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#graph

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*
grobi

"Well, that sounded like a concert in a cosmic stalactite cave and leads us back to the bottom of our earthly seas. This and the next three posts are about very special sounds from the depths of the oceans!"

2010 April 27

The Bloop: A Mysterious
Sound from the Deep Ocean
* Credit: NOAA, SOSUS
pmel.noaa.gov/eoi/
irp.fas.org/program/collect/so

Explanation: What created this strange sound in Earth's Pacific Ocean? Pictured above is a visual representation of a loud and unusual sound, dubbed a Bloop, captured by deep sea microphones in 1997. In the above graph, time is shown on the horizontal axis, deep pitch is shown on the vertical axis, and brightness designates loudness. Although Bloops are some of the loudest sounds of any type ever recorded in Earth's oceans, their origin remains unknown. The Bloop sound was placed as occurring several times off the southern coast of South America and was audible 5,000 kilometers away. Although the sound has similarities to those vocalized by living organisms, not even a blue whale is large enough to croon this loud. The sounds point to the intriguing hypothesis that even larger life forms lurk in the unexplored darkness of Earth's deep oceans. A less imagination-inspiring possibility, however, is that the sounds resulted from some sort of iceberg calving. No further Bloops have been heard since 1997, although other loud and unexplained sounds have been recorded.

apod.nasa.gov/apod/ap100427.ht

Original icequake (bloop) sound:
The broad spectrum sounds recorded in the summer of 1997 are consistent with icequakes generated by large icebergs as they crack and fracture. NOAA hydrophones deployed in the Scotia Sea detected numerous icequakes with spectrograms very similar to “Bloop”. Recorded signal sped up 16 times.

[...]

pmel.noaa.gov/acoustics/specs_

CREDIT
DOC / NOAA/ OAR / PMEL / Acoustics Program

#space#earth#sonification
dr 🛠️🛰️📡🎧:blobfoxcomputer:

I've been spending time wondering why implementing panning/zooming on a polar #graph was so much more fiddly than I expected

#software #engineering: I wasn't expecting so many weird corner cases, so I reacted to them too late. If I rewrote the code, it would probably be simpler

#math: I think this is really the big one. I was talking with one of the kids and they pointed out that a panned/zoomed cartesian graph is just another cartesian graph, but a panned/zoomed polar graph isn't.

(I *think* what they mean is that pan/zoom are affine transforms in a cartesian graph. Even if the axes are sheared, this is still pretty simple. In polar coordinates this isn't true anymore. But maybe "affine" isn't what I mean or care about. Maybe it's more about self-similarity.)

If that is what's going on, I'm not sure what to do with that information.

What if I converted polar into a wrapped cartesian (i.e. cylindrical) graph, panned/zoomed, then converted back...? That probably doesn't help, since the zoombox also has to transform.

Mike Wong

Another #graph, showing how it's wasteful to shut off a productive deep space mission (New Horizons). The main costs have already been paid.

From a June 9 Michael Hiltzik article all over the internet about "Trump's NASA cuts would destroy decades of science and wipe out its future," but the graph is credited to Planetary Society.

*
utzer [Pleroma]
Hey everyone!
I’m looking for a good way to create a #graph or #chart from a #dataset under #Linux.

The data is in a #CSV file and has around 180,000 rows. One column contains the timestamps, and several other columns contain the actual #measurement values.

Not every value is recorded at every timestamp, so there are different sampling rates across columns, and some fields are empty. The solution should be able to handle that – missing data, large file size, and multiple series plotted over #time.

What’s your preferred tool or approach for this kind of visualization?
Ideally something easily repeatable.

#DataVisualization #CSVHandling #Linux
Replied in thread
C.

@peterdrake @mkj @jitseniesen @apa

Well, I confirmed that the bizarro text at the top of the Y axis is not in fact part of the Y axis. If you set the style of the Y axis tick labels to plain, so it doesn't use scientific notation:

>>> plt.ticklabel_format(axis="y", style="plain")

... that one bizarro value is still shown in scientific format.

I don't recall if matplotlib supports multiple scales/sets of ticks on an axis, so I'm not sure where that value is coming from. I looked at the data generated by your code and didn't see anything weird.

I think you need either a matplotlib expert, or a user discussion group. Or at least someone who's used matplotlib more recently than the Clinton administration... 😉

#matplotlib#Python#plot
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