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Showing 202 open source projects for "gmail source code"
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Matplotlib
matplotlib: plotting with Python
Matplotlib is a comprehensive library for creating static, animated, and interactive visualizations in Python. Matplotlib makes easy things easy and hard things possible. Matplotlib ships with several add-on toolkits, including 3D plotting with mplot3d, axes helpers in axes_grid1 and axis helpers in axisartist. A large number of third party packages extend and build on Matplotlib functionality, including several higher-level plotting interfaces (seaborn, HoloViews, ggplot, ...), and a... -
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JuliaWorkshop
Intensive Julia workshop that takes you from zero to hero
This is an intensive workshop for the Julia language, composed out of three 2-hour segments. It targets people already familiar with programming, so that the established basics such as for-loops are skipped through quickly and efficiently. Nevertheless, it assumes only rudimentary programming familiarity and does explain concepts that go beyond the basics. The goal of the workshop is to take you from zero to hero (regarding Julia): even if you know nothing about Julia, by the end you should... -
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Reduce.jl
Symbolic parser for Julia language term rewriting using REDUCE algebra
...It can be used interactively for simple calculations (as illustrated in the screenshot below) but also provides a full programming language, with a syntax similar to other modern programming languages. REDUCE supports alternative user interfaces including Run-REDUCE, TeXmacs and GNU Emacs. REDUCE (and its complete source code) is available free of charge for most common computing systems, in some cases in more than one version for the same machine. The manual and other support documents and tutorials are also included in the distributions. -
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EAGO.jl
A development environment for robust and global optimization
EAGO is an open-source development environment for robust and global optimization in Julia. EAGO is a deterministic global optimizer designed to address a wide variety of optimization problems, emphasizing nonlinear programs (NLPs), by propagating McCormick relaxations along the factorable structure of each expression in the NLP. Most operators supported by modern automatic differentiation (AD) packages (e.g., +, sin, cosh) are supported by EAGO and a number of utilities for sanitizing native Julia code and generating relaxations on a wide variety of user-defined functions have been included. ... -
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Wflow.jl
Hydrological modeling
Wflow is Deltares’ solution for modeling hydrological processes, allowing users to account for precipitation, interception, snow accumulation and melt, evapotranspiration, soil water, surface water and groundwater recharge in a fully distributed environment. Successfully applied worldwide for analyzing flood hazards, drought, climate change impacts and land use changes, wflow is growing to be a leader in hydrology solutions. Wflow is conceived as a framework, within which multiple... -
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DynamicHMC
Implementation of robust dynamic Hamiltonian Monte Carlo methods
Implementation of robust dynamic Hamiltonian Monte Carlo methods in Julia. In contrast to frameworks that utilize a directed acyclic graph to build a posterior for a Bayesian model from small components, this package requires that you code a log-density function of the posterior in Julia. Derivatives can be provided manually, or using automatic differentiation. Consequently, this package requires that the user is comfortable with the basics of the theory of Bayesian inference, to the extent... -
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SPX
A simple & straight-to-the-point PHP profiling extension
SPX, which stands for Simple Profiling eXtension, is just another profiling extension for PHP. It differentiates itself from other similar extensions as being totally free and confined to your infrastructure (i.e. no data leaks to a SaaS). Very simple to use: just set an environment variable (command line) or switch on a radio button (web request) to profile your script. Thus, you are free of manually instrumenting your code (Ctrl-C a long running command line script is even supported).... -
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101-0250-00
ETH course - Solving PDEs in parallel on GPUs
This course aims to cover state-of-the-art methods in modern parallel Graphical Processing Unit (GPU) computing, supercomputing and code development with applications to natural sciences and engineering. -
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LinearSolve.jl
High-Performance Unified Interface for Linear Solvers in Julia
LinearSolve.jl is a unified interface for the linear solving packages of Julia. It interfaces with other packages of the Julia ecosystem to make it easy to test alternative solver packages and pass small types to control algorithm swapping. It also interfaces with the ModelingToolkit.jl world of symbolic modeling to allow for automatically generating high-performance code. Performance is key: the current methods are made to be highly performant on scalar and statically sized small problems,... -
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Gridap.jl
Grid-based approximation of partial differential equations in Julia
Gridap provides a set of tools for the grid-based approximation of partial differential equations (PDEs) written in the Julia programming language. The library currently supports linear and nonlinear PDE systems for scalar and vector fields, single and multi-field problems, conforming and nonconforming finite element (FE) discretizations, on structured and unstructured meshes of simplices and n-cubes. It also provides methods for time integration. Gridap is extensible and modular. One can... -
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errsole.js
Collect, Store, and Visualize Logs with a Single Module
Errsole is an open-source logger for Node.js. It has a built-in web dashboard to view, filter, and search your app logs. -
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CUDA.jl
CUDA programming in Julia
High-performance GPU programming in a high-level language. JuliaGPU is a GitHub organization created to unify the many packages for programming GPUs in Julia. With its high-level syntax and flexible compiler, Julia is well-positioned to productively program hardware accelerators like GPUs without sacrificing performance. The latest development version of CUDA.jl requires Julia 1.8 or higher. If you are using an older version of Julia, you need to use a previous version of CUDA.jl. This will... -
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XCharts
A charting and data visualization library for Unity
A charting and data visualization library for Unity. Unity data visualization chart plugin. A UGUIpowerful, easy-to-use, parameter-configurable data visualization chart plug-in. It supports ten built-in charts. A powerful, easy-to-use, configurable charting and data visualization library for Unity. Visual configuration of parameters, real-time preview of effects, and pure code drawing without additional resources. Support ten built-in charts such as line chart, column chart, pie chart, radar... -
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Cytoscape.js
Graph theory library for visualization and analysis
A fully featured graph library written in pure JS. Permissive open source license (MIT) for the core Cytoscape.js library and all first-party extensions. Used in commercial projects and open-source projects in production. Designed for users first, for both frontfacing app usecases and developer usecases. Highly optimized. Compatible with All modern browsers. Legacy browsers with ES5 and canvas support. -
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LossFunctions.jl
Julia package of loss functions for machine learning
This package represents a community effort to centralize the definition and implementation of loss functions in Julia. As such, it is a part of the JuliaML ecosystem. The sole purpose of this package is to provide an efficient and extensible implementation of various loss functions used throughout Machine Learning (ML). It is thus intended to serve as a special purpose back-end for other ML libraries that require losses to accomplish their tasks. To that end we provide a considerable amount... -
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Chokidar
Minimal and efficient cross-platform file watching library
Chokidar is a solution for all the users of Node.js fs.watch who are tired of it not reporting filenames on MacOS and events at all when using editors like Sublime on MacOS. Node.js fs.watch often reports events twice, emits most changes as rename, and it does not provide an easy way to recursively watch file trees nor supports recursive watching on Linux. Same as with Node.js fs.watchFile. Therefore, Chokidar resolves these problems. Initially made for Brunch (an ultra-swift web app build... -
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jlrs
Julia bindings for Rust
jlrs is a crate that provides access to most of the Julia C API, it can be used to embed Julia in Rust applications and to use functionality it provides when writing ccallable functions in Rust. Currently, this crate is only tested in combination with Julia 1.6 and 1.9, but also supports Julia 1.7, 1.8, and 1.10. Using the current stable version is highly recommended. The minimum supported Rust version is currently 1.65. Julia must be installed before jlrs can be used, jlrs is compatible... -
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ParallelStencil.jl
Package for writing high-level code for parallel stencil computations
ParallelStencil empowers domain scientists to write architecture-agnostic high-level code for parallel high-performance stencil computations on GPUs and CPUs. Performance similar to CUDA C / HIP can be achieved, which is typically a large improvement over the performance reached when using only CUDA.jl or AMDGPU.jl GPU Array programming. For example, a 2-D shallow ice solver presented at JuliaCon 2020 [1] achieved a nearly 20 times better performance than a corresponding GPU Array... -
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Digital Earth Australia notebooks
Repository for Digital Earth Australia Jupyter Notebooks
The knowledge hub brings together information about Digital Earth Australia’s products and services, allowing you to utilize our free and open-source satellite imagery archive. Browse our catalog of data products to find supporting information and ways to access the data. The Digital Earth Australia notebooks and tools repository (dea-notebooks) hosts Jupyter Notebooks, Python scripts and workflows for analyzing Digital Earth Australia (DEA) satellite data and derived products. This... -
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plotly
An interactive graphing library for R
This part of the book teaches you how to leverage the plotly R package to create a variety of interactive graphics. There are two main ways to creating a plotly object: either by transforming a ggplot2 object (via ggplotly()) into a plotly object or by directly initializing a plotly object with plot_ly()/plot_geo()/plot_mapbox(). Both approaches have somewhat complementary strengths and weaknesses, so it can pay off to learn both approaches. Moreover, both approaches are an implementation of... -
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Sweetviz
Visualize and compare datasets, target values and associations
Sweetviz is an open-source Python library that generates beautiful, high-density visualizations to kickstart EDA (Exploratory Data Analysis) with just two lines of code. Output is a fully self-contained HTML application. The system is built around quickly visualizing target values and comparing datasets. Its goal is to help quick analysis of target characteristics, training vs testing data, and other such data characterization tasks. -
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DIY Split-Flap Display
DIY split-flap display
This is a work in progress split-flap display. Each module can flip between 40 unique characters: letters, numbers, and a few symbols. Multiple modules fit perfectly alongside each other to build bigger displays. The primary design goal was to make something that's possible to fabricate at home in small or single quantities and can be customized and built by an intermediate hobbyist at a reasonable price. This meant using widely available materials and avoiding any tooling with a high... -
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city-roads
Visualization of all roads within any city
city-roads is a data visualization and mapping project that renders street networks of cities as vector paths, offering an interactive, zoomable experience that highlights how cities are stitched together by their road infrastructure. It typically fetches open map data (such as from OpenStreetMap) and then processes that data into geometry suited for rendering in the browser, allowing users to explore intricate road layouts at various scales. The visual style often abstracts away labels and... -
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Data Formulator
Create rich visualizations with AI
To create rich visualizations, data analysts often need to iterate back and forth among data processing and chart specification to achieve their goals. To achieve this, analysts need not only proficiency in data transformation and visualization tools but also efforts to manage the branching history consisting of many different versions of data and charts. Recent LLM-powered AI systems have greatly improved visualization authoring experiences, for example by mitigating manual data... -
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TensorBoardX
tensorboard for pytorch (and chainer, mxnet, numpy, etc.)
The SummaryWriter class provides a high-level API to create an event file in a given directory and add summaries and events to it. The class updates the file contents asynchronously. This allows a training program to call methods to add data to the file directly from the training loop, without slowing down training. TensorboardX now supports logging directly to Comet. Comet is a free cloud based solution that allows you to automatically track, compare and explain your experiments. It adds a...
