Journal: Journal of Open Source Software

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Open Journals

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2475-9066

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2018 - 201952020 - 202513
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Publications 1 - 10 of 18
  • uDALES: large-eddy-simulation software for urban flow, dispersion, and microclimate modelling
    Item type: Journal Article
    Grylls, Tom; Suter, Ivo; Sützl, Birgit; et al. (2021)
    Journal of Open Source Software
  • A Module for Calibrating Impact Functions in the Climate Risk Modeling Platform CLIMADA
    Item type: Journal Article
    Riedel, Lukas; Kropf, Chahan Michael; Schmid, Timo (2024)
    Journal of Open Source Software
    Impact functions model the vulnerability of people and assets exposed to weather and climate hazards. Given probabilistic hazard event sets or weather forecasts, they enable the computation of associated risks or impacts, respectively. Because impact functions are difficult to determine on larger spatial and temporal scales of interest, they are often calibrated using hazard, exposure, and impact data from past events. We present a module for calibrating impact functions based on such data using established calibration techniques like Bayesian optimization. It is implemented as Python submodule climada.util.calibrate of the climate risk modeling platform CLIMADA, and fully integrates into its workflow.
  • solid_dmft: gray-boxing DFT+DMFT materials simulations
    Item type: Journal Article
    Merkel, Maximilian E.; Carta, Alberto; Beck, Sophie; et al. (2022)
    Journal of Open Source Software
    Strongly correlated systems are a class of materials whose electronic structure is heavily influenced by the effect of electron-electron interactions. In these systems, an effective single-particle description may not capture the many-body effects accurately. Although density functional theory (DFT) plus dynamical mean-field theory (DMFT) has proven successful in describing strongly correlated electron systems for over two decades, only very recently ready-to-use software packages have begun to become available, with most scientific research carried out by in-house codes developed and used in individual research groups. Given the complexity of the method, there is also the question of whether users should implement the formalism themselves for each problem or whether black-box software, analogous to popular DFT packages, would be beneficial to the community. The goal of solid_dmft is to find a middle ground, i.e., a gray-box tool as a ready-to-use implementation. Such a gray-box approach is widely used in other areas of materials simulation (Larsen et al., 2017; Sun et al., 2018). This means that while the code contains all the functionality needed for many standard DMFT calculations, it is highly modular, based on open-source and community-developed software, and therefore can be easily adapted to specific applications and needs. Hence, this project is targeted towards researchers aiming to apply DMFT methods on top of DFT simulations to describe the physics of strongly correlated electron systems. While our approach allows one to fully perform these computations using standardized input flags without need for coding, the end user can easily extend the functionality by modifying relevant modules in the code. The package is MPI-parallelized and written in Python 3, utilizing the publicly available TRIQS software library (Parcollet et al., 2015) and applications based on TRIQS, such as different solvers or interfaces to DFT codes. The goal of this package is to increase reproducibility of DFT+DMFT calculations, provide clearer convergence metrics, and allow one to run calculations for a large variety of systems without adapting the code manually, i.e., on a level similar to widely available DFT simulation packages.
  • reper: Genome-wide identification, classification and quantification of repetitive elements without an assembled genome
    Item type: Journal Article
    Terhoeven, Niklas; Schultz, Jörg; Hackl, Thomas (2018)
    Journal of Open Source Software
  • ThermoFun: A C++/Python library for computing standard thermodynamic properties of substances and reactions across wide ranges of temperatures and pressures
    Item type: Journal Article
    Miron, George Dan; Moreira Mulin Leal, Allan; Dmytrieva, Svitlana V.; et al. (2023)
    Journal of Open Source Software
    ThermoFun is an open source library that facilitates the calculation and retrieval of standard thermodynamic properties of chemical substances, compounds, and reactions among them at a range of temperatures and pressures. The library is developed in C++ for performance, but it also has a Python API for broader and more convenient usage. It employs a variety of thermodynamic models and equations of state for solid, aqueous, surface, gaseous, and molten substances, and their reactions with input properties and parameters from various thermodynamic datasets that are collected and curated in the in ThermoHub database. The library can be used as a standalone code for searching and tabulating thermodynamic properties or linked to other modeling codes that require standard thermodynamic data as input. It offers the flexibility to use different thermodynamic datasets, including custom datasets and datasets retrieved from the online ThermoHub database, and to choose the most suitable models for different classes of substances necessary in various modeling applications. It can serve as a common source of thermodynamic models for standard properties of substances and reactions that can be easily integrated and combined, significantly improving the modeling capabilities for diverse (geo)chemical systems and over wide ranges of conditions.
  • netroles: A Java library for role equivalence analysis
    Item type: Journal Article
    Müller, Julian (2024)
    Journal of Open Source Software
    An important problem in the analysis of networks is structural similarity. It has commonly been expressed in terms of role equivalences, which have often been considered to formalize the concepts of social role and position as discussed by Linton (1936), Merton (1957) and Nadel (1957) in their analyses of social structure (Borgatti & Everett, 1992a). Role equivalences are based on the idea that actors are equivalent or play the same role if they form ties to similar others in similar ways. For example, the role of “doctor” is characterized by a set of ties to others playing related roles like “nurses”, “patients” and “colleagues”. However, this equivalence idea has been interpreted by different authors in different ways, resulting in the proposition of diverse definitions of role equivalence such as structural (Lorrain & White, 1971) or regular equivalence (White & Reitz, 1983). The netroles library provides implementations of many established notions of role equivalence, but more importantly, it offers a unified approach to role equivalence analysis that generalizes beyond the classic role equivalences, allowing users to express more complex kinds of role notions suitable for networks with multiple relations and attributes.
  • chloroExtractor: extraction and assembly of the chloroplast genome from whole genome shotgun data
    Item type: Journal Article
    Ankenbrand, Markus J.; Pfaff, Simon; Terhoeven, Niklas; et al. (2018)
    Journal of Open Source Software
  • DYCO: A Python package to dynamically detect and compensate for time lags in ecosystem time series
    Item type: Journal Article
    Hörtnagl, Lukas (2021)
    Journal of Open Source Software
    In ecosystem research, the eddy covariance (EC) method is widely used to quantify the biosphere-atmosphere exchange of greenhouse gases (GHGs) and energy (Aubinet et al., 2012; Baldocchi et al., 1988). The raw ecosystem flux (i.e., net exchange) is calculated by the covariance between the turbulent vertical wind component measured by a sonic anemometer and the entity of interest, e.g., CO2, measured by a gas analyzer. Due to the application of two different instruments, wind and gas are not recorded at exactly the same time, resulting in a time lag between the two time series. For the calculation of ecosystem fluxes this time delay has to be quantified and corrected for, otherwise fluxes are systematically biased. Time lags for each averaging interval can be estimated by finding the maximum absolute covariance between the two turbulent time series at different time steps in a pre-defined time window of physically possible time-lags (e.g., McMillen, 1988; Moncrieff et al., 1997). Lag detection works well when processing fluxes for compounds with high signal-to-noise ratio (SNR), which is typically the case for e.g. CO2. In contrast, for compounds with low SNR (e.g., N2O, CH4) the cross-covariance function with the turbulent wind component yields noisier results and calculated fluxes are biased towards larger absolute flux values (Langford et al., 2015), which in turn renders the accurate calculation of yearly ecosystem GHG budgets more difficult and results may be inaccurate. One method to adequately calculate fluxes for compounds with low SNR is to first calculate the time lag for a reference compound with high SNR (e.g., CO2) and then to apply the same time lag to the target compound of interest (e.g., N2O), with both compounds being recorded by the same analyzer (Nemitz et al., 2018). DYCO uses this method by facilitating the dynamic lag-detection between the turbulent wind data and a reference compound and the subsequent application of found reference time lags to one or more target compounds.
  • PourPy - A python package to generate potential-pH diagrams
    Item type: Journal Article
    Korber, Anja; Furcas, Fabio E.; Pundir, Mohit; et al. (2024)
    Journal of Open Source Software
    PourPy is an open-source Python package for generating thermodynamic stability diagrams of solid phases and complexes in aqueous electrolytes. These so-called Pourbaix diagrams provide valuable information about the reactivity of chemical elements and compounds as a function of the electrochemical potential and the pH. In the context of corrosion science, environmental and process engineering, Pourbaix diagrams are useful to predict the reactivity of aqueous complexes, the passivation behaviour of metals, and the electrochemical stability of the aqueous electrolyte. PourPy is a tool enabling users to inspect the reactivity of aqueous systems under full control of all chemical species considered. Users can define custom reactive systems containing multiple solid, aqueous and gaseous species thereof and build all (electro)chemical reactions to be considered. The package provides additional functionality to perform basic manipulations on the thermodynamic parameters associated with each chemical component, change the system’s reference electrode as well as calculate the number of phases stable across a given potential-pH space or at discrete values. Future releases are planned to retrieve thermodynamic parameters from established databases including SUPCRT92 (Johnson et al., 1992) and PHREEQC (Parkhurst et al., 1999, 2013).
  • ReinforcementLearning: A Package to Perform Model-Free Reinforcement Learning in R
    Item type: Journal Article
    Pröllochs, Nicolas; Feuerriegel, Stefan (2019)
    Journal of Open Source Software
Publications 1 - 10 of 18