May 6, 2016 — Silvia Hao, Consultant, Technical Communications and Strategy Group

Stippling in art

Stippling is a kind of drawing style using only points to mimic lines, edges, and grayscale. The entire drawing consists only of dots on a white background. The density of the points gives the impression of grayscale shading.

Back in 1510, stippling was first invented as an engraving technique, and then became popular in many fields because it requires just one color of ink.

Here is a photo of a fine example taken from an exhibition of lithography and copperplate art (the Centenary of European Engraving Exhibition held at the Hubei Museum of Art in March 2015; in case you’re curious, here is the museum’s official page in English).

Photo of a piece from lithography and copperplate art exhibit at Hubei Museum of Art

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April 21, 2016 — Jofre Espigule-Pons, Consultant, Technical Communications and Strategy Group

Putting some color in Shakespeare’s tragedies with the Wolfram Language

After four hundred years, Shakespeare’s works are still highly present in our culture. He mastered the English language as never before, and he deeply understood the emotions of the human mind.

Have you ever explored Shakespeare’s texts from the perspective of a data scientist? Wolfram technologies can provide you with new insights into the semantics and statistical analysis of Shakespeare’s plays and the social networks of their characters.

William Shakespeare (April 26, 1564 (baptized)–April 23, 1616) is considered by many to be the greatest writer of the English language. He wrote 154 sonnets, 38 plays (divided into three main groups: comedy, history, and tragedy), and 4 long narrative poems.

Shakespeare's works

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April 15, 2016 — Eila Stiegler, Quality Analysis Manager, Wolfram|Alpha Quality Analysis

It’s four months into the new year. Spring is here. Well, so they say. And if the temperatures do not convince you, the influx of the number of runners on our roads definitely should. I have always loved running. Despite the fact that during each mile I complain about various combinations of the weather, the mileage, and my general state of mind, I met up with 37,000 other runners for the Chicago Marathon on October 11, 2015. As it turns out, this single event makes for a great example to explore what the Wolfram Language can do with larger datasets. The data we are using below is available on the Chicago Marathon results website.

This marathon is one of the six Abbott World Marathon Majors: the Tokyo, Boston, Virgin Money London, BMW Berlin, Bank of America Chicago, and TCS New York City marathons. If you are looking for things to add to your bucket list, I believe these are great candidates. Given the international appeal, let’s have a look at the runners’ nationalities and their travel paths. Our GeoGraphics functionality easily enables us to do so. Clearly many people traveled very far to participate:

GeoGraphics shows where runners have traveled from

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March 2, 2016 — Michael Trott, Chief Scientist

An investigation of the golden ratio’s appearance in the position of human faces in paintings and photographs.

There is a vast amount of literature on the appearance of the golden ratio in nature, in physiology and psychology, and in human artifacts (see this page on the golden ratio; these articles on the golden ratio in art, in nature, and in the human body; and this paper on the structure of the creative process in science and art). In the past thirty years, there has been increasing skepticism about the prevalence of the golden ratio in these domains. Earlier studies have been revisited or redone. See, for example, Foutakis, Markowsky on Greek temples, Foster et al., Holland, Benjafield, and Svobodova et al. for human physiology.

In my last blog, I analyzed the aspect ratios of more than one million old and new paintings. Based on psychological experiments from the second half of the nineteenth century, especially by Fechner in the 1870s, one would expect many paintings to have a height-to-width ratio equal to the golden ratio or its inverse. But the large sets of paintings analyzed did not confirm such a conjecture.

While we did not find the expected prevalence of the golden ratio in external measurements of paintings, maybe looking “inside” will show signs of the golden ratio (or its inverse)?

In today’s blog, we will analyze collections of paintings, photographs, and magazine covers that feature human faces. We will also analyze where human faces appear in a few selected movies.

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February 26, 2016 — Emily Suess, Technical Writer, Technical Communications and Strategy Group

Kip Thorne, physicist, New York Times bestselling author, and professor emeritus at Caltech, ignited fans’ passion for science through his work on the movie Interstellar. The sci-fi adventure won the 2015 Academy Award for Best Visual Effects, and the first cuts of some of those stunning visuals were created with Mathematica and the Wolfram Language.

“Mathematica was my way of testing whether or not I had the equations right,” says Thorne, whose computational approach to producing images led to publication in the American Journal of Physics and Classical and Quantum Gravity.

Gravitational lensing of the Prawn Nebula by a black hole

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February 3, 2016 — Bernat Espigulé-Pons, Consultant, Technical Communications and Strategy Group

When I hear about something like January’s United States blizzard, I remember the day I was hit by the discovery of an infinitely large family of Koch-like snowflakes.

The Koch snowflake (shown below) is a popular mathematical curve and one of the earliest fractal curves to have been described. It’s easy to understand because you can construct it by starting with a regular hexagon, removing the inner third of each side, building an equilateral triangle at the location where the side was removed, and then repeating the process indefinitely:

Koch snowflakes

If you isolate the hexagon’s lower side in the process above you’ll get the Koch curve, described in a 1904 paper by Helge von Koch (1870–1924). It has a long history that goes back way before the age of computer graphics. See, for example, this handmade drawing by the French mathematician Paul Lévy (1886–1971):

Handmade drawing by the French mathematician Paul Lévy

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December 4, 2015 — Bernat Espigulé-Pons, Consultant, Technical Communications and Strategy Group

About a year ago, I decided to record every single move I make using Runkeeper, and now I want to make some visualizations of my activity throughout the whole year. This is a fairly straightforward project where I will download the data from Runkeeper, then use the Wolfram Language to process, analyze, and visualize my activities. I will show how to create animations like this one that superimposes 24 minutes of all my activities recorded in Barcelona:

Runkeeper Barcelona GPS

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October 14, 2015 — Wolfram Blog Team

The first Democratic debate of the 2016 election season has finally come to pass. Although the Democratic party has less than half the number of candidates as the Republican party, this event was just as lively and saw just as much hype. As we did for the two GOP debates, we used last night’s transcripts of everything the candidates said to create linguistic images using the WordCloud function.

In case you missed our previous posts, WordCloud is a Wolfram Language function that allows anyone to visualize words, sized by their frequency in a text. With just one line of code, you can create a word cloud graphic from data, text, or URLs.

Lincoln Chafee Hillary Clinton Martin O'Malley Bernie Sanders Jim Webb

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September 18, 2015 — Jonathan Wallace, Manager, Marketing Communications

After the first Republican presidential debate, we showed you how the WordCloud function in the Wolfram Language can be used to create compelling visualizations of what the candidates said.

This time around, Alan Joyce and Vitaliy Kaurov have done an even cooler analysis over at Wolfram Community, delving further into what words were used most frequently and what subjects the candidates had in common—and how they set themselves apart.

For example, check out the words uniquely used by each candidate in Wednesday’s debate below.

Jeb Bush WordCloud Ben Carson WordCloud Chris Christie WordCloud Ted Cruz WordCloud Carly Fiorina WordCloud Mike Huckabee WordCloud John Kasich WordCloud Rand Paul WordCloud Marco Rubio WordCloud Donald Trump WordCloud Scott Walker WordCloud

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August 13, 2015 — Jonathan Wallace, Manager, Marketing Communications

A few days ago, Fox News hosted the first presidential primary debate of 2016. The candidates met onstage, vying for support from the GOP electorate. Among the cacophony and crafty messaging, a truly artful winner has emerged: word clouds.

The WordCloud function (1 of 5000+ functions) in the Wolfram Language allows anyone to visualize words, sized by their frequency in a text. With a mere line of code, you can create a compelling word cloud graphic from data, text, or URLs.

But don’t take my word for it; let’s make the WordCloud function earn your support.

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