prettymaps
A minimal Python library to draw customized maps from OpenStreetMap created using the osmnx, matplotlib, shapely and vsketch libraries.
This work is licensed under a GNU Affero General Public License v3.0 (you can make commercial use, distribute and modify this project, but must disclose the source code with the license and copyright notice)
Note about crediting and NFTs:
- Please keep the printed message on the figures crediting my repository and OpenStreetMap (mandatory by their license).
- I am personally against NFTs for their environmental impact, the fact that they're a giant money-laundering pyramid scheme and the structural incentives they create for theft in the open source and generative art communities.
- I do not authorize in any way this project to be used for selling NFTs, although I cannot legally enforce it. Respect the creator.
- The AeternaCivitas and geoartnft projects have used this work to sell NFTs and refused to credit it. See how they reacted after being exposed: AeternaCivitas, geoartnft.
- I have closed my other generative art projects on Github and won't be sharing new ones as open source to protect me from the NFT community.
As seen on Hacker News:
Read the docs
prettymaps subreddit
Google Colaboratory Demo
Installation
PIP
Install with
$ pip install prettymaps
Arch Linux
Use the AUR
yay -S python-prettymaps
Usage example (For more examples, see this Jupyter Notebook):
# Init matplotlib figure
fig, ax = plt.subplots(figsize = (12, 12), constrained_layout = True)
backup = plot(
# Address:
'Praça Ferreira do Amaral, Macau',
# Plot geometries in a circle of radius:
radius = 1100,
# Matplotlib axis
ax = ax,
# Which OpenStreetMap layers to plot and their parameters:
layers = {
# Perimeter (in this case, a circle)
'perimeter': {},
# Streets and their widths
'streets': {
'width': {
'motorway': 5,
'trunk': 5,
'primary': 4.5,
'secondary': 4,
'tertiary': 3.5,
'residential': 3,
'service': 2,
'unclassified': 2,
'pedestrian': 2,
'footway': 1,
}
},
# Other layers:
# Specify a name (for example, 'building') and which OpenStreetMap tags to fetch
'building': {'tags': {'building': True, 'landuse': 'construction'}, 'union': False},
'water': {'tags': {'natural': ['water', 'bay']}},
'green': {'tags': {'landuse': 'grass', 'natural': ['island', 'wood'], 'leisure': 'park'}},
'forest': {'tags': {'landuse': 'forest'}},
'parking': {'tags': {'amenity': 'parking', 'highway': 'pedestrian', 'man_made': 'pier'}}
},
# drawing_kwargs:
# Reference a name previously defined in the 'layers' argument and specify matplotlib parameters to draw it
drawing_kwargs = {
'background': {'fc': '#F2F4CB', 'ec': '#dadbc1', 'hatch': 'ooo...', 'zorder': -1},
'perimeter': {'fc': '#F2F4CB', 'ec': '#dadbc1', 'lw': 0, 'hatch': 'ooo...', 'zorder': 0},
'green': {'fc': '#D0F1BF', 'ec': '#2F3737', 'lw': 1, 'zorder': 1},
'forest': {'fc': '#64B96A', 'ec': '#2F3737', 'lw': 1, 'zorder': 1},
'water': {'fc': '#a1e3ff', 'ec': '#2F3737', 'hatch': 'ooo...', 'hatch_c': '#85c9e6', 'lw': 1, 'zorder': 2},
'parking': {'fc': '#F2F4CB', 'ec': '#2F3737', 'lw': 1, 'zorder': 3},
'streets': {'fc': '#2F3737', 'ec': '#475657', 'alpha': 1, 'lw': 0, 'zorder': 3},
'building': {'palette': ['#FFC857', '#E9724C', '#C5283D'], 'ec': '#2F3737', 'lw': .5, 'zorder': 4},
}
)
Gallery:
Barcelona:
Heerhugowaard:
Barra da Tijuca:
Porto Alegre:
