Search Results for "make" - Page 4
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Showing 152 open source projects for "make"
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Datafor Visualization and Analysis
Visualization and Analysis
Datafor is a self-service agile BI tool that provides intuitive and user-friendly data visualization and analysis capabilities to help users quickly explore, analyze, and make decisions with their data. -
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qvge
Qt Visual Graph Editor
qvge is a multiplatform graph editor written in C++/Qt. Its main goal is to make possible visually edit two-dimensional graphs in a simple and intuitive way. Please note that qvge is not a replacement for such a software like Gephi, Graphvis, Dot, yEd, Dia and so on. It is neither a tool for "big data analysis" nor a math application. It is really just a simple graph editor :) -
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cogli2
A simple tool for the visualisation of coarse-grained systems
cogli2 (formerly known as cogli1) is a simple tool to visualise configurations of coarse-grained simulations. It is straightforward to use and it has a few features that make it very handy to produce publication-ready figures. It supports its own file format but implementing additional parsers is fairly easy. As of now it is not well documented, but this is something we will improve upon in the near future. -
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Orbit
ORBIT : Operating Business Intelligence Tool
ORBIT : Operating Business Intelligence Tool Making Data Accessible Through Centralized Database Access ORBIT is a business intelligence tool designed to make data accessible to a broad audience within your company by centralizing access to databases. With this application, users can easily create reports, perform interactive analyses, and extract insights from raw data. The application simplifies data handling by providing easy-to-use features for non-technical users while maintaining flexibility for advanced queries. -
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PlateEditor
PlateEditor, a free web application to work with multi-well plates
... - PlateEditor is available at this address: https://plateeditor.sourceforge.io - The source code is also available on GitHub, visit: https://github.com/vindelorme/PlateEditor More information about the source code and the API are available there (the wiki is still under construction, thanks for your patience!) For a list of recent updates, visit: https://sourceforge.net/p/plateeditor/wiki/Updates/ Hoping PlateEditor will make your life easier in the lab! If yes, please cite us: https://doi.org/10.1371/journal.pone.0252488 -
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Mara Pipelines
A lightweight opinionated ETL framework, halfway between plain scripts
...Data integration pipelines as code: pipelines, tasks and commands are created using declarative Python code. PostgreSQL as a data processing engine. Extensive web ui. The web browser as the main tool for inspecting, running and debugging pipelines. GNU make semantics. Nodes depend on the completion of upstream nodes. No data dependencies or data flows. No in-app data processing: command line tools as the main tool for interacting with databases and data. Single machine pipeline execution based on Python's multiprocessing. No need for distributed task queues. Easy debugging and output logging. ... -
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123VCF
An Intuitive and Efficient Tool for VCF file filtration
123VCF has been developed to make the filtration step of VCF files efficient and more importantly easy to understand. It can be used in the most important step of whole exome/genome sequencing data analysis in the research and also clinical settings. User manual: https://dl.adbioinformatics.net/123VCF/123VCF_Manual.ver2.pdf If you use 123VCF, please cite its paper: Eidi, M., Abdolalizadeh, S., Moeini, S. et al. 123VCF: an intuitive and efficient tool for filtering VCF files. ... -
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PANDORA
Revolutionizing Biomedical Research with Advanced Machine Learning
...In order to run a test instance of PANDORA, users will first need to prepare their local environment by downloading, installing, and configuring Docker. genular is a community behind SIMON an open-source Machine Learning KnowledgeDiscovery software, built by a vibrant community of people just like you! Join us and make SIMON even cooler! Exploratory analysis of machine learning results with the help of many different visualization techniques will give you instant insights into models and data. -
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TOAST UI Chart
Beautiful chart for data visualization
...Chart components like the title, axes, legends, tooltips, plots, series, and more can be customized through the options. Add different options and animations according to the charts' sizes by using the responsive option. Make the data presented in the Line, Area, and Treemap Charts zoomable with the zoomable option. View and manage new data as they are added realtime with the addData API and the options.series.shift option. -
MongoDB Atlas runs apps anywhereMongoDB Atlas gives you the freedom to build and run modern applications anywhere—across AWS, Azure, and Google Cloud. With global availability in over 115 regions, Atlas lets you deploy close to your users, meet compliance needs, and scale with confidence across any geography.
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Diana.jl
GraphQL for Julia
GraphQL is a data query language for APIs and a runtime for fulfilling those queries with your existing data developed by Facebook in 2012 and launched on the internet in 2015. It is an alternative to REST and ad-hoc web service architectures. -
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Augmentor.jl
A fast image augmentation library in Julia for machine learning
A fast library for increasing the number of training images by applying various transformations. Augmentor is a real-time image augmentation library designed to render the process of artificial dataset enlargement more convenient, less error prone, and easier to reproduce. It offers the user the ability to build a stochastic image-processing pipeline (or simply augmentation pipeline) using image operations as building blocks. In other words, an augmentation pipeline is little more but a... -
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Starlight.jl
A greedy game engine for greedy programmers
Welcome to the documentation for Starlight.jl, a greedy application framework for greedy developers. Its primary use case is video games, but the power of Julia, SDL2, Vulkan, and the Bullet Physics SDK can be leveraged to make just about anything you want. With a focus on flexibility and code quality, Starlight aims to be such a framework. It includes a suite of components and integrations that make it particuarly well-suited for video games, so it is not a stretch to call it a "game engine". However, Starlight is most fundamentally a scripting layer for SDL, Vulkan, and Bullet (via the Telescope backend), meaning it can be used for any application that needs high-performance rendering and physics. ... -
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Semagrams.jl
A graphical editor for graph-like structures
...Legacy version built with typescript is in the legacy branch, and will not receive updates; new version with scala is now in the main branch. The core of Semagrams is just a library; in order to make it do things, one needs to create an "app" that uses it. Currently, the only app that is being developed is a Petri net editor, though this will soon change. In order to run the Petri net editor standalone, install Mill and npm, and then in one terminal in scala/ run mill --watch apps.petri.fullLinkJS and in another terminal in scala/ run npm run dev. ... -
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UE Viewer
Viewer and exporter for Unreal Engine 1-4 assets
...You may find a Perl script in Tools/genmake. This script generates makefiles from some human-friendly project format. After that you may build generated makefile using 'nmake' for Visual Studio or 'make' for gcc. -
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LogicalSets
Integrated Comprehensive Data Architecture & Methodology
This is an advanced data architecture and methodology. A comprehensive Enterprise Resource Management System. A re-usable database with rules for customization, While being a data driven transaction processing engine, this system has very advanced reporting capabilities. This design eliminates up to 90% of business logic due to the way the data is structured. Uses a concept called Table Sets. Has a compound key that tells the programmer what tableset, which record which applet... -
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Hedgehog Lab
Run, compile and execute JavaScript for Scientific Computing
Hedgehog Lab is an open-source scientific computation tool in the browser. Before the development, Pleases make sure you are already installed and enabled the yarn. Once cloned, switch to the dev branch and navigate to the folder by typing cd hedgehog-lab and then running the provided commands. On each run the program compiles and it takes time. Please wait until it shows "Compiled successfully!" and instructions about with which IP:PORT to connect. -
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Actors.jl
Concurrent computing in Julia based on the Actor Model
Concurrent computing in Julia based on the Actor Model. Actors make(s) concurrency easy to understand and reason about and integrate(s) well with Julia's multi-threading and distributed computing. It provides an API for writing reactive applications. -
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TensorBase
TensorBase is a new big data warehousing with modern efforts
TensorBase hopes the open source not become a copy game. TensorBase has a clear-cut opposition to fork communities, repeat wheels, or hack traffic for so-called reputations (like Github stars). After thoughts, we decided to temporarily leave the general data warehousing field. For people who want to learn how a database system can be built up, or how to apply modern Rust to the high-performance field, or embed a lightweight data analysis system into your own big one. You can still try, ask... -
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Kale
Kubeflow’s superfood for Data Scientists
...Kubeflow is a great platform for orchestrating complex workflows on top Kubernetes and Kubeflow Pipeline provides the mean to create reusable components that can be executed as part of workflows. The self-service nature of Kubeflow make it extremely appealing for Data Science use, at it provides an easy access to advanced distributed jobs orchestration, re-usability of components, Jupyter Notebooks, rich UIs and more. Still, developing and maintaining Kubeflow workflows can be hard for data scientists, who may not be experts in working orchestration platforms and related SDKs. ... -
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MLDataUtils.jl
Utility package for generating, loading, and processing ML datasets
...Most of the following sub-categories are covered by a single back-end package that is specialized on that specific problem. Consequently, if one of the following topics is of special interest to you, make sure to check out the corresponding documentation of that package. -
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ReplMaker.jl
Simple API for building repl modes in Julia
The idea behind ReplMaker.jl is to make a tool for building (domain-specific) languages in Julia. Suppose you've invented some language called MyLang and you've implemented a parser that turns MyLang code into Julia code which is then supposed to be executed by the Julia runtime. With ReplMaker.jl, you can simply hook your parser into the package and ReplMaker will then create a REPL mode where end users just type MyLang code and have it executed automatically. -
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Reproducible-research
A Reproducible Data Analysis Workflow with R Markdown, Git, Make, etc.
...The workflow leverages established tools and practices from software engineering. It combines the benefits of various open-source software tools including R Markdown, Git, Make, and Docker, whose interplay ensures seamless integration of version management, dynamic report generation conforming to various journal styles, and full cross-platform and long-term computational reproducibility. The workflow ensures meeting the primary goals that 1) the reporting of statistical results is consistent with the actual statistical results (dynamic report generation), 2) the analysis exactly reproduces at a later point in time even if the computing platform or software is changed (computational reproducibility), and 3) changes at any time (during development and post-publication) are tracked, tagged, and documented while earlier versions of both data and code remain accessible. -
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repo2docker GitHub Action
A GitHub action to build data science environment images
Trigger repo2docker to build a Jupyter enabled Docker image from your GitHub repository and push this image to a Docker registry of your choice. This will automatically attempt to build an environment from configuration files found in your repository. Images generated by this action are automatically tagged with both latest and <SHA> corresponding to the relevant commit SHA on GitHub. Both tags are pushed to the Docker registry specified by the user. If an existing image with the latest tag... -
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Forecasting Best Practices
Time Series Forecasting Best Practices & Examples
Time series forecasting is one of the most important topics in data science. Almost every business needs to predict the future in order to make better decisions and allocate resources more effectively. This repository provides examples and best practice guidelines for building forecasting solutions. The goal of this repository is to build a comprehensive set of tools and examples that leverage recent advances in forecasting algorithms to build solutions and operationalize them. ... -
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Strategems
Quantitative systematic trading strategy development and backtesting
Strategems is a Julia package aimed at simplifying and streamlining the process of developing, testing, and optimizing algorithmic/systematic trading strategies. This package is inspired in large part by the quantstrat1,2 package in R, adopting a similar general structure to the building blocks that make up a strategy. Given the highly iterative nature of event-driven trading strategy development, Julia's high-performance design (particularly in the context of loops) and straightforward syntax would seem to make it a natural fit as a language for systematic strategy research and development. While this package remains early in development, with time the hope is to be able to rapidly implement a trading idea, construct a historical backtest, analyze its results, optimize over a given parameter set, and visualize all of this with great detail.
