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nomad-lab
parser-lammps
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temok-mx
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# LAMMPS Parser
This is a NOMAD parser for
[
LAMMPS
](
https://lammps.sandia.gov/
)
. It will read LAMMPS input and
output files and provide all information in NOMAD's unified Metainfo based Archive format.
This is the parser for
[
LAMMPS
](
http://lammps.sandia.gov/
)
.
It is part of the
[
NOMAD Laboratory
](
http://nomad-lab.eu
)
.
The official version lives at
## Preparing code input and output file for uploading to NOMAD
git@gitlab.mpcdf.mpg.de:nomad-lab/parser-lammps.git
NOMAD accepts
`.zip`
and
`.tar.gz`
archives as uploads. Each upload can contain arbitrary
files and directories. NOMAD will automatically try to choose the right parser for you files.
For each parser (i.e. for each supported code) there is one type of file that the respective
parser can recognize. We call these files
`mainfiles`
as they typically are the main
output file a code. For each
`mainfile`
that NOMAD discovers it will create an entry
in the database that users can search, view, and download. NOMAD will associate all files
in the same directory as files that also belong to that entry. Parsers
might also read information from these auxillary files. This way you can add more files
to an entry, even if the respective parser/code might not directly support it.
you can browse it at
For lammps please provide at least the files from this table if applicable to your
calculations (remember that you can provide more files if you want):
https://gitlab.mpcdf.mpg.de/nomad-lab/parser-lammps
It relies on having the nomad-meta-info and the python common repositories one level higher.
The simplest way to have this is to check out nomad-lab-base recursively:
git clone --recursive git@gitlab.mpcdf.mpg.de:nomad-lab/nomad-lab-base.git
To create an upload with all calculations in a directory structure:
then this will be in parsers/lammps.
```
zip -r <upload-file>.zip <directory>/*
```
# Running and Testing the Parser
Go to the
[
NOMAD upload page
](
https://nomad-lab.eu/prod/rae/gui/uploads
)
to upload files
or find instructions about how to upload files from the command line.
## Usage
LAMMPS input/output files can be parsed with:
## Using the parser
python LAMMPSParserControl.py ../../test/examples/input.1_methyl_naphthalene
You can use NOMAD's parsers and normalizers locally on your computer. You need to install
NOMAD's pypi package:
## Test Files
Example input/output files of LAMMPS can be found in the directory test/examples.
```
pip install nomad-lab
```
- /methane/ : NVT simulation on pure CH4 with different logging styles (see input file name)
- /methane_MD_traj/ : NVT simulation on pure CH4 with different trajectory styles (see input file name)
- /hexane_cyclohexane/ : NVT simulation on a binary (equimolar mixture)
- /1_methyl_naphthalene/ : NVT simualtion on pure 1-methylnaphthalene (no trajectory)
To parse code input/output from the command line, you can use NOMAD's command line
interface (CLI) and print the processing results output to stdout:
```
nomad parse --show-archive <path-to-file>
```
To parse a file in Python, you can program something like this:
```
python
import
sys
from
nomad.cli.parse
import
parse
,
normalize_all
# match and run the parser
backend
=
parse
(
sys
.
argv
[
1
])
# run all normalizers
normalize_all
(
backend
)
# get the 'main section' section_run as a metainfo object
section_run
=
backend
.
resource
.
contents
[
0
].
section_run
[
0
]
# get the same data as JSON serializable Python dict
python_dict
=
section_run
.
m_to_dict
()
```
## Developing the parser
Also install NOMAD's pypi package:
```
pip install nomad-lab
```
Clone the parser project and install it in development mode:
```
git clone https://gitlab.mpcdf.mpg.de/nomad-lab/parser-lammps parser-lammps
pip install -e parser-lammps
```
Running the parser now, will use the parser's Python code from the clone project.
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code-label
:
LAMMPS
code-label-style
:
All in capitals
code-url
:
https://lammps.sandia.gov/
parser-dir-name
:
dependencies/parsers/lammps/
parser-git-url
:
https://gitlab.mpcdf.mpg.de/nomad-lab/parser-lammps
table-of-files
:
'
'
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