Legacy Documentation

This section describes the legacy interface using the File class. This interface is maintained for backward compatibility.

Getting log data

from lammps_logfile import File
import os

# We are in docs/api_reference/legacy/python
# We need to go up to api_reference, then docs, then root, then examples/logfiles/crack_log.lammps
# That is ../../../../examples/logfiles/crack_log.lammps

Now the arrays t and temp contain the log data corresponding to the Time and Temp columns in the log file.

Plotting log data


t = log.get("Time")
temp = log.get("Temp")

import matplotlib.pyplot as plt

plt.plot(t, temp)

To make the plot pop up in a window rather than being saved to a file, run plt.show() rather than plt.savefig(...).

Plot of temperature vs. time

Plot of temperature vs. time

Running average

plt.ylabel("Temperature (K)")
plt.ylim([215, 225])
plt.savefig("time_temp.png")

from lammps_logfile import running_mean

temp_avg = running_mean(temp, 100)

plt.plot(t, temp_avg)
Plot of temperature vs. time

Plot of temperature vs. time. The blue curve is the raw output, whereas in the orange curve the temperature has been smoothed over a 100 log entries wide averaging window.

What data are available in the log file?

To inspect what columns are available, you can run the get_keywords-method on the File object:

print(log.get_keywords())

This command yields an output like the one below, which shows what columns we may get from the File object:

['Density', 'E_angle', 'E_bond', 'E_coul', 'E_dihed', 'E_impro', 'E_long', 'E_vdwl', 'KinEng', 'Lx', 'Ly', 'Lz', 'PotEng', 'Press', 'Pxx', 'Pxy', 'Pxz', 'Pyy', 'Pyz', 'Pzz', 'Step', 'Temp', 'Time', 'TotEng', 'methaneM', 'waterMsd']

Legacy File API

class File(ifile)

Bases: object

Class for handling lammps log files.

Parameters:

ifile (str or file) – Path to lammps log file or a file-like object.

flush_dict_and_set_new_keyword(keywords)
get(entry_name, run_num=-1)

Get time-series from log file by name.

If the rows in the log file changes between runs, the logs are being flushed.

Parameters:

  • entry_name (str) – Name of the entry, for example “Temp”.

  • run_num (int, optional) – Lammps simulations commonly involve several run-commands. Here you may choose what run you want the log data from. Default of -1 returns data from all runs concatenated.

Returns:

Array containing the requested data, or None if the entry is not found.

Return type:

numpy.ndarray or None

get_keywords(run_num=-1)

Return list of available data columns in the log file.

Parameters:

run_num (int, optional) – The run number to get keywords for. Default is -1 (all unique keywords found).

Returns:

Sorted list of available data columns.

Return type:

list

get_num_partial_logs()

Returns the number of partial logs (runs) found in the file.

Returns:

Number of runs.

Return type:

int

property names

Exposes the keywords returned by get_keywords.

Returns:

List of keywords.

Return type:

list

read_file_to_dict()
to_dataframe(run_num=-1)

Converts the log data for a specific run to a pandas DataFrame.

Parameters:

run_num (int, optional) – The run number to convert. Default is -1 (last run).

Returns:

DataFrame containing the log data for the specified run.

Return type:

pandas.DataFrame

to_exdir_group(name, exdirfile)

Writes the log file data to an Exdir group.

Parameters:

  • name (str) – Name of the group to create.

  • exdirfile (exdir.File) – The Exdir file object to write to.