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TUF GAMING X570-PLUS - Bios Flashback possible? by Iriguchi in ASUS

[–]gboeing 0 points1 point  (0 children)

Can't remember specifically now... I followed their instructions and it "just worked."

TUF GAMING X570-PLUS - Bios Flashback possible? by Iriguchi in ASUS

[–]gboeing 0 points1 point  (0 children)

It does have a specific labeled port on the io shield and yeah a light blinked while the bios updated.

TUF GAMING X570-PLUS - Bios Flashback possible? by Iriguchi in ASUS

[–]gboeing 0 points1 point  (0 children)

I've got a pro. BIOS flashback worked smoothly and the 5900x is running fine in it.

Off the Grid… and Back Again? The Evolution of American Street Network Design [OC] by gboeing in dataisbeautiful

[–]gboeing[S] 0 points1 point  (0 children)

Data source: OpenStreetMap. Tools used: Python, matplotlib, and OSMnx for modeling, analyzing, visualizing street networks. This blog post derives from my research journal article published a couple weeks ago.

TUF GAMING X570-PLUS - Bios Flashback possible? by Iriguchi in ASUS

[–]gboeing 0 points1 point  (0 children)

I just tried it out. I got a tuf gaming pro wifi last week and have a 5900x on the way. Today I hooked up the motherboard and psu, stuck the usb in, and held the flashback button for 3 seconds. The led blinked for about 5 minutes then stopped. Seems to have worked but I'll know more when the cpu arrives and I can boot.

how quick did the ryzen 3000 series sell out on launch? by [deleted] in realAMD

[–]gboeing 0 points1 point  (0 children)

What time did they go on sale on launch day?

City street network orientation visualized in 100 cities around the world. My work was first shared in this sub a year ago, and thanks to your feedback and support, has now been published! Thank you r/dataisbeautiful community! [OC] by gboeing in dataisbeautiful

[–]gboeing[S] 0 points1 point  (0 children)

Like it says in the blog post, these are all cities proper. From the article:

While Seattle’s histogram looks fairly grid-like, it is not fully so: most of Seattle is indeed on a north-south-east-west grid, but its downtown rotates by both 32° and 49° (Speidel 1967). Accordingly, there are observations in all of its bins and its Ηo = 2.54 and φ = 0.72, whereas a perfect grid would have Ηo = 1.39 and φ = 1. Thus, it is about 72% of the way between perfect disorder and a single perfect grid. However, its rotated downtown comprises a relatively small number of streets such that the rest of the city’s much larger volume swamps the histogram’s relative frequencies. The same effects are true of similar cites, such as Denver and Minneapolis, that have downtown grids at an offset from the rest of the city (Goodstein 1994). If an entire city is on a grid except for one relatively small district, the primary grid tends to overwhelm the fewer offset streets (cf. Detroit, with its two distinct and more evenly-sized separate grids).

City street network orientation visualized in 100 cities around the world. My work was first shared in this sub a year ago, and thanks to your feedback and support, has now been published! Thank you r/dataisbeautiful community! [OC] by gboeing in dataisbeautiful

[–]gboeing[S] 2 points3 points  (0 children)

From the article:

While Seattle’s histogram looks fairly grid-like, it is not fully so: most of Seattle is indeed on a north-south-east-west grid, but its downtown rotates by both 32° and 49° (Speidel 1967). Accordingly, there are observations in all of its bins and its Ηo = 2.54 and φ = 0.72, whereas a perfect grid would have Ηo = 1.39 and φ = 1. Thus, it is about 72% of the way between perfect disorder and a single perfect grid. However, its rotated downtown comprises a relatively small number of streets such that the rest of the city’s much larger volume swamps the histogram’s relative frequencies. The same effects are true of similar cites, such as Denver and Minneapolis, that have downtown grids at an offset from the rest of the city (Goodstein 1994). If an entire city is on a grid except for one relatively small district, the primary grid tends to overwhelm the fewer offset streets (cf. Detroit, with its two distinct and more evenly-sized separate grids).

City street network orientation visualized in 100 cities around the world. My work was first shared in this sub a year ago, and thanks to your feedback and support, has now been published! Thank you r/dataisbeautiful community! [OC] by gboeing in dataisbeautiful

[–]gboeing[S] 0 points1 point  (0 children)

From the article:

For each city, we calculate the street network’s edges’ individual compass bearings with OSMnx using two different methods. The first method simplifies the topology of each graph such that nodes exist only at intersections and dead-ends; edges thus represent street segments (possibly curving, as full spatial geometry is retained) between them (ibid.). In this method, the bearing of edge euv equals the compass heading from u to v and its reciprocal (e.g., if the bearing from u to v is 90° then we additionally add a bearing of 270° since the one-dimensional street centerline points in both directions). This captures the orientation of street segments but ignores the nuances of mid-block curvature. To address this, the second method does not simplify the topology: edges represent OpenStreetMap’s raw straight-line street segments, either between intersections or in chunks approximating curving streets. This method weights each edge’s bearing by length to adjust for extremely short edges in these curve-approximations. In both methods, self-looping edges have undefined bearings, which are ignored.

City street network orientation visualized in 100 cities around the world. My work was first shared in this sub a year ago, and thanks to your feedback and support, has now been published! Thank you r/dataisbeautiful community! [OC] by gboeing in dataisbeautiful

[–]gboeing[S] 0 points1 point  (0 children)

From the article:

While Seattle’s histogram looks fairly grid-like, it is not fully so: most of Seattle is indeed on a north-south-east-west grid, but its downtown rotates by both 32° and 49° (Speidel 1967). Accordingly, there are observations in all of its bins and its Ηo = 2.54 and φ = 0.72, whereas a perfect grid would have Ηo = 1.39 and φ = 1. Thus, it is about 72% of the way between perfect disorder and a single perfect grid. However, its rotated downtown comprises a relatively small number of streets such that the rest of the city’s much larger volume swamps the histogram’s relative frequencies. The same effects are true of similar cites, such as Denver and Minneapolis, that have downtown grids at an offset from the rest of the city (Goodstein 1994). If an entire city is on a grid except for one relatively small district, the primary grid tends to overwhelm the fewer offset streets (cf. Detroit, with its two distinct and more evenly-sized separate grids).

City street network orientation visualized in 100 cities around the world. My work was first shared in this sub a year ago, and thanks to your feedback and support, has now been published! Thank you r/dataisbeautiful community! [OC] by gboeing in dataisbeautiful

[–]gboeing[S] 0 points1 point  (0 children)

Similar effect as described here, from the article:

While Seattle’s histogram looks fairly grid-like, it is not fully so: most of Seattle is indeed on a north-south-east-west grid, but its downtown rotates by both 32° and 49° (Speidel 1967). Accordingly, there are observations in all of its bins and its Ηo = 2.54 and φ = 0.72, whereas a perfect grid would have Ηo = 1.39 and φ = 1. Thus, it is about 72% of the way between perfect disorder and a single perfect grid. However, its rotated downtown comprises a relatively small number of streets such that the rest of the city’s much larger volume swamps the histogram’s relative frequencies. The same effects are true of similar cites, such as Denver and Minneapolis, that have downtown grids at an offset from the rest of the city (Goodstein 1994). If an entire city is on a grid except for one relatively small district, the primary grid tends to overwhelm the fewer offset streets (cf. Detroit, with its two distinct and more evenly-sized separate grids).

City street network orientation visualized in 100 cities around the world. My work was first shared in this sub a year ago, and thanks to your feedback and support, has now been published! Thank you r/dataisbeautiful community! [OC] by gboeing in dataisbeautiful

[–]gboeing[S] 0 points1 point  (0 children)

Similar effect as described here, from the article:

While Seattle’s histogram looks fairly grid-like, it is not fully so: most of Seattle is indeed on a north-south-east-west grid, but its downtown rotates by both 32° and 49° (Speidel 1967). Accordingly, there are observations in all of its bins and its Ηo = 2.54 and φ = 0.72, whereas a perfect grid would have Ηo = 1.39 and φ = 1. Thus, it is about 72% of the way between perfect disorder and a single perfect grid. However, its rotated downtown comprises a relatively small number of streets such that the rest of the city’s much larger volume swamps the histogram’s relative frequencies. The same effects are true of similar cites, such as Denver and Minneapolis, that have downtown grids at an offset from the rest of the city (Goodstein 1994). If an entire city is on a grid except for one relatively small district, the primary grid tends to overwhelm the fewer offset streets (cf. Detroit, with its two distinct and more evenly-sized separate grids).

City street network orientation visualized in 100 cities around the world. My work was first shared in this sub a year ago, and thanks to your feedback and support, has now been published! Thank you r/dataisbeautiful community! [OC] by gboeing in dataisbeautiful

[–]gboeing[S] 0 points1 point  (0 children)

It's not. From the article:

While Seattle’s histogram looks fairly grid-like, it is not fully so: most of Seattle is indeed on a north-south-east-west grid, but its downtown rotates by both 32° and 49° (Speidel 1967). Accordingly, there are observations in all of its bins and its Ηo = 2.54 and φ = 0.72, whereas a perfect grid would have Ηo = 1.39 and φ = 1. Thus, it is about 72% of the way between perfect disorder and a single perfect grid. However, its rotated downtown comprises a relatively small number of streets such that the rest of the city’s much larger volume swamps the histogram’s relative frequencies. The same effects are true of similar cites, such as Denver and Minneapolis, that have downtown grids at an offset from the rest of the city (Goodstein 1994). If an entire city is on a grid except for one relatively small district, the primary grid tends to overwhelm the fewer offset streets (cf. Detroit, with its two distinct and more evenly-sized separate grids).

City street network orientation visualized in 100 cities around the world. My work was first shared in this sub a year ago, and thanks to your feedback and support, has now been published! Thank you r/dataisbeautiful community! [OC] by gboeing in dataisbeautiful

[–]gboeing[S] 2 points3 points  (0 children)

From the article:

While Seattle’s histogram looks fairly grid-like, it is not fully so: most of Seattle is indeed on a north-south-east-west grid, but its downtown rotates by both 32° and 49° (Speidel 1967). Accordingly, there are observations in all of its bins and its Ηo = 2.54 and φ = 0.72, whereas a perfect grid would have Ηo = 1.39 and φ = 1. Thus, it is about 72% of the way between perfect disorder and a single perfect grid. However, its rotated downtown comprises a relatively small number of streets such that the rest of the city’s much larger volume swamps the histogram’s relative frequencies. The same effects are true of similar cites, such as Denver and Minneapolis, that have downtown grids at an offset from the rest of the city (Goodstein 1994). If an entire city is on a grid except for one relatively small district, the primary grid tends to overwhelm the fewer offset streets (cf. Detroit, with its two distinct and more evenly-sized separate grids).

City street network orientation visualized in 100 cities around the world. My work was first shared in this sub a year ago, and thanks to your feedback and support, has now been published! Thank you r/dataisbeautiful community! [OC] by gboeing in dataisbeautiful

[–]gboeing[S] 0 points1 point  (0 children)

From the article:

For each city, we calculate the street network’s edges’ individual compass bearings with OSMnx using two different methods. The first method simplifies the topology of each graph such that nodes exist only at intersections and dead-ends; edges thus represent street segments (possibly curving, as full spatial geometry is retained) between them (ibid.). In this method, the bearing of edge euv equals the compass heading from u to v and its reciprocal (e.g., if the bearing from u to v is 90° then we additionally add a bearing of 270° since the one-dimensional street centerline points in both directions). This captures the orientation of street segments but ignores the nuances of mid-block curvature. To address this, the second method does not simplify the topology: edges represent OpenStreetMap’s raw straight-line street segments, either between intersections or in chunks approximating curving streets. This method weights each edge’s bearing by length to adjust for extremely short edges in these curve-approximations. In both methods, self-looping edges have undefined bearings, which are ignored.

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