Installation Guide Version 4.5 Copyright © 2014 András Varga and Opensim Ltd
Total Page:16
File Type:pdf, Size:1020Kb
Load more
Recommended publications
-
Networkx Tutorial
5.03.2020 tutorial NetworkX tutorial Source: https://github.com/networkx/notebooks (https://github.com/networkx/notebooks) Minor corrections: JS, 27.02.2019 Creating a graph Create an empty graph with no nodes and no edges. In [1]: import networkx as nx In [2]: G = nx.Graph() By definition, a Graph is a collection of nodes (vertices) along with identified pairs of nodes (called edges, links, etc). In NetworkX, nodes can be any hashable object e.g. a text string, an image, an XML object, another Graph, a customized node object, etc. (Note: Python's None object should not be used as a node as it determines whether optional function arguments have been assigned in many functions.) Nodes The graph G can be grown in several ways. NetworkX includes many graph generator functions and facilities to read and write graphs in many formats. To get started though we'll look at simple manipulations. You can add one node at a time, In [3]: G.add_node(1) add a list of nodes, In [4]: G.add_nodes_from([2, 3]) or add any nbunch of nodes. An nbunch is any iterable container of nodes that is not itself a node in the graph. (e.g. a list, set, graph, file, etc..) In [5]: H = nx.path_graph(10) file:///home/szwabin/Dropbox/Praca/Zajecia/Diffusion/Lectures/1_intro/networkx_tutorial/tutorial.html 1/18 5.03.2020 tutorial In [6]: G.add_nodes_from(H) Note that G now contains the nodes of H as nodes of G. In contrast, you could use the graph H as a node in G. -
Networkx: Network Analysis with Python
NetworkX: Network Analysis with Python Salvatore Scellato Full tutorial presented at the XXX SunBelt Conference “NetworkX introduction: Hacking social networks using the Python programming language” by Aric Hagberg & Drew Conway Outline 1. Introduction to NetworkX 2. Getting started with Python and NetworkX 3. Basic network analysis 4. Writing your own code 5. You are ready for your project! 1. Introduction to NetworkX. Introduction to NetworkX - network analysis Vast amounts of network data are being generated and collected • Sociology: web pages, mobile phones, social networks • Technology: Internet routers, vehicular flows, power grids How can we analyze this networks? Introduction to NetworkX - Python awesomeness Introduction to NetworkX “Python package for the creation, manipulation and study of the structure, dynamics and functions of complex networks.” • Data structures for representing many types of networks, or graphs • Nodes can be any (hashable) Python object, edges can contain arbitrary data • Flexibility ideal for representing networks found in many different fields • Easy to install on multiple platforms • Online up-to-date documentation • First public release in April 2005 Introduction to NetworkX - design requirements • Tool to study the structure and dynamics of social, biological, and infrastructure networks • Ease-of-use and rapid development in a collaborative, multidisciplinary environment • Easy to learn, easy to teach • Open-source tool base that can easily grow in a multidisciplinary environment with non-expert users -
Nix on SHARCNET
Nix on SHARCNET Tyson Whitehead May 14, 2015 Nix Overview An enterprise approach to package management I a package is a specific piece of code compiled in a specific way I each package is entirely self contained and does not change I each users select what packages they want and gets a custom enviornment https://nixos.org/nix Ships with several thousand packages already created https://nixos.org/nixos/packages.html SHARCNET What this adds to SHARCNET I each user can have their own custom environments I environments should work everywhere (closed with no external dependencies) I several thousand new and newer packages Current issues (first is permanent, second will likely be resolved) I newer glibc requires kernel 2.6.32 so no requin I package can be used but not installed/removed on viz/vdi https: //sourceware.org/ml/libc-alpha/2014-01/msg00511.html Enabling Nix Nix is installed under /home/nixbld on SHARCNET. Enable for a single sessiong by running source /home/nixbld/profile.d/nix-profile.sh To always enable add this to the end of ~/.bash_profile echo source /home/nixbld/profile.d/nix-profile.sh \ >> ~/.bash_profile Reseting Nix A basic reset is done by removing all .nix* files from your home directory rm -fr ~/.nix* A complete reset done by remove your Nix per-user directories rm -fr /home/nixbld/var/nix/profile/per-user/$USER rm -fr /home/nixbld/var/nix/gcroots/per-user/$USER The nix-profile.sh script will re-create these with the defaults next time it runs. Environment The nix-env commands maintains your environments I query packages (available and installed) I create a new environment from current one by adding packages I create a new environment from current one by removing packages I switching between existing environments I delete unused environements Querying Packages The nix-env {--query | -q} .. -
Graph Database Fundamental Services
Bachelor Project Czech Technical University in Prague Faculty of Electrical Engineering F3 Department of Cybernetics Graph Database Fundamental Services Tomáš Roun Supervisor: RNDr. Marko Genyk-Berezovskyj Field of study: Open Informatics Subfield: Computer and Informatic Science May 2018 ii Acknowledgements Declaration I would like to thank my advisor RNDr. I declare that the presented work was de- Marko Genyk-Berezovskyj for his guid- veloped independently and that I have ance and advice. I would also like to thank listed all sources of information used Sergej Kurbanov and Herbert Ullrich for within it in accordance with the methodi- their help and contributions to the project. cal instructions for observing the ethical Special thanks go to my family for their principles in the preparation of university never-ending support. theses. Prague, date ............................ ........................................... signature iii Abstract Abstrakt The goal of this thesis is to provide an Cílem této práce je vyvinout webovou easy-to-use web service offering a database službu nabízející databázi neorientova- of undirected graphs that can be searched ných grafů, kterou bude možno efektivně based on the graph properties. In addi- prohledávat na základě vlastností grafů. tion, it should also allow to compute prop- Tato služba zároveň umožní vypočítávat erties of user-supplied graphs with the grafové vlastnosti pro grafy zadané uži- help graph libraries and generate graph vatelem s pomocí grafových knihoven a images. Last but not least, we implement zobrazovat obrázky grafů. V neposlední a system that allows bulk adding of new řadě je také cílem navrhnout systém na graphs to the database and computing hromadné přidávání grafů do databáze a their properties. -
Gephi Tools for Network Analysis and Visualization
Frontiers of Network Science Fall 2018 Class 8: Introduction to Gephi Tools for network analysis and visualization Boleslaw Szymanski CLASS PLAN Main Topics • Overview of tools for network analysis and visualization • Installing and using Gephi • Gephi hands-on labs Frontiers of Network Science: Introduction to Gephi 2018 2 TOOLS OVERVIEW (LISTED ALPHABETICALLY) Tools for network analysis and visualization • Computing model and interface – Desktop GUI applications – API/code libraries, Web services – Web GUI front-ends (cloud, distributed, HPC) • Extensibility model – Only by the original developers – By other users/developers (add-ins, modules, additional packages, etc.) • Source availability model – Open-source – Closed-source • Business model – Free of charge – Commercial Frontiers of Network Science: Introduction to Gephi 2018 3 TOOLS CINET CyberInfrastructure for NETwork science • Accessed via a Web-based portal (http://cinet.vbi.vt.edu/granite/granite.html) • Supported by grants, no charge for end users • Aims to provide researchers, analysts, and educators interested in Network Science with an easy-to-use cyber-environment that is accessible from their desktop and integrates into their daily work • Users can contribute new networks, data, algorithms, hardware, and research results • Primarily for research, teaching, and collaboration • No programming experience is required Frontiers of Network Science: Introduction to Gephi 2018 4 TOOLS Cytoscape Network Data Integration, Analysis, and Visualization • A standalone GUI application -
Downloads." the Open Information Security Foundation
Performance Testing Suricata The Effect of Configuration Variables On Offline Suricata Performance A Project Completed for CS 6266 Under Jonathon T. Giffin, Assistant Professor, Georgia Institute of Technology by Winston H Messer Project Advisor: Matt Jonkman, President, Open Information Security Foundation December 2011 Messer ii Abstract The Suricata IDS/IPS engine, a viable alternative to Snort, has a multitude of potential configurations. A simplified automated testing system was devised for the purpose of performance testing Suricata in an offline environment. Of the available configuration variables, seventeen were analyzed independently by testing in fifty-six configurations. Of these, three variables were found to have a statistically significant effect on performance: Detect Engine Profile, Multi Pattern Algorithm, and CPU affinity. Acknowledgements In writing the final report on this endeavor, I would like to start by thanking four people who made this project possible: Matt Jonkman, President, Open Information Security Foundation: For allowing me the opportunity to carry out this project under his supervision. Victor Julien, Lead Programmer, Open Information Security Foundation and Anne-Fleur Koolstra, Documentation Specialist, Open Information Security Foundation: For their willingness to share their wisdom and experience of Suricata via email for the past four months. John M. Weathersby, Jr., Executive Director, Open Source Software Institute: For allowing me the use of Institute equipment for the creation of a suitable testing -
Gephi-Poster-Sunbelt-July10.Pdf
The Open Graph Viz Platform Gephi is a new open-source network visualization platform. It aims to create a sustainable software and technical Download Gephi at ecosystem, driven by a large international open-source community, who shares common interests in networks and http://gephi.org complex systems. The rendering engine can handle networks larger than 100K elements and guarantees responsiveness. Designed to make data navigation and manipulation easy, it aims to fulll the complete chain from data importing to aesthetics renements and interaction. Particular focus is made on the software usability and interoperability with other tools. A lot of eorts are made to facilitate the community growth, by providing tutorials, plug-ins development documentation, support and student projects. Current developments include Dynamic Network Analysis (DNA) and Goals spigots (Emails, Twitter, Facebook …) import. Create the Photoshop of network visualization, by combining a rich set of Gephi aims at being built-in features and a sustainable, open to friendly user interface. many kind of users, and creating a large, Design a modular and international and extensible software diverse open-source architecture, facilitate plug-ins development, community reuse and mashup. Build a large, international Features Highlight and diverse open-source community. Community Join the network, participate designing the roadmap, get help to quickly code plug-ins or simply share your ideas. Select, move, paint, resize, connect, group Just with the mouse Export in SVG/PDF to include your infographics Metrics Architecture * Betweenness, Eigenvector, Closeness The modular architecture allows developers adding and extending features * Eccentricity with ease by developing plug-ins. Gephi can also be used as Java library in * Diameter, Average Shortest Path other applications and build for instance, a layout server. -
Plantuml Language Reference Guide (Version 1.2021.2)
Drawing UML with PlantUML PlantUML Language Reference Guide (Version 1.2021.2) PlantUML is a component that allows to quickly write : • Sequence diagram • Usecase diagram • Class diagram • Object diagram • Activity diagram • Component diagram • Deployment diagram • State diagram • Timing diagram The following non-UML diagrams are also supported: • JSON Data • YAML Data • Network diagram (nwdiag) • Wireframe graphical interface • Archimate diagram • Specification and Description Language (SDL) • Ditaa diagram • Gantt diagram • MindMap diagram • Work Breakdown Structure diagram • Mathematic with AsciiMath or JLaTeXMath notation • Entity Relationship diagram Diagrams are defined using a simple and intuitive language. 1 SEQUENCE DIAGRAM 1 Sequence Diagram 1.1 Basic examples The sequence -> is used to draw a message between two participants. Participants do not have to be explicitly declared. To have a dotted arrow, you use --> It is also possible to use <- and <--. That does not change the drawing, but may improve readability. Note that this is only true for sequence diagrams, rules are different for the other diagrams. @startuml Alice -> Bob: Authentication Request Bob --> Alice: Authentication Response Alice -> Bob: Another authentication Request Alice <-- Bob: Another authentication Response @enduml 1.2 Declaring participant If the keyword participant is used to declare a participant, more control on that participant is possible. The order of declaration will be the (default) order of display. Using these other keywords to declare participants -
Travels of Baron Munchausen
Songs for Scribus Travels of Baron Munchausen Songs for Scribus Travels of Baron Munchausen Travels of Baron Munchausen How should I disengage myself? I was not much pleased with my awkward situation – with a wolf face to face; our ogling was not of the most pleasant kind. If I withdrew my arm, then the animal would fly the more furiously upon me; that I saw in his flaming eyes. In short, I laid hold of his tail, turned him inside out like a glove, and flung him to the ground, where I left him. On January 3 2011, the first working day of the year, OSP gathered around Scribus. We wanted to explore framerendering, bootstrapping Scribus and to play around with the incredible adventures of Baron von Munchausen. The idea was to produce some kind of experimental result, a follow- up of to our earlier attempts to turn a frog into a prince. One day we asked Scribus team-members what their favourite Scribus feature was. After some hesitation they pointed us to the magical framerender. Framerenderer The Framerender is an image frame with a wrapper, a GUI, and a configuration scheme. External programs are invoked from inside of Scribus, and their output is placed into the frame! By default, the current Scribus is configured to host the following friends: LaTeX, Lilypond, gnuplot, dot/GraphViz and POV-Ray Today we are working with Lilypond. We are also creating cus- tom tools that generate PostScript/PDF via Imagemagick and other command line tools. Lilypond LilyPond is a music engraving program, devoted to producing the highest-quality sheet music possible. -
FFV1, Matroska, LPCM (And More)
MediaConch Implementation and policy checking on FFV1, Matroska, LPCM (and more) Jérôme Martinez, MediaArea Innovation Workshop ‑ March 2017 What is MediaConch? MediaConch is a conformance checker Implementation checker Policy checker Reporter Fixer What is MediaConch? Implementation and Policy reporter What is MediaConch? Implementation report: Policy report: What is MediaConch? General information about your files What is MediaConch? Inspect your files What is MediaConch? Policy editor What is MediaConch? Public policies What is MediaConch? Fixer Segment sizes in Matroska Matroska “bit flip” correction FFV1 “bit flip” correction Integration Archivematica is an integrated suite of open‑source software tools that allows users to process digital objects from ingest to access in compliance with the ISO‑OAIS functional model MediaConch interfaces Graphical interface Web interface Command line Server (REST API) (Work in progress) a library (.dll/.so/.dylib) MediaConch output formats XML (native format) Text HTML (Work in progress) PDF Tweakable! (with XSL) Open source GPLv3+ and MPLv2+ Relies on MediaInfo (metadata extraction tool) Use well‑known open source libraries: Qt, sqlite, libevent, libxml2, libxslt, libexslt... Supported formats Priorities for the implementation checker Matroska FFV1 PCM Can accept any format supported by MediaInfo for the policy checker MXF + JP2k QuickTime/MOV Audio files (WAV, BWF, AIFF...) ... Supported formats Can be expanded By plugins Support of PDF checker: VeraPDF plugin Support of TIFF checker: DPF Manager plugin You use another checker? Let us know By internal development More tests on your preferred format is possible It depends on you! Versatile Several input formats are accepted FFV1 from MOV or AVI Matroska with other video formats (Work in progress) Extraction of a PDF or TIFF aachement from a Matroska container and analyze with a plugin (e.g. -
Feature-Oriented Defect Prediction: Scenarios, Metrics, and Classifiers
1 Feature-Oriented Defect Prediction: Scenarios, Metrics, and Classifiers Mukelabai Mukelabai, Stefan Strüder, Daniel Strüber, Thorsten Berger Abstract—Software defects are a major nuisance in software development and can lead to considerable financial losses or reputation damage for companies. To this end, a large number of techniques for predicting software defects, largely based on machine learning methods, has been developed over the past decades. These techniques usually rely on code-structure and process metrics to predict defects at the granularity of typical software assets, such as subsystems, components, and files. In this paper, we systematically investigate feature-oriented defect prediction: predicting defects at the granularity of features—domain-entities that abstractly represent software functionality and often cross-cut software assets. Feature-oriented prediction can be beneficial, since: (i) particular features might be more error-prone than others, (ii) characteristics of features known as defective might be useful to predict other error-prone features, and (iii) feature-specific code might be especially prone to faults arising from feature interactions. We explore the feasibility and solution space for feature-oriented defect prediction. We design and investigate scenarios, metrics, and classifiers. Our study relies on 12 software projects from which we analyzed 13,685 bug-introducing and corrective commits, and systematically generated 62,868 training and test datasets to evaluate the designed classifiers, metrics, and scenarios. The datasets were generated based on the 13,685 commits, 81 releases, and 24, 532 permutations of our 12 projects depending on the scenario addressed. We covered scenarios, such as just-in-time (JIT) and cross-project defect prediction. -
FME® Desktop Copyright © 1994 – 2018, Safe Software Inc. All Rights Reserved
FME® Desktop Copyright © 1994 – 2018, Safe Software Inc. All rights reserved. FME® is the registered trademark of Safe Software Inc. All brands and their product names mentioned herein may be trademarks or registered trademarks of their respective holders and should be noted as such. FME Desktop includes components licensed as described below: Autodesk FBX This software contains Autodesk® FBX® code developed by Autodesk, Inc. Copyright 2016 Autodesk, Inc. All rights, reserved. Such code is provided “as is” and Autodesk, Inc. disclaims any and all warranties, whether express or implied, including without limitation the implied warranties of merchantability, fitness for a particular purpose or non-infringement of third party rights. In no event shall Autodesk, Inc. be liable for any direct, indirect, incidental, special, exemplary, or consequential damages (including, but not limited to, procurement of substitute goods or services; loss of use, data, or profits; or business interruption) however caused and on any theory of liability, whether in contract, strict liability, or tort (including negligence or otherwise) arising in any way out of such code. Autodesk Libraries Contains Autodesk® RealDWG by Autodesk, Inc., Copyright © 2017 Autodesk, Inc. All rights reserved. Home page: www.autodesk.com/realdwg Belge72/b.Lambert72A NTv2 Grid Copyright © 2014-2016 Nicolas SIMON and validated by Service Public de Wallonie and Nationaal Geografisch Instituut. Under Creative Commons Attribution license (CC BY). Bentley i-Model SDK This software includes some components from the Bentley i-Model SDK. Copyright © Bentley Systems International Limited CARIS CSAR GDAL Plugin CARIS CSAR GDAL Plugin is owned by and copyright © 2013 Universal Systems Ltd.