Search Results for "dynamicreports-examples" - Page 5
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Showing 184 open source projects for "dynamicreports-examples"
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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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The PyPlot module for Julia
Plotting for Julia based on matplotlib.pyplot
This module provides a Julia interface to the Matplotlib plotting library from Python, and specifically to the matplotlib.pyplot module. PyPlot uses the Julia PyCall package to call Matplotlib directly from Julia with little or no overhead (arrays are passed without making a copy). (See also PythonPlot.jl for a version of PyPlot.jl using the alternative PythonCall.jl package.) This package takes advantage of Julia's multimedia I/O API to display plots in any Julia graphical backend,... -
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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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LineSearches.jl
Line search methods for optimization and root-finding
Line search methods for optimization and root-finding. This package provides an interface to line search algorithms implemented in Julia. The code was originally written as part of Optim, but has now been separated out to its own package. -
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OpenCL.jl
OpenCL Julia bindings
Julia interface for the OpenCL parallel computation API. This package aims to be a complete solution for OpenCL programming in Julia, similar in scope to PyOpenCL for Python. It provides a high level API for OpenCL to make programing hardware accelerators, such as GPUs, FPGAs, and DSPs, as well as multicore CPUs much less onerous. -
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Fermi.jl
Fermi quantum chemistry program
Fermi.jl is a quantum chemistry framework written in pure Julia. This code is developed at the Center for Computational Quantum Chemistry at the University of Georgia under the supervision of Dr. Justin M. Turney and Prof. Henry F. Schaefer. This work is supported by the U.S. National Science Foundation under grant number CHE-1661604. Fermi focuses on post Hartree--Fock methods. Currently, only restricted references are supported. This is intended as a research code with an ever growing... -
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BetaML.jl
Beta Machine Learning Toolkit
The Beta Machine Learning Toolkit is a package including many algorithms and utilities to implement machine learning workflows in Julia, Python, R and any other language with a Julia binding. All models are implemented entirely in Julia and are hosted in the repository itself (i.e. they are not wrapper to third-party models). If your favorite option or model is missing, you can try to implement it yourself and open a pull request to share it (see the section Contribute below) or request its... -
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GMT.jl
Generic Mapping Tools Library Wrapper for Julia
The Generic Mapping Tools, GMT, is an open source collection of tools for manipulating geographic and Cartesian data sets (including filtering, trend fitting, gridding, projecting, etc.) and producing PostScript illustrations ranging from simple x–y plots via contour maps to artificially illuminated surfaces and 3D perspective views. This link will take you to an impressive collection of figures made with GMT. The GMT Julia wrapper was designed to work in a way the close as possible to the... -
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FFTW.jl
Julia bindings to the FFTW library for fast Fourier transforms
This package provides Julia bindings to the FFTW library for fast Fourier transforms (FFTs), as well as functionality useful for signal processing. These functions were formerly a part of Base Julia. Users with a build of Julia based on Intel's Math Kernel Library (MKL) can use MKL for FFTs by setting a preference in their top-level project by either using the FFTW.set_provider!() method, or by directly setting the preference using Preferences.jl. Note that this choice will be recorded for... -
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HDF5.jl
Save and load data in the HDF5 file format from Julia
HDF5 stands for Hierarchical Data Format v5 and is closely modeled on file systems. In HDF5, a "group" is analogous to a directory, a "dataset" is like a file. HDF5 also uses "attributes" to associate metadata with a particular group or dataset. HDF5 uses ASCII names for these different objects, and objects can be accessed by Unix-like pathnames, e.g., "/sample1/tempsensor/firsttrial" for a top-level group "sample1", a subgroup "tempsensor", and a dataset "firsttrial". For simple types... -
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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... -
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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.... -
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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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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;... -
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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.... -
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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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Functors.jl
Parameterise all the things
Functors.jl provides tools to express a powerful design pattern for dealing with large/ nested structures, as in machine learning and optimization. For large machine learning models, it can be cumbersome or inefficient to work with parameters as one big, flat vector, and structs help manage complexity; but it is also desirable to easily operate over all parameters at once, e.g. for changing precision or applying an optimizer update step. -
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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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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... -
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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). -
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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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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... -
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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... -
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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... -
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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...