Posts tagged with visualisation










Three different ways of looking at a 𝔸²→𝔸¹ function:
colour the plane
number the plane
heights in a 3-D view
Is this a simple or complex function? It has lots of discontinuities; it doesn’t correspond in any obvious way to any classical mathematical functions; to program it would surely take a lot of “arbitrary”, non-simple specifications. And yet it’s easily recognisable to any of us.
image by Gonzalez & Woods

Three different ways of looking at a 𝔸²→𝔸¹ function:

  • colour the plane
  • number the plane
  • heights in a 3-D view

Is this a simple or complex function? It has lots of discontinuities; it doesn’t correspond in any obvious way to any classical mathematical functions; to program it would surely take a lot of “arbitrary”, non-simple specifications. And yet it’s easily recognisable to any of us.

image by Gonzalez & Woods

(Source: class.coursera.org)


hi-res




Simulated Annealing




afrographique:

An infographic celebrating African Nobel Prize winners from across the continent.

afrographique:

An infographic celebrating African Nobel Prize winners from across the continent.


hi-res




How much money can you make from advertising online?
Maybe $10 per thousand clicks.
On statistical chart-making: All of the interesting information is contained on the left-hand scale numberings. But that information is de-emphasised in the presentation.

How much money can you make from advertising online?

Maybe $10 per thousand clicks.

On statistical chart-making: All of the interesting information is contained on the left-hand scale numberings. But that information is de-emphasised in the presentation.


hi-res




roads in the USA
by Fathom.info, makers of Processing HT @traviskolton
Compare to those famous light maps of the USA:






Other nice ones on the same topic. You can’t compare visually to the “new view” of the roads vis-à-vis the lights, but who doesn’t love looking at these pics? I don’t want to leave most of the world out just because the US produces the most data.
Don’t have a roads pic of the world but here’s a lights-at-night pic of the world:




Europe:

European Night Lights A recently released satellite picture from NOAA illustrates the changes in nighttime lights in Europe between 1992 and 2009. Yellow regions show where lights have increased, purple places indicate where lights have decreased, and white areas show no change.



Mother India:

And some O(10MB) images of the world at night: http://visibleearth.nasa.gov/view.php?id=55167



Nighttime satellite image of Europe, derived from U.S. Air Force Defense Meteorological Satellite Program (DMSP) Operational Linescan System (OLS).


Dear Heavenly Leader in North Korea keeping the light pollution down:



links may be broken on this one, but promises dark-sky pics of SA, ME, Africa, and some “remote” (primitive living) areas
Back to the USA roadmap by Fathom.info, here’s San Francisco:

Appalachia:

Interesting twitters, if you like this, are @fathominfo and @impure140. (Impure being another visual programming language besides Processing.)

roads in the USA

by Fathom.info, makers of Processing HT @traviskolton

Compare to those famous light maps of the USA:

http://cdn2.sbnation.com/imported_assets/721758/image_thumbnail_aspx.jpg

http://dmsp.ngdc.noaa.gov/pres/low_light_120701/images/USA_29.GIF

usa_small.jpg

http://dmsp.ngdc.noaa.gov/pres/low_light_120701/images/USA_POS.GIF

Thumbnail goes

Other nice ones on the same topic. You can’t compare visually to the “new view” of the roads vis-à-vis the lights, but who doesn’t love looking at these pics? I don’t want to leave most of the world out just because the US produces the most data.

Don’t have a roads pic of the world but here’s a lights-at-night pic of the world:

http://aidwatchers.com/wp/wp-content/uploads/2011/01/Lights-at-night.png

http://www.giss.nasa.gov/research/news/20011105/flat_earth_nightm.jpg

http://www.giss.nasa.gov/research/news/20011105/usa_nightm.jpg

http://www.giss.nasa.gov/research/news/20011105/europe_nightm.jpg

Europe:

Photograph from satellite data showing nighttime lights throughout Europe.



European Night Lights

A recently released satellite picture from NOAA illustrates the changes in nighttime lights in Europe between 1992 and 2009. Yellow regions show where lights have increased, purple places indicate where lights have decreased, and white areas show no change.

http://eol.jsc.nasa.gov/sseop/images/EFS/lowres/ISS023/ISS023-E-29061.JPG

http://1.bp.blogspot.com/_UeuaziTfv8Q/TOhGTAVwtuI/AAAAAAAAAGo/CImF7gX483g/s1600/france+italy+border+small.jpg

Mother India:

http://www.ngdc.noaa.gov/dmsp/image/india_03_98_92_a.jpg

http://eoimages.gsfc.nasa.gov/images/imagerecords/55000/55167/earth_lights.gif

And some O(10MB) images of the world at night: http://visibleearth.nasa.gov/view.php?id=55167

http://img1.jurko.net/wall/paper/earth_at_the_night_1024x768.jpg

Photograph from satellite data showing nighttime lights throughout Europe.

Nighttime satellite image of Europe, derived from U.S. Air Force Defense Meteorological Satellite Program (DMSP) Operational Linescan System (OLS).

http://images.texas.ynn.com/media/weather/onair/0727-london_lights_at_night.jpg

Map of night lights showing the growth of urban lights in Europe between 1992 and 2010.

Dear Heavenly Leader in North Korea keeping the light pollution down:

http://whyfiles.org/wp-content/uploads/2012/01/citylights_china.jpg

links may be broken on this one, but promises dark-sky pics of SA, ME, Africa, and some “remote” (primitive living) areas

Back to the USA roadmap by Fathom.info, here’s San Francisco:

Appalachia:

Interesting twitters, if you like this, are @fathominfo and @impure140. (Impure being another visual programming language besides Processing.)


hi-res







Economic geography of the eastern USA
circa 1999, median incomes by zip code
Code and data source to follow in a longer post.

Economic geography of the eastern USA

circa 1999, median incomes by zip code


Code and data source to follow in a longer post.


hi-res




These charts are undeniably beautiful, but they violate Tufte principles 1, 4, 7, 10, 11, 12.

Charts can look great but E Tufte says we should let the data do the talking, rather than the design. Adding some sparkle to the data is “wrong” or at least, Tufte-wrong, for data-graphics.

Here it seems like the talented artist has tried to “add some sparkle and theme” to “boring numbers” — rather than accentuating what’s exciting about the numbers themselves. To my way of thinking, if the message the numbers are telling you is interesting, then that makes the numbers worth looking at.

  • Did you say I could get a 25% raise?!
  • Did you say people are 30% taller than they were 250 years ago?
  • Did you say a 19% chance of rain on our wedding today? Or 90%?
  • Did you say the cost of electricity is one-one-hundredth of what it was 90 years ago?
  • Did you say my heating bill is double what it needs to be if I insulated better?
  • A man and a mouse are only one order of magnitude apart?
  • I could commute across America on a bike if I were two orders of magnitude faster?
  • Did you say that 99% of the people own 1% of the wealth? Or was it 99.999% of the people owning .000001% of the wealth? Or both? Wait, these numbers are actually crucial to the story!

Of course it’s no surprise that most people think cifras son aburridas — since their main memory of figures is through boring maths class, rather than as integral elements of a story.

What it’s talking about:

As in the wieners I drew, it’s not easy to make the logically beautiful look visually beautiful.

(Source: softwareadvice.com)










Mapping from
discrete domain: length × width →
discrete codomain: {A,B,Q,Q+} = stocking size.
Two things.
First, it’s a scale in the sense of Hadley Wickham’s ggplot: an association between logic and graphics.
Second, it depicts a well-known phase space.Just like certain pressure & temperature combinations make plumbumappear as a solid, liquid, or gas [for instance the point (3180℉, 1 atmosphere)] — so do certain height & weight combinations recommend a stocking of A, B, or Q.

Mapping from

  • discrete domain: length × width →
  • discrete codomain: {A,B,Q,Q+} = stocking size.

Two things.

  1. First, it’s a scale in the sense of Hadley Wickham’s ggplot: an association between logic and graphics.
  2. Second, it depicts a well-known phase space.

    Just like certain pressure & temperature combinations make plumbum

    appear as a solid, liquid, or gas [for instance the point (3180, 1 atmosphere)] — so do certain height & weight combinations recommend a stocking of A, B, or Q.