Association has become one of the most commonly used symbols for developers working with any kind of data since it was introduced in Version 10 of the Wolfram Language in 2014. While there are many built-in tools for working with an Association, developers also made many tools themselves as they modernized their code. Now many of those tools have found their way into the Wolfram Function Repository. Here I’ll highlight some of my favorites and show how they compare to built-in Wolfram Language functions.
Earth has experienced five major extinctions since life first appeared almost four billion years ago. The sixth is happening right now; the current extinction rate is between one hundred and one thousand times greater than what it was before 1800.
Despite the alarming extinction rate, it’s easier than ever to document biodiversity with the help of the Wolfram Language. Using the monarch butterfly as an example, I will explore the new biodiversity data access functions in the Wolfram Function Repository and how they can help you join a community of thousands of citizen scientists from iNaturalist in preserving biodiversity.
While programming in the Wolfram Language, I am able to quickly and easily get results—one of the best aspects of writing code in a high-level language. The Wolfram Language is so easy to use that I have the freedom to pursue ideas on a whim, even if I know those ideas may not accomplish anything great or work toward a larger goal. In most cases, within a few minutes I figure out if the idea is a dead end. I also figure out if I am on the path to creating something useful or, better yet, fun.
Playing Cards with Alice and Bob: Using Secure Multi‑Party Computation and the Wolfram Language to Determine a Winner
While catching up with my old friends Alice and Bob on Zoom a few days ago, I became intrigued by their recent card game hobby—and how they used the Wolfram Language to settle an argument. To figure out who gets to go first at the start of the game, they take one suit (spades) from a full deck, and each draws a card. Then, the person with the highest card value wins. Because they are using only one suit, there can be no ties. Simple, right?
When the world is in distress, Wolfram users turn to computation! Even in the midst of this global pandemic, Wolfram staff, friends and colleagues continue to show the power of computational curiosity. We’ve provided a centralized COVID-19 data and resources page, with ways to get free licenses for Wolfram technology through August, livestreamed multiparadigm explorations into the science and data behind the virus, computational explorations from Wolfram users and more. This resource will be continually updated, so make sure to check back often!Our community of staff and users have been incredibly active, creating their own innovative resources and exploring available data from many different angles. Wolfram Community gathers talented and experienced data scientists, biologists, chemists, supply chain experts, epidemiologists, mathematicians, physicists and more. In recent weeks, we’ve seen a flurry of activity and exploration, a willingness to share ideas and information, and mutual encouragement from industry professionals and high-school students alike.
In June 2019, Stephen Wolfram announced the Wolfram Function Repository, a curated repository of functions that can be employed immediately in the Wolfram Language. Since then, the Repository has grown to include more than 1,000 functions in over 20 categories.
Functions included in the Repository range from those that are more general and utilitarian in nature to others with very specific applications. As with all Wolfram Language functions, Repository documentation pages contain examples showing how to use the functions. We’re featuring a few of the functions submitted to the Repository so far that showcase the variety of functions our users have built.
Readers who follow the Mathematica Stack Exchange (which I highly recommend to any Wolfram Language user) may have seen this post recently, in which I showed a function I wrote to make Bayesian linear regression easy to do. After finishing that function, I have been playing around with it to get a better feel of what it can do, and how it compares against regular fitting algorithms such as those used by Fit. In this blog post, I don’t want to focus too much on the underlying technicalities (check out my previous blog post to learn more about Bayesian neural network regression); rather, I will show you some of the practical applications and interpretations of Bayesian regression, and share some of the surprising results you can get from it.
Cerne Abbas Walk is an artwork by Richard Long, in the collection of the Tate Modern in London and on display at the time of this writing. Several of Long’s works involve geographic representations of his walks, some abstract and some concrete. Cerne Abbas Walk is described by the artist as “a six-day walk over all roads, lanes and double tracks inside a six-mile-wide circle centred on the Giant of Cerne Abbas.” The Tate catalog notes that “the map shows his route, retracing and re-crossing many roads to stay within a predetermined circle.”
The Giant in question is a 180-foot-high chalk figure carved into a hill near the village of Cerne Abbas in South West England. Some archaeologists believe it to be of Iron Age pedigree, some think it to date from the Roman or subsequent Saxon periods and yet others find the bulk of evidence to indicate a 17th-century origin as a political satire. (I find the last theory to be both the most amusing and the most convincing.)
I found the geographic premise of Cerne Abbas Walk intriguing, so I decided to replicate it computationally.