# Maths, Stats & Functional Programming Formerly known as Idontgetoutmuch's Weblog This is one page of public article previews, not the complete archive. Follow Next page to continue. Summaries are not the original full articles. ## Stochastic Systems, Fokker-Planck and the Heat Equation via Haskell DevFeed: [Stochastic Systems, Fokker-Planck and the Heat Equation via Haskell]() Original publisher: [Read original article]() Author: Dominic Steinitz Published: 2020-04-26T14:20:10Z Content type: tutorial Language: en Sources: [Maths, Stats & Functional Programming]() Topics: [systems](), [Haskell](), [Library](), [C]() Tags: [c](), [example](), [examples](), [haskell](), [library](), [numerical-methods](), [numerics](), [partial-differential-equations](), [source](), [system](), [systems](), [using](), [with]() ### AI overview A short Haskell example models a stochastic system with the Fokker-Planck method, converts it to a partial differential equation, and solves a two-dimensional equation using SUNDIALS through the hmatrix-sundials library. The example is based on C examples included with the SUNDIALS source. ### Source excerpt This is a short example of taking a stochastic system, using Fokker-Planck to convert it to a PDES and using SUNDIALS to solve a 2D partial differential equation in Haskell via the hmatrix-sundials library. The example is taken from the C examples that come with the SUNDIALS source. Here's the full blog. ## One Dimensional Heat Equation via SUNDIALS and Haskell DevFeed: [One Dimensional Heat Equation via SUNDIALS and Haskell]() Original publisher: [Read original article]() Author: Dominic Steinitz Published: 2019-10-22T09:45:32Z Content type: tutorial Language: en Sources: [Maths, Stats & Functional Programming]() Topics: [Haskell](), [Library]() Tags: [example](), [haskell](), [library](), [uncategorized]() ### AI overview A short Haskell example showing how to use SUNDIALS through the hmatrix-sundials library to solve a simple one-dimensional heat-equation partial differential equation. The example is based on C examples included with the SUNDIALS source. ### Source excerpt This is a short example of how to use SUNDIALS to solve a simple partial differential equation in Haskell via the hmatrix-sundials library. The example is taken from the C examples that come with the SUNDIALS source. Here's the full blog. I'll give a better URL soonish. ## Data Science in Haskell: An example using temperature data from Thailand and Myanmar DevFeed: [Data Science in Haskell: An example using temperature data from Thailand and Myanmar]() Original publisher: [Read original article]() Author: Dominic Steinitz Published: 2019-04-04T15:52:52Z Content type: article Language: en Sources: [Maths, Stats & Functional Programming]() Topics: [Haskell](), [Data Science](), [data]() Tags: [blog-post](), [data](), [data-science](), [haskell](), [statistics](), [thailand]() ### AI overview This blog post presents a data science example in Haskell using temperature data from Thailand and Myanmar. The supplied text does not provide the methods or findings. ### Source excerpt Blog post on my new site. ## Cartography in Haskell DevFeed: [Cartography in Haskell]() Original publisher: [Read original article]() Author: Dominic Steinitz Published: 2018-05-19T11:18:39Z Content type: article Language: en Sources: [Maths, Stats & Functional Programming]() Topics: [Haskell](), [Nix](), [data](), [CSV](), [Query (disambiguation)](), [parallel]() Tags: [code](), [csv](), [data](), [haskell](), [nix](), [parallel](), [r](), [statistics]() ### AI overview A tutorial-style blog article explains how to analyze local election results and create a choropleth map using Haskell, inline-r, and Nix. It discusses reproducible Haskell and R dependencies, CSV data, parallel filters and queries, and geographical shapefiles. ### Source excerpt Introduction This blog started off life as a blog post on how I use nix but somehow transformed itself into a "how I do data visualisation" blog post. The nix is still here though quietly doing its work in the background. Suppose you want to analyze your local election results and visualize them using a ... Continue reading Cartography in Haskell ## Workshop on Numerical Programming in Functional Languages (NPFL) DevFeed: [Workshop on Numerical Programming in Functional Languages (NPFL)]() Original publisher: [Read original article]() Author: Dominic Steinitz Published: 2018-04-23T15:54:27Z Content type: news Language: en Sources: [Maths, Stats & Functional Programming]() Topics: [Programming](), [Code]() Tags: [demo](), [functional](), [international](), [keynote](), [languages](), [numerical-methods](), [programming](), [submission](), [talk](), [video](), [workshop]() ### AI overview An announcement invites submissions for the first ACM SIGPLAN International Workshop on Numerical Programming in Functional Languages, co-located with ICFP in September in St. Louis. Submissions should describe a talk and may be accompanied by slides or a demo; talks are planned to be recorded. ### Source excerpt I'm the chair this year for the first(!) ACM SIGPLAN International Workshop on Numerical Programming in Functional Languages (NPFL), which will be co-located with ICFP this September in St. Louis, Missouri, USA. Please consider submitting something! All you have to do is submit between half a page and a page describing your talk. There will ... Continue reading Workshop on Numerical Programming in Functional Languages (NPFL) ## Implicit Runge Kutta and GNU Scientific Library DevFeed: [Implicit Runge Kutta and GNU Scientific Library]() Original publisher: [Read original article]() Author: Dominic Steinitz Published: 2018-03-04T13:59:17Z Content type: tutorial Language: en Sources: [Maths, Stats & Functional Programming]() Topics: [Algorithm](), [Haskell](), [Code](), [Library]() Tags: [algorithm](), [c](), [code](), [haskell](), [implementation](), [nix](), [numerical-methods]() ### AI overview Technical notes on implicit Runge-Kutta methods, including IRK2 and IRK4, their Butcher tableaux, and an implementation using the GNU Scientific Library and Haskell. ### Source excerpt Introduction These are some very hasty notes on Runge-Kutta methods and IRK2 in particular. I make no apologies for missing lots of details. I may try and put these in a more digestible form but not today. Some Uncomprehensive Theory In general, an implicit Runge-Kutta method is given by where and Traditionally this is written ... Continue reading Implicit Runge Kutta and GNU Scientific Library ## Reproducibility and Old Faithful DevFeed: [Reproducibility and Old Faithful]() Original publisher: [Read original article]() Author: Dominic Steinitz Published: 2018-02-25T09:49:10Z Content type: article Language: en Sources: [Maths, Stats & Functional Programming]() Topics: [reproducibility](), [data](), [dataset](), [R](), [Haskell](), [Nix]() Tags: [data](), [dataset](), [documentation](), [haskell](), [r](), [reproducibility](), [statistics]() ### AI overview This article investigates the provenance and reproducibility of the Old Faithful geyser datasets available in R. It compares the datasets with cited source tables, notes differing observation counts and apparent differences between versions, and reports that one dataset covers continuous observations collected from August 1 to August 15, 1985. The investigation uses Haskell, embedded R, data frames, and Nix. ### Source excerpt Introduction For the blog post still being written on variatonal methods, I referred to the still excellent Bishop (2006) who uses as his example data, the data available in R for the geyser in Yellowstone National Park called "Old Faithful". While explaining this to another statistician, they started to ask about the dataset. Since I ... Continue reading Reproducibility and Old Faithful ## Comparing Haskell and Julia for High-Performance Numerical Code DevFeed: [Comparing Haskell and Julia for High-Performance Numerical Code]() Original publisher: [Read original article]() Author: Dominic Steinitz Published: 2017-06-02T15:47:12Z Content type: opinion Language: en Sources: [Maths, Stats & Functional Programming]() Topics: [Haskell](), [The Julia Language](), [Programming](), [floating-point]() Tags: [analysis](), [code](), [haskell](), [llvm](), [numerical-methods](), [numerics](), [programming]() ### AI overview The article compares Julia with a Haskell approach using the Accelerate domain-specific embedded language for numerical computing. It discusses the goal of combining type safety with high performance and the motivation of supporting statistical inference methods. ### Source excerpt Introduction Summary Back in January, a colleague pointed out to me that GHC did not produce very efficient code for performing floating point abs. I have yet to produce a write-up of my notes about hacking on GHC: in summary it wasn't as difficult as I had feared and the #ghc folks were extremely helpful. ... Continue reading Haskell for Numerics?