When the 63-story Address Downtown Dubai hotel went up in flames on New Year’s Eve, photojournalist Dennis Mallari dangled from a cable on the 48th floor and kept shooting.
Photographer Kirill Neiezhmakov was also photographing the blaze at the same time, except he was on the other side of town. From a safe distance, Neiezhmakov captured the hauntingly beautiful time-lapse video above that shows the fire spewing smoke and embers onto the Dubai skyline.
(via Kirill Neiezhmakov via DIYP)
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Not cool, 2016. Not cool.
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Inoue’s shot was recently featured in the Daily Dozen.
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Labrie’s shot was recently featured in the Best of the World story.
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Back in 2013, we shared the work of photographer Richard Gottardo, who spent months in the Rocky Mountains hunting and photographing northern lights. Now, 2 years and 6,500+ photos later, Gottardo has combined his beautiful images into this dazzling new 3-minute time-lapse short film, aptly titled “Alberta’s Northern Lights.”
(via Richard Gottardo via Reddit)
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Chisholms’s shot was recently featured in the Daily Dozen.
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Photographer and programmer Saulius Lukse made this clever 22-second-long time-lapse video in which the windows of a large apartment building are used as a ticker to wish viewers a happy new year — all while the time-lapse continues to run in the rest of the scene.
“This can be done spending few days of non stop work on GIMP or Photoshop,” Lukse says, but he used “a more intelligent way” that involves using a script do the heavy lifting.
Lukse started by shooting a traditional time-lapse by shooting a photo every minute for about 12 hours starting from close to sunset. To create his “improvised dot matrix display” from building windows, Lukse first created a dark “off” background layer by finding instances in which each window isn’t illuminated in the large collection of photos (this step takes some work):
Next, he did the opposite, finding copies of each window while they’re illuminated and gathering them into a frame. Each window was placed in a separate layer (named after the x,y coordinate) to create the pixels of the display. This “time consuming process” took Lukse about 30 minutes:
The “pixel display” was saved as a PSD file for his script to use.
Finally, Lukse created his overlay layer with an LED matrix control software called jinx to create the scrolling message and then used a “quick and dirty” Python script to do the rest of the time-lapse creation magic for the final result.
You can find the nitty-gritty technical details (and source code) of this project on this page.
]]>Theze’s shot was recently featured in the Daily Dozen.
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See more pictures from the January 2016 feature story “This Is Your Brain on Nature.”
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See more pictures from the January 2016 feature story “How Our National Parks Tell Our Story—and Show Who We Are.”
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See more pictures from the January 2016 feature story “Vultures Are Revolting. Here's Why We Need to Save Them.”
So have you been looking for something like RStudio, but for Python?
It’s been out for some time, but a recently updated release of Rodeo gives an increasingly workable RStudio-like environment for Python users.
The layout resembles the RStudio layout – file editor top left, interactive console bottom left, variable inspector and history top right, charts, directory view and plugins bottom right. (For plugins, read: packages).
The preferences panel lets you set the initial working directory as well as the path the required python executable.
Code selected in the file editor can be run in the console. Charts can be generated using matplotlib and are displayed in the chart view area bottom right.
As with RStudio, you can write reproducible research documents that blend markdown and code and render the result as HTML or PDF.
As you might expect, charts can be embedded as outputs in the document too.
Whilst the first version of Rodeo was a flask app viewable via a browser, and installable via pip, the latest version is an electron app, like RStudio. I found the ability to run Rodeo directly in the browser really useful, but the RStudio folks appear to have found a way of running RStudio via a browser using their RStudio server, so I’m hoping there’ll also be an open source version of Rodeo server available too?
One thing I’m wondering is whether Rodeo is a front end that can run against other Jupyter kernels? I notice that there is already a branch on the Rodeo github repo called r-backend, for example…?
Another thing I haven’t really clarified for myself are the differences between authoring (and teaching/learning) using the “Rmd/knitr” RStudio/Rodeo style workflow, and authoring in Jupyter notebooks. Notebook extensions are available that can suppress cell output etc to provide some level of control over what get rendered from a notebook used as an authoring environment. I guess what I’d like for Jupyter notebooks is a simple dropdown that lets me specify the equivalent of knitr text result options that control how code cells are rendered in an output document.
See also: IPython Markdown Opportunities in IPython Notebooks and RStudio and Notebooks, knitr and the Language-Markdown View Source Option….
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