TY - JOUR
T1 - TANGOS
T2 - The Agile Numerical Galaxy Organization System
AU - Pontzen, Andrew
AU - Tremmel, Michael
N1 - Publisher Copyright:
© 2018. The American Astronomical Society. All rights reserved.
PY - 2018/8
Y1 - 2018/8
N2 - We present tangos, a Python framework and web interface for database-driven analysis of numerical structure formation simulations. To understand the role that such a tool can play, consider constructing a history for the absolute magnitude of each galaxy within a simulation. The magnitudes must first be calculated for all halos at all timesteps and then linked using a merger tree; folding the required information into a final analysis can entail significant effort. Tangos is a generic solution to this information organization problem, aiming to free users from the details of data management. At the querying stage, our example of gathering properties over history is reduced to a few clicks or a simple, single-line Python command. The framework is highly extensible; in particular, users are expected to define their own properties, which tangos will write into the database. A variety of parallelization options are available and the raw simulation data can be read using existing libraries such as pynbody or yt. Finally, tangos-based databases and analysis pipelines can easily be shared with collaborators or the broader community to ensure reproducibility. User documentation is provided separately.
AB - We present tangos, a Python framework and web interface for database-driven analysis of numerical structure formation simulations. To understand the role that such a tool can play, consider constructing a history for the absolute magnitude of each galaxy within a simulation. The magnitudes must first be calculated for all halos at all timesteps and then linked using a merger tree; folding the required information into a final analysis can entail significant effort. Tangos is a generic solution to this information organization problem, aiming to free users from the details of data management. At the querying stage, our example of gathering properties over history is reduced to a few clicks or a simple, single-line Python command. The framework is highly extensible; in particular, users are expected to define their own properties, which tangos will write into the database. A variety of parallelization options are available and the raw simulation data can be read using existing libraries such as pynbody or yt. Finally, tangos-based databases and analysis pipelines can easily be shared with collaborators or the broader community to ensure reproducibility. User documentation is provided separately.
KW - methods: data analysis
KW - methods: numerical
UR - https://www.scopus.com/pages/publications/85052368277
U2 - 10.3847/1538-4365/aac832
DO - 10.3847/1538-4365/aac832
M3 - Article
AN - SCOPUS:85052368277
SN - 0067-0049
VL - 237
JO - Astrophysical Journal, Supplement Series
JF - Astrophysical Journal, Supplement Series
IS - 2
M1 - 23
ER -