Lips that taste of tears, they say, are the best for kissing.get crankymore quotes

# 3.14: beautiful

The Outbreak Poems — artistic emissions in a pandemic

# visualization + design

“Transcendental Tree Map” from Yearning for the Infinite. This video premiered on 2020 Pi Day. Music by Max Cooper. Animation by Nick Cobby and myself.
The 2020 Pi Day art celebrates digits of $\pi$ with piku (パイク) —poetry inspired by haiku.
They serve as the form for The Outbreak Poems.
A $\pi$ day music video!: Transcendental Tree Map premieres on 2020 Pi Day from Max Cooper's Yearning for the Infinite. Animation by Nick Cobby and myself. Watch live from Barbican Centre.

# $\pi$ Day 2018 Art Posters - Stitched city road maps from around the world

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.

And if you've got to sleep a moment on the road
I will steer for you
And if you want to work the street alone
I'll disappear for you

This year's is the 30th anniversary of $\pi$ day. The theme of the art is bridging the world and making friends. So myself I again team up with my long-time friend and collaborator Jake Lever. I worled with Jake on the snowflake catalogue, where we build a world of flakes.

And so, this year we also build a world. We start with all the roads in the world and stitch them together in brand new ways. And if you walk more than 1 km in this world, you'll likely to be transported somewhere completely different.

This year's $\pi$ day song is Trance Groove: Paris. Why? Because it's worth to go to new places—real or imagined.

The input data set to the art are all the roads in the world, as obtained from Open Street Map.

Road segments between intersections are represented by polylines and ends at intersections are snapped together to coincide with a resolution of 5–10 meters.

There are 108,366,429 polylines and together they span about 39,930,000 km.

## extracting cities

We took 44 cities and sampled a square patch of 0.6 × 0.6 degrees of roads from the data set centered on the longitude and latitude coordinates below. This roughly corresponds to a square of 65 km × 65 km.

These center coordinates might be slightly different from the canonical ones associated with a city—I used Google Maps to center the coordinates on what I felt was a useful center for sampling streets. Below are these coordinates along with the number of polylines extracted.

$CITY LATITUDE LONGITUDE POLYLINES --------------- ------------ ------------- --------- amsterdam 52.38179720 4.90840330 98,965 bangkok 13.72635950 100.53609560 154,348 barcelona 41.38759720 2.17333560 86,575 beijing 39.90487690 116.39331750 49,867 berlin 52.51864170 13.40732310 64,336 buenos_aires -34.61566250 -58.50333750 267,432 cairo 30.05371250 31.23528970 108,524 copenhagen 55.67346250 12.58781160 45,025 doha 25.28233490 51.53479620 50,458 dublin 53.34316360 -6.24433520 44,109 edinburgh 55.94884870 -3.18828100 34,211 hong_kong 22.31338230 114.16994610 36,329 istanbul 41.03592820 28.98158110 190,938 jakarta -6.21858830 106.85252890 253,211 johannesburg -26.20653880 28.05113830 128,840 lisbon 38.73064000 -9.13667460 98,118 london 51.50838960 -0.08585320 169,164 los_angeles 34.04362360 -118.24505510 193,899 madrid 40.41671290 -3.70329570 112,495 marrakesh 31.63192610 -7.98895890 17,442 melbourne -37.88286720 145.11800540 140,817 mexico_city 19.39741470 -99.15827060 273,477 moscow 55.75202630 37.61531070 40,043 mumbai 19.18775070 72.97777590 65,316 nairobi -1.28718700 36.83157870 31,317 new_delhi 28.61245350 77.21369970 262,503 new_york 40.72187290 -73.92426750 199,652 nice 43.70006260 7.26974590 25,564 osaka 34.66944300 135.49965600 376,652 paris 48.85837360 2.29229260 175,028 prague 50.08022370 14.43002100 58,659 rome 41.89659480 12.49983650 81,370 san_francisco 37.77526950 -122.40966350 82,462 sao_paulo -23.57343700 -46.63341590 267,742 seoul 37.54869140 126.99479350 169,593 shanghai 31.22590500 121.47386710 50,036 st_petersburg 59.93029690 30.33955910 31,186 stockholm 59.32318770 18.07408060 48,321 sydney -33.86772020 151.20734660 76,820 tokyo 35.69220740 139.75613010 694,893 toronto 43.66328030 -79.38932030 73,173 vancouver 49.25782630 -123.19394300 34,081 vienna 48.20740250 16.37336040 53,669 warsaw 52.23101840 21.01639680 54,870$

Each city's road coordinates were then transformed using the equirectangular projection to make the distance between longitude meridians constant with latitude. This was done by $$\phi' \leftarrow \phi - \text{avg}(\phi)$$ $$\lambda' \leftarrow (\lambda - avg(\lambda)) \text{cos} (avg(\phi))$$

where $\phi$ is the latitude and $\lambda$ is the longitude. The average is taken over the patch of roads extracted for the city. For all steps below these transformed coordinates were used.

## copenhagen

Let's look at one city—Copenhagen—to get a feel for the data set.

The roads in and around Copenhagen. (zoom)

In the zoom crop below, you can see the intersections (dots) and the individual polylines that connect the intersections.

Downtown Copenhagen. (zoom)

Zooming in even more you can see the Christiansborg Slot, one of the Danish Palaces and the seat of the Danish Parliament (corresponding Google Map view).

In and around Christiansborg Slot (red dot) in downtown Copenhagen. (zoom)

## creating city strips

City strips were created by sampling patches of 0.015 × 0.015 degrees (after transformation). This corresponds roughly to 1.7 km.

For each position in the strip, patches were sampled in order of the digits of $\pi$ only if the number of polylines in the was $40d \le N < 40(d+1)-1$ where $d$ is the digit of $\pi$. Patches for $d=9$ only need to have $360 \le N$ polylines.

For example, the first patch is assigned to $d=3$ and it must have $120 \le N < 159$ polylines. The second patch is sampled so that its density is $40 \le N < 79$ because it is associated with the next digit, $d=1$.

Further selection on acceptable patches is performed so that the streets line up with the previous patch. Minor local adjustments and stitching are performed to make the join appear seamless.

Below is an example of a set of city strips for Amsterdam, Bangkok, Beijing, Berlin, Copenhagen, Edinburgh, Hong Kong, Johannesburg, Marrakesh and Melbourne.

On the road with 10 digits of $\pi$. City strips for Moscow, Mumbai, Nairobi, New Delhi, Nice, Prague, Rome, Stockholm, Vancouver and Warsaw. (BUY ARTWORK)

Below I zoom in on a portion of the city strips above to show the result of the stitching—individual street patches are outlined in blue squares.

Close-up of stitched streets in a city strip.

It's interesting to see that some patches (e.g. 4th one on the bottom strip, which is Copenhagen) don't necessarily have roads that across the patch horizontally.

## creating world patches

World patches are a two-dimension version of city strips but they use more than one city.

Patches are sampled from cities based on the order of the digits of $\pi$, as arranged on a 6 × 6 grid. For example, the first row of patches corresponds to 314159 and the second 265358. Each digit is assigned to a city from which the corresponding patch is sampled.

As for city strips, patches are selected only if they align with previous patches. This is now trickier to do in two-dimensions because we must match a selected patch with up to two other patches already placed.

Unlike for city strips, there is no selection made for street density.

Below is a world patch using the following digit-to-city assignment: 0:Amsterdam, 1:Doha, 2:Marrakesh, 3:Mumbai, 4:Nairobi, 5:Rome, 6:San Francisco, 7:Seoul, 8:Shanghai and 9:Vancouver.

On the road with 36 digits of $\pi$. A world patch using Amsterdam, Doha, Marrakesh, Mumbai, Nairobi, Rome, San Francisco, Seoul, Shanghai and Vancouver (BUY ARTWORK)

Below I zoom in on patches in the center of the image and show the cities from which the patches were sampled.

Close-up of stitched streets in a world patch.

# Virus Mutations Reveal How COVID-19 Really Spread

Mon 04-05-2020

Genetic sequences of the coronavirus tell story of when the virus arrived in each country and where it came from.

Our graphic in Scientific American's Graphic Science section in the June 2020 issue shows a phylogenetic tree based on a snapshot of the data model from Nextstrain as of 31 March 2020.

Virus Mutations Reveal How COVID-19 Really Spread. Text by Mark Fischetti (Senior Editor), art direction by Jen Christiansen (Senior Graphics Editor), source: Nextstrain (enabled by data from GISAID).

# Cover of Nature Cancer April 2020

Mon 27-04-2020

Our design on the cover of Nature Cancer's April 2020 issue shows mutation spectra of patients from the POG570 cohort of 570 individuals with advanced metastatic cancer.

Each ellipse system represents the mutation spectrum of an individual patient. Individual ellipses in the system correspond to the number of base changes in a given class and are layered by mutation count. Ellipse angle is controlled by the proportion of mutations in a class within the sample and its size is determined by a sigmoid mapping of mutation count scaled within the layer. The opacity of each system represents the duration since the diagnosis of advanced disease. (read more)

The cover design accompanies our report in the issue Pleasance, E., Titmuss, E., Williamson, L. et al. (2020) Pan-cancer analysis of advanced patient tumors reveals interactions between therapy and genomic landscapes. Nat Cancer 1:452–468.

# Modeling infectious epidemics

Wed 06-05-2020

Every day sadder and sadder news of its increase. In the City died this week 7496; and of them, 6102 of the plague. But it is feared that the true number of the dead this week is near 10,000 ....
—Samuel Pepys, 1665

This month, we begin a series of columns on epidemiological models. We start with the basic SIR model, which models the spread of an infection between three groups in a population: susceptible, infected and recovered.

Nature Methods Points of Significance column: Modeling infectious epidemics. (read)

We discuss conditions under which an outbreak occurs, estimates of spread characteristics and the effects that mitigation can play on disease trajectories. We show the trends that arise when "flattenting the curve" by decreasing $R_0$.

Nature Methods Points of Significance column: Modeling infectious epidemics. (read)

This column has an interactive supplemental component that allows you to explore how the model curves change with parameters such as infectious period, basic reproduction number and vaccination level.

Nature Methods Points of Significance column: Modeling infectious epidemics. (Interactive supplemental materials)

Bjørnstad, O.N., Shea, K., Krzywinski, M. & Altman, N. (2020) Points of significance: Modeling infectious epidemics. Nature Methods 17:455–456.

# The Outbreak Poems

Sat 04-04-2020

I'm writing poetry daily to put my feelings into words more often during the COVID-19 outbreak.

$That moment when you know a moment.$
$Branch to branch, flit, look everywhere, chirp.$
$Memory, scent of thought fleeting.$
$Distant pasts all ways in plural form.$

# Deadly Genomes: Genome Structure and Size of Harmful Bacteria and Viruses

Tue 17-03-2020

A poster full of epidemiological worry and statistics. Now updated with the genome of SARS-CoV-2 and COVID-19 case statistics as of 3 March 2020.

Deadly Genomes: Genome Structure and Size of Harmful Bacteria and Viruses (zoom)

Bacterial and viral genomes of various diseases are drawn as paths with color encoding local GC content and curvature encoding local repeat content. Position of the genome encodes prevalence and mortality rate.

The deadly genomes collection has been updated with a posters of the genomes of SARS-CoV-2, the novel coronavirus that causes COVID-19.

Genomes of 56 SARS-CoV-2 coronaviruses that causes COVID-19.
Ball of 56 SARS-CoV-2 coronaviruses that causes COVID-19.
The first SARS-CoV-2 genome (MT019529) to be sequenced appears first on the poster.

# Using Circos in Galaxy Australia Workshop

Wed 04-03-2020

A workshop in using the Circos Galaxy wrapper by Hiltemann and Rasche. Event organized by Australian Biocommons.

Using Circos in Galaxy Australia workshop. (zoom)

Galaxy wrapper training materials, Saskia Hiltemann, Helena Rasche, 2020 Visualisation with Circos (Galaxy Training Materials).