Showing 248 open source projects for "dynamicreports-examples"

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  • 1
    DataFramesMeta.jl

    DataFramesMeta.jl

    Metaprogramming tools for DataFrames

    Metaprogramming tools for DataFrames.jl objects to provide more convenient syntax. DataFrames.jl has the functions select, transform, and combine, as well as the in-place select! and transform! for manipulating data frames. DataFramesMeta.jl provides the macros @select, @transform, @combine, @select!, and @transform! to mirror these functions with more convenient syntax. Inspired by dplyr in R and LINQ in C#.
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  • 2
    JuliaConnectoR

    JuliaConnectoR

    A functionally oriented interface for calling Julia from R

    This R-package provides a functionally oriented interface between R and Julia. The goal is to call functions from Julia packages directly as R functions. Julia functions imported via the JuliaConnectoR can accept and return R variables. It is also possible to pass R functions as arguments in place of Julia functions, which allows callbacks from Julia to R. From a technical perspective, R data structures are serialized with an optimized custom streaming format, sent to a (local) Julia TCP...
    Downloads: 1 This Week
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  • 3
    CondaPkg.jl

    CondaPkg.jl

    Add Conda dependencies to your Julia project

    Add Conda dependencies to your Julia project. This package is a lot like Pkg from the Julia standard library, except that it is for managing Conda packages. Conda dependencies are defined in CondaPkg.toml, which is analogous to Project.toml. CondaPkg will install these dependencies into a Conda environment specific to the current Julia project. Hence dependencies are isolated from other projects or environments. Functions like add, rm, status exist to edit the dependencies programmatically....
    Downloads: 1 This Week
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  • 4
    JuliaWorkshop

    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...
    Downloads: 1 This Week
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  • 5
    StaticTools.jl

    StaticTools.jl

    Enabling StaticCompiler.jl-based compilation of (some) Julia code

    Tools to enable StaticCompiler.jl-based static compilation of Julia code (or more accurately, a subset of Julia which we might call "unsafe Julia") to standalone native binaries by avoiding GC allocations and llvmcall-ing all the things. This package currently requires Julia 1.8 or greater for best results (if in doubt, check which versions are passing CI). Integration tests against StaticCompiler.jl and LoopVectorization.jl are currently run with Julia 1.8 and 1.9 on x86-64 Linux and mac;...
    Downloads: 1 This Week
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  • 6
    HomotopyContinuation.jl

    HomotopyContinuation.jl

    A Julia package for solving systems of polynomials

    HomotopyContinuation.jl is a Julia package for solving systems of polynomial equations by numerical homotopy continuation. Many models in the sciences and engineering are expressed as sets of real solutions to systems of polynomial equations. We can optimize any objective whose gradient is an algebraic function using homotopy methods by computing all critical points of the objective function. An important special case is when the objective function is the euclidean distance to a given point....
    Downloads: 1 This Week
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  • 7
    Infiltrator.jl

    Infiltrator.jl

    No-overhead breakpoints in Julia

    This package provides the @infiltrate macro, which acts as a breakpoint with negligible runtime performance overhead. Note that you cannot access other function scopes or step into further calls. Use an actual debugger if you need that level of flexibility. Running code that ends up triggering the @infiltrate REPL mode via inline evaluation in VS Code or Juno can cause issues, so it's recommended to always use the REPL directly. When the infiltration point is hit, it will drop you into an...
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  • 8
    ImageInTerminal.jl

    ImageInTerminal.jl

    Julia package for displaying images in the terminal using ANSI colors

    ImageInTerminal is a drop-in package that once imported changes how a single Colorant and whole Colorant arrays (regular images) are displayed in the interactive REPL. The displayed images will be downscaled to fit into the size of your active terminal session. By default, this package will detect if your running terminal supports 24-bit colors (true colors). If it does, the image will be displayed in 24-bit colors, otherwise, it falls back to 8-bit (256 colors).
    Downloads: 0 This Week
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  • 9
    ReachabilityAnalysis.jl

    ReachabilityAnalysis.jl

    Compute reachable states of dynamical systems

    Reachability analysis is concerned with computing rigorous approximations of the set of states reachable by a dynamical system. In the scope of this package are systems modeled by continuous or hybrid dynamical systems, where the dynamics change with discrete events. Systems are modeled by ordinary differential equations (ODEs) or semi-discrete partial differential equations (PDEs), with uncertain initial states, uncertain parameters or non-deterministic inputs.
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  • 10
    Observable Plot

    Observable Plot

    A concise API for exploratory data visualization

    Observable Plot is a free, open-source JavaScript library to help you quickly visualize tabular data. It has a concise and (hopefully) memorable API to foster fluency — and plenty of examples to learn from and copy-paste. In the spirit of show don’t tell, below is a scatterplot of the height and weight of Olympic athletes (sourced from Matt Riggott), constructed using a dot mark. We assign columns of data (such as weight) to visual properties (such as the dot’s x), and Plot infers the rest. You can configure much more, if needed, but Plot’s goal is to help you get a meaningful visualization quickly. ...
    Downloads: 3 This Week
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  • 11
    WordCloud.jl

    WordCloud.jl

    Word cloud generator in julia

    Word cloud (tag cloud or wordle) is a novelty visual representation of text data. The importance of each word is shown with its font size, position, or color. WordCloud.jl is the perfect tool for generating word clouds, offering several advantages. You have control over every aspect of generating a word cloud. You can customize the shape, color, angle, position, distribution, density, and spacing to align with your preferences and artistic style. This visualization solution guarantees...
    Downloads: 2 This Week
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  • 12
    SciML Style Guide for Julia

    SciML Style Guide for Julia

    A style guide for stylish Julia developers

    The SciML Style Guide is a style guide for the Julia programming language. It is used by the SciML Open Source Scientific Machine Learning Organization. As such, it is open to discussion with the community. If the standard for code contributions is that every PR needs to support every possible input type that anyone can think of, the barrier would be too high for newcomers. Instead, the principle is to be as correct as possible to begin with, and grow the generic support over time. All...
    Downloads: 1 This Week
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  • 13
    Wavelets.jl

    Wavelets.jl

    A Julia package for fast discrete wavelet transforms and utilities

    A Julia package for fast wavelet transforms (1-D, 2-D, 3-D, by filtering or lifting). The package includes discrete wavelet transforms, column-wise discrete wavelet transforms, and wavelet packet transforms. 1st generation wavelets using filter banks (periodic and orthogonal). Filters are included for the following types: Haar, Daubechies, Coiflet, Symmlet, Battle-Lemarie, Beylkin, Vaidyanathan. 2nd generation wavelets by lifting (periodic and general type including orthogonal and...
    Downloads: 1 This Week
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  • 14
    AppleAccelerate.jl

    AppleAccelerate.jl

    Julia interface to the macOS Accelerate framework

    Julia interface to the macOS Accelerate framework. This provides a Julia interface to some of the macOS Accelerate frameworks. At the moment, this package provides access to Accelerate BLAS and LAPACK using the libblastrampoline framework, an interface to the array-oriented functions, which provide a vectorized form for many common mathematical functions. The performance is significantly better than using standard libm functions in some cases, though there does appear to be some reduced...
    Downloads: 0 This Week
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  • 15
    CausalityTools.jl

    CausalityTools.jl

    Algorithms for detecting associations, dynamical influences

    CausalityTools.jl is a package for quantifying associations and dynamical coupling between datasets, independence testing, and causal inference. Association measures from conventional statistics, information theory, and dynamical systems theory, for example, distance correlation, mutual information, transfer entropy, convergent cross mapping and a lot more. A dedicated API for independence testing, which comes with automatic compatibility with every measure-estimator combination you can...
    Downloads: 0 This Week
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  • 16
    ComponentArrays.jl

    ComponentArrays.jl

    Arrays with arbitrarily nested named components

    The main export of this package is the ComponentArray type. "Components" of ComponentArrays are really just array blocks that can be accessed through a named index. This will create a new ComponentArray whose data is a view into the original, allowing for standalone models to be composed together by simple function composition. In essence, ComponentArrays allow you to do the things you would usually need a modeling language for, but without actually needing a modeling language. The main...
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  • 17
    Digital Earth Australia notebooks

    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...
    Downloads: 2 This Week
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  • 18
    FEniCS.jl

    FEniCS.jl

    A scientific machine learning (SciML) wrapper for the FEniCS

    FEniCS.jl is a wrapper for the FEniCS library for finite element discretizations of PDEs. This wrapper includes three parts. Installation and direct access to FEniCS via a Conda installation. Alternatively one may use their current FEniCS installation. A low-level development API and provides some functionality to make directly dealing with the library a little bit easier, but still requires knowledge of FEniCS itself. Interfaces have been provided for the main functions and their...
    Downloads: 2 This Week
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  • 19
    Promviz

    Promviz

    Visualize traffic of your clusters in realtime from Prometheus data

    Promviz is a visualization tool for Prometheus, enabling users to create custom dashboards and analyze Prometheus metrics interactively.
    Downloads: 7 This Week
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  • 20
    Chromatone

    Chromatone

    Chromatone is a digital garden of visual music theory

    Cards and short overviews on the physics and physiology of vision and hearing and their intersection at visual music research, exploration, practice, and self-expression. Useful tools to have in the pocket like a pack of interactive cards to learn and use in everyday music practice. These are open source web experiments with different aspects of sound and color. Chromatone is an open source research and design project to explore, develop and implement the scientific way of visual music...
    Downloads: 1 This Week
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  • 21
    NeuralOperators.jl

    NeuralOperators.jl

    DeepONets, Neural Operators, Physics-Informed Neural Ops in Julia

    Neural operator is a novel deep learning architecture. It learns an operator, which is a mapping between infinite-dimensional function spaces. It can be used to resolve partial differential equations (PDE). Instead of solving by finite element method, a PDE problem can be resolved by training a neural network to learn an operator mapping from infinite-dimensional space (u, t) to infinite-dimensional space f(u, t). Neural operator learns a continuous function between two continuous function...
    Downloads: 1 This Week
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  • 22
    Java Tablesaw

    Java Tablesaw

    Java dataframe and visualization library

    ...Import data from RDBMS, Excel, CSV, TSV, JSON, HTML, or Fixed Width text files, whether they are local or remote (http, S3, etc.) Tablesaw supports data visualization by providing a wrapper for the Plot.ly JavaScript plotting library. Here are a few examples of the new library in action. Descriptive stats: mean, min, max, median, sum, product, standard deviation, variance, percentiles, geometric mean, skewness, kurtosis, etc. Add tablesaw-core to your project. You can find the version number for the latest release in the release notes.
    Downloads: 1 This Week
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  • 23
    billboard.js

    billboard.js

    Re-usable, easy interface JavaScript chart library based on D3.js

    ...Yes, billboard.js works on D3 v4+; what everybody was waiting for! All of the code was written as an ESM(ES Module) with ES6+ syntax. Combine hundreds of options to satisfy your needs. Checkout the examples to see in action! Play with the diverse options generated on the fly! If you want to use 'billboard.js' without installation, load files directly from one of the CDN providers.
    Downloads: 1 This Week
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  • 24
    JDF.jl

    JDF.jl

    Julia DataFrames serialization format

    JDF is a DataFrames serialization format with the following goals, fast save and load times, compressed storage on disk, enabled disk-based data manipulation (not yet achieved), and support for machine learning workloads, e.g. mini-batch, sampling (not yet achieved). JDF stores a DataFrame in a folder with each column stored as a separate file. There is also a metadata.jls file that stores metadata about the original DataFrame. Collectively, the column files, the metadata file, and the...
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  • 25
    DiffOpt.jl

    DiffOpt.jl

    Differentiating convex optimization programs w.r.t. program parameters

    DiffOpt.jl is a package for differentiating convex optimization programs (JuMP.jl or MathOptInterface.jl models) with respect to program parameters. Note that this package does not contain any solver. This package has two major backends, available via the reverse_differentiate! and forward_differentiate! methods, to differentiate models (quadratic or conic) with optimal solutions. Differentiable optimization is a promising field of convex optimization and has many potential applications in...
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