Tools for exploring and using the ThermoML Archive from the NIST TRC.
See the arXiv preprint:
Towards Automated Benchmarking of Atomistic Forcefields: Neat Liquid Densities and Static Dielectric Constants from the ThermoML Data Archive Kyle A. Beauchamp, Julie M. Behr, Ariën S. Rustenburg, Christopher I. Bayly, Kenneth Kroenlein, John D. Chodera arXiv:1506.00262
The easiest way to install ThermoPyL is via the conda package manager, which comes with the Anaconda Scientific Python Distribution:
conda config --add channels choderalab
conda install thermopyl
- Create a local mirror of the ThermoML Archive:
thermoml-update-mirror
By default, the archive is placed in ~/.thermoml/
.
You can use the environment variable THERMOML_PATH
to store its location on your disk.
Re-running this command will update the local mirror with new data published in the ThermoML Archive RSS feeds.
2. Run thermoml-build-pandas
to create a pandas version of the database, saved as an HDF5 file in the archive directory.
You can restrict the data subset that will be compiled with command-line arguments. See the command-line help:
% thermoml-build-pandas --help
usage: thermoml-build-pandas [-h] [--journalprefix JOURNALPREFIX]
[--path path]
Build a Pandas dataset from local ThermoML Archive mirror.
optional arguments:
-h, --help show this help message and exit
--journalprefix JOURNALPREFIX
journal prefix to use in globbing *.xml files
--path path path to local ThermoML Archive mirror
- Use Pandas to query the experimental literature:
import thermopyl
# Read ThermoML archive data into pandas dataframe
df = thermopyl.pandas_dataframe()
Datatypes are listed in columns (in addition to useful fields like components
, filename
, and phase
):
datatypes = list(df.columns)
Unavailable data is labeled as NaN
. You can use this to extract useful data by querying on data that is not NaN
.
For example, to extract dataframe rows with mass densities:
# Extract rows with mass densities
densities = df[np.isnan(df['Mass density, kg/m3'])==False]
# Get a list of unique components
unique_components = set(df['components'])
To update an existing locally saved archive via the Python API:
import thermopyl
thermopyl.update_archive()
- Kyle A Beaucamp (MSKCC)
- John D. Chodera (MSKCC)
- Arien Sebastian Rustenburg (MSKCC)