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1
Coverage.jl
Take Julia code coverage and memory allocation results, do useful thin
Julia can track how many times, if any, each line of your code is run. This is useful for measuring how much of your code base your tests actually test, and can reveal the parts of your code that are not tested and might be hiding a bug. You can use Coverage.jl to summarize the results of this tracking or to send them to a service like Coveralls.io or Codecov.io. Julia can track how much memory is allocated by each line of your code. This can reveal problems like type instability, or... -
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PowerSystems.jl
Data structures in Julia to enable power systems analysis
The PowerSystems.jl package provides a rigorous data model using Julia structures to enable power systems analysis and modeling. In addition to stand-alone system analysis tools and data model building, the PowerSystems.jl package is used as the foundational data container for the PowerSimulations.jl and PowerSimulationsDynamics.jl packages. PowerSystems.jl supports a limited number of data file formats for parsing. -
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UnicodePlots
Unicode-based scientific plotting for working in the terminal
Unicode-based scientific plotting for working in the terminal. -
4
MacroTools.jl
MacroTools provides a library of tools for working with Julia code
MacroTools provides a library of tools for working with Julia code and expressions. This includes a powerful template-matching system and code-walking tools that let you do deep transformations of code in a few lines. See the docs for more info. -
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5
AlphaZero.jl
A generic, simple and fast implementation of Deepmind's AlphaZero
Beyond its much publicized success in attaining superhuman level at games such as Chess and Go, DeepMind's AlphaZero algorithm illustrates a more general methodology of combining learning and search to explore large combinatorial spaces effectively. We believe that this methodology can have exciting applications in many different research areas. Because AlphaZero is resource-hungry, successful open-source implementations (such as Leela Zero) are written in low-level languages (such as C++)... -
6
DynamicalBilliards.jl
An easy-to-use, modular, extendable and absurdly fast Julia package
A Julia package for dynamical billiard systems in two dimensions. The goals of the package is to provide a flexible and intuitive framework for fast implementation of billiard systems of arbitrary construction. -
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Agents.jl
Agent-based modeling framework in Julia
...The simplicity of Agents.jl is due to the intuitive space-agnostic modeling approach we have implemented: agent actions are specified using generically named functions (such as "move agent" or "find nearby agents") that do not depend on the actual space the agents exist in, nor on the properties of the agents themselves. Overall this leads to ultra-fast model prototyping where even changing the space the agents live in is a matter of only a couple of lines of code. -
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ImplicitGlobalGrid.jl
Distributed parallelization of stencil-based GPU and CPU applications
ImplicitGlobalGrid is an outcome of a collaboration of the Swiss National Supercomputing Centre, ETH Zurich (Dr. Samuel Omlin) with Stanford University (Dr. Ludovic Räss) and the Swiss Geocomputing Centre (Prof. Yuri Podladchikov). It renders the distributed parallelization of stencil-based GPU and CPU applications on a regular staggered grid almost trivial and enables close to ideal weak scaling of real-world applications on thousands of GPUs [1, 2, 3]. ImplicitGlobalGrid relies on the... -
9
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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10
ReinforcementLearning.jl
A reinforcement learning package for Julia
A collection of tools for doing reinforcement learning research in Julia. Provide elaborately designed components and interfaces to help users implement new algorithms. Make it easy for new users to run benchmark experiments, compare different algorithms, and evaluate and diagnose agents. Facilitate reproducibility from traditional tabular methods to modern deep reinforcement learning algorithms. Make it easy for new users to run benchmark experiments, compare different algorithms, and... -
11
InteractiveErrors.jl
Interactive error messages for the Julia REPL
...Call toggle() again to turn it back on. Press up and down arrows to move through the stacktrace. Press space to fold or unfold the currently selected line. A + will appear on folded lines. Press enter once finished. If you are on a line that references a particular file then that will present additional options in the next menu. q can be pressed to exit back to the REPL. -
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StatProfilerHTML.jl
Show Julia profiling data in an explorable HTML page
This module formats the output from Julia's Profile module into an html rendering of the source function lines and functions, allowing for interactive exploration of any bottlenecks that may exist in your code. -
13
ACME.jl
Analog Circuit Modeling and Emulation for Julia
ACME is a Julia package for the simulation of electrical circuits, focusing on audio effect circuits. It allows one to programmatically describe a circuit in terms of elements and connections between them and then automatically derive a model for the circuit. The model can then be run on varying input data.
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