mirror of
https://github.com/marceloprates/prettymaps.git
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99 lines
4.2 KiB
Markdown
99 lines
4.2 KiB
Markdown
# prettymaps
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A minimal Python library to draw customized maps from OpenStreetMap data.
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Based on [osmnx](https://github.com/gboeing/osmnx), [matplotlib](https://matplotlib.org/), [shapely](https://shapely.readthedocs.io/en/stable/index.html) and [vsketch](https://github.com/abey79/vsketch) libraries.
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## Important:
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<a href='https://ko-fi.com/marceloprates_' target='_blank'><img height='36' style='border:0px;height:36px;' src='https://cdn.ko-fi.com/cdn/kofi1.png?v=3' border='0' alt='Buy Me a Coffee at ko-fi.com' /></a>
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- I've made the `plot` function print by default a message in the corner containing the [mandatory OpenStreetMap credit](https://www.openstreetmap.org/copyright) and the link to this repository. Please keep it.
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- You can make commercial use of `prettymaps` drawings, but I ask that you credit OpenStreetMaps and myself.
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- Share your creations on the [prettymaps subreddit](https://www.reddit.com/r/prettymaps_/)
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## As seen on [Hacker News](https://web.archive.org/web/20210825160918/https://news.ycombinator.com/news):
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## Read the [docs](https://prettymaps.readthedocs.io/en/latest/prettymaps.html#module-prettymaps)
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## Google Colaboratory Demo
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[](https://colab.research.google.com/github/marceloprates/prettymaps/blob/master/notebooks/examples.ipynb)
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## Installation
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Install with
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```
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$ pip install prettymaps
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```
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## Usage example (For more examples, see [this Jupyter Notebook](https://nbviewer.jupyter.org/github/marceloprates/prettymaps/blob/main/notebooks/examples.ipynb)):
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```python
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# Init matplotlib figure
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fig, ax = plt.subplots(figsize = (12, 12), constrained_layout = True)
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backup = plot(
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# Address:
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'Praça Ferreira do Amaral, Macau',
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# Plot geometries in a circle of radius:
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radius = 1100,
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# Matplotlib axis
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ax = ax,
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# Which OpenStreetMap layers to plot and their parameters:
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layers = {
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# Perimeter (in this case, a circle)
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'perimeter': {},
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# Streets and their widths
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'streets': {
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'width': {
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'motorway': 5,
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'trunk': 5,
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'primary': 4.5,
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'secondary': 4,
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'tertiary': 3.5,
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'residential': 3,
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'service': 2,
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'unclassified': 2,
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'pedestrian': 2,
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'footway': 1,
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}
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},
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# Other layers:
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# Specify a name (for example, 'building') and which OpenStreetMap tags to fetch
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'building': {'tags': {'building': True, 'landuse': 'construction'}, 'union': False},
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'water': {'tags': {'natural': ['water', 'bay']}},
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'green': {'tags': {'landuse': 'grass', 'natural': ['island', 'wood'], 'leisure': 'park'}},
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'forest': {'tags': {'landuse': 'forest'}},
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'parking': {'tags': {'amenity': 'parking', 'highway': 'pedestrian', 'man_made': 'pier'}}
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},
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# drawing_kwargs:
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# Reference a name previously defined in the 'layers' argument and specify matplotlib parameters to draw it
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drawing_kwargs = {
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'background': {'fc': '#F2F4CB', 'ec': '#dadbc1', 'hatch': 'ooo...', 'zorder': -1},
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'perimeter': {'fc': '#F2F4CB', 'ec': '#dadbc1', 'lw': 0, 'hatch': 'ooo...', 'zorder': 0},
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'green': {'fc': '#D0F1BF', 'ec': '#2F3737', 'lw': 1, 'zorder': 1},
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'forest': {'fc': '#64B96A', 'ec': '#2F3737', 'lw': 1, 'zorder': 1},
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'water': {'fc': '#a1e3ff', 'ec': '#2F3737', 'hatch': 'ooo...', 'hatch_c': '#85c9e6', 'lw': 1, 'zorder': 2},
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'parking': {'fc': '#F2F4CB', 'ec': '#2F3737', 'lw': 1, 'zorder': 3},
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'streets': {'fc': '#2F3737', 'ec': '#475657', 'alpha': 1, 'lw': 0, 'zorder': 3},
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'building': {'palette': ['#FFC857', '#E9724C', '#C5283D'], 'ec': '#2F3737', 'lw': .5, 'zorder': 4},
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}
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)
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```
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## Gallery:
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### Barcelona:
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### Heerhugowaard:
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### Barra da Tijuca:
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### Porto Alegre:
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