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Showing 98 open source projects for "scalar"
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ConnectWise CPQ, formerly ConnectWise Sell, is a professional quote and proposal automation software for IT solution providers. ConnectWise CPQ offers a wide range of tools that enables IT solution providers to save time, quote more, and win big. Top features include professional quote or proposal templates, product catalog and sourcing, workflow automation, sales reporting, and integrations with best-in-breed solutions like Cisco, Dell, HP, and Salesforce.
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Our robust pre-built connectors and our no-code, drag-and-drop interface makes it easy and fast to automatically sync vendors, invoices, and invoice payment data between Tipalti and your ERP or accounting software.
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SQLiteStudio
A free, open source, multi-platform SQLite database manager
... encrypted, password-protected SQLite variations are SQLCipher, WxSQLite3, and System.Data.SQLite. You can execute SQL statements that refer to multiple databases within a single query, thanks to a transparent database attaching mechanism built into the SQL Editor of SQLiteStudio. You can implement your own SQL functions (scalar & aggregate) using JavaScript, Python, or Tcl. There is a repository of ready-to-use scripts on the wiki page. -
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OpenBLAS
Optimized BLAS library based on GotoBLAS2 1.13 BSD version
OpenBLAS is an optimized BLAS library based on GotoBLAS2 1.13 BSD version. The BLAS (Basic Linear Algebra Subprograms) are routines that provide standard building blocks for performing basic vector and matrix operations. The Level 1 BLAS performs scalar, vector and vector-vector operations, the Level 2 BLAS performs matrix-vector operations, and the Level 3 BLAS performs matrix-matrix operations. Because the BLAS are efficient, portable, and widely available, they are commonly used... -
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GraphQL Scalars
A library of custom GraphQL Scalars for creating precise schemas
GraphQL is a wonderful new approach to application data and API layers that's gaining momentum. However, for all of GraphQL's greatness, it is missing a couple of things that we have (and you might) find very useful in defining your schemas. Namely GraphQL has a limited set of scalar types, and we have found there are some additional scalar types that are useful in being more precise in our schemas. Thankfully, those sharp GraphQL folks provided a simple way to add new custom scalar types... -
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graphql upload typescript
Middleware and an Upload scalar to add support for GraphQL
Minimalistic and developer-friendly middleware and an Upload scalar to add support for GraphQL multipart requests (file uploads via queries and mutations) to various Node.js GraphQL servers. This module was forked from the amazing graphql-upload-minimal. The original module is exceptionally well-documented and well-written. It was very easy to fork and amend. -
Managing your therapy and rehab practice is a time-consuming process. You spend hours on paperwork, billing, scheduling, and more. Raintree’s Therapy & Rehab EHR is here to help you manage your practice more efficiently. With our all-in-one solution, you’ll get the tools you need to streamline your therapy and rehab practice, improve patient care, and get back to doing what you love.
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PolyChaos.jl
Julia package to construct orthogonal polynomials
PolyChaos is a collection of numerical routines for orthogonal polynomials written in the Julia programming language. Starting from some non-negative weight (aka an absolutely continuous nonnegative measure). -
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StatsBase.jl
Basic statistics for Julia
StatsBase.jl is a Julia package that provides basic support for statistics. Particularly, it implements a variety of statistics-related functions, such as scalar statistics, high-order moment computation, counting, ranking, covariances, sampling, and empirical density estimation. -
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TurboPFor
Fastest Integer Compression
Fastest Integer Compression. ALL functions are available for AMD/Intel, 64-bit ARMv8 NEON Linux+MacOS/M1 & Power9 Altivec. 100% C (C++ headers), as simple as memcpy. OS:Linux amd64, arm64, Power9, MacOs (Amd/intel + Apple M1). -
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Autograd
Efficiently computes derivatives of numpy code
Autograd can automatically differentiate native Python and Numpy code. It can handle a large subset of Python's features, including loops, ifs, recursion and closures, and it can even take derivatives of derivatives of derivatives. It supports reverse-mode differentiation (a.k.a. backpropagation), which means it can efficiently take gradients of scalar-valued functions with respect to array-valued arguments, as well as forward-mode differentiation, and the two can be composed arbitrarily... -
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SymEngine.jl
Julia wrappers of SymEngine
Julia Wrappers for SymEngine, a fast symbolic manipulation library, written in C++. -
ConnectWise PSA (formerly Manage) allows you to stop working in separate systems, and helps you build a more profitable business. No more duplicate data entries, inefficient employees, manual invoices, and the inability to accurately track client service issues. Get a behind the scenes look into the award-winning PSA that automates processes for each area of business: sales, help desk, support, finance, and HR.
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ForwardDiff.jl
Forward Mode Automatic Differentiation for Julia
ForwardDiff implements methods to take derivatives, gradients, Jacobians, Hessians, and higher-order derivatives of native Julia functions (or any callable object, really) using forward mode automatic differentiation (AD). While performance can vary depending on the functions you evaluate, the algorithms implemented by ForwardDiff generally outperform non-AD algorithms (such as finite-differencing) in both speed and accuracy. Functions like f which map a vector to a scalar are the best case... -
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Vearch
A distributed system for embedding-based vector retrieval
Vearch is the vector search infrastructure for deep learning and AI applications. Vearch is a distributed vector storage and retrieval system which can be easily extended to billions scale. Vearch implements a high-performance, lockless real-time vector indexing subsystem that utilizes various optimization techniques to support millisecond vector update and retrieval. End-to-end one-click deployment. Through the module of the plugin, a complete default visual search system can be deployed... -
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MultivariatePolynomials.jl
Multivariate polynomials interface
MultivariatePolynomials.jl is an implementation-independent library for manipulating multivariate polynomials. It defines abstract types and an API for multivariate monomials, terms, and polynomials and gives default implementation for common operations on them using the API. On the one hand, This packages allows you to implement algorithms on multivariate polynomials that will be independant on the representation of the polynomial that will be chosen by the user. On the other hand, it... -
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Handmade Math
A simple math library for games and computer graphics
A single-file, cross-platform, public domain game math library for C/C++. Fully inlined HandmadeMath.h. No need for HANDMADE_MATH_IMPLEMENTATION anymore. Added extra parentheses around some macros. Renamed the 'Rows' member of hmm_mat4 to 'Columns'. Since our matrices are column-major, this should have been named 'Columns' from the start. 'Rows' is still present, but has been deprecated. Added array subscript operators for vector and matrix types in C++. This is provided as a convenience,... -
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TensorBoardLogger.jl
Easy peasy logging to TensorBoard with Julia
TensorBoardLogger.jl is a native library for logging arbitrary data to Tensorboard, extending Julia's standard Logging framework. It can also be used to deserialize TensoBoard's .proto files. The fundamental type defined in this package is a TBLogger, which behaves like other standard loggers in Julia such as ConsoleLogger or TextLogger. You can create one by passing it the path to the folder where you want to store the data. You can also pass an optional second argument to specify the... -
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NonlinearSolve.jl
High-performance and differentiation-enabled nonlinear solvers
Fast implementations of root-finding algorithms in Julia that satisfy the SciML common interface. For information on using the package, see the stable documentation. Use the in-development documentation for the version of the documentation that contains the unreleased features. NonlinearSolve.jl is a unified interface for the nonlinear solving packages of Julia. The package includes its own high-performance nonlinear solvers which include the ability to swap out to fast direct and iterative... -
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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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Reduce.jl
Symbolic parser for Julia language term rewriting using REDUCE algebra
REDUCE is a portable general-purpose computer algebra system. It is a system for doing scalar, vector and matrix algebra by computer, which also supports arbitrary precision numerical approximation and interfaces to gnuplot to provide graphics. 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... -
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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 (one... -
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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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StringZilla
10x faster string search, split, sort, and shuffle for long strings
StringZilla is the Godzilla of string libraries, splitting, sorting, and shuffling large textual datasets. StringZilla uses a heuristic so simple it's almost stupid... but it works. It matches the first few letters of words with hyper-scalar code to achieve memcpy speeds. The implementation fits into a single C 99 header file and uses different SIMD flavors and SWAR on older platforms. The Str is designed to replace long Python str strings and wrap our C-level API. On the other hand, the File... -
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Apollo Kotlin
A strongly-typed, caching GraphQL client for the JVM, Android, etc.
A strongly-typed, caching GraphQL client for Java and Kotlin multiplatform. Apollo Kotlin (formerly Apollo Android) is a GraphQL client that generates Kotlin and Java models from GraphQL queries. Apollo Kotlin executes queries and mutations against a GraphQL server and returns results as query-specific Kotlin types. This means you don't have to deal with parsing JSON, or passing around Maps and making clients cast values to the right type manually. You also don't have to write model types... -
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Darts
A python library for easy manipulation and forecasting of time series
darts is a Python library for easy manipulation and forecasting of time series. It contains a variety of models, from classics such as ARIMA to deep neural networks. The models can all be used in the same way, using fit() and predict() functions, similar to scikit-learn. The library also makes it easy to backtest models, combine the predictions of several models, and take external data into account. Darts supports both univariate and multivariate time series and models. The ML-based models... -
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OpenGL Mathematics
Highly Optimized Graphics Math (glm) for C
Highly optimized 2D|3D math library, also known as OpenGL Mathematics (glm) for `C`. cglm provides lot of utils to help math operations to be fast and quick to write. It is community-friendly, feel free to bring any issues, bugs you faced. Almost all functions (inline versions) and parameters are documented inside the corresponding headers. OpenGL-related functions are dropped to make this lib platform/third-party independent. Make sure you have the latest version and feel free to report... -
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PyMC3
Probabilistic programming in Python
... in a model is not a scalar value or a fixed-length vector, but a function. A Gaussian process (GP) can be used as a prior probability distribution whose support is over the space of continuous functions. PyMC3 provides rich support for defining and using GPs. Variational inference saves computational cost by turning a problem of integration into one of optimization. PyMC3's variational API supports a number of cutting edge algorithms, as well as minibatch for scaling to large datasets. -
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graphql-upload
Middleware and an Upload scalar to add support for GraphQL multipart
Middleware and an Upload scalar to add support for GraphQL multipart requests (file uploads via queries and mutations) to various Node.js GraphQL servers. Clients implementing the GraphQL multipart request spec upload files as Upload scalar query or mutation variables. Their resolver values are promises that resolve file upload details for processing and storage. Files are typically streamed into cloud storage but may also be stored in the filesystem. Use the middleware graphqlUploadKoa...