This package allows the user to run any OpenKIM Test Drivers written using the kim-tools package locally. A “Test Driver” is a computational protocol that reports one or more material properties using the KIM Properties Framework
List of included Test Drivers:
EquilibriumCrystalStructure
ElasticConstantsCrystal
VacancyFormationEnergyRelaxationVolumeCrystal
HeatCapacityThermalExpansionCrystalNPT
GibbsFreeEnergyCrystal
CrystalStructureAndEnergyVsPressure
NPTCrystalStructure
To run one of these calculations, instantiate the class with an interatomic model, which can be a KIM potential installed on your system or an ASE Calculator (not all Test Drivers support ASE Calculators):
from kimvv import ElasticConstantsCrystal
elast = ElasticConstantsCrystal('LennardJones_Ar')
The object you instantiated can now be used to perform property calculations. You are required to provide a crystal structure, which can be specified as an ASE Atoms object (it is also possible to specify a symmetry-reduced crystallographic description, see examples below):
from ase.build import bulk
atoms = bulk('Ar')
results = elast(atoms)
Most Test Drivers accept other optional and/or required arguments. Use the printdoc method for an explanation of each Test Driver’s operation, e.g. ElasticConstantsCrystal.printdoc(). Besides the structure, all Test Drivers accept the universal argument temperature_K, and the mutually exclusive pressure_eV_angstrom3 and cell_cauchy_stress_eV_angstrom3. These are ignored by Test Drivers that are restricted zero temperature and/or stress-free conditions.
Installation
kimvv and all requirements are available in the KIM Developer Platform (KDP) container available here: https://github.com/openkim/developer-platform
kimvv is installable with pip install kimvv, but it requires some non-Python rquirements to be installed first. These prerequisites are decribed in installation info for kim-tools, the backend for kimvv, here: https://kim-tools.readthedocs.io/en/stable/#doc-standalone-installation.
Basic usage example:
Computing elastic constants for FCC argon using an example KIM potential
from kimvv import ElasticConstantsCrystal
from ase.build import bulk
from json import dumps
# The Test Driver must be instantiated with an ASE Calculator object
# or a string indicating a KIM model name
elast = ElasticConstantsCrystal('LennardJones_Ar')
# To perform the computation, call the Test Driver object. The first argument
# to most Test Drivers is the crystal structure to perform the computation on.
# To see an explanation of the calculation and a description of the
# additonal arguments, use .printdoc()
elast.printdoc()
# For the sake of speed, let's compute the elastic constants with the
# "stress-condensed" method, instead of the default robust computation loop.
# The crystal structure can be specified as an Atoms object. Any dependencies
# (e.g. relaxing the crystal structure with EquilibriumCrystalStructure) are
# automatically run.
atoms = bulk("Ar", "fcc", 5.0)
results = elast(atoms, method="stress-condensed")
# Each Test Driver computes a list of one or more dictionaries, each defining
# a material property in the format specified by the KIM Properties Framework.
# The name of the property is in the "property-id" key. See
# https://openkim.org/properties for the definition of each property.
print(dumps(results, indent=2))
Usage example 2
Getting the anisotropic pressure-volume curve of HCP Ag using a non-KIM ASE Calculator and saving the output files
from kimvv import CrystalStructureAndEnergyVsPressure
from ase.build import bulk
from ase.calculators.emt import EMT
# The Test Driver must be instantiated with an ASE Calculator object
# or a string indicating a KIM model name
scan = CrystalStructureAndEnergyVsPressure(EMT())
# To perform the computation, call the Test Driver object. The first argument
# to most Test Drivers is the crystal structure to perform the compuation on.
# To see the additonal arguments, use .printdoc() to print the docstring
scan.printdoc()
# The default volume range of 0.25-4.0 will take a long time to scan. Let's
# do a much smaller range
results = scan(
bulk("Ag", "hcp", 2.92), min_fractional_volume=0.98, max_fractional_volume=1.02
)
# In addition to accessing the results as a Python dictionary, you can save them to
# a file in .edn format. This is especially useful if the Test Driver produces
# auxiliary files, like the pressure scan does. All auxiliary files will be written
# to the parent directory of the path you specified.
scan.write_property_instances_to_file("scan_output/results.edn")
Usage example 3
This example is functionally identical to the previous example, except the crystal is specified by passing a dictionary specifying the symmetry-reduced description of the crystal
from kimvv import CrystalStructureAndEnergyVsPressure
from ase.calculators.emt import EMT
scan = CrystalStructureAndEnergyVsPressure(EMT())
# Specify the material using a symmetry-reduced dictionary.
# Internally, all kimvv Test Drivers use this representation,
# so this allows more direct control, as an Atoms object will
# be converted to this regardless. This allows you to specify
# the crystal in a specific orientation that will be maintained
# Notionally, this should be an instance of the
# `crystal-structure-npt` OpenKIM Property, but the exact schema
# is not enforced. As long as the following fields are present,
# it will work: "prototype-label.source-value",
# "stoichiometric-species.source-value", "a.source-value",
# and, if the crystal has any free parameters,
# "parameter-values.source-value".
# For an exact definition of these fields, see
# https://openkim.org/properties/show/crystal-structure-npt
# For more info about the AFLOW Prototype Designation,
# see section B here: https://arxiv.org/pdf/2401.06875
material = {
"prototype-label": {"source-value": "A_hP2_194_c"},
"stoichiometric-species": {"source-value": ["Ag"]},
"a": {
"source-value": 2.933,
"source-unit": "angstrom",
},
"parameter-names": {"source-value": ["c/a"]},
"parameter-values": {"source-value": [1.6373338]},
}
results = scan(material, min_fractional_volume=0.98, max_fractional_volume=1.02)
scan.write_property_instances_to_file("scan_output/results.edn")
Usage example 4
Querying for all DFT-relaxed structures for a given combination of elements in OpenKIM and relaxing them with your potential
from kimvv import EquilibriumCrystalStructure
from kim_tools import (
query_crystal_structures,
get_deduplicated_property_instances
)
from json import dumps
from ase.calculators.lj import LennardJones
# Query for all relaxed Argon reference data in OpenKIM
# You can narrow the query further by specifying more information
# about the crystal, see
# https://kim-tools.readthedocs.io/en/stable/kim_tools.test_driver.html#kim_tools.test_driver.core.query_crystal_structures
raw_structs = query_crystal_structures(stoichiometric_species=["Ar"])
# Deduplicate them
unique_structs = get_deduplicated_property_instances(raw_structs, allow_rotation=True)
# Instantiate the Driver with your model
relax = EquilibriumCrystalStructure(LennardJones(sigma=3.4,epsilon=0.0104,rc=8.15))
# Run the Driver with each structure. As this is run, the driver internally accumulates
# Property Instances
for struct in unique_structs:
relax(struct)
# In addition to returning the Property Instances for the current run, Test Drivers
# accumulate all computed Property Instances. They can be accessed like this:
print(dumps(relax.property_instances, indent=2))
Metadata
Release files for kimvv 0.1.13
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| kimvv-0.1.13.tar.gz | 120.2 kB | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| kimvv-0.1.13-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 253.1 kB
Release files / kimvv-0.1.13.tar.gz
| Download URL | kimvv-0.1.13.tar.gz |
|---|---|
| Size | 120.2 kB |
| Tags | Source |
|
SHA-256 checksum How to use checksums |
af51950911e274c0e2bf962f06fe0ed1dd5acc69b2aa155f85edccd982c0b313
|
|
BLAKE2b-256 checksum How to use checksums |
aaa0e0f06df819a720779e7d4f56688f4fb1fc19f50c83865595e4585c1c4925
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
Yes |
| Uploaded via |
twine/6.1.0 CPython/3.12.8
|
Provenance
Provenance describes where a file came from. On PyPI, provenance is shared via attestations, which provide a verifiable record of the build or publishing details. View details, limitations and caveats.
PyPI Publish Attestation
PyPI verified that this artifact, at this checksum, originated from the publisher listed below.
Signed by GitHub Actions, verified by PyPI on Jul 30, 2026.
Transparency logRelease files / kimvv-0.1.13-py3-none-any.whl
| Download URL | kimvv-0.1.13-py3-none-any.whl |
|---|---|
| Size | 132.8 kB |
| Tags | Python 3 |
|
SHA-256 checksum How to use checksums |
77fc109cc0585f653681a918984c213fee2451a980666e221954095d0e7b89b5
|
|
BLAKE2b-256 checksum How to use checksums |
97c9dd2ed925cd307e0c353d49e974efc2c18d6b8167995cfb1b853c72671b79
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
Yes |
| Uploaded via |
twine/6.1.0 CPython/3.12.8
|
Provenance
Provenance describes where a file came from. On PyPI, provenance is shared via attestations, which provide a verifiable record of the build or publishing details. View details, limitations and caveats.
PyPI Publish Attestation
PyPI verified that this artifact, at this checksum, originated from the publisher listed below.
Signed by GitHub Actions, verified by PyPI on Jul 30, 2026.
Transparency log