10,308 research outputs found

    mage: Fluid Moves Between Code and Graphical Work in Computational Notebooks

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    We aim to increase the flexibility at which a data worker can choose the right tool for the job, regardless of whether the tool is a code library or an interactive graphical user interface (GUI). To achieve this flexibility, we extend computational notebooks with a new API mage, which supports tools that can represent themselves as both code and GUI as needed. We discuss the design of mage as well as design opportunities in the space of flexible code/GUI tools for data work. To understand tooling needs, we conduct a study with nine professional practitioners and elicit their feedback on mage and potential areas for flexible code/GUI tooling. We then implement six client tools for mage that illustrate the main themes of our study findings. Finally, we discuss open challenges in providing flexible code/GUI interactions for data workers

    ImageJ2: ImageJ for the next generation of scientific image data

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    ImageJ is an image analysis program extensively used in the biological sciences and beyond. Due to its ease of use, recordable macro language, and extensible plug-in architecture, ImageJ enjoys contributions from non-programmers, amateur programmers, and professional developers alike. Enabling such a diversity of contributors has resulted in a large community that spans the biological and physical sciences. However, a rapidly growing user base, diverging plugin suites, and technical limitations have revealed a clear need for a concerted software engineering effort to support emerging imaging paradigms, to ensure the software's ability to handle the requirements of modern science. Due to these new and emerging challenges in scientific imaging, ImageJ is at a critical development crossroads. We present ImageJ2, a total redesign of ImageJ offering a host of new functionality. It separates concerns, fully decoupling the data model from the user interface. It emphasizes integration with external applications to maximize interoperability. Its robust new plugin framework allows everything from image formats, to scripting languages, to visualization to be extended by the community. The redesigned data model supports arbitrarily large, N-dimensional datasets, which are increasingly common in modern image acquisition. Despite the scope of these changes, backwards compatibility is maintained such that this new functionality can be seamlessly integrated with the classic ImageJ interface, allowing users and developers to migrate to these new methods at their own pace. ImageJ2 provides a framework engineered for flexibility, intended to support these requirements as well as accommodate future needs

    Notebook articles: towards a transformative publishing experience in nonlinear science

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    Open Science, Reproducible Research, Findable, Accessible, Interoperable and Reusable (FAIR) data principles are long term goals for scientific dissemination. However, the implementation of these principles calls for a reinspection of our means of dissemination. In our viewpoint, we discuss and advocate, in the context of nonlinear science, how a notebook article represents an essential step toward this objective by fully embracing cloud computing solutions. Notebook articles as scholar articles offer an alternative, efficient and more ethical way to disseminate research through their versatile environment. This format invites the readers to delve deeper into the reported research. Through the interactivity of the notebook articles, research results such as for instance equations and figures are reproducible even for non-expert readers. The codes and methods are available, in a transparent manner, to interested readers. The methods can be reused and adapted to answer additional questions in related topics. The codes run on cloud computing services, which provide easy access, even to low-income countries and research groups. The versatility of this environment provides the stakeholders - from the researchers to the publishers - with opportunities to disseminate the research results in innovative ways.Comment: This article is an editorial viewpoin

    Study on the use of a combination of IPython Notebook and an industry‐standard package in educating a CFD course

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    It is common that industry‐standard packages are used in teaching professional engineering courses in final‐year undergraduate and postgraduate levels. To improve the competency of students in using such professional packages, it is important that students develop a good understanding of theoretical/fundamental concepts used on the packages. However, it is always a challenge to teach theoretical/fundamental concepts in the computational‐related courses. The teaching of such subjects can be improved by the use of advanced open‐source web applications. The present research proposes an approach based upon the combination of Jupyter Notebook and an industry‐standard package to teach an applied, computationally related course. We investigate the use of backward design and a novel tool called IPython (Jupyter) Notebook to redesign a postgraduate Computational Fluid Dynamics (CFD) course. IPython Notebook is used to design a series of integrated lecture slides and tutorial tasks, and also one of the assignments for the blended‐learning‐based, semester‐run, CFD course. The tool allows the implementation of backward curriculum design and a learn‐by‐doing approach in redesigning the course. The materials produced were used on the first part of the course which contributed 40% towards the course's final mark and delivered the fundamental concepts of CFD over the first half of the semester. The remaining 60% of the mark was based on a final project from the materials taught on using an industry‐standard CFD package in solving complex CFD problems during the second half of the semester. It was shown that the Ipython environment is a very useful tool which provides learning‐by‐doing practices allowing students to have a coherent integrated lecture, tutorial, and assignment material in a highly interactive way. It improved (a) students' engagement in teaching complex theoretical concepts, (b) students satisfaction of the course and (c) students performance in working with the industry‐standard package over the second half of the semester

    Numerical Study of Nonlinear Dispersive Wave Models with SpecTraVVave

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    In nonlinear dispersive evolution equations, the competing effects of nonlinearity and dispersion make a number of interesting phenomena possible. In the current work, the focus is on the numerical approximation of traveling-wave solutions of such equations. We describe our efforts to write a dedicated Python code which is able to compute traveling-wave solutions of nonlinear dispersive equations of the general form \begin{equation*} u_t + [f(u)]_{x} + \mathcal{L} u_x = 0, \end{equation*} where L\mathcal{L} is a self-adjoint operator, and ff is a real-valued function with f(0)=0f(0) = 0. The SpectraVVave code uses a continuation method coupled with a spectral projection to compute approximations of steady symmetric solutions of this equation. The code is used in a number of situations to gain an understanding of traveling-wave solutions. The first case is the Whitham equation, where numerical evidence points to the conclusion that the main bifurcation branch features three distinct points of interest, namely a turning point, a point of stability inversion, and a terminal point which corresponds to a cusped wave. The second case is the so-called modified Benjamin-Ono equation where the interaction of two solitary waves is investigated. It is found that is possible for two solitary waves to interact in such a way that the smaller wave is annihilated. The third case concerns the Benjamin equation which features two competing dispersive operators. In this case, it is found that bifurcation curves of periodic traveling-wave solutions may cross and connect high up on the branch in the nonlinear regime

    GadenTools: a toolkit for testing and simulating robotic olfaction tasks with Jupyter Notebook support

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    This work presents GadenTools, a toolkit designed to ease the development and integration of mobile robotic olfaction applications by enabling a convenient and user-friendly access to Gaden’s realistic gas dispersion simulations. It is based on an easy-to-use Python API, and includes an extensive tutorial developed with Jupyter Notebook and Google Colab technologies. A detailed set of examples illustrates aspects ranging from basic access to sensory data or the generation of ground truth images, to the more advanced implementation of plume tracking algorithms, all in an online web-editor with no installation requirements. All the resources, including the source code, are made available in an online open repository.Universidad de Málaga. Campus de Excelencia Internacional Andalucía Tech
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