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Pybel: a python wrapper for the OpenBabel cheminformatics toolkit

CHEMISTRY CENTRAL JOURNAL 2008年第1期2卷 1-7页

作者： O'Boyle, Noel M. Morley, Chris Hutchison, Geoffrey R. Univ Cambridge Unilever Ctr Mol Sci Informat Dept Chem Cambridge CB2 1EW England Cambridge Crystallog Data Ctr Cambridge CB2 1EZ England Univ Pittsburgh Chevron Sci Ctr OpenBabel Dev Team Pittsburgh PA 15260 USA Univ Pittsburgh Chevron Sci Ctr Dept Chem Pittsburgh PA 15260 USA

Background: Scripting languages such as python are ideally suited to common programming tasks in cheminformatics such as data analysis and parsing information from files. However, for reasons of efficiency, cheminformatics toolkits such as the OpenBabel toolkit are often implemented in compiled languages such as C++. We describe Pybel, a python module that provides access to the OpenBabel toolkit. Results: Pybel wraps the direct toolkit bindings to simplify common tasks such as reading and writing molecular files and calculating fingerprints. Extensive use is made of python iterators to simplify loops such as that over all the molecules in a file. A Pybel Molecule can be easily interconverted to an OpenBabel OBMol to access those methods or attributes not wrapped by Pybel. Conclusion: Pybel allows cheminformaticians to rapidly develop python scripts that manipulate chemical information. It is open source, available cross-platform, and offers the power of the OpenBabel toolkit to python programmers.

关键词： Common Task Molecular Fingerprint Tanimoto Coefficient python Language python module

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PyOphidia: A python library for High Performance Data Analytics at scale

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SOFTWAREX 2023年 24卷

作者： Elia, Donatello Palazzo, Cosimo Fiore, Sandro D'Anca, Alessandro Mariello, Andrea Aloisio, Giovanni Fdn Ctr Euro Mediterraneo Cambiamenti Climat I-73100 Lecce Italy Univ Trento I-38122 Trento Italy

The increasing size of scientific datasets has caused a deep transformation in the way scientific research is currently carried out. In multiple domains, Big Data challenges have called for novel software solutions capable of exploiting fast computing resources, workflows technologies and parallel paradigms at scale, by providing a high-level of abstraction while hiding, at the same time, the underlying infrastructural and software complexity from scientists. This paper describes PyOphidia, an open-source python module for High Performance Data Analytics on multi-dimensional scientific datasets. PyOphidia aims to simplify the execution of parallel data analysis over scientific datacubes on High Performance Computing infrastructures. It can be easily integrated with other existing python libraries and tools, within multiple data science environments.

关键词： High Performance Data Analytics Scientific datacube Climate analytics Data science python module

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Benchmarks of Cuda-Based GMRES Solver for Toeplitz and Hankel Matrices and Applications to Topology Optimization of Photonic Components

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Computational Mathematics and Modeling 2021年第4期32卷 438-452页

作者： Minin, Iu. B. Matveev, S.A. Fedorov, M.V. Zacharov, I.E. Rykovanov, S.G. Skoltech Center for Computational and Data-Intensive Science and Engineering Skolkovo Institute of Science and Technology Moscow Russian Federation Fryazino Branch of Kotel’nikov Institute of Radio-Engineering and Electronics of Russian Academy of Sciences Moscow Fryazino Russian Federation Faculty of Computational Mathematics and Cybernetics Lomonosov Moscow State University Moscow Russian Federation Marchuk Institute of Numerical Mathematics Russian Academy of Sciences Moscow Russian Federation Sirius University of Science and Technology Krasnodar Krai Sochi Russian Federation

Generalized Minimal Residual Method (GMRES) was benchmarked on many types of GPUs for solving linear systems based on dense and sparse matrices. However, there are still no GMRES implementation benchmarks on Tesla V100 compared to GTX 1080 Ti ones or even for Toeplitz-like matrices. The introduced software consists of a python module and a C++ library which enable to manage streams for concurrent computations of separated linear systems on a GPU (and GPUs). The GMRES solver is parallelized for running on a NVIDIA GPGPU accelerator. The parallelization efficiency is explored when GMRES is applied to solve (Helmholtz equation) linear systems based on the use of Green’s Function Integral Equation Method (GFIEM) for computing electric field distribution in the design domain. The proposed implementation shew the maximal speedup of 55 (t¯=0.017s) and of 125 (t¯=0.77s) for 1024 × 1024 (on GTX 1080 Ti) and 8192 × 8192 (on Tesla V100) dense Toeplitz matrices generated from GFIEM. 1024 × 1024 resolution provides accuracy 6.1% that can be acceptable according to testing and demonstrating on gradient computations and topology optimization. We open up possibilities for robust topology optimization of passive photonic integrated components. That has the advantage, e. g., of faster and more accurate designing photonic components on a PC without a supercomputer. © 2022, Springer Science+Business Media, LLC, part of Springer Nature.

关键词： CUDA C++ GMRES GPU Helmholtz equation parallelization performance python module Toeplitz-like matrix topology optimization

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INCA: Infrastructure for Content Analysis 14

INCA: Infrastructure for Content Analysis

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14th IEEE International Conference on E-Science (E-Science)

作者： Trilling, Damian van de Velde, Bob Kroon, Anne C. Locherbach, Felicia Araujo, Theo Strycharz, Joanna Raats, Tamara de Klerk, Lisa Jonkman, Jeroen G. F. Univ Amsterdam Amsterdam Sch Commun Res Dept Commun Sci Amsterdam Netherlands Univ Amsterdam Informat Inst Amsterdam Netherlands Univ Amsterdam Grad Sch Commun Dept Commun Sci Amsterdam Netherlands

ISBN: (纸本)9781538691564

We present INCA (short for INfrastructure for Content Analysis), a python module for collecting, storing, processing, and analyzing a wide variety of media content, including but not limited to news, political debates, social media, forums, and customer reviews. Using Elasticsearch as a database backend and Celery for task management, it makes automated content analysis scalable. INCA's main objective is to enable and promote an integrated workflow. INCA focuses on re-usability of data, processors, and analyses;making all steps of automated content analysis (ACA) accessible to social scientists, without requiring advanced programming skills. Here, we present the aim, implementation, and recommended workflow for INCA.

关键词： automated content analysis python module social science communication science

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Raspi Issue 12 2015 Uk

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2017年

Raspi Issue 12 2015 Uk by published by

关键词： analog input arduino arduino ide bitscope bitscope dso bitscope micro cluster code ipython issue justa score linuxusermag scored major scale mpi pis power supply python python module raspberry raspberry pis raspi sudo

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Notifikační robot

Notifikační robot

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作者： Hudák, Filip Brno University of Technology

Bakalárska práca sa venuje vytvoreniu notifikačného bota na vhodne zvolenom komunikačnom kanály. V teoretickej časti sa porovnávajú rôzne komunikačné kanály s ohľadom na ce... 详细信息

Bakalárska práca sa venuje vytvoreniu notifikačného bota na vhodne zvolenom komunikačnom kanály. V teoretickej časti sa porovnávajú rôzne komunikačné kanály s ohľadom na cenovú stránku, súkromie, šifrovanie, popularitu a ďalšie. Praktická časť popisuje registráciu a aplikačné nastavenie komunikácie, testy získavania dát a posielania správ na daný komunikačný kanál. Zaoberá sa návrhom komunikačného modulu s ukladaním tokenu a tajného kľúča spolu s zjednodušeným posielaním správ. Uvádza návrh a štruktúru notifikačného bota, ako aj návrh komunikačných rozhraní s možným pripojením aplikácií tretích strán. Kladie dôraz na rýchle a bezpečné šifrovanie cez vytvorené komunikačné rozhrania pomocou osvedčených postupov. Ďalším bodom v praktickej časti sa opisuje monitorovanie jednotlivých webových stránok s jednoduchým pridávaním webových stránok. Na záver sa preberá inštalácia obrazov a následné nasadenie programov vo vlastných kontajneroch pomocou programu Docker.

关键词： asymetrické šifrovanie automatizácia bot monitorovanie webových stránok python python modul REST API slack slackclient Slack API symetrické šifrovanie asymmetric encryption automatization bot python python module REST API slack slackclie

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Thermodynamic coefficients of ideal Fermi gas

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CONTRIBUTIONS TO PLASMA PHYSICS 2021年第10期61卷 e202100139-e202100139页

作者： Kozharin, Alexey S. Levashov, Pavel R. RAS Joint Inst High Temp Izhorskaya 13Bldg 2 Moscow 125412 Russia Moscow Inst Phys & Technol Moscow Russia

We present analytical formulae for the first and second derivatives of the Helmholtz free energy of non-relativistic ideal Fermi gas. Important thermodynamic quantities such as heat capacity, sound velocity, heat capacity ratio, and others are explicitly expressed through the derivatives. We demonstrate correct ideal Boltzmann gas and low-temperature Fermi gas asymptotes and derive corrections to thermodynamic functions for these limiting cases. Numerical computations of thermodynamic properties of ideal Fermi gas can be accurately performed using the developed freely available python module ifg.

关键词： ideal Fermi gas python module thermodynamic coefficients

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PanSuite: A free simulation environment for the analysis of hybrid electrical power systems

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ELECTRIC POWER SYSTEMS RESEARCH 2022年 212卷

作者： Linaro, Daniele del Giudice, Davide Bizzarri, Federico Brambilla, Angelo Politecn Milan DEIB Pza Leonardo da Vinci 32 I-20133 Milan Italy

In many engineering domains, complex systems are composed of several interconnected and interacting parts that are modeled and analyzed in different ways. This is the case, for instance, of modern power systems, which are commonly labeled as "hybrid "for this very reason. This heterogeneity has triggered the development of numerical tools capable of simulating the different parts making up a hybrid system. Often, however, these tools either tackle a very specific aspect of power systems analysis (e.g., power flow computation), or are composed of interacting parts that rely on heuristics for their correct functioning. In this paper we describe pan, a free simulator developed in our group combining very high numerical efficiency with a vast choice of simulation algorithms suited for power system analysis. We also introduce three recently developed open -source interfaces to pan written in the MATLAB, python, and Julia programming languages, which greatly reduce development times and allow the user to incorporate power system analysis into extended simulation and analysis workflows. Together, these tools make up pansuite.

关键词： Power system simulation Hybrid system simulation MATLAB toolbox python module Julia module

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Update (1.2) to ANDURIL and ANDURYL: Performance improvements and a graphical user interface

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SOFTWAREX 2020年 12卷

作者： Rongen, Guus 't Hart, Cornelis Marcel Pieter Leontaris, Georgios Morales-Napoles, Oswaldo Delft Univ Technol Civil Engn & Geosci Delft Netherlands HKV Consultants Lelystad Netherlands Tunnel Engn Consultants TEC Amersfoort Netherlands Vattenfall Amsterdam Netherlands

This is an update to PII: S2352711018300608 and S2352711019302419 and In this paper, we present three main improvements of ANDURIL and its python version ANDURYL. First the MATLAB version ANDURIL is brought to the python version standard by implementing (i) user defined quantiles and (ii) the possibility to deal with missing values. Second, the computational engines of both ANDURIL and ANDURYL were significantly improved making calculation time lower and improving further accuracy. Finally a standalone Graphical User Interface is presented which we believe will make the software more accessible to practitioners of Cooke's method. (C) 2020 Published by Elsevier B.V.

关键词： Structured expert judgment Cooke's classical model Expert opinion python module EXCALIBUR software ANDURIL GUI

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