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This is the call stack from top to bottom when an individual Drupal node is loaded -- focuses only on the views_playlist.module functions that are called. The debug_print_backtrace(); php command was placed at the beginning of each function, and then a node was loaded.

 

I then did a view source, and then did some text replacements to get rid of extra line breaks, and place two line breaks at the beginning on a new stack trace (i.e. with each instance of #0).

 

These are the text replacements I did in Microsoft Word

REPLACE ^p# WITH TEMPTEXTFLAG#

REPLACE ^p WITH ""

REPLACE TEMPTEXTFLAG# WITH ^p#

REPLACE ^p#0 WITH ^p^p#0

REPLACE "called at " with ^t

 

I could then import the data into MicroSoft Excel.

I then

 

A1 = 1 and in A2 =

=IF(E2="",A1+1,A1)

 

B1 = 0 and B2 =

=IF(E2="",-1,B1+1)

 

That gave columns that looked like

1 0

1 1

1 2

1 3

1 3

 

I copied column A & B and then did a paste by value via "Paste Special..." I selected columns A through D, and sorted first by Column A (ascending), and then Column B (descending) This showed the chronological order in which the functions were called.

 

I then copied the cell values from the excel spread sheet into omnigraffle pro where the were treated as a single object. I had to paste multiple sections and group them together so that I could copy it, and then paste it into Preview. Once it was in preview, then I could export it as a PNG and then upload it here.

 

I'm a geek.

screenshot of the iTunes visualizer

Visualization of Flickr geotagged photos, uploaded between 2007 to 2015 and geotagged with the highest accuracy (street-level). I generated a number of different visualizations. Some are more artistic in style while others are designed more informative.

 

This type of visualization has been done years before (check out Eric Fischer's maps). Maybe the statistics going on on the lower-right corner provide some additional information not available so far.

 

Here is an animated version of this map

 

Created as part of my research project (maps.alexanderdunkel.com).

 

Here's a blog entry with more info.

Visualization of Flickr geotagged photos, uploaded between 2007 to 2015 and geotagged with the highest accuracy (street-level). I generated a number of different visualizations. Some are more artistic in style while others are designed more informative.

 

This type of visualization has been done years before (check out Eric Fischer's maps). Maybe the statistics going on on the lower-right corner provide some additional information not available so far.

 

Created as part of my research project (maps.alexanderdunkel.com).

 

Here's a blog entry with more info.

visualizing online social networks

jheer.org/vizster/

Kiva has quite a few API and SQL interfaces for grabbing data and visualizing it. Actually makes the whole process all the more interactive.

Frontop serves 3d architectural renderings, 3d architectural animations, architectural visualization, 3D floor plan, etc. Our 3d renderings have gained wide recognition. We are also the partner of Zaha Hadid Architect.

Kinetic race at Da Vinci Days 2011 in Corvallis, Oregon.

Everybody got the demon in here, okay? The demon lives in here. It feeds on your hate -- it cuts, kills, rapes -- it uses your weak- ness, your fear... A little, uh, madness goin' on. I don't know. Death just -- death kinda becomes what you are. After a while, you begin to like it...

("Natural born killers" - Mickey Knox)

Some shots from my Mac visualizer.

Some shots from my Mac visualizer.

Geocoding and visualizing dad's flight log data. GeoTIff and kml reprojection done with TileMill. More info and how-to here: raph.ae/2014/04/how-to-geocode-and-visualize-flight-paths...

 

Original image by Marc Imhoff of NASA GSFC and Christopher Elvidge of NOAA NGDC, Craig Mayhew and Robert Simmon, NASA GSFC. visibleearth.nasa.gov/view.php?id=55167

Photo of a Man on Sunset Drive: 1914, 2008

by: Richard Blanco

 

And so it began: the earth torn, split open

by a dirt road cutting through palmettos

and wild tamarind trees defending the land

against the sun. Beside the road, a shack

leaning into the wind, on the wooden porch,

crates of avocados and limes, white chickens

pecking at the floor boards, and a man

under the shadow of his straw hat, staring

into the camera in 1914. He doesn't know

within a lifetime the unclaimed land behind

him will be cleared of scrub and sawgrass,

the soil will be turned, made to give back

what the farmers wish, their lonely houses

will stand acres apart from one another,

jailed behind the boughs of their orchards.

He'll never buy sugar at the general store,

mail love letters at the post office, or take

a train at the depot of the town that will rise

out of hundred-million years of coral rock

on promises of paradise. He'll never ride

a Model-T puttering down the dirt road

that will be paved over, stretch farther and

farther west into the horizon, reaching for

the setting sun after which it will be named.

He can't even begin to imagine the shadows

of buildings rising taller than the palm trees,

the street lights glowing like counterfeit stars

dotting the sky above the road, the thousands

who will take the road everyday, who'll also

call this place home less than a hundred years

after the photograph of him hanging today

in City Hall as testament. He'll never meet

me, the engineer hired to transform the road

again, bring back tree shadows and birdsongs,

build another promise of another paradise

meant to last another forever. He'll never see

me, the poet standing before him, trying

to read his mind across time, wondering if

he was thinking what I'm today, both of us

looking down the road that will stretch on

for years after I too disappear into a photo.

 

Some shots from my Mac visualizer.

DNA sequence alignment data shown on the TACC Visualization Wall.

Another way to discover interesting people is to look at your friend's friend list: www.neuroproductions.be/twitter_friends_network_browser/

Loving couple in beautiful composition of flowers, hearts and butterflies

Edited topographical visualization of the surface of Titan from the Cassini-Huygens probe that landed there in 2005. Color/processing variant.

 

Image source: photojournal.jpl.nasa.gov/catalog/PIA06442

 

Original caption: This perspective view shows dark plains on the surface of Saturn's moon Titan about 3 miles (5 kilometers) from the Huygens probe landing site. In this area many discrete bright feature are scattered across the dark plains.

 

This provides stereo coverage with a resolution of about 45 feet per pixel (about 14 meters) and a convergence angle of about 6 degrees. The perspective image is color-coded in altitude with blue lowest and red highest. The ridges in the center of the view are about 150 feet-high (roughly 50 meters); the area covered is about 1.6 miles by 1.6 miles (2.5 by 2.5 kilometers). The topographic features toward the bottom right part of the view are suggestive of flow and erosion by fluids on the surface.

 

A stereo pair of images (insert) was acquired from the Huygens descent imager/spectral radiometer. The left image was acquired from 8 miles (12.2 kilometers) above the surface with the high resolution imager; the right from 4 miles (6.9 kilometers) altitude with the medium resolution imager.

 

The Huygens probe was delivered to Saturn's moon Titan by the Cassini spacecraft, which is managed by NASA's Jet Propulsion Laboratory, Pasadena, Calif. NASA supplied two instruments on the probe, the descent imager/spectral radiometer and the gas chromatograph mass spectrometer.

 

The Cassini-Huygens mission is a cooperative project of NASA, the European Space Agency and the Italian Space Agency. The Jet Propulsion Laboratory, a division of the California Institute of Technology in Pasadena, manages the mission for NASA's Science Mission Directorate, Washington, D.C.

 

For more information about the Cassini-Huygens mission visit saturn.jpl.nasa.gov.

 

Image Credit:

ESA/NASA/JPL/University of Arizona/USGS

 

Image Addition Date:

2005-12-02

ZoomCharts data visualization tools have become very popular amongst government agencies and bureaus because of its capabilities to process massive amounts of data in a blink of an eye. Users get a seamless experience without having to wait for data to load or for a chart or graph to update on the screen.

 

Another very important feature is how users can interact with ZoomCharts charts and graphs. Instead of a simple static visual display of information, you can easily extract data and see how it is related to other entries. Try it yourself!

 

Finally, ZoomCharts tools are touchscreen friendly, which means you can use them on all your mobile devices, including smartphones and tablets.

 

ZoomCharts advanced data visualization tools are being used by a growing number of organizations in business and educational sectors, including sciences and mathematics, such as anatomy, biochemistry, ecology, microbiology, nutrition, neuroscience, physiology, zoology, chemical engineering, geochemistry, molecular biology, geology, paleontology, physics, astronomy, algebra, computer science, geometry, logic, and statistics, and the arts such as, music, dance, theatre, film, animation, architecture, applied arts, photography, graphic design, interior design, and mixed media.

 

Business owners who have discovered ZoomChartsâ software hold it in high regard, with its ability to unlock the possibilities of their business in bringing data analysis and data presentation to the next level.

 

See how the Procurement Monitoring Bureau of Latvia has integrated ZoomCharts data visualization tools on their website to provide a functional and visually stimulating data display on the Latvian public sector:

www.iub.gov.lv/lv/mekletiepirkumus

 

Established and in operation since 2002, the Procurement Monitoring Bureau is a State administrative authority and autonomous watchdog that ensures public procurement regulations are followed in state and local government through monitoring and regulation. It operates in accordance with the law to publish tender notices and contract award notices, examine complaints, provide methodological assistance and consultations, and compile and analyze statistical information.

 

Check out ZoomCharts products:

 

Network Chart

Big network exploration

Explore linked data sets. Highlight relevant data with dynamic filters and visual styles. Incremental data loading. Exploration with focus nodes.

 

Time Chart

Time navigation and exploration tool

Browse activity logs, select time ranges. Multiple data series and value axes. Switch between time units.

 

Pie Chart

Amazingly intuitive hierarchical data exploration

Get quick overview of your data and drill down when necessary. All in a single easy to use chart.

 

Facet Chart

Scrollable bar chart with drill-down

Compare values side by side and provide easy access to the long tail.

 

ZoomCharts

www.zoomcharts.com

The worldâs most interactive data visualization software

  

#zoomcharts #interactive #data #datavisualization #charts #graphs #bigdata #dataviz #Latvia #procurement #monitoring #bureau #public #sector

3D Visualization of a room, just test render again i'll post the fnal renderings soon :D

 

A more complete version of my UN general assembly voting visualization. Each line is a country. Red lines are Africa, Green are Europe, Blue are Asia, Orange are N. America, Yellow are S. America, Purple are Oceania. A yes vote makes the line continue on a tight curve around the centre, a no vote puts them into a spiral farther from the centre, and an abstain or absence makes the line go straight out from the centre. Every absence reduces the alpha of the line by 10, so countries like the Central African Republic, which never show up, quickly vanish.

Beginning Python Visualization: Crafting Visual Transformation Scripts

by Shai Vaingast

 

Seen at University of Washington Book Store and subsequently I bought this on my Kindle, it is a well written introductory book, I am amazed what you can do with the Python language.

 

sea 031

Thank you volunteers you did it AGAIN on 5/10/14! Despite an absolutely dismal weather prediction 85 volunteers showed up to remove a huge amount of trash from Bear Creek and Charlesmont Park! Together we filled a 40 yard dumpster to capacity including 12 shopping carts, 6 couches, 4 bicycles, 6 tires, 2 vacuum cleaners, 2 mattresses, 2 wooden chairs, one wing-back chair one box spring, one entertainment system, and electric Barbie Guitar and much more! Thank you volunteers you rock! We will try to post more photos shortly but if you took any photos at our cleanup today please send them to us – Thank you!

 

We would like to send a special “Thank You!” out to all the dedicated volunteers from the U.S. Navy, Bear Creek Recreation Council, and Towson University!

 

We would also like to Thank Papa John’s of Dundalk for Donating Pizza and Bill Bateman’s Perry Hall for donating wings! Thank you Walmart, Mars and Giant for donating Gift Cards that helped us pay for many of our supplies! Also thank you to the Alliance for the Chesapeake Bay and American Rivers for supplies as well!

 

We also wish to thank historian and author of “Terror on the Chesapeake” Christopher George and the very talented artist Tom Spicer for coming out to the event. Mr. George explained the historical significance of Bear Creek and Charlesmont Park during the Battle of North point, War of 1812 and Mr. Spicer’s incredible paintings helps us all the visualize incredible scenes from this important historical event.

 

Thanks as well to Hannah Grice for acting as our photographer and taking most of these wonderful photos of the event!

 

This visualization shows 1 million Manga pages sorted by their visual characteristics.

 

Software: imagej macro written by Lev Manovich

 

X = standard deviation

Y = entropy

 

this produces the following map:

 

horizontal dimension:

the pages on the left progressively haver fewer grey values; the pages on the right have a both black and white

 

vertical dimension:

pages at the bottom have only black and white

pages on the top have more grey / more detail / more realism

 

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As we can see, the stylistic space of Manga does not have any distinct clusters. Visualization allows us to describe such a space much better than discrete linguistic categories.

 

The two visual features chosen for this visualization describe only some dimensions of visual style in Manga - however in terms of these dimensions, we can state this:

 

the concept of "style" (as a set of distinct categories used to describe a set of objects) may turn out to be meaningless

 

then we analyze enough objects, their variability can be better described using a continuous function

 

(our present research in Manga user-generated genre tags is suggesting that the same may apply for genre categories)

 

therefore visualization is a better language for describing cultural variability than natural languages

 

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Note that some of the pages - such as all covers - are in color. However in order to be able to render image at this size (the original is 44,000x44,000 pixels - scaled to 10,000x10,000 for posting to Flickr), we rendered everything in grey scale.

 

Finally, because pages are rendered on top of each other, you don't actually see 1 million of distinct pages - rather visualization shows a distribution of all pages with typical examples appearing on the top.

 

@ Long Nguyen & Thu Nguyen

Architecture - Interior Design & 3D Visualization

0979 962 864, Ho Chi Minh City

advlongnguyen@gmail.com

Some shots from my Mac visualizer.

pathfinding algorithm is reversed, examining longest paths first instead of shortest paths.

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