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Bokeh – Interactive web visualization library in Python

bokeh.pydata.org

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Re: Bokeh – Interactive web visualization library in Python

#21

Post by slantyyz »

vph wrote: post #17
slantyyz wrote: post #16

Earlier quoted context omitted.

As someone who likes photography and analytics, I disagree about the name. As you say, bokeh is about out-of-focus blur. That's sort of the opposite impression you want to present in a tool that's intended to give you "clarity" via its visualizations.

As someone who likes photography, I have to disagree about your reasoning. The clarity of your subject is as much about how much it is in focus as how much irrelevant things are out of focus. Portrait photos are often beautiful when the lens has good bokeh characteristics.

>> The clarity of your subject is as much about how much it is in focus as how much irrelevant things are out of focus.

If you actually look at the sample output of the library, there's nothing out of focus, at least from the perspective of depth of field. In my opinion (and it is just an opinion), calling all de-emphasized data bokeh is a stretch at best. Blurring and de-emphasis using color and size are two different things.

>> Portrait photos are often beautiful when the lens has good bokeh characteristics.

Let's be clear -- while bokeh can enhance the beauty of a portrait, it doesn't make a portrait beautiful. Most people don't know the difference between good bokeh and bad bokeh (pwang's definition of bokeh in his response to me is very good), but they can usually identify a blurred background vs. a sharp background.

Many people tend to prefer a sharp subject against a blurred background, and that's usually enough for most people to consider a portrait beautiful even if the bokeh is quite ugly. Without getting into a long drawn out discussion of bokeh, you have to remember that there's also more to a beautiful portrait than the novelty of a blurred background.

Re: Bokeh – Interactive web visualization library in Python

#22

Post by pwang »

slantyyz wrote: post #21
vph wrote: post #17

Earlier quoted context omitted.

As someone who likes photography, I have to disagree about your reasoning. The clarity of your subject is as much about how much it is in focus as how much irrelevant things are out of focus. Portrait photos are often beautiful when the lens has good bokeh characteristics.

>> The clarity of your subject is as much about how much it is in focus as how much irrelevant things are out of focus. If you actually look at the sample output of the library, there's nothing out of focus, at least from the perspective of depth of field. In my opinion (and it is just an opinion), calling all de-emphasized data bokeh is a stretch at best. Blurring and de-emphasis using color and size are two differe…

> If you actually look at the sample output of the library, there's nothing out of focus,

We are working on the semantic downsampling and perceptual integration aspects of visualizing large data. This currently lives in its own repo: https://github.com/JosephCottam/AbstractRendering

> calling all de-emphasized data bokeh is a stretch at best

It's really just meant to be an evocative metaphor... :-)

Re: Bokeh – Interactive web visualization library in Python

#23

Post by slantyyz »

pwang wrote: post #20
slantyyz wrote: post #16

Earlier quoted context omitted.

As someone who likes photography and analytics, I disagree about the name. As you say, bokeh is about out-of-focus blur. That's sort of the opposite impression you want to present in a tool that's intended to give you "clarity" via its visualizations.

Actual, bokeh is about the quality of the blur. Yes, blur can have quality. If you simply removed everything that was not in focus, you lose context and texture about the subject. If you use a pinhole camera and present everything in sharp focus, you lose the insight. This is actually mentioned in the documentation: http://bokeh.pydata.org/#technical-vision """ Photographers use the Japanese word “bokeh” to describe…

>> Actual, bokeh is about the quality of the blur.

Yes, you're right. But most people tend to treat out-of-focus blur synonymously with bokeh (the quality of the blur) -- they're related but not the same. In this particular library's case, I think they're talking about out-of-focus blur, not bokeh.

Re: Bokeh – Interactive web visualization library in Python

#24

Post by Keyframe »

What does 'large datasets' mean here? We are building a visualization service to abstract users from fiddling with d3 and other libraries. We want users to be able to use all of viz libraries out there with just providing data input and tweaking settings, so this looks interesting.

Re: Bokeh – Interactive web visualization library in Python

#25

Post by slantyyz »

pwang wrote: post #22
slantyyz wrote: post #21

Earlier quoted context omitted.

>> The clarity of your subject is as much about how much it is in focus as how much irrelevant things are out of focus. If you actually look at the sample output of the library, there's nothing out of focus, at least from the perspective of depth of field. In my opinion (and it is just an opinion), calling all de-emphasized data bokeh is a stretch at best. Blurring and de-emphasis using color and size are two differe…

> If you actually look at the sample output of the library, there's nothing out of focus, We are working on the semantic downsampling and perceptual integration aspects of visualizing large data. This currently lives in its own repo: https://github.com/JosephCottam/AbstractRendering > calling all de-emphasized data bokeh is a stretch at best It's really just meant to be an evocative metaphor... :-)

>> It's really just meant to be an evocative metaphor... :-)

Gotcha - me not liking a name is just my own personal opinion. The library itself is interesting.

You can't please everyone all of the time. ;)

Re: Bokeh – Interactive web visualization library in Python

#26

Post by clebio »

pwang wrote: post #22
slantyyz wrote: post #21

Earlier quoted context omitted.

>> The clarity of your subject is as much about how much it is in focus as how much irrelevant things are out of focus. If you actually look at the sample output of the library, there's nothing out of focus, at least from the perspective of depth of field. In my opinion (and it is just an opinion), calling all de-emphasized data bokeh is a stretch at best. Blurring and de-emphasis using color and size are two differe…

> If you actually look at the sample output of the library, there's nothing out of focus, We are working on the semantic downsampling and perceptual integration aspects of visualizing large data. This currently lives in its own repo: https://github.com/JosephCottam/AbstractRendering > calling all de-emphasized data bokeh is a stretch at best It's really just meant to be an evocative metaphor... :-)

If you're thinking in terms of the _spirit_ of bokeh, and understand 'semantic downsampling', you've got my vote. As someone whose tried to use D3, I like this a lot. I'll be experimenting with Bokeh now soon.

Re: Bokeh – Interactive web visualization library in Python

#27

Post by hhuuggoo »

Keyframe wrote: post #24

What does 'large datasets' mean here? We are building a visualization service to abstract users from fiddling with d3 and other libraries. We want users to be able to use all of viz libraries out there with just providing data input and tweaking settings, so this looks interesting.

Part of the 0.4 release is to incorporate the concept of abstract rendering - which means you render on the server, and then send the necessary information over to the client on demand. For example, if someone tries to scatter a billion points, instead of just drawing a useless point cloud, you would figure out where all the points fit inside your 512x512 canvas (or whatever size you have), figure out how all the points stack up, compute an alpha that is meaningful for that number of points, and then send the heatmap to the client.

You can easily imagine as similar approach for line plots which does selectively downsampling of datapoints in order to preserve interesting features in the plot.

And then we'll build interactors on top of that, so you can actually treat it like a scatter plot, even though it's a heatmap that's being sent to your browser.

So the answer is - large datasets, means, as large as our abstract rendering algorithm can handle on your hardware, so those data sets should be pretty big.

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