I had a go at doing roughly the same thing a couple of years ago [0]. It was mostly straightforward, but the part I really struggled with were rendering the sea. The encoding of OSM coastline is quite quirky [1]. When the edge of the rendering intersects with the coastline it's very tricky to compute which side of a coastline is sea and which is land. As an example - how would you render this [2]?
I wasn't sure how I could solve this, so I wrote up a more abstract formulation of the problem here [3], and asked for help. I think the proposed solution make sense, but I think I would have to implement it by rendering individual pixels and wouldn't be able to lean on a higher level graphics library.
I'm looking forward to seeing how the author solved this problem.
Potentially dumb suggestion: what if one just declares anything that has a significant chunk of non-bridge or non-tunnel street on it land? It's not a universal solution but perhaps sufficient for the application?
I recently made a map (using Generic Mapping Tools) of one of the Aleutian Islands in Alaska, for one of my dad’s grad students to use in a paper. That would constitute a good example of where you couldn’t just tell my # of built structures (since at certain zoom levels, there are none!)
Sure, but are you likely to have users want to A/B test traffic light configurations there? My suggestion was very specific to the application in question.
You might want to look into OSMCoastline, a separate piece of software written specifically to make the coastline usable for renders: https://osmcode.org/osmcoastline/
A simple solution is paint the sea with triangles of which one side is perfectly horizontal. And always work bottom to top.
You will have to pre scan the ways for instance where they change from ascending to descending. Here the sea will spilt into a left and right section. Make a list of these and sort them from top to bottom.
While generating triangles, check that list to where you should split.
Agreed. This is a good library but it is let down by lack of documentation. Reading the source doesn't help, e.g. this is "explaining" the parameters in the plot function:
# Whether to use a backup for the layers
backup = None,
# Custom postprocessing function on layers
postprocessing = None,
# Radius (in case of circular plot)
radius = None,
These sorts of comments merely repeat what's in the code and are worse than useless.
Knowledge, and capability are like the surface of a balloon. Each day the balloon is expanded and it is only after a while you realise how far away from the surface point you are on, all the other surface points have reached. I mean i toyed with python and maps back in the day, and my intuition for how good looking you could make one of these is completely off.
This stuff is amazing.
I think I want there to be a professional software "continuing-education" [#] service. A course I do each 6 months that just gets me to run something for an hour (from astronomy to 3d-printing).
I know i could do it myself but the 10 -20 hours spent on each install wasted though bad configs seems something I would happily pay to avoid.
[#] Not a "re-education" camp. Although I know few devs I could send to one if someone provides seed funding. ;-)
Yes, but it's not a good practice to specify full git url in setup.py, where I would expect to have sheer module name and version constraints if necessary. There is a convention about overriding requirements from setup.py via requirements.txt file, but here the author just decided to note it in a readme file instead to avoid the need to clone his repository manually.
Like for all languages there are a bunch of dependency managers. And everyone you ask will praise the one they use.
In my opinion, setup.py is best approach. I don't want to be forced to use some specific dependency manager. I just want to run setup.py and expect it to take care of dependencies.
Add these imports to the top of the readme example to make it work. For the life of me I don't understand people who strip imports out of code examples.
import matplotlib.pyplot as plt
from prettymaps import plot
Looks really nice. The big blob of parameters in the kwargs looks pretty intimidating to get correct. Maybe consider a builder object for the config: https://en.wikipedia.org/wiki/Builder_pattern. It would probably be easier to document, too (document the setter methods of the Builder rather than try to explain the nested dict). Feel free to ignore me.
The option of not just setting a fixed colour for certain features (like a building), but supplying a palette of colours for the renderer to randomly use is interesting. It makes the output playful. I don't think I've seen that feature before in OpenStreetMap renderers.
Have you thought about building a site where users could order framed posters of any address they like using the output of this library? I think that would be cool
It's fun to see a fresh new take on how to draw maps in Python. I'm still mired in 10 year old concepts from when this stuff was much harder. This project just looks joyful.
Does anyone have a simple way to make rendered images from osm data? Usually it involves postgres, but I wish there was a renderer that could use the vector tiles directly...
the tricky part is to known which xtile, ytile to fetch, but Stack Overflow has the answer [1].
Then you can draw over them with `PIL` and also `cairo`, in order to lay SVG shapes onto the map. Cairo is somewhat hard to grasp, because it is outdated, but it draws perfectly smooth lines.
OSMs source of truth is not organized around vector tiles, i believe.
https://github.com/dfyz/osm-renderer might be similar to what you are looking for
I was hoping for a more generic version. As they say in the repo, "The Grapher is currently not well designed for immediate reuse as a standalone visualization library, it relies heavily on our database structure".
Beautiful. I wish there was a way to simplify OSM roads. For example, southbound/northbound highways are correctly stored as separate roads in OSM. But to draw an atlas, it's often enough to show the single highway.
Plotly is a fantastic library if you want interactive graphs/visualizations. It has good documentation and support. It fits my definition of easy to do simple things and possible to do hard things. You can also easily move your graphs to front-end since Plotly Python is basically binding to plotly.js . The downside is exactly that - there is javascript underneath.
Seaborn is good if you want something pretty and static with matplotlib underneath but do not want to mess with defaults too much.
I had a go at doing roughly the same thing a couple of years ago [0]. It was mostly straightforward, but the part I really struggled with were rendering the sea. The encoding of OSM coastline is quite quirky [1]. When the edge of the rendering intersects with the coastline it's very tricky to compute which side of a coastline is sea and which is land. As an example - how would you render this [2]?
I wasn't sure how I could solve this, so I wrote up a more abstract formulation of the problem here [3], and asked for help. I think the proposed solution make sense, but I think I would have to implement it by rendering individual pixels and wouldn't be able to lean on a higher level graphics library.
I'm looking forward to seeing how the author solved this problem.
[0] https://twitter.com/willsewell_/status/1172523752699113473
[1] https://wiki.openstreetmap.org/wiki/Tag:natural%3Dcoastline#...
[2] https://www.openstreetmap.org/#map=15/22.0330/88.8819
[3] https://leetcode.com/discuss/general-discussion/1104642/im-s...