Swede White

Citizen Data Science with Civic Hacking: The Safe Drinking Water Data Challenge

August 9, 2018 — Swede White, Lead Communications Strategist, Public Relations

Code for America’s National Day of Civic Hacking is coming up on August 11, 2018, which presents a nice opportunity for individuals and teams of all skill levels to participate in the Safe Drinking Water Data Challenge—a program Wolfram is supporting through free access to Wolfram|One and by hosting relevant structured datasets in the Wolfram Data Repository.

According to the state of California, some 200,000 residents of the state have unsafe drinking water coming out of their taps. While the Safe Drinking Water Data Challenge focuses on California, data science solutions could have impacts and applications for providing greater access to potable water in other areas with similar problems.

The goal of this post is to show how Wolfram technologies make it easy to grab data and ask questions of it, so we’ll be taking a multiparadigm approach and allowing our analysis to be driven by those questions in an exploratory analysis, a way to quickly get familiar with the data.

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Aaron Enright
Eric Weisstein

Computational Exploration of the Mathematics Genealogy Project in the Wolfram Language

August 2, 2018
Aaron Enright, Data Scientist, Wolfram|Alpha Socioeconomic Content
Eric Weisstein, Senior Researcher, Wolfram|Alpha Scientific Content

The Mathematics Genealogy Project (MGP) is a project dedicated to the compilation of information about all mathematicians of the world, storing this information in a database and exposing it via a web-based search interface. The MGP database contains more than 230,000 mathematicians as of July 2018, and has continued to grow roughly linearly in size since its inception in 1997.

In order to make this data more accessible and easily computable, we created an internal version of the MGP data using the Wolfram Language’s entity framework. Using this dataset within the Wolfram Language allows one to easily make computations and visualizations that provide interesting and sometimes unexpected insights into mathematicians and their works. Note that for the time being, these entities are defined only in our private dataset and so are not (yet) available for general use.

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Chapin Langenheim

New Wolfram Language Books: Don’t Stop Learning Just Because It’s Summer

July 31, 2018 — Chapin Langenheim, Coordinating Editor, Document and Media Systems

It’s not really late summer unless you’re armed with an apple and a good book. There’s been a recent slew of incredible books utilizing the capabilities of the Wolfram Language that make sure your coding knowledge never stops growing and your reading list stays stocked. (And be sure to check the farmers’ market for those apples.)

Book1

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Posted in: Books

Itai Seggev

Big O and Friends: Tales of the Big, the Small and Every Scale in Between

July 26, 2018 — Itai Seggev, Senior Kernel Developer, Algorithms R&D

One of the many beautiful aspects of mathematics is that often, things that look radically different are in fact the same—or at least share a common core. On their faces, algorithm analysis, function approximation and number theory seem radically different. After all, the first is about computer programs, the second is about smooth functions and the third is about whole numbers. However, they share a common toolset: asymptotic relations and the important concept of asymptotic scale.

By comparing the “important parts” of two functions—a common trick in mathematics—asymptotic analysis classifies functions based on the relative size of their absolute values near a particular point. Depending on the application, this comparison provides quantitative answers to questions such as “Which of these algorithms is fastest?” or “Is function a good approximation to function g?”. Version 11.3 of the Wolfram Language introduces six of these relations, summarized in the following table.

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Jon McLoone

Four Minecraft Projects with the Wolfram Language

July 24, 2018 — Jon McLoone, Director, Technical Communication & Strategy

Hero

A couple of weeks ago I shared a package for controlling the Raspberry Pi version of Minecraft from Mathematica (either on the Pi or from another computer). You can control the Minecraft API from lots of languages, but the Wolfram Language is very well aligned to this task—both because the rich, literate, multiparadigm style of the language makes it great for learning coding, and because its high-level data and computation features let you get exciting results very quickly.

Today, I wanted to share four fun Minecraft project ideas that I had, together with simple code for achieving them. There are also some ideas for taking the projects further.

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Devendra Kapadia

Getting to the Point: Asymptotic Expansions in the Wolfram Language

July 19, 2018 — Devendra Kapadia, Kernel Developer, Algorithms R&D

Asymptotic expansions have played a key role in the development of fields such as aerodynamics, quantum physics and mathematical analysis, as they allow us to bridge the gap between intricate theories and practical calculations. Indeed, the leading term in such an expansion often gives more insight into the solution of a problem than a long and complicated exact solution. Version 11.3 of the Wolfram Language introduces two new functions, AsymptoticDSolveValue and AsymptoticIntegrate, which compute asymptotic expansions for differential equations and integrals, respectively. Here, I would like to give you an introduction to asymptotic expansions using these new functions.

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Patrik Ekenberg
Anna Palmer

Why Is Sickle Cell Anemia Common in Areas with Malaria? Teaching Life Science with Modeling

July 12, 2018
Patrik Ekenberg, Applications Engineer, Wolfram MathCore
Anna Palmer, Intern, Wolfram MathCore

Life science teaches us to answer everything from “How can vaccines be used to indirectly protect people who haven’t been immunized?” to “Why are variations in eye color almost exclusively present among humans and domesticated animals?” You can now learn to answer these questions by using modeling with Wolfram’s virtual labs. Virtual labs are interactive course materials that are used to make teaching come alive, provide an easy way to study different concepts and promote student curiosity.

Cat with different eye colors

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Jon McLoone

Programming Minecraft on the Raspberry Pi

July 5, 2018 — Jon McLoone, Director, Technical Communication & Strategy

The standard Raspbian software on the Raspberry Pi comes with a basic implementation of Minecraft and a full implementation of the Wolfram Language. Combining the two provides a fun playground for learning coding. If you are a gamer, you can use the richness of the Wolfram Language to programmatically generate all kinds of interesting structures in the game world, or to add new capabilities to the game. If you are a coder, then you can consider Minecraft just as a fun 3D rendering engine for the output of your code.

Minecraft

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Brian Wood

The Shape of the Vote: Exploring Congressional Districts with Computation

June 26, 2018 — Brian Wood, Lead Technical Marketing Writer, Technical Communications and Strategy Group

In the past few decades, the process of redistricting has moved squarely into the computational realm, and with it the political practice of gerrymandering. But how can one solve the problem of equal representation mathematically? And what can be done to test the fairness of districts? In this post I’ll take a deeper dive with the Wolfram Language—using data exploration with Import and Association, built-in knowledge through the Entity framework and various GeoGraphics visualizations to better understand how redistricting works, where issues can arise and how to identify the effects of gerrymandering.

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Stephen Wolfram

We’ve Come a Long Way in 30 Years (But You Haven’t Seen Anything Yet!)

June 21, 2018 — Stephen Wolfram

30 years of Mathematica

Technology for the Long Term

On June 23 we celebrate the 30th anniversary of the launch of Mathematica. Most software from 30 years ago is now long gone. But not Mathematica. In fact, it feels in many ways like even after 30 years, we’re really just getting started. Our mission has always been a big one: to make the world as computable as possible, and to add a layer of computational intelligence to everything.

Our first big application area was math (hence the name “Mathematica”). And we’ve kept pushing the frontiers of what’s possible with math. But over the past 30 years, we’ve been able to build on the framework that we defined in Mathematica 1.0 to create the whole edifice of computational capabilities that we now call the Wolfram Language—and that corresponds to Mathematica as it is today.

From when I first began to design Mathematica, my goal was to create a system that would stand the test of time, and would provide the foundation to fill out my vision for the future of computation. It’s exciting to see how well it’s all worked out. My original core concepts of language design continue to infuse everything we do. And over the years we’ve been able to just keep building and building on what’s already there, to create a taller and taller tower of carefully integrated capabilities.

It’s fun today to launch Mathematica 1.0 on an old computer, and compare it with today:

Older Mac versus iPhone

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