Skip to main content

Peirce's Criterion: command-line tool

I've written a simple command-line tool filter out statistical outliers using the rigourous Peirce's Criterion.

The algorithm has been available in Sasa for awhile, and will be in the forthcoming v0.9.3 release.

I've also packaged the command-line tool binary for running Peirce's Criterion over multi-column CSV files (LGPL source available here).

Comments

Popular posts from this blog

async.h - asynchronous, stackless subroutines in C

The async/await idiom is becoming increasingly popular. The first widely used language to include it was C#, and it has now spread into JavaScript and Rust. Now C/C++ programmers don't have to feel left out, because async.h is a header-only library that brings async/await to C! Features: It's 100% portable C. It requires very little state (2 bytes). It's not dependent on an OS. It's a bit simpler to understand than protothreads because the async state is caller-saved rather than callee-saved. #include "async.h" struct async pt; struct timer timer; async example(struct async *pt) { async_begin(pt); while(1) { if(initiate_io()) { timer_start(&timer); await(io_completed() || timer_expired(&timer)); read_data(); } } async_end; } This library is basically a modified version of the idioms found in the Protothreads library by Adam Dunkels, so it's not truly ground bre

Simple, Extensible IoC in C#

I just committed the core of a simple dependency injection container to a standalone assembly, Sasa.IoC . The interface is pretty straightforward: public static class Dependency { // static, type-indexed operations public static T Resolve<T>(); public static void Register<T>(Func<T> create) public static void Register<TInterface, TRegistrant>() where TRegistrant : TInterface, new() // dynamic, runtime type operations public static object Resolve(Type registrant); public static void Register(Type publicInterface, Type registrant, params Type[] dependencies) } If you were ever curious about IoC, the Dependency class is only about 100 lines of code. You can even skip the dynamic operations and it's only ~50 lines of code. The dynamic operations then just use reflection to invoke the typed operations. Dependency uses static generic fields, so resolution is pretty much just a field access + invoking a

Easy Automatic Differentiation in C#

I've recently been researching optimization and automatic differentiation (AD) , and decided to take a crack at distilling its essence in C#. Note that automatic differentiation (AD) is different than numerical differentiation . Math.NET already provides excellent support for numerical differentiation . C# doesn't seem to have many options for automatic differentiation, consisting mainly of an F# library with an interop layer, or paid libraries . Neither of these are suitable for learning how AD works. So here's a simple C# implementation of AD that relies on only two things: C#'s operator overloading, and arrays to represent the derivatives, which I think makes it pretty easy to understand. It's not particularly efficient, but it's simple! See the "Optimizations" section at the end if you want a very efficient specialization of this technique. What is Automatic Differentiation? Simply put, automatic differentiation is a technique for calcu