pysrim is a python package that aims to wrap and extend SRIM a
popular tool for simulating ions traveling through a material. There
are many pain points to SRIM and this package aims to address
them. These include compatibility with all OS's, automation and crash
recovery of SRIM calculations, parsing of all output files, and
publication quality plots.
There is now a docker image
costrouc/pysrim for
running pysrim and SRIM! No setup necissary and does not require a
display so it is server ready. If you would like to try it run the
short command below (obviously requires docker). All output files will
be stored in /tmp/output for this example. Benchmarks
show the
docker container is around 50-60% faster. I believe this is due to
using xvfb
docker run -v $PWD/examples/docker:/opt/pysrim/ \
-v /tmp/output:/tmp/output \
-it costrouc/pysrim sh -c "xvfb-run -a python3.6 /opt/pysrim/ni.py"
ls /tmp/output| Latest Release |  |
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| License |  |
| Build Status |  |
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| Documentation | |
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Link to documentation on readthedocs
While TRIM is a great code it has many downsides regarding
automation. The TRIM.IN input file is tedious to write yourself and
the gui that constructs the TRIM.IN will crash at unexpeced moments.
One of these crashes everyone has encountered is the fact that a float
text field can never be empty. TRIM also has a tendancy to crash
becuase it stores all cascades in memory. Meaning that for large runs
with full cascades greater than 1,000 ions it will run out of
memory. pysrim addresses all of these issues by providing a simple
API wrapper for the input file (supporting all of the features),
ability to run on all operating systems (using
wine
for linux and OSX), and allowing batch runs of calculations see this
notebook
example.
Below is a hello world example of using pysrim for running a TRIM
calcualtion. Note that /tmp/srim is the path to the SRIM executable
directory (SRIM.exe should reside in this directory). pysrim will
add all the necessary input files. If this ran successfully for you a
SRIM window will popup and start the calculation.
from srim import Ion, Layer, Target, TRIM
# Construct a 3MeV Nickel ion
ion = Ion('Ni', energy=3.0e6)
# Construct a layer of nick 20um thick with a displacement energy of 30 eV
layer = Layer({
'Ni': {
'stoich': 1.0,
'E_d': 30.0,
'lattice': 0.0,
'surface': 3.0
}}, density=8.9, width=20000.0)
# Construct a target of a single layer of Nickel
target = Target([layer])
# Initialize a TRIM calculation with given target and ion for 25 ions, quick calculation
trim = TRIM(target, ion, number_ions=25, calculation=1)
# Specify the directory of SRIM.exe
# For windows users the path will include C://...
srim_executable_directory = '/tmp/srim'
# takes about 10 seconds on my laptop
results = trim.run(srim_executable_directory)
# If all went successfull you should have seen a TRIM window popup and run 25 ions!
# results is `srim.output.Results` and contains all output files parsedSee documentation for all available options.
After a SRIM calculation has completed run copy_output_files to take
all of the output files and move them to a directory of your liking.
from srim import TRIM
TRIM.copy_output_files('/tmp/srim', '/home/costrouc/scratch/srim')By far the hardest part about running TRIM calculations is analyzing
the output files. pysrim comes with parsers for
IONIZ.txt,
VACANCY.txt,
NOVAC.txt,
E2RECOIL.txt,
PHONON.txt,
RANGE.txt,
and
COLLISON.txt. The
COLLISON.txt file can get quite large so the Collision parser uses a
buffered reader that can handle any file size. Additinally a class
srim.output.Results
will processes all output files in a directory and provide a
dictionary of each parsed output file. pysrim comes with some
helpful plotting utilities such a plotting the DPA vs depth. However,
pysrim's most powerful feature is that all of the text files are
exposed as numpy arrays. The example below shows how to plot DPA using
a simple math and numpy. This enables the user to seamlessly use TRIM
and do analysis.
from srim.output import Phonons, Ioniz
def plot_damage_energy(folder, ax):
phon = Phonons(folder)
dx = max(phon.depth) / 100.0
energy_damage = (phon.ions + phon.recoils) * dx
ax.plot(phon.depth, energy_damage / phon.num_ions, label='{}'.format(folder))
return sum(energy_damage)
def plot_ionization(folder, ax):
ioniz = Ioniz(folder)
dx = max(ioniz.depth) / 100.0
ax.plot(ioniz.depth, ioniz.ions, label='Ionization from Ions')
ax.plot(ioniz.depth, ioniz.recoils, label='Ionization from Recoils')Set folders to list of directories to SRIM outputs. See
Analysis
for detailed example. Notice how there is a python class for each SRIM
output file and gives simple access to each column. This did require
some complex regex to get working just right.
folders = ['test_files/2', 'test_files/4']
image_directory = 'examples/images'
fig, axes = plt.subplots(1, len(folders), sharey=True, sharex=True)
for ax, folder in zip(np.ravel(axes), folders):
plot_damage_energy(folder, ax)
plot_ionization(folder, ax)
ax.legend()
ax.set_ylabel('eV')
ax.set_xlabel('Depth [Angstroms]')
fig.suptitle('Ionization Energy vs Depth', fontsize=15)
fig.set_size_inches((20, 6))
fig.savefig(os.path.join(image_directory, 'ionizationvsdepth.png'), transparent=True)
See [jupyter notebook](<https://gitlab.com/costrouc/pysrim/blob/master/examples/notebooks/Analysis.ipynb) for full demonstration of features.
An example of creating some publication graphics with pysrim can also be found in that directory. I have used this in a publication.
Installation of pysrim is easy via pip or conda.
Available on PyPi
pip install pysrim
Available on Conda
conda install -c costrouc pysrim
Available on Docker
docker pull costrouc/pysrim
Unless you are using the docker image, you will need to install SRIM on your machine using the instructions bellow for linux, OSX, and windows.
There is a docker container with pysrim and SRIM already
installed. Some interesting tricks had to be done with using wine and
faking an X11 session. xvfb-run -a creates a fake X11 session
within the docker container therefore allowing SRIM to run on servers
without displays. This is the method that I always use to run SRIM.
Image: costrouc/pysrim
For linux an OSX you will need to first have wine installed. See this
post on
installation of wine on OSX. For linux you will typically be able to
install wine via apt get install wine or yum install wine. SRIM is
compatible
with wine.
Once you have wine installed run the installer
script
install.sh.
Click extract and then done.
A collegue of mine has gotten it to work easily on Windows but I
myself have no experience. Just download the executable at
srim.org. Next you will extract the SRIM files
into a directory on your windows machine. Note the directory of
installation as it will be needed from trim.run().
All contributions, bug reports, bug fixes, documentation improvements, enhancements and ideas are welcome! These should be submitted at the Github repository. Github is only used for visibility.
Contributors:
- Chris Ostrouchov (maintainer)
- Alex Hanson
- dschwen
MIT