Found 12 packages
Package Description
Foundational classes for financial, engineering, and scientific applications, including complex number classes, general vector and matrix classes, structured sparse matrix classes and factorizations, general sparse matrix classes and factorizations, general matrix decompositions, least squares solutions, random number generators, Fast Fourier Transforms (FFTs), numerical integration and differentiation methods, function minimization, curve fitting, root-finding, linear and nonlinear programming. This package also provides functions for statistical computation and biostatistics, including descriptive statistics, probability distributions, combinatorial functions, multiple linear regression, hypothesis testing, analysis of variance, multivariate statistics, partial least squares, and nonnegative matrix factorization. Built on .NET Standard 2.0. Requires a minimum of .NET Standard 2.0, .NET 5, .NET Core 2.0 or .NET Framework 4.6.1. Requires libgcc linux. Requires x64 hardware.
This package offers several Density-Peaks based algorithms for clustering (including KNN and MultiManifold) The core algorithm relies on Rodriguez and Laio 2014 (see http://science.sciencemag.org/content/344/6191/1492.full)
This package will transport the user interface from an app built using RemoteBlazorWebView to a server running in the cloud. This allows an app running behind a firewall to be accessed through a browser via a cloud server.
Agent Cooper as a NuGet package
This package will transport the user interface from an app built using BlazorWebView to a server running in the cloud. This allows an app running behind a firewall to be accessed through a browser by accessing the cloud server.
Support Package for RemoteBlazorWebView.WindowsForms and RemoteBlazorWebView.Wpf
This package will transport the user interface from an app built using BlazorWebView to a server running in the cloud. This allows an app running behind a firewall to be accessed through a browser by accessing the cloud server.
.NET 9 package that hosts a remote Blazor UI on Windows, Mac, and Linux
Using combined evidence from replicates to evaluate ChIP-seq peaks
Attempts to automatically remove pespective distortion from an image without the need to manually pick control points. This technique is limited and relies upon the ability to isolate the outline or boundary of the distorted quadrilateral in the input image from its surrounding background. This technique will not look for internal edges or other details to assess the distortion. This technique also works to correct affine distortions such as rotation and/or skew. The basic principal is to isolate the quadrilateral of the distorted region from its background to form a binary mask. The mask is converted from cartesian coordinates to polar coordinates and averaged down to one row. This row is then processed either to find the highest peaks or the highest second derivative peaks. The four peaks identified are then converted back to cartesian coordinates and used with the ouput dimensions determined from the user specified (or computed) aspect ratio and user specified dimension.
Library for hosting the RemoteWebViewService.