Search Results for "google-visualization-python" - Page 15

Showing 3087 open source projects for "google-visualization-python"

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  • 1
    ChainRulesCore

    ChainRulesCore

    AD-backend agnostic system defining custom forward and reverse rules

    AD-backend agnostic system defining custom forward and reverse mode rules. This is the light weight core to allow you to define rules for your functions in your packages, without depending on any particular AD system. The ChainRulesCore package provides a light-weight dependency for defining sensitivities for functions in your packages, without you needing to depend on ChainRules itself. This will allow your package to be used with ChainRules.jl, which aims to provide a variety of common...
    Downloads: 14 This Week
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  • 2
    Roots.jl

    Roots.jl

    Root finding functions for Julia

    This package contains simple routines for finding roots, or zeros, of scalar functions of a single real variable using floating-point math. The find_zero function provides the primary interface. The basic call is find_zero(f, x0, [M], [p]; kws...) where, typically, f is a function, x0 a starting point or bracketing interval, M is used to adjust the default algorithms used, and p can be used to pass in parameters. Bisection-like algorithms. For functions where a bracketing interval is known...
    Downloads: 20 This Week
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  • 3
    SimpleTraits.jl

    SimpleTraits.jl

    Simple Traits for Julia

    This package provides a macro-based implementation of traits, using Tim Holy's trait trick. The main idea behind traits is to group types outside the type-hierarchy and to make dispatch work with that grouping. The difference to Union-types is that types can be added to a trait after the creation of the trait, whereas Union types are fixed after creation. The cool thing about Tim's trick is that there is no performance impact compared to using ordinary dispatch. For a bit of background and a...
    Downloads: 9 This Week
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  • 4
    Interpolations.jl

    Interpolations.jl

    Fast, continuous interpolation of discrete datasets in Julia

    This package implements a variety of interpolation schemes for the Julia language. It has the goals of ease of use, broad algorithmic support, and exceptional performance. Currently, this package supports B-splines and irregular grids. The API has been designed with the intent to support more options. Initial support for Lanczos interpolation was recently added. Pull requests are more than welcome! It should be noted that the API may continue to evolve over time.
    Downloads: 9 This Week
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  • 5
    ReactiveMP.jl

    ReactiveMP.jl

    High-performance reactive message-passing based Bayesian engine

    ReactiveMP.jl is a Julia package that provides an efficient reactive message passing based Bayesian inference engine on a factor graph. The package is a part of the bigger and user-friendly ecosystem for automatic Bayesian inference called RxInfer. While ReactiveMP.jl exports only the inference engine, RxInfer provides convenient tools for model and inference constraints specification as well as routines for running efficient inference both for static and real-time datasets.
    Downloads: 7 This Week
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  • 6
    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: 7 This Week
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  • 7
    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: 13 This Week
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  • 8
    BlockArrays.jl

    BlockArrays.jl

    BlockArrays for Julia

    A block array is a partition of an array into blocks or subarrays, see Wikipedia for a more extensive description. This package has two purposes. Firstly, it defines an interface for an AbstractBlockArray block arrays that can be shared among types representing different types of block arrays. The advantage to this is that it provides a consistent API for block arrays. Secondly, it also implements two different types of block arrays that follow the AbstractBlockArray interface. The type...
    Downloads: 13 This Week
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  • 9
    Flet

    Flet

    Flet enables developers to easily build realtime web and mobile apps

    ...With Flet you just write a monolith stateful app in Python only and get a multi-user, real-time Single-Page Application (SPA). To start developing with Flet, you just need your favorite IDE or text editor. With no SDKs, no thousands of dependencies, no complex tooling, Flet has a built-in web server with assets hosting and desktop clients.
    Downloads: 67 This Week
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  • 10
    PowerSimulations.jl

    PowerSimulations.jl

    Julia for optimization simulation and modeling of PowerSystems

    PowerSimulations.jl is a Julia package for power system modeling and simulation of Power Systems operations. Provide a flexible modeling framework that can accommodate problems of different complexity and at different time scales. Streamline the construction of large-scale optimization problems to avoid repetition of work when adding/modifying model details. Exploit Julia's capabilities to improve computational performance of large-scale power system quasi-static simulations. The flexible...
    Downloads: 25 This Week
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  • 11
    Coverage.jl

    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...
    Downloads: 10 This Week
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  • 12
    LaTeXStrings.jl

    LaTeXStrings.jl

    convenient input and display of LaTeX equation strings for Julia

    This is a small package to make it easier to type LaTeX equations in string literals in the Julia language, written by Steven G. Johnson. With ordinary strings in Julia, to enter a string literal with embedded LaTeX equations you need to manually escape all backslashes and dollar signs: for example, $\alpha^2$ is written \$\\alpha^2\$. Also, even though IJulia is capable of displaying formatted LaTeX equations (via MathJax), an ordinary string will not exploit this.
    Downloads: 8 This Week
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  • 13
    QuadGK.jl

    QuadGK.jl

    adaptive 1d numerical Gauss–Kronrod integration in Julia

    This package provides support for one-dimensional numerical integration in Julia using adaptive Gauss-Kronrod quadrature. The code was originally part of Base Julia. It supports the integration of arbitrary numeric types, including arbitrary-precision (BigFloat), and even the integration of arbitrary normed vector spaces. The package provides three basic functions: quadgk, gauss, and kronrod. quadgk performs the integration, gauss computes Gaussian quadrature points and weights for...
    Downloads: 10 This Week
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  • 14
    LinearSolve.jl

    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,...
    Downloads: 17 This Week
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  • 15
    EasyAppointments

    EasyAppointments

    Easy!Appointments - Self Hosted Appointment Scheduler

    ...It offers a web-based interface where clients can book appointments online, while administrators can manage staff schedules, services, and customer data. The system is highly customizable and can be integrated with other tools like Google Calendar, making it ideal for small businesses, clinics, and service providers.
    Downloads: 4 This Week
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  • 16
    Rackula

    Rackula

    Drag and drop rack visualizer

    Rackula is a browser-based rack layout designer aimed at homelabbers, audio/video technicians, and equipment organizers who want a visual way to plan and document physical device racks. It runs entirely client-side with no backend server required, making it lightweight, fast, and easy to self-host or run locally without external dependencies. Users can drag and drop devices into customizable rack spaces, annotate equipment, set unit sizes, and manage complex layouts as their setup evolves....
    Downloads: 23 This Week
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  • 17
    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: 23 This Week
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  • 18
    DynamicHMC

    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...
    Downloads: 11 This Week
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  • 19
    scikit-learn

    scikit-learn

    Machine learning in Python

    scikit-learn is an open source Python module for machine learning built on NumPy, SciPy and matplotlib. It offers simple and efficient tools for predictive data analysis and is reusable in various contexts.
    Downloads: 18 This Week
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  • 20
    GLFW.jl

    GLFW.jl

    Julia interface to GLFW, a multi-platform library for creating windows

    Julia interface to GLFW 3, a multi-platform library for creating windows with OpenGL or OpenGL ES contexts and receiving many kinds of input. GLFW has native support for Windows, OS X and many Unix-like systems using the X Window System, such as Linux and FreeBSD.
    Downloads: 7 This Week
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  • 21
    The NLopt module for Julia

    The NLopt module for Julia

    Package to call the NLopt nonlinear-optimization library from Julia

    This module provides a Julia-language interface to the free/open-source NLopt library for nonlinear optimization. NLopt provides a common interface for many different optimization algorithms.
    Downloads: 7 This Week
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  • 22
    Literate

    Literate

    Simple package for literate programming in Julia

    Literate is a package for Literate Programming. The main purpose is to facilitate writing Julia examples/tutorials that can be included in your package documentation. Literate can generate markdown pages (for e.g. Documenter.jl), and Jupyter notebooks, from the same source file. There is also an option to "clean" the source from all metadata, and produce a pure Julia script. Using a single source file for multiple purposes reduces maintenance, and makes sure your different output formats are...
    Downloads: 7 This Week
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  • 23
    jlrs

    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...
    Downloads: 15 This Week
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  • 24
    Convex.jl

    Convex.jl

    A Julia package for disciplined convex programming

    Convex.jl is a Julia package for Disciplined Convex Programming (DCP). Convex.jl makes it easy to describe optimization problems in a natural, mathematical syntax, and to solve those problems using a variety of different (commercial and open-source) solvers. Convex.jl works by transforming the problem—which possibly has nonsmooth, nonlinear constructions like the nuclear norm, the log determinant, and so forth—into a linear optimization problem subject to conic constraints. This...
    Downloads: 15 This Week
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  • 25
    Metabase

    Metabase

    The simplest, fastest way to share business intelligence and analytics

    Metabase is the easiest way to let everyone in your company access business data and analytics, learn from it and ask questions. Even if you or your colleagues have no experience in SQL, you can easily summarize and visualize your data, share it and let your team ask questions about it. Metabase creates beautiful graphs and charts, with an easy-to-use dashboard where everyone can create, organize and share exceptionally visualized data. It supports a great number of databases, including...
    Downloads: 21 This Week
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