Output structured data from LAMMPS ################################## LAMMPS can output structured data with the :doc:`print ` and :doc:`fix print ` command. This gives you flexibility since you can build custom data formats that contain system properties, thermo data, and variables values. This output can be directed to the screen and/or to a file for post processing. Writing the current system state, thermo data, variable values ============================================================== Use the :doc:`print ` command to output the current system state, which can include system properties, thermo data and variable values. YAML ---- .. code-block:: LAMMPS print """--- timestep: $(step) pe: $(pe) ke: $(ke) ...""" file current_state.yaml screen no .. code-block:: yaml :caption: current_state.yaml --- timestep: 250 pe: -4.7774327356321810711 ke: 2.4962152903997174569 JSON ---- .. code-block:: LAMMPS print """{ "timestep": $(step), "pe": $(pe), "ke": $(ke) }""" file current_state.json screen no .. code-block:: JSON :caption: current_state.json { "timestep": 250, "pe": -4.7774327356321810711, "ke": 2.4962152903997174569 } YAML format thermo_style output =============================== .. versionadded:: 24Mar2022 LAMMPS supports the thermo style "yaml" and for "custom" style thermodynamic output the format can be changed to YAML with :doc:`thermo_modify line yaml `. This will produce a block of output in a compact YAML format - one "document" per run - of the following style: .. code-block:: yaml --- keywords: [Step, Temp, E_pair, E_mol, TotEng, Press, ] data: - [100, 0.757453103239935, -5.7585054860159, 0, -4.62236133677021, 0.207261053624721, ] - [110, 0.759322359337036, -5.7614668389562, 0, -4.62251889318624, 0.194314975399602, ] - [120, 0.759372342462676, -5.76149365656489, 0, -4.62247073844943, 0.191600048851267, ] - [130, 0.756833027516501, -5.75777334823494, 0, -4.62255928350835, 0.208792327853067, ] ... This data can be extracted and parsed from a log file using python with: .. code-block:: python import re, yaml try: from yaml import CSafeLoader as Loader, CSafeDumper as Dumper except ImportError: from yaml import SafeLoader as Loader, SafeDumper as Dumper docs = "" with open("log.lammps") as f: for line in f: m = re.search(r"^(keywords:.*$|data:$|---$|\.\.\.$| - \[.*\]$)", line) if m: docs += m.group(0) + '\n' thermo = list(yaml.load_all(docs, Loader=Loader)) print("Number of runs: ", len(thermo)) print(thermo[1]['keywords'][4], ' = ', thermo[1]['data'][2][4]) After loading the YAML data, `thermo` is a list containing a dictionary for each "run" where the tag "keywords" maps to the list of thermo header strings and the tag "data" has a list of lists where the outer list represents the lines of output and the inner list the values of the columns matching the header keywords for that step. The second print() command for example will print the header string for the fifth keyword of the second run and the corresponding value for the third output line of that run: .. parsed-literal:: Number of runs: 2 TotEng = -4.62140097780047 Writing continuous data during a simulation =========================================== The :doc:`fix print ` command allows you to output an arbitrary string at defined times during a simulation run. YAML ---- .. code-block:: LAMMPS fix extra all print 50 """ - timestep: $(step) pe: $(pe) ke: $(ke)""" file output.yaml screen no .. code-block:: yaml :caption: output.yaml # Fix print output for fix extra - timestep: 0 pe: -6.77336805325924729 ke: 4.4988750000000026219 - timestep: 50 pe: -4.8082494418323200591 ke: 2.5257981827119797558 - timestep: 100 pe: -4.7875608875581505686 ke: 2.5062598821985102582 - timestep: 150 pe: -4.7471033686005483787 ke: 2.466095925545450207 - timestep: 200 pe: -4.7509052858544134068 ke: 2.4701136792591693592 - timestep: 250 pe: -4.7774327356321810711 ke: 2.4962152903997174569 Post-processing of YAML files can be easily be done with Python and other scripting languages. In case of Python the `yaml` package allows you to load the data files and obtain a list of dictionaries. .. code-block:: python import yaml with open("output.yaml") as f: data = yaml.load(f, Loader=yaml.FullLoader) print(data) .. code-block:: [{'timestep': 0, 'pe': -6.773368053259247, 'ke': 4.498875000000003}, {'timestep': 50, 'pe': -4.80824944183232, 'ke': 2.5257981827119798}, {'timestep': 100, 'pe': -4.787560887558151, 'ke': 2.5062598821985103}, {'timestep': 150, 'pe': -4.747103368600548, 'ke': 2.46609592554545}, {'timestep': 200, 'pe': -4.750905285854413, 'ke': 2.4701136792591694}, {'timestep': 250, 'pe': -4.777432735632181, 'ke': 2.4962152903997175}] Line Delimited JSON (LD-JSON) ----------------------------- The JSON format itself is very strict when it comes to delimiters. For continuous output/streaming data it is beneficial use the *line delimited JSON* format. Each line represents one JSON object. .. code-block:: LAMMPS fix extra all print 50 """{"timestep": $(step), "pe": $(pe), "ke": $(ke)}""" title "" file output.json screen no .. code-block:: json :caption: output.json {"timestep": 0, "pe": -6.77336805325924729, "ke": 4.4988750000000026219} {"timestep": 50, "pe": -4.8082494418323200591, "ke": 2.5257981827119797558} {"timestep": 100, "pe": -4.7875608875581505686, "ke": 2.5062598821985102582} {"timestep": 150, "pe": -4.7471033686005483787, "ke": 2.466095925545450207} {"timestep": 200, "pe": -4.7509052858544134068, "ke": 2.4701136792591693592} {"timestep": 250, "pe": -4.7774327356321810711, "ke": 2.4962152903997174569} One simple way to load this data into a Python script is to use the `pandas` package. It can directly load these files into a data frame: .. code-block:: python import pandas as pd data = pd.read_json('output.json', lines=True) print(data) .. code-block:: bash timestep pe ke 0 0 -6.773368 4.498875 1 50 -4.808249 2.525798 2 100 -4.787561 2.506260 3 150 -4.747103 2.466096 4 200 -4.750905 2.470114 5 250 -4.777433 2.496215