title Warning ::: When accessing per-atom data, please note that this data is the per-processor local data and indexed accordingly. These arrays can change sizes and order at every neighbor list rebuild and atom sort event as atoms are migrating between subdomains. :::: ::::: tabs ::: tab lammps API ``` python from lammps import lammps lmp = lammps() lmp.file("in.sysinit") natoms = lmp.get_natoms() print(f"running simulation with {natoms} atoms") lmp.command("run 1000 post no"); for i in range(10): lmp.command("run 100 pre no post no") pe = lmp.get_thermo("pe") ke = lmp.get_thermo("ke") print(f"PE = {pe}\nKE = {ke}") lmp.close() ``` **Methods**: - `version() `{.interpreted-text role="py:meth"}\_\_: return the numerical version id, e.g. LAMMPS 2 Sep 2015 -\> 20150902 - `get_thermo() `{.interpreted-text role="py:meth"}\_\_: return current value of a thermo keyword - `last_thermo() `{.interpreted-text role="py:meth"}\_\_: return a dictionary of the last thermodynamic output - `get_natoms() `{.interpreted-text role="py:meth"}\_\_: total \# of atoms as int - `reset_box() `{.interpreted-text role="py:meth"}\_\_: reset the simulation box size - `extract_setting() `{.interpreted-text role="py:meth"}\_\_: return a global setting - `extract_global() `{.interpreted-text role="py:meth"}\_\_: extract a global quantity - `extract_box() `{.interpreted-text role="py:meth"}\_\_: extract box info - `create_atoms() `{.interpreted-text role="py:meth"}\_\_: create N atoms with IDs, types, x, v, and image flags **Properties**: - `last_thermo_step `{.interpreted-text role="py:attr"}\_\_: the last timestep thermodynamic output was computed ::: ::: tab PyLammps/IPyLammps API In addition to the functions provided by `lammps `{.interpreted-text role="py:class"}\_\_, `PyLammps `{.interpreted-text role="py:class"}\_\_ objects have several properties which allow you to query the system state: L.system : Is a dictionary describing the system such as the bounding box or number of atoms L.system.xlo, L.system.xhi : bounding box limits along x-axis L.system.ylo, L.system.yhi : bounding box limits along y-axis L.system.zlo, L.system.zhi : bounding box limits along z-axis L.communication : configuration of communication subsystem, such as the number of threads or processors L.communication.nthreads : number of threads used by each LAMMPS process L.communication.nprocs : number of MPI processes used by LAMMPS L.fixes : List of fixes in the current system L.computes : List of active computes in the current system L.dump : List of active dumps in the current system L.groups : List of groups present in the current system **Retrieving the value of an arbitrary LAMMPS expressions** LAMMPS expressions can be immediately evaluated by using the `eval` method. The passed string parameter can be any expression containing global [thermo]{.title-ref} values, variables, compute or fix data (see [Howto_output]{.title-ref}): ``` python result = L.eval("ke") # kinetic energy result = L.eval("pe") # potential energy result = L.eval("v_t/2.0") ``` **Example** ``` python from lammps import PyLammps L = PyLammps() L.file("in.sysinit") print(f"running simulation with {L.system.natoms} atoms") L.run(1000, "post no"); for i in range(10): L.run(100, "pre no post no") pe = L.eval("pe") ke = L.eval("ke") print(f"PE = {pe}\nKE = {ke}") ``` ::: :::::