View allAll Photos Tagged Visualize
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.
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).
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).
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.
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)
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.
Another way to discover interesting people is to look at your friend's friend list: www.neuroproductions.be/twitter_friends_network_browser/
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
The worldâs most interactive data visualization software
#zoomcharts #interactive #data #datavisualization #charts #graphs #bigdata #dataviz #Latvia #procurement #monitoring #bureau #public #sector
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
------------------
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
---------------
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.