Mad about you, orchestrally.feel the vibe, feel the terror, feel the painmore quotes

circles: fun

Visualizaiton workshop at UBC B.I.G. Research Day. 11 May 2016

visualization + design

Typography geek? If you like the geometry and mathematics of these posters, you may enjoy something more lettered. Visions of type: Type Peep Show: The Private Curves of Letters posters.

$pi$ Approximation Day 2014 Art Posters

Support Ellie Balk's Kickstarter community math mural project in which Brooklyn students learn math and art to visualize $pi$.
2013 $pi$ day
2014 $pi$ day
2015 $pi$ day
2014 $pi$ approx day
Circular $pi$ art

The never-repeating digits of $pi$ can be approximated by $22/7 = 3.142857$ to within 0.04%. These pages artistically and mathematically explore rational approximations to $pi$. This 22/7 ratio is celebrated each year on July 22nd. If you like hand waving or back-of-envelope mathematics, this day is for you: $pi$ approximation day!

Want more math + art? Discover the Accidental Similarity Number. Find humor in my poster of the first 2,000 4s of $pi$.

getting it mostly right

Curiously, the 22/7 rational approximation of $pi$ is more accurate (0.04%) than using the first three digits $3.14$, which are accurate to 0.05%.

It seems that $pi$ Approximation Day is 20% more accurate! And therefore worth celebrating.

art of $pi$ rational approximation

The poster shows the accuracy of 10,000 rational approximations of $pi$ for each $m/n$ and $m=1..10,000$. Read about the details of the method.

Pi Approximation Day Art Poster | July 22nd is Pi Approximation Day. Celebrate with this post-modern poster. (PNG, BUY ARTWORK)
VIEW ALL

Pathways

Mon 04-01-2016

Apply visual grouping principles to add clarity to information flow in pathway diagrams.

We draw on the Gestalt principles of connection, grouping and enclosure to construct practical guidelines for drawing pathways with a clear layout that maintains hierarchy.

Nature Methods Points of View column: Pathways. (read)

We include tips about how to use negative space and align nodes to emphasizxe groups and how to effectively draw curved arrows to clearly show paths.

Hunnicutt, B.J. & Krzywinski, M. (2016) Points of Viev: Pathways. Nature Methods 13:5.

Wong, B. (2010) Points of Viev: Gestalt principles (part 1). Nature Methods 7:863.

Wong, B. (2010) Points of Viev: Gestalt principles (part 2). Nature Methods 7:941.

Multiple Linear Regression

Mon 04-01-2016

When multiple variables are associated with a response, the interpretation of a prediction equation is seldom simple.

This month we continue with the topic of regression and expand the discussion of simple linear regression to include more than one variable. As it turns out, although the analysis and presentation of results builds naturally on the case with a single variable, the interpretation of the results is confounded by the presence of correlation between the variables.

By extending the example of the relationship of weight and height—we now include jump height as a second variable that influences weight—we show that the regression coefficient estimates can be very inaccurate and even have the wrong sign when the predictors are correlated and only one is considered in the model.

Nature Methods Points of Significance column: Multiple Linear Regression. (read)

Care must be taken! Accurate prediction of the response is not an indication that regression slopes reflect the true relationship between the predictors and the response.

Altman, N. & Krzywinski, M. (2015) Points of Significance: Multiple Linear Regression Nature Methods 12:1103-1104.

Altman, N. & Krzywinski, M. (2015) Points of significance: Simple Linear Regression Nature Methods 12:999-1000.

Circos and Hive Workshop Workshop—Poznan, Poland

Sun 13-12-2015

Taught how Circos and hive plots can be used to show sequence relationships at Biotalent Functional Annotation of Genome Sequences Workshop at the Institute for Plant Genetics in Poznan, Poland.

Students generated images published in Fast Diploidization in Close Mesopolyploid Relatives of Arabidopsis.

Workshop materials: slides, handout, Circos and hive plot files.

Drawing synteny between modern and ancient genomes with Circos.

Students also learned how to use hive plots to show synteny.

Hive plots are great at showing 3-way sequence comparisons. Here three modern species of Australian Brassicaceae (S. nutans, S. lineare, B. antipoda) are compared based on their common relationships to the ancestral karotype.

Mandakova, T. et al. Fast Diploidization in Close Mesopolyploid Relatives of Arabidopsis The Plant Cell, Vol. 22: 2277-2290, July 2010

Play the Bacteria Game

Mon 14-12-2015

Nobody likes dusting but everyone should find dust interesting.

Working with Jeannie Hunnicutt and with Jen Christiansen's art direction, I created this month's Scientific American Graphic Science visualization based on a recent paper The Ecology of microscopic life in household dust.

An analysis of dust reveals how the presence of men, women, dogs and cats affects the variety of bacteria in a household. Appears on Graphic Science page in December 2015 issue of Scientific American.

We have also written about the making of the graphic, for those interested in how these things come together.

This was my third information graphic for the Graphic Science page. Unlike the previous ones, it's visually simple and ... interactive. Or, at least, as interactive as a printed page can be.

More of my American Scientific Graphic Science designs

Barberan A et al. (2015) The ecology of microscopic life in household dust. Proc. R. Soc. B 282: 20151139.

Names for 5,092 colors

Tue 03-11-2015

A very large list of named colors generated from combining some of the many lists that already exist (X11, Crayola, Raveling, Resene, wikipedia, xkcd, etc).

Confused? So am I. That's why I made a list.

For each color, coordinates in RGB, HSV, XYZ, Lab and LCH space are given along with the 5 nearest, as measured with ΔE, named neighbours.

I also provide a web service. Simply call this URL with an RGB string.

Simple Linear Regression

Sat 07-11-2015

It is possible to predict the values of unsampled data by using linear regression on correlated sample data.

This month, we begin our column with a quote, shown here in its full context from Box's paper Science and Statistics.

In applying mathematics to subjects such as physics or statistics we make tentative assumptions about the real world which we know are false but which we believe may be useful nonetheless. The physicist knows that particles have mass and yet certain results, approximating what really happens, may be derived from the assumption that they do not. Equally, the statistician knows, for example, that in nature there never was a normal distribution, there never was a straight line, yet with normal and linear assumptions, known to be false, he can often derive results which match, to a useful approximation, those found in the real world.

Nature Methods Points of Significance column: Simple Linear Regression. (read)

This column is our first in the series about regression. We show that regression and correlation are related concepts—they both quantify trends—and that the calculations for simple linear regression are essentially the same as for one-way ANOVA.

While correlation provides a measure of a specific kind of association between variables, regression allows us to fit correlated sample data to a model, which can be used to predict the values of unsampled data.

Altman, N. & Krzywinski, M. (2015) Points of Significance: Simple Linear Regression Nature Methods 12:999-1000.