Schrangl, Lukas · Zenodo (CERN European Organization for Nuclear Research) · 2024
sdt-python is a collection of tools for analysis of fluorescence microscopy data. It contains algorithms for localization of fluorescent features in images methods for evaluation of tracking data functions to evaluate brightness data as well as multi-color data support for automated determination and correction of chromatic aberrations methods for reading and writing single molecule data in various formats handling of ROIs (both rectangular and described by arbitrary paths) methods for simulation of fluorescence microscopy images much more.
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Schrangl, Lukas · Zenodo (CERN European Organization for Nuclear Research) · 2024
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Joseph Dedy Irawan, Emmalia Adriantantri · Jurnal Mnemonic · 2019
Setiap orang membutuhkan istirahat yang cukup agar dapat melakukan aktfitas sehari-hari dengan maksimal, kurangnya istirahat dapat menyebabkan tubuh menjadi tidak sehat dan mengakibatkan mengantuk pada saat sedang melakukan aktifitas, rasa kantuk dapat mengakibatkan aktifitas terganggu karena konsentrasi berkurang, mengantuk saat berkendaraan akan sangat membahayakan, dengan bantuan kamera dan kecerdasan buatan, dapat dibuat sebuah peralatan yang dapat mendeteksi jika seseorang dalam keadaan mengantuk, sehingga dapat memberikan peringatan misalnya pada saat sedang mengendarai kendaraan, dengan menggunakan library python dapat dibuat sebuah aplikasi yang dapat mendeteksi dan memberikan peringatan jika sedang mengantuk terutama saat mengendarai kendaraan bermotor.
Cited by 4Open access
Islam, Mohayeminul, Nadi, Sarah, Akhmetov, Ildar et al. · Figshare · 2024
Artifacts for the paper <i>Characterizing Python Library Migrations</i>.This is the archival data linked to the paper. Please visit our GitHub repository for any future updates.
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Schrangl, Lukas · Zenodo (CERN European Organization for Nuclear Research) · 2025
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Schrangl, Lukas · Zenodo (CERN European Organization for Nuclear Research) · 2023
<em>sdt-python</em> is a collection of tools for analysis of fluorescence microscopy data. It contains algorithms for localization of fluorescent features in images methods for evaluation of tracking data functions to evaluate brightness data as well as multi-color data support for automated determination and correction of chromatic aberrations methods for reading and writing single molecule data in various formats handling of ROIs (both rectangular and described by arbitrary paths) methods for simulation of fluorescence microscopy images much more.
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Schrangl, Lukas · Zenodo (CERN European Organization for Nuclear Research) · 2022
<em>sdt-python</em> is a collection of tools for analysis of fluorescence microscopy data. It contains algorithms for localization of fluorescent features in images methods for evaluation of tracking data functions to evaluate brightness data as well as multi-color data support for automated determination and correction of chromatic aberrations methods for reading and writing single molecule data in various formats handling of ROIs (both rectangular and described by arbitrary paths) methods for simulation of fluorescence microscopy images much more.
Cited by 0Open access
Schrangl, Lukas · Zenodo (CERN European Organization for Nuclear Research) · 2022
<em>sdt-python</em> is a collection of tools for analysis of fluorescence microscopy data. It contains algorithms for localization of fluorescent features in images methods for evaluation of tracking data functions to evaluate brightness data as well as multi-color data support for automated determination and correction of chromatic aberrations methods for reading and writing single molecule data in various formats handling of ROIs (both rectangular and described by arbitrary paths) methods for simulation of fluorescence microscopy images much more.
Cited by 0Open access
Schrangl, Lukas · Zenodo (CERN European Organization for Nuclear Research) · 2023
sdt-python is a collection of tools for analysis of fluorescence microscopy data. It contains algorithms for localization of fluorescent features in images methods for evaluation of tracking data functions to evaluate brightness data as well as multi-color data support for automated determination and correction of chromatic aberrations methods for reading and writing single molecule data in various formats handling of ROIs (both rectangular and described by arbitrary paths) methods for simulation of fluorescence microscopy images much more.
Cited by 1Open access
Schrangl, Lukas · Zenodo (CERN European Organization for Nuclear Research) · 2021
<em>sdt-python</em> is a collection of tools for analysis of fluorescence microscopy data. It contains algorithms for localization of fluorescent features in images methods for evaluation of tracking data functions to evaluate brightness data as well as multi-color data support for automated determination and correction of chromatic aberrations methods for reading and writing single molecule data in various formats handling of ROIs (both rectangular and described by arbitrary paths) methods for simulation of fluorescence microscopy images much more.
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Florian Krause, Oliver Lindemann · 2013
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Jonas Fankhauser (12895304), Christoph Goering (12895307), Jürg Dual (7352183) · Figshare · 2022
<p>In this article, we present the Open-Source AcoustoFluidics Theories (OSAFT) library (version 0.9.14), a Python library for acoustofluidics. The focus of the library is the classical problem of a particle suspended in a fluid and subjected to an incident acoustic wave. The Python code provides easy access to a number of theories describing acoustic scattering, acoustic streaming, and most importantly the acoustic radiation force exerted on the particle. At the time of submission of this article, six different theoretical models and various limiting cases thereof are available. All are treating the problem of a single, spherical particle in an infinite 3D-domain subjected to an incident plane standing or plane traveling wave. The implementations of further theories are currently under development. Our code is designed to be extensible. A library of fluid and solid material models facilitates the implementation of new theories. A unified application programming interface (API), which is used across all models, makes comparisons between different theories straightforward. Such comparisons can be made directly by the user or through the plotting capabilities of our library. The code is distributed through Python’s standard software repository PyPi. Illustrative examples on the project’s website serve as a starting point for learning the library’s API. For a more in-depth understanding of the code, complete documentation of the codebase, directed at users as well as future collaborators, is available online. In an effort to make the library as extensive as possible, the authors of this article are looking for collaborators on the project.</p>
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Dandage, Rohan · Zenodo (CERN European Organization for Nuclear Research) · 2024
Chromosome Visualization library in python.
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A. S. Androsov, Sergey P. Shary · Vestnik NSU Series Information Technologies · 2023
The article presents the IntvalPy library which implements interval computations in Python. Unlike other existing interval libraries, IntvalPy allows one to work with both classical interval arithmetic and complete Kaucher interval arithmetic. In addition, the library was developed taking into account the IEEE 1788-2015 standard for interval arithmetic on digital computers, which guarantees high accuracy of the results and compatibility with the other existing software products. The top-level functionality of the IntvalPy library implements state-of-the-art methods for recognizing and estimating solution sets for interval linear systems of equations, computing their formal solutions, and visualizing solution sets for interval equations and systems of equations. As an example of the library application, we solve the practically important problem of estimating the parameters of the electrochemical process of the formation of loose metal powder precipitates. Additionally, numerical computation was carried out, as well as qualitative comparisons with other interval libraries, in order to demonstrate the functionality and optimality of implemented interval classes.
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Yoo, Ji Oh, Ramanathan, Aravind, Langmead, Christopher J. · KiltHub Repository · 2018
Multi-dimensional (or multi-way) analysis have evinced considerable interest within the datamining community. In this technical report, we describe the development and implementation of a python based library to perform multi-way analysis. Our results show that the python implementation runs comparable to the MATLAB implementation. The implementation is available from http://pytensor.googlecode.com/.
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Smith Clark, Alexander, Johnson, Eric T., Chen, Zhi et al. · Zenodo (CERN European Organization for Nuclear Research) · 2022
This submission contains all the supplemental Jupyter notebooks that generates the figures of the journal article entitled: A Python Library for Nuclear Astrophysics.
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Little, Christopher C. · Zenodo (CERN European Organization for Nuclear Research) · 2020
Abydos is a Python library of phonetic algorithms, string distance measures & metrics, stemmers, and string fingerprinters such as Soundex, (Double) Metaphone, NYSIIS, Alpha-SIS, Beider-Morse Phonetic Matching, Levenshtein(-Damerau) distance, Jaro(-Winkler) distance, Jaccard similarity, and Pollock & Zomora's skeleton & omission keys.
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Karev, Evgeny, Camilleri, Pierre, Baptista, Vitor et al. · Zenodo (CERN European Organization for Nuclear Research) · 2023
Data management framework for Python that provides functionality to describe, extract, validate, and transform tabular data
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Little, Christopher C. · Zenodo (CERN European Organization for Nuclear Research) · 2018
Abydos is a Python library of phonetic algorithms, string distance measures & metrics, stemmers, and string fingerprinters such as Soundex, (Double) Metaphone, NYSIIS, Alpha-SIS, Beider-Morse Phonetic Matching, Levenshtein(-Damerau) distance, Jaro(-Winkler) distance, Jaccard similarity, and Pollock & Zomora's skeleton & omission keys.
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Jim Duggan · 2018
Using the R package 'reticulate', this package creates an interface to the 'pysd' toolset. The package provides an R interface to a number of 'pysd' functions, and can read files in 'Vensim' 'mdl' format, and 'xmile' format. The resulting simulations are returned as a 'tibble', and from that the results can be processed using 'dplyr' and 'ggplot2'. The package has been tested using 'python3'.
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