Open Source Mac UML Tools - Page 2

The ECLiPSe Constraint Logic Programming System is designed for solving combinatorial optimization problems, for the development of new constraint solver technology and their hybrids, and for the teaching of modelling, solving and search techniques.

Constructs are classes that define a "piece of system state". Constructs can be composed together to form higher-level building blocks which represent a more complex state. Constructs are often used to represent the desired state of cloud applications. For example, in the AWS CDK, which is used to define the desired state for AWS infrastructure using CloudFormation, the lowest-level construct represents a resource definition in a CloudFormation template. These resources are composed to represent higher-level logical units of a cloud application, etc.

PyMC3 allows you to write down models using an intuitive syntax to describe a data generating process. Fit your model using gradient-based MCMC algorithms like NUTS, using ADVI for fast approximate inference — including minibatch-ADVI for scaling to large datasets, or using Gaussian processes to build Bayesian nonparametric models. PyMC3 includes a comprehensive set of pre-defined statistical distributions that can be used as model building blocks. Sometimes an unknown parameter or variable in a model is not a scalar value or a fixed-length vector, but a function. A Gaussian process (GP) can be used as a prior probability distribution whose support is over the space of continuous functions. PyMC3 provides rich support for defining and using GPs. Variational inference saves computational cost by turning a problem of integration into one of optimization. PyMC3's variational API supports a number of cutting edge algorithms, as well as minibatch for scaling to large datasets.

PyText is a deep-learning based NLP modeling framework built on PyTorch. PyText addresses the often-conflicting requirements of enabling rapid experimentation and of serving models at scale. It achieves this by providing simple and extensible interfaces and abstractions for model components, and by using PyTorch’s capabilities of exporting models for inference via the optimized Caffe2 execution engine. We use PyText at Facebook to iterate quickly on new modeling ideas and then seamlessly ship them at scale. Distributed-training support built on the new C10d backend in PyTorch 1.0. Mixed precision training support through APEX (trains faster with less GPU memory on NVIDIA Tensor Cores). Extensible components that allows easy creation of new models and tasks.

The torchvision package consists of popular datasets, model architectures, and common image transformations for computer vision. We recommend Anaconda as Python package management system. Torchvision currently supports Pillow (default), Pillow-SIMD, which is a much faster drop-in replacement for Pillow with SIMD, if installed will be used as the default. Also, accimage, if installed can be activated by calling torchvision.set_image_backend('accimage'), libpng, which can be installed via conda conda install libpng or any of the package managers for debian-based and RHEL-based Linux distributions, and libjpeg, which can be installed via conda conda install jpeg or any of the package managers for debian-based and RHEL-based Linux distributions. It supports libjpeg-turbo as well. libpng and libjpeg must be available at compilation time in order to be available. TorchVision also offers a C++ API that contains C++ equivalent of python models.

Fourth generation database designer and code-generator for educational purposes and speeding-up database designing and creating work.

A simple editor for PlantUML. Requires PlantUML (and its dependencies, java and graphviz/dot). Some features: * update the diagram while editing * code assistant to insert ready-made code snipets * written in Qt4, so it should run on all platforms supported by Qt4 and PlantUML * option to cache the PlantUML output to speed redo, undo and loading from disk * can be used as a PlantUML viewer (see the wiki for more info)

An MS Excel VBA macro converts XML to CSV. It demonstrates this capability by converting an XML-based Continuity of Care Document (CCD) into a slim Comma Separated Value (CSV) file.

The Object-Role Modeling (ORM) standard version 2, associated schemas and generation tools, and a reference implementation in the form of the Natural Object-Role Modeling Architect for Visual Studio (NORMA) product.

The Adobe Source Libraries (ASL) are a collection of C++ libraries building foundation technology to allow the construction of commercial applications by assembling generic algorithms through declarative descriptions.

NOTE: The GROOVE codebase has moved to https://github.com/nl-utwente-groove

Mimosa is a modeling and simulation platform, covering the process from building conceptual models to running the simulations. The specification uses ontologies and an extensible set of formalisms for the dynamics. The simulation kernel is based on DEVS.

EasyStruts provide advanced support for developing Struts web applications with Eclipse . keywords: MVC, Struts, Eclipse, Java

ConceptBase.cc is a multi-user deductive and object-oriented database system for metamodeling and method engineering. Includes a graphical client that builds upon the logic-based features of the ConceptBase.cc server. The data model is O-Telos. ConceptBase.cc can represent information at the data level (example data, traces of process executions etc.), the class level (schemas, process definitions etc.), the metaclass level (constructs of modeling languages), the meta-metaclass level (constructs for defining modeling languages), and so forth. ConceptBase.cc is developed by the ConceptBase Team at University of Skövde (HIS). ConceptBase.cc supports Linux, Mac OS X and Windows. ConceptBase.cc is free software distributed under a FreeBSD-style license.

DAE Tools is a cross-platform equation-based object-oriented modelling, simulation and optimisation software. It is not a modelling language nor a collection of numerical libraries but rather a higher level structure – an architectural design of interdependent software components providing an API for: - Model development/specification - Activities on developed models, such as simulation, optimisation, sensitivity analysis and parameter estimation - Processing of the results, such as plotting and exporting to various file formats - Report generation - Code generation, co-simulation and model exchange The following class of problems can be solved by DAE Tools: - Initial value problems of implicit form - Index-1 DAE systems - With lumped or distributed parameters - Steady-state or dynamic - Continuous with some elements of event-driven systems

JAG - the Java Application Generator - is a 100% Java application that generates working projects containing complete, best-of-breed J2EE applications.

Custom add-in (MDG technology) for Sparx Systems Enterprise Architect UML modelling tool (https://sparxsystems.com/products/ea/index.html) to create architecture descriptions using TRAK https://sf.net/projects/trak Provides: - the set of TRAK views that can be represented using UML and SysML . Each view display a custom toolbox palette with the objects and relationships that are needed for that TRAK view - relationships can be made directly from the objects on a view using the Quicklink feature which presents the allowed relationship(s) by TRAK between the pair of objects selected - a custom set of searches. When run these will list objects of a particular type (e.g. all Systems, all Enterprise Goals), potential quality problems (e.g. diagrams and objects without any description, objects not linked to any other), things of interest (e.g. open, closed concerns) and view-like results e.g. all structural relationships in the solution - model views to list object

TRUC is a web-based tool for requirement and use case tracking. It has fileupload, discussions, version control, usecase history, build and release management. It supports assignment of requirements & use-cases to releases and filtering over all fields.

Eddy is a graphical editor for the specification and visualization of Graphol ontologies. Eddy features a design environment specifically thought out for generating Graphol ontologies through ad-hoc functionalities. Drawing features allow designers to comfortably edit ontologies in a central viewport area, while two lateral docking areas contains specifically-tailored widgets for editing, navigating and inspecting open diagrams. Eddy is equipped with design-time syntax validation functionalities which prevents ontology designers from constructing invalid Graphol expressions: feedback on the validity of the expression is given through color coding diagram elements. Eddy also supports the standard profiles of OWL 2, i.e. OWL 2 QL, OWL 2 RL, and OWL 2 EL (to appear). Moreover, to support interaction with third-party tools such as OWL 2 reasoners and editors like Protégé, Eddy is able to export the produced Graphol ontology into an OWL 2 ontology.

JSDAI is a toolkit for STEP (ISO 10303), the STandard for the Exchange of Product Model data, that enables linking of CAD, CAM, PDM, PLM, CAx systems. JSDAI supports the development of Express data models (ISO 10303-11) and their implementation in Java.

Green, an Eclipse plugin, is an advanced yet simple UML class-diagram tool, developed primarily for student use. It does live round-tripping, so it's easy to move between diagram and code views. It's extensible: users can define their own relations

GenLab abbreviation of Genetics Laboratory .It is a user-friendly bioinformatics tool to support your bioinformatics lab work. GenLab creates a software user-friendly environment, which makes users to make a large number of protein, DNA, and RNA sequence analysis and excellent graphical viewing. It also provides powerful environment for simulations of Protein 3D molecular models. GenLab typically provides: •User-friendly graphical tools used for finding and working with relevant regions of DNA, RNA, and protein sequences. •Full integration of data input, data management, calculation results. This eliminates time spent on manual data transfers between different programs and databases. •Output functionalities, including generation of graphics output.

Multi-categorization Recommendation Adjusting (MRA) is to optimize the results of recommendation based on traditional(basic) recommendation models, through introducing objective category information and taking use of the feature that users always get the habits of preferring certain categories. Besides this, there are two advantages of this improved model: 1) it can be easily applied to any kind of existing recommendation models. And 2) a controller is set in this improved model to provide controllable adjustment range, which thereby makes it possible to provide optional modes of recommendation aiming different kinds of users.

** ATTENTION ** THIS PROJECT HAS MOVED TO: https://github.com/pgmodeler/pgmodeler New releases only will be available on GitHub. PostgreSQL Database Modeler, or simply pgModeler is an open source project of a CASE tool for modeling PostgreSQL that merges the classical concepts of modeling using entity-relationship diagrams with specific features that only PostgreSQL implements. The pgModeler translates the models created by the user to SQL code and apply them onto database clusters from version 8.0 to 9.1. Please, let me know how the pgModeler is working on your computer! Help to improve this project, give your feedback about the software or report any bug at "Tickets" page. Do not forget to detail the bug and if possible attach a screenshot or model database which expressed the bug. Follow the pgModeler profile on Facebook/Twitter and be up-to-date with new features, fixes and releases. https://www.facebook.com/pgmodeler https://twitter.com/pgmodeler

The architecture viewpoints (specifications for architecture views iaw ISO 42010) for TRAK. TRAK is a general systems-thinkers'/system engineering enterprise architecture framework. It is simple, user-friendly, pragmatic and not limited to IT. 100% triple-centric and semantically-sound. Defines a total of 24 viewpoints. The ones needed are selected by taking the task sponsor's concerns and matching them to the typical concerns that each TRAK viewpoint addresses. The triples that address each concern are defined in the TRAK metamodel (https://sf.net/p/trakmetamodel). The mapping between metamodel triple and architecture viewpoint is held with a Neo4J graph model (https://doi.org/10.1002/eng2.12168) and defined using (more) architecture viewpoints (https://www.researchgate.net/publication/335176248_Architecture_Description_Viewpoints_Metamodel_Description_Implementation_and_Model_Changes). The minimal process is defined in the overall TRAK specification (https://sf.net/p/trak)