Martin Krzywinski / Genome Sciences Center / mkweb.bcgsc.ca Martin Krzywinski / Genome Sciences Center / mkweb.bcgsc.ca - contact me Martin Krzywinski / Genome Sciences Center / mkweb.bcgsc.ca on Twitter Martin Krzywinski / Genome Sciences Center / mkweb.bcgsc.ca - Lumondo Photography Martin Krzywinski / Genome Sciences Center / mkweb.bcgsc.ca - Pi Art Martin Krzywinski / Genome Sciences Center / mkweb.bcgsc.ca - Hilbertonians - Creatures on the Hilbert Curve
Twenty — minutes — maybe — more.Naomichoose four wordsmore quotes

orbits: exciting


EMBO Practical Course: Bioinformatics and Genome Analysis, 5–17 June 2017.


visualization + design

Martin Krzywinski @MKrzywinski mkweb.bcgsc.ca
The 2017 Pi Day art imagines the digits of Pi as a star catalogue with constellations of extinct animals and plants. The work is featured in the article Pi in the Sky at the Scientific American SA Visual blog.

`\pi` Day 2016 Art Posters


Pi Day 2016 Art Posters
 / Martin Krzywinski @MKrzywinski mkweb.bcgsc.ca
2017 `\pi` day

Pi Day 2016 Art Posters
 / Martin Krzywinski @MKrzywinski mkweb.bcgsc.ca
2016 `\pi` approximation day

Pi Day 2016 Art Posters
 / Martin Krzywinski @MKrzywinski mkweb.bcgsc.ca
2016 `\pi` day

Pi Day 2016 Art Posters
 / Martin Krzywinski @MKrzywinski mkweb.bcgsc.ca
2015 `\pi` day

Pi Day 2016 Art Posters
 / Martin Krzywinski @MKrzywinski mkweb.bcgsc.ca
2014 `\pi` approx day

Pi Day 2016 Art Posters
 / Martin Krzywinski @MKrzywinski mkweb.bcgsc.ca
2014 `\pi` day

Pi Day 2016 Art Posters
 / Martin Krzywinski @MKrzywinski mkweb.bcgsc.ca
2013 `\pi` day

Pi Day 2016 Art Posters
 / Martin Krzywinski @MKrzywinski mkweb.bcgsc.ca
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.

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.

Martin Krzywinski @MKrzywinski mkweb.bcgsc.ca
All art posters are available for purchase.
I take custom requests.

This year's `\pi` day art collection celebrates not only the digit but also one of the fundamental forces in nature: gravity.

In February of 2016, for the first time, gravitational waves were detected at the Laser Interferometer Gravitational-Wave Observatory (LIGO).

The signal in the detector was sonified—a process by which any data can be encoded into sound to provide hints at patterns and structure that we might otherwise miss—and we finally heard what two black holes sound like. A buzz and chirp.

The art is featured in the Gravity of Pi article on the Scientific American SA Visual blog.

this year's theme music

All the art was processed while listening to Roses by Coeur de Pirate, a brilliant female French-Canadian songwriter, who sounds like a mix of Patricia Kaas and Lhasa. The lyrics Oublie-moi (Forget me) are fitting with this year's theme of gravity.

Mais laisse-moi tomber, laisse-nous tomber
Laisse la nuit trembler en moi
Laisse-moi tomber, laisse nous tomber
Cette fois

But let me fall, let us fall
Let the night tremble in me
Let me fall, let us fall
This time

The art is generated by running a simulation of gravity in which digits of `\pi` are each assigned a mass and allowed to collide eand orbit each other.

The mathematical details of the simulation can be found in the code section.

exploring force of gravity in `\pi`

A simulation starts with taking `n` digits of `\pi` and arranging them uniformly around a circle. The mass of each digit, `d_i` (e.g. 3), is given by `(1+d)^k` where `k` is a mass power parameter between 0.01 and 1. For example, if `k=0.42` then the mass of 3 is `(1+3)^{0.42} = 1.79`.

collapsing three digits—3.14 collide

The figure below shows the evolution of a simulation with `n=3` digits and `k=1`. The digits 3 and 4 collide to form the digit `3+4 = 7` and immediately collides with 1 to form `7+1=8`. With only one mass left in the system, the simulation stops.


Pi Day 2016 Art Posters
 / Martin Krzywinski @MKrzywinski mkweb.bcgsc.ca
The evolution of a simulation of gravity using `n=3` digits of `\pi` and the mass power `k=1`. The masses are initialized with zero velocity. (zoom)

adding initial velocity to each mass

When masses have initial velocities, the patterns quickly start to get interesting. In the figure above, the masses are initalized with zero velocity. As soon as the simulation, each mass immediately starts to move directly towards the center of mass of the other two masses.

When the initial velocity is non-zero, such as in the figure below, the masses don't immediately collapse towards one another. The masses first travel with their initial velocity but immediately the gravitational force imparts acceleration that alters this velocity. In the examples below, only those simulations in which the masses collapsed within a time cutoff are shown.


Pi Day 2016 Art Posters
 / Martin Krzywinski @MKrzywinski mkweb.bcgsc.ca
The evolution of a simulation of gravity using `n=3` digits of `\pi` and the mass power `k=1` in which all masses collapsed. The masses are initialized with a random velocity. (zoom)

Pi Day 2016 Art Posters
 / Martin Krzywinski @MKrzywinski mkweb.bcgsc.ca
The evolution of 16 simulations of gravity using `n=3` digits of `\pi` and the mass power `k=1` in which all masses collapsed. The masses are initialized with a random velocity. (zoom)

Pi Day 2016 Art Posters
 / Martin Krzywinski @MKrzywinski mkweb.bcgsc.ca
The evolution of 49 simulations of gravity using `n=3` digits of `\pi` and the mass power `k=1` in which all masses collapsed. The masses are initialized with a random velocity. (zoom)

allowing the simulation to evolve

Depending on the initial velocities, some systems collapse very quickly, which doesn't make for interesting patterns.

For example, the simulations above evolved over 100,000 steps and in some cases the masses collapsed within 10,000 steps. In the figure below, I require that the system evolves for at least 15,000 steps before collapsing. Lovely doddles, don't you think?


Pi Day 2016 Art Posters
 / Martin Krzywinski @MKrzywinski mkweb.bcgsc.ca
The evolution of 36 simulations of gravity using `n=3` digits of `\pi` and the mass power `k=1` in which all masses collapsed after a minimum amount of time. The masses are initialized with a random velocity. (zoom)

exploring ensembles

When a simulation is repeated with different initial conditions, the set of outcomes is called an ensemble.

Below, I repeat the simulation 100 times with `n=3` and `k=0.2`, each time with slightly different initial velocity. The velocities have their `x`- and `y`-components normally distributed with zero mean and a fixed variance. Each of the four ensembles has its simulations evolve over progressively more time steps: 5,000, 7,500, 10,000, and 20,000.

You can see that with 5,000 steps the masses don't yet have a chance to collide. After 7,500, there have been collisions in a small number of systems. The blue mass corresponds to the 3 colliding with 4 and the green mass to 1 colliding with 4. After 10,000, even more collisions are seen and in 3 cases we see total collapse (all three digits collided). After 20,000,


Pi Day 2016 Art Posters
 / Martin Krzywinski @MKrzywinski mkweb.bcgsc.ca
The evolution of 100 simulations of gravity over total time `t` using `n=3` digits of `\pi` and the mass power `k=0.2`. Within each ensemble, the masses are initialized with a different random velocity in each instance. (zoom)

varying masses

The value of `k` greatly impacts the outcome of the simulation. When `k` is very small, all the digits have essentially the same mass. For example, when `k=0.01` the 0 has a mass of 1 and 9 has a mass of 1.02.

When `k` is large, the difference in masses is much greater. For example, for `k=2` the lightest mass is `(1+0)^2=1` and the heaviest `(1+9)^2=10`. Because the acceleration of a mass is proportional to the mass that is attracting it, in a pair of masses the light mass will accelerate faster.


Pi Day 2016 Art Posters
 / Martin Krzywinski @MKrzywinski mkweb.bcgsc.ca
Larger values of `k` create greater diversity among the masses. Shown are simulations of 36 digits with `k` values varying from 0.1 to 3. The total mass of the system, `\Sigma m`, is also shown.`. (zoom)

increasing number of masses

As the number of digits is increased, the pattern of collapse doesn't qualitatively change.


Pi Day 2016 Art Posters
 / Martin Krzywinski @MKrzywinski mkweb.bcgsc.ca
Simulations for `n = 50, 100, 250` and `500` masses with `k = 0.5`. (zoom)

gravity makes beautiful doodles

I ran a large number of simulations. For various values of `n` and `k`, I repeated the simulation several times to sample different intial velocities.


Pi Day 2016 Art Posters
 / Martin Krzywinski @MKrzywinski mkweb.bcgsc.ca
Thumbnails of `\pi` digit orbital simulations for various values of `n` and `k`. (zoom)

Pi Day 2016 Art Posters
 / Martin Krzywinski @MKrzywinski mkweb.bcgsc.ca
Gravitational attraction paths of the first 100 digits of `\pi` for `k = 0.3`, `0.6` and `0.8` with initial velocities randomly set. Three instances of the simulation are shown, each with different intital velocities. (zoom)

Pi Day 2016 Art Posters
 / Martin Krzywinski @MKrzywinski mkweb.bcgsc.ca
Gravitational attraction paths of the first 60 digits of `\pi` for `k = 1`. After 100,000 time steps, some masses are still orbiting within the canvas (e.g. green mass at bottom right). The numbers next to the masses correspond to the digits (those around the circle are the first 50 digits of `\pi` and others are the sum (mod 10) of digits that collided). Also shown next to the numbers is their mass, index and indices of masses that formed them. (zoom)

Pi Day 2016 Art Posters
 / Martin Krzywinski @MKrzywinski mkweb.bcgsc.ca
Gravitational attraction paths of the first 50 digits of `\pi` for `k = 0.4`. The numbers next to the masses correspond to the digits (those around the circle are the first 50 digits of `\pi` and others are the sum (mod 10) of digits that collided). (zoom)

Below is a great example of how a stable orbital pattern of a pair of masses can be disrupted by the presence of another mass. You can see on the left that once the light red mass moves away from the orange/green pair, they settle into a stable pattern.


Pi Day 2016 Art Posters
 / Martin Krzywinski @MKrzywinski mkweb.bcgsc.ca
Gravitational attraction paths of the first 50 digits of `\pi` for `k = 0.9`. The numbers next to the masses correspond to the digits (those around the circle are the first 50 digits of `\pi` and others are the sum (mod 10) of digits that collided). (zoom)

The figure below shows one of my favourite patterns. As the digits collide, three masses remain, which leave the system. They remain under each other's gravitational influence, but are moving too quickly to return to the canvas within the time of the simulation.


Pi Day 2016 Art Posters
 / Martin Krzywinski @MKrzywinski mkweb.bcgsc.ca
Gravitational attraction paths of the first 90 digits of `\pi` for `k = 0.8`. The digits collide, leaving three rapidly-moving masses, which leave the canvas. (zoom)

how the idea developed

interactive gravity simulator

Use this fun inteactive gravity simulator if you want to drop your own masses and watch them orbit.

VIEW ALL

news + thoughts

Personal Oncogenomics Program 5 Year Anniversary Art

Wed 26-07-2017

The artwork was created in collaboration with my colleagues at the Genome Sciences Center to celebrate the 5 year anniversary of the Personalized Oncogenomics Program (POG).

Martin Krzywinski @MKrzywinski mkweb.bcgsc.ca
5 Years of Personalized Oncogenomics Program at Canada's Michael Smith Genome Sciences Centre. The poster shows 545 cancer cases. (left) Cases ordered chronologically by case number. (right) Cases grouped by diagnosis (tissue type) and then by similarity within group.

The Personal Oncogenomics Program (POG) is a collaborative research study including many BC Cancer Agency oncologists, pathologists and other clinicians along with Canada's Michael Smith Genome Sciences Centre with support from BC Cancer Foundation.

The aim of the program is to sequence, analyze and compare the genome of each patient's cancer—the entire DNA and RNA inside tumor cells— in order to understand what is enabling it to identify less toxic and more effective treatment options.

Principal component analysis

Thu 06-07-2017
PCA helps you interpret your data, but it will not always find the important patterns.

Principal component analysis (PCA) simplifies the complexity in high-dimensional data by reducing its number of dimensions.

Martin Krzywinski @MKrzywinski mkweb.bcgsc.ca
Nature Methods Points of Significance column: Principal component analysis. (read)

To retain trend and patterns in the reduced representation, PCA finds linear combinations of canonical dimensions that maximize the variance of the projection of the data.

PCA is helpful in visualizing high-dimensional data and scatter plots based on 2-dimensional PCA can reveal clusters.

Altman, N. & Krzywinski, M. (2017) Points of Significance: Principal component analysis. Nature Methods 14:641–642.

Background reading

Altman, N. & Krzywinski, M. (2017) Points of Significance: Clustering. Nature Methods 14:545–546.

...more about the Points of Significance column

`k` index: a weightlighting and Crossfit performance measure

Wed 07-06-2017

Similar to the `h` index in publishing, the `k` index is a measure of fitness performance.

To achieve a `k` index for a movement you must perform `k` unbroken reps at `k`% 1RM.

The expected value for the `k` index is probably somewhere in the range of `k = 26` to `k=35`, with higher values progressively more difficult to achieve.

In my `k` index introduction article I provide detailed explanation, rep scheme table and WOD example.

Dark Matter of the English Language—the unwords

Wed 07-06-2017

I've applied the char-rnn recurrent neural network to generate new words, names of drugs and countries.

The effect is intriguing and facetious—yes, those are real words.

But these are not: necronology, abobionalism, gabdologist, and nonerify.

These places only exist in the mind: Conchar and Pobacia, Hzuuland, New Kain, Rabibus and Megee Islands, Sentip and Sitina, Sinistan and Urzenia.

And these are the imaginary afflictions of the imagination: ictophobia, myconomascophobia, and talmatomania.

And these, of the body: ophalosis, icabulosis, mediatopathy and bellotalgia.

Want to name your baby? Or someone else's baby? Try Ginavietta Xilly Anganelel or Ferandulde Hommanloco Kictortick.

When taking new therapeutics, never mix salivac and labromine. And don't forget that abadarone is best taken on an empty stomach.

And nothing increases the chance of getting that grant funded than proposing the study of a new –ome! We really need someone to looking into the femome and manome.

Dark Matter of the Genome—the nullomers

Wed 31-05-2017

An exploration of things that are missing in the human genome. The nullomers.

Julia Herold, Stefan Kurtz and Robert Giegerich. Efficient computation of absent words in genomic sequences. BMC Bioinformatics (2008) 9:167

Clustering

Sat 01-07-2017
Clustering finds patterns in data—whether they are there or not.

We've already seen how data can be grouped into classes in our series on classifiers. In this column, we look at how data can be grouped by similarity in an unsupervised way.

Martin Krzywinski @MKrzywinski mkweb.bcgsc.ca
Nature Methods Points of Significance column: Clustering. (read)

We look at two common clustering approaches: `k`-means and hierarchical clustering. All clustering methods share the same approach: they first calculate similarity and then use it to group objects into clusters. The details of the methods, and outputs, vary widely.

Altman, N. & Krzywinski, M. (2017) Points of Significance: Clustering. Nature Methods 14:545–546.

Background reading

Lever, J., Krzywinski, M. & Altman, N. (2016) Points of Significance: Logistic regression. Nature Methods 13:541-542.

Lever, J., Krzywinski, M. & Altman, N. (2016) Points of Significance: Classifier evaluation. Nature Methods 13:603-604.

...more about the Points of Significance column