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caipre

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[ my public key: https://keybase.io/caipre; my proof: https://keybase.io/caipre/sigs/U_psVMC-FxBA_5cziS_cDQkfRuDJ4SzJwhRX1FUJI7c ]

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The federal body said work it was doing to revise and update information about where the historic quake struck had caused computer systems to misinterpret the data and think it was seeing a novel event.

It doesn't seem that implausible for a program to be reading through a dataset and issue a notice for a measurement above some value. If the dataset encoded years in just two digits, it (almost) makes sense that the program would report it 100 years off.

Imagine:

    with open(file) as f:
        for record in f:
            year, month, day, time, magnitude = record.split()
            
            if magnitude > 5:
                raise_alarm()
National Park Maps 9 years ago

On iOS, I've used Pocket Earth for years and really like it. They added topographic maps awhile back, and also have integrations with Wikipedia/Wikivoyage. I have pins and stars of POIs from all my trips saved (and exported) through that app.

https://pocketearth.com/

Definitely going to be looking more into this. I am just about to start a project that needs ACLs, and I was surprised to find that I was going to have to write a solution myself.

In case I just missed them, are there some comparable projects to this? Is there an established library in the space?

I'm not too familiar with how heavily locked down iOS is: does this "WebView only" policy only apply to apps released via the AppStore? Meaning, can I build locally and sideload install an app that uses my own engine? And if that existed, could I open source it for others to use?

I'm reading through now, and would love to contribute. I've been trying to break into this space (systems programming, especially OS and compilers) for a long time and the biggest hurdle for me has been to actually do it. I really appreciate that this project is focused on explaining just enough to jump in, complemented with nods to further resources that can add on to whatever knowledge the reader brings.

Steve, thanks for all your work on this and with Rust. Your attitude toward teaching and your writing ability go a long way in encouraging people to learn and in having the lesson be worthwhile.

    > Lidar data is collected by low-, slow-flying aircraft with equipment
    > that shoots millions of laser points to the ground. ... It is
    > possible to strip buildings and vegetation from the images, so that
    > only the ground is shown. In the Willamette River poster, the shades
    > of white and blue show elevations. The purest white color is the
    > baseline, (the zero point, at the lowest point near Independence on
    > the upper part of the image). The darkest blue is 50 feet (or higher)
    > than the baseline.
Very cool, and really a beautiful image. Contour lines on a topographic map show the same data, but mapping the elevation to a color range and clipping out elevations outside the river's effects really make this unlike anything I've seen before.

Edit: The original submission (see dang's post) references a similar set of maps[0] for the Mississippi River, which are equally beautiful and even more impressive.

[0] http://www.radicalcartography.net/index.html?fisk

I suppose just that it can be difficult to get an ampersand right drawing it straight-on, let alone in reverse. The painter accidentally painted the "Q" backwards (forwards, relative to them); it probably took some concentration to get the ampersand correct.

Awhile back I read another disaster recovery story, along the lines of recovering a long pipeline command from a long-running process by reading the resident memory of the containing shell. I've not managed to find it, but I think it was posted to HN sometime last year or so. Anyone know about it?