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# pi day: fun

In Silico Flurries: Computing a world of snow. Scientific American. 23 December 2017

# visualization + design

The 2019 Pi Day art celebrates digits of $\pi$ with hundreds of languages and alphabets. If you're a kid at heart—rejoice—there's a special edition for you!

# $\pi$ Day 2014 Art Posters

2019 $\pi$ has hundreds of digits, hundreds of languages and a special kids' edition.
2018 $\pi$ day
2017 $\pi$ day
2016 $\pi$ approximation day
2016 $\pi$ day
2015 $\pi$ day
2014 $\pi$ approx day
2014 $\pi$ day
2013 $\pi$ day
Circular $\pi$ art

On March 14th celebrate $\pi$ Day. Hug $\pi$—find a way to do it.

For those who favour $\tau=2\pi$ will have to postpone celebrations until July 26th. That's what you get for thinking that $\pi$ is wrong. I sympathize with this position and have $\tau$ day art too!

If you're not into details, you may opt to party on July 22nd, which is $\pi$ approximation day ($\pi$ ≈ 22/7). It's 20% more accurate that the official $\pi$ day!

Finally, if you believe that $\pi = 3$, you should read why $\pi$ is not equal to 3.

All art posters are available for purchase.
I take custom requests.

For the 2014 $\pi$ day, two styles of posters are available: folded paths and frequency circles.

The folded paths show $\pi$ on a path that maximizes adjacent prime digits and were created using a protein-folding algorithm.

The frequency circles colourfully depict the ratio of digits in groupings of 3 or 6. Oh, look, there's the Feynman Point!

## the many paths of $pi$—how to fold numbers

Pi Day art for 2014 is based on the idea of folding the digits of the number into a path. Here one of the most energetically favourable paths is mapped onto a circle — planet π (zoom)

This year's Pi Day art expands on the work from last year, which showed Pi as colored circles on a grid. For those of you who really liked this minimalist depiction of π , I've created something slightly more complicated, but still stylish: Pi digit frequency circles. These are pretty and easy to understand. If you like random distribution of colors (and circles), these are your thing.

But to take drawing Pi a step further, I've experimented with folding its digits into a path. The method used is the same kind used to simulate protein folding. Research into protein folding is very active — the 3-dimensional structure of proteins is necessary for their function. Understanding how structure is affected by changes to underlying sequence is necessary for identifying how things go wrong in a cell.

Folding a protein in 2-dimensions is a difficult challenge. The problem is NP-complete, even when restricted to a lattice. Simulations are used to search for energetically favourable paths. The ultimate goal is to be able to predict the 3-dimensional structure of proteins from its sequence. Images from Wikipedia. (2d folding, 3d shapes)
Enough with proteins, you're here for the art.

## method — folding a number

I will be using the replica exchange Monte Carlo algorithm to create folded paths (download code).

Folding a number | Digits of a number are assigned to a polar (black) or hydrophobic state (red). We search for a path that maximizes the number of neighbours assigned to the hydrophobic (red) state. In this example, the 64 digit number of 7s and 9s has an energy of -42, indicating the path has 42 pairs of neighbouring 7s.

The choice of mapping between digit (0-9) and state (polar, hydrophobic) is arbitrary. I have chosen to assign the prime digits (2, 3, 5, 7) as hydrophobic. Another way can be to use perfect squares (1, 2, 4, 9). I construct the path by assigning each digit to a path node. One can partition π into two (or more) digit groupings (31, 41, 59, 26, ...) as well.

Want more math + art? Look at 2013 Pi Day art, discover the Accidental Similarity Number and other number art. Find humor in my poster of the first 2,000 4s of Pi.

## folding 64 digits of π

Folding Pi | Prime digits in π (2, 3, 5, 7) are assigned a hydrophobic state. The best path is one that maximizes the number of neighbouring prime digits. The path shown here as $E=-23$, indicating 23 neighbouring pairs. A color scheme after the Bauhaus style will be used for the art, with a different scheme for white and black backgrounds.

The quality of the path will depend on how hard you look. Each time the folding simulation is run you run the chance of finding a better solution. For the 64 digits of π shown above, I ran the simulation 500 times and found over 200 paths with the same low energy. It's interesting to note that the path with $E=-22$ was found in <1 second and it took most of the computing time to find the next move.

Below I show 100 paths of 64-digits with $E=-23$, sorted by their aspect ratio.

100 lowest energy paths | These are 100 $E=-23$ 64-digit paths — there are many more paths with this energy. The paths are in increasing order of aspect ratio (width/height). First is 6x14 (0.429) and last is 8x9 (0.889). (zoom)

Running the simulation for 64 digits is very practical — it takes only a few minutes. In a sectino below, I show you how to run your own simulation.

## folding 768 digits of π — the Feynman Point

Let's fold more digits! How about 768 digits — all the way to "...999999". This is the famous The Feynman Point in π where we see the first set of six 9s in row. This happens surprisingly early — at digit 762. In this sequence there are 298 prime digits with the other 470 being composite.

Folding 768 digits of Pi | The best path I could find of the first 768 digits of π with $E=-223$ (width=38, height=52, r=0.73, cm=1, cmabs=13). (zoom)

I have chosen not to emphasize the start and end of the path — finding them is part of the fun (You are haven't fun, aren't you?). The end is easier to spot — the 6 9s stand out. Finding the start, on the other hand, is harder.

## (d,n) points in π — sequences of repeating digits

The Feynman Point is a specific instance of repeating digits, which I call (d,n) points.

You can read more about these locations, where I have enumerated all such locations in the first 268 million digits of π .

## Optimal paths of π up to Feynman Point

Below is a list of the 20 best paths that I've been able to find. They range from $E=-223$ to $E=-219$. I annotate each path with a few geometrical properties, such as width, height, area and so on. In some of the art these properties annotate the path (energy x×y r cm,cmabs).

$# e - energy, as positive number # x,y - path width and height # r - aspect ratio = x/y # area - area (x*y) # cm - center of mass |(sum(x),sum(y))|/n and |(sum(|x|),sum(|y|))|/n # dend - distance between start and end of path 0 e 223 size 37 51 r 0.725 area 1887 cm 1.9 13.4 dend 24.4 1 e 222 size 36 44 r 0.818 area 1584 cm 17.3 18.8 dend 10.4 2 e 221 size 37 50 r 0.740 area 1850 cm 7.6 14.0 dend 16.3 3 e 221 size 70 36 r 1.944 area 2520 cm 1.0 17.3 dend 30.1 4 e 221 size 41 55 r 0.745 area 2255 cm 17.9 20.6 dend 29.5 5 e 221 size 50 49 r 1.020 area 2450 cm 20.8 22.1 dend 34.1 6 e 221 size 61 35 r 1.743 area 2135 cm 11.4 18.2 dend 15.0 7 e 221 size 53 45 r 1.178 area 2385 cm 14.7 18.1 dend 18.8 8 e 221 size 32 52 r 0.615 area 1664 cm 14.0 18.1 dend 33.8 9 e 220 size 46 70 r 0.657 area 3220 cm 26.6 27.8 dend 27.3 10 e 220 size 55 55 r 1.000 area 3025 cm 5.1 16.8 dend 15.0 11 e 220 size 58 34 r 1.706 area 1972 cm 9.3 14.6 dend 43.4 12 e 220 size 62 50 r 1.240 area 3100 cm 30.6 31.4 dend 33.4 13 e 220 size 41 45 r 0.911 area 1845 cm 15.4 17.6 dend 19.2 14 e 220 size 47 51 r 0.922 area 2397 cm 25.6 26.7 dend 16.0 15 e 220 size 38 52 r 0.731 area 1976 cm 13.1 15.9 dend 23.6 16 e 220 size 57 46 r 1.239 area 2622 cm 20.7 22.7 dend 51.7 17 e 220 size 43 57 r 0.754 area 2451 cm 21.3 23.3 dend 29.6 18 e 219 size 45 45 r 1.000 area 2025 cm 16.5 18.2 dend 33.1 19 e 219 size 51 46 r 1.109 area 2346 cm 16.0 19.2 dend 44.4$

As you can see, the dimensions of the paths vary greatly. Low energy paths are not necessarily symmetrical. Paths with a small $cm$ are balanced around their center. Paths with $r$≈1 are confined in a square boundary. Paths with small $dend$ have their start and end points close to one another.

## planet π — path lattice on a circle

The art would not be complete if we didn't somehow try to further force things into a circle! The path lattice is rectangular, but can be deformed into an ellipse or circle using the following transformation

$[(x'),(y')] = [(x sqrt(1-y^2/2)),(y sqrt(1-x^2/2)) ]$

Deforming the path lattice | A path of π on a square lattice is blasphemous! Here the path is transformed to either an ellipse (preserving the path's aspect ratio) or a circle. So much better.
Planet π | Let's go there. The 64-digit path shown here has $E=-219$. (zoom)
VIEW ALL

# Two-level factorial experiments

Fri 22-03-2019
To find which experimental factors have an effect, simultaneously examine the difference between the high and low levels of each.

Two-level factorial experiments, in which all combinations of multiple factor levels are used, efficiently estimate factor effects and detect interactions—desirable statistical qualities that can provide deep insight into a system.

They offer two benefits over the widely used one-factor-at-a-time (OFAT) experiments: efficiency and ability to detect interactions.

Nature Methods Points of Significance column: Two-level factorial experiments. (read)

Since the number of factor combinations can quickly increase, one approach is to model only some of the factorial effects using empirically-validated assumptions of effect sparsity and effect hierarchy. Effect sparsity tells us that in factorial experiments most of the factorial terms are likely to be unimportant. Effect hierarchy tells us that low-order terms (e.g. main effects) tend to be larger than higher-order terms (e.g. two-factor or three-factor interactions).

Smucker, B., Krzywinski, M. & Altman, N. (2019) Points of significance: Two-level factorial experiments Nature Methods 16:211–212.

Krzywinski, M. & Altman, N. (2014) Points of significance: Designing comparative experiments.. Nature Methods 11:597–598.

# Happy 2019 $\pi$ Day—Digits, internationally

Tue 12-03-2019

Celebrate $\pi$ Day (March 14th) and set out on an exploration explore accents unknown (to you)!

This year is purely typographical, with something for everyone. Hundreds of digits and hundreds of languages.

A special kids' edition merges math with color and fat fonts.

116 digits in 64 languages. (details)
223 digits in 102 languages. (details)

Check out art from previous years: 2013 $\pi$ Day and 2014 $\pi$ Day, 2015 $\pi$ Day, 2016 $\pi$ Day, 2017 $\pi$ Day and 2018 $\pi$ Day.

# Tree of Emotional Life

Sun 17-02-2019

One moment you're $:)$ and the next you're $:-.$

Make sense of it all with my Tree of Emotional life—a hierarchical account of how we feel.

A section of the Tree of Emotional Life.

# Find and snap to colors in an image

Sat 29-12-2018

One of my color tools, the $colorsnap$ application snaps colors in an image to a set of reference colors and reports their proportion.

Below is Times Square rendered using the colors of the MTA subway lines.

Colors used by the New York MTA subway lines.

Times Square in New York City.
Times Square in New York City rendered using colors of the MTA subway lines.
Granger rainbow snapped to subway lines colors from four cities. (zoom)

# Take your medicine ... now

Wed 19-12-2018

Drugs could be more effective if taken when the genetic proteins they target are most active.

Design tip: rediscover CMYK primaries.

More of my American Scientific Graphic Science designs

Ruben et al. A database of tissue-specific rhythmically expressed human genes has potential applications in circadian medicine Science Translational Medicine 10 Issue 458, eaat8806.

# Predicting with confidence and tolerance

Wed 07-11-2018
I abhor averages. I like the individual case. —J.D. Brandeis.

We focus on the important distinction between confidence intervals, typically used to express uncertainty of a sampling statistic such as the mean and, prediction and tolerance intervals, used to make statements about the next value to be drawn from the population.

Confidence intervals provide coverage of a single point—the population mean—with the assurance that the probability of non-coverage is some acceptable value (e.g. 0.05). On the other hand, prediction and tolerance intervals both give information about typical values from the population and the percentage of the population expected to be in the interval. For example, a tolerance interval can be configured to tell us what fraction of sampled values (e.g. 95%) will fall into an interval some fraction of the time (e.g. 95%).

Nature Methods Points of Significance column: Predicting with confidence and tolerance. (read)

Altman, N. & Krzywinski, M. (2018) Points of significance: Predicting with confidence and tolerance Nature Methods 15:843–844.