kopia lustrzana https://github.com/marceloprates/prettymaps
1047 wiersze
31 KiB
Markdown
1047 wiersze
31 KiB
Markdown
# prettymaps
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A Python package to draw maps with customizable styles from [OpenStreetMap](https://www.openstreetmap.org/#map=12/11.0733/106.3078) data. Created using the [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) packages.
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> **This work is [licensed](LICENSE) 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)**
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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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# Installation
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### Install using with [pip](https://pypi.org):
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```
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pip install prettymaps
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```
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# [Google Colab Demo](https://colab.research.google.com/github/marceloprates/prettymaps/blob/master/notebooks/examples.ipynb)
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# Note about crediting and NFTs:
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- Please keep the printed message on the figures crediting my repository and OpenStreetMap ([mandatory by their license](https://www.openstreetmap.org/copyright)).
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- I am personally **against** NFTs for their [environmental impact](https://earth.org/nfts-environmental-impact/), the fact that they're a [giant money-laundering pyramid scheme](https://twitter.com/smdiehl/status/1445795667826208770) and the structural incentives they create for [theft](https://twitter.com/NFTtheft) in the open source and generative art communities.
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- **I do not authorize in any way this project to be used for selling NFTs**, although I cannot legally enforce it. **Respect the creator**.
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- The [AeternaCivitas](https://magiceden.io/marketplace/aeterna_civitas) and [geoartnft](https://www.geo-nft.com/) projects have used this work to sell NFTs and refused to credit it. See how they reacted after being exposed: [AeternaCivitas](etc/NFT_theft_AeternaCivitas.jpg), [geoartnft](etc/NFT_theft_geoart.jpg).
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- **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**.
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# As seen on [Hacker News](https://web.archive.org/web/20210825160918/https://news.ycombinator.com/news):
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# [prettymaps subreddit](https://www.reddit.com/r/prettymaps_/)
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# Tutorial
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Plotting with prettymaps is very simple. Run:
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```python
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prettymaps.plot(your_query)
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```
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**your_query** can be:
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1. An address (Example: "Porto Alegre"),
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2. Latitude / Longitude coordinates (Example: (-30.0324999, -51.2303767))
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3. A custom boundary in GeoDataFrame format
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```python
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import prettymaps
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plot = prettymaps.plot('Stad van de Zon, Heerhugowaard, Netherlands')
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```
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You can also choose from different "presets" (parameter combinations saved in JSON files)
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See below an example using the "minimal" preset
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```python
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plot = prettymaps.plot(
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'Stad van de Zon, Heerhugowaard, Netherlands',
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preset = 'minimal'
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)
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```
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Run
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```python
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prettymaps.presets()
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```
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to list all available presets:
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<div>
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<table border="1" class="dataframe">
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<thead>
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<tr style="text-align: right;">
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<th></th>
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<th>preset</th>
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<th>params</th>
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</tr>
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</thead>
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<tbody>
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<tr>
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<th>0</th>
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<td>barcelona</td>
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<td>{'layers': {'perimeter': {'circle': False}, 's...</td>
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</tr>
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<tr>
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<th>1</th>
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<td>barcelona-plotter</td>
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<td>{'layers': {'streets': {'width': {'primary': 5...</td>
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</tr>
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<tr>
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<th>2</th>
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<td>cb-bf-f</td>
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<td>{'layers': {'streets': {'width': {'trunk': 6, ...</td>
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</tr>
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<tr>
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<th>3</th>
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<td>default</td>
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<td>{'layers': {'perimeter': {}, 'streets': {'widt...</td>
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</tr>
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<tr>
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<th>4</th>
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<td>heerhugowaard</td>
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<td>{'layers': {'perimeter': {}, 'streets': {'widt...</td>
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</tr>
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<tr>
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<th>5</th>
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<td>macao</td>
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<td>{'layers': {'perimeter': {}, 'streets': {'cust...</td>
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</tr>
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<tr>
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<th>6</th>
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<td>minimal</td>
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<td>{'layers': {'perimeter': {}, 'streets': {'widt...</td>
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</tr>
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<tr>
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<th>7</th>
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<td>tijuca</td>
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<td>{'layers': {'perimeter': {}, 'streets': {'widt...</td>
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</tr>
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</tbody>
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</table>
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</div>
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To examine a specific preset, run:
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```python
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prettymaps.preset('default')
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```
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| | layers | style | circle | radius |
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|:-----------|:----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|:------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|:----------------|:---------------|
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| perimeter | {}<br> | fill: false<br>lw: 0<br>zorder: 0<br> | null<br>...<br> | 500<br>...<br> |
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| streets | width:<br> cycleway: 3.5<br> footway: 1<br> motorway: 5<br> pedestrian: 2<br> primary: 4.5<br> residential: 3<br> secondary: 4<br> service: 2<br> tertiary: 3.5<br> trunk: 5<br> unclassified: 2<br> | alpha: 1<br>ec: '<span style="background-color:#475657; color:#fff">#475657</span>'<br>fc: '<span style="background-color:#2F3737; color:#fff">#2F3737</span>'<br>lw: 0<br>zorder: 4<br> | | |
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| building | tags:<br> building: true<br> landuse: construction<br> | ec: '<span style="background-color:#2F3737; color:#fff">#2F3737</span>'<br>lw: 0.5<br>palette:<br>- '<span style="background-color:#433633; color:#fff">#433633</span>'<br>- '<span style="background-color:#FF5E5B; color:#000">#FF5E5B</span>'<br>zorder: 5<br> | | |
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| water | tags:<br> natural:<br> - water<br> - bay<br> | ec: '<span style="background-color:#2F3737; color:#fff">#2F3737</span>'<br>fc: '<span style="background-color:#a8e1e6; color:#000">#a8e1e6</span>'<br>hatch: ooo...<br>hatch_c: '<span style="background-color:#9bc3d4; color:#000">#9bc3d4</span>'<br>lw: 1<br>zorder: 3<br> | | |
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| forest | tags:<br> landuse: forest<br> | ec: '<span style="background-color:#2F3737; color:#fff">#2F3737</span>'<br>fc: '<span style="background-color:#64B96A; color:#000">#64B96A</span>'<br>lw: 1<br>zorder: 2<br> | | |
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| green | tags:<br> landuse:<br> - grass<br> - orchard<br> leisure: park<br> natural:<br> - island<br> - wood<br> | ec: '<span style="background-color:#2F3737; color:#fff">#2F3737</span>'<br>fc: '<span style="background-color:#8BB174; color:#000">#8BB174</span>'<br>hatch: ooo...<br>hatch_c: '<span style="background-color:#A7C497; color:#000">#A7C497</span>'<br>lw: 1<br>zorder: 1<br> | | |
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| beach | tags:<br> natural: beach<br> | ec: '<span style="background-color:#2F3737; color:#fff">#2F3737</span>'<br>fc: '<span style="background-color:#FCE19C; color:#000">#FCE19C</span>'<br>hatch: ooo...<br>hatch_c: '<span style="background-color:#d4d196; color:#000">#d4d196</span>'<br>lw: 1<br>zorder: 3<br> | | |
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| parking | tags:<br> amenity: parking<br> highway: pedestrian<br> man_made: pier<br> | ec: '<span style="background-color:#2F3737; color:#fff">#2F3737</span>'<br>fc: '<span style="background-color:#F2F4CB; color:#000">#F2F4CB</span>'<br>lw: 1<br>zorder: 3<br> | | |
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| background | .nan<br>...<br> | fc: '<span style="background-color:#F2F4CB; color:#000">#F2F4CB</span>'<br>zorder: -1<br> | | |
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Insted of using the default configuration you can customize several parameters. The most important are:
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- layers: A dictionary of OpenStreetMap layers to fetch.
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- Keys: layer names (arbitrary)
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- Values: dicts representing OpenStreetMap queries
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- style: Matplotlib style parameters
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- Keys: layer names (the same as before)
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- Values: dicts representing Matplotlib style parameters
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```python
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plot = prettymaps.plot(
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# Your query. Example: "Porto Alegre" or (-30.0324999, -51.2303767) (GPS coords)
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your_query,
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# Dict of OpenStreetMap Layers to plot. Example:
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# {'building': {'tags': {'building': True}}, 'water': {'tags': {'natural': 'water'}}}
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# Check the /presets folder for more examples
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layers,
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# Dict of style parameters for matplotlib. Example:
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# {'building': {'palette': ['#f00','#0f0','#00f'], 'edge_color': '#333'}}
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style,
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# Preset to load. Options include:
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# ['default', 'minimal', 'macao', 'tijuca']
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preset,
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# Save current parameters to a preset file.
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# Example: "my-preset" will save to "presets/my-preset.json"
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save_preset,
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# Whether to update loaded preset with additional provided parameters. Boolean
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update_preset,
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# Plot with circular boundary. Boolean
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circle,
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# Plot area radius. Float
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radius,
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# Dilate the boundary by this amount. Float
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dilate
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)
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```
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**plot** is a python dataclass containing:
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```python
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@dataclass
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class Plot:
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# A dictionary of GeoDataFrames (one for each plot layer)
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geodataframes: Dict[str, gp.GeoDataFrame]
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# A matplotlib figure
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fig: matplotlib.figure.Figure
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# A matplotlib axis object
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ax: matplotlib.axes.Axes
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```
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Here's an example of running prettymaps.plot() with customized parameters:
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```python
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plot = prettymaps.plot(
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'Praça Ferreira do Amaral, Macau',
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circle = True,
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radius = 1100,
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layers = {
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"green": {
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"tags": {
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"landuse": "grass",
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"natural": ["island", "wood"],
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"leisure": "park"
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}
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},
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"forest": {
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"tags": {
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"landuse": "forest"
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}
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},
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"water": {
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"tags": {
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"natural": ["water", "bay"]
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}
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},
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"parking": {
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"tags": {
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"amenity": "parking",
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"highway": "pedestrian",
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"man_made": "pier"
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}
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},
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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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}
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},
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"building": {
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"tags": {"building": True},
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},
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},
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style = {
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"background": {
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"fc": "#F2F4CB",
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"ec": "#dadbc1",
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"hatch": "ooo...",
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},
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"perimeter": {
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"fc": "#F2F4CB",
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"ec": "#dadbc1",
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"lw": 0,
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"hatch": "ooo...",
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},
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"green": {
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"fc": "#D0F1BF",
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"ec": "#2F3737",
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"lw": 1,
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},
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"forest": {
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"fc": "#64B96A",
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"ec": "#2F3737",
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"lw": 1,
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},
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"water": {
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"fc": "#a1e3ff",
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"ec": "#2F3737",
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"hatch": "ooo...",
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"hatch_c": "#85c9e6",
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"lw": 1,
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},
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"parking": {
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"fc": "#F2F4CB",
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"ec": "#2F3737",
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"lw": 1,
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},
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"streets": {
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"fc": "#2F3737",
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"ec": "#475657",
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"alpha": 1,
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"lw": 0,
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},
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"building": {
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"palette": [
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"#FFC857",
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"#E9724C",
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"#C5283D"
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],
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"ec": "#2F3737",
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"lw": 0.5,
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}
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}
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)
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```
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In order to plot an entire region and not just a rectangular or circular area, set
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```python
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radius = False
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```
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```python
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plot = prettymaps.plot(
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'Bom Fim, Porto Alegre, Brasil', radius = False,
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)
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```
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You can access layers's GeoDataFrames directly like this:
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```python
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# Run prettymaps in show = False mode (we're only interested in obtaining the GeoDataFrames)
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plot = prettymaps.plot('Centro Histórico, Porto Alegre', show = False)
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plot.geodataframes['building']
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```
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<div>
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<table border="1" class="dataframe">
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<thead>
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<tr style="text-align: right;">
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<th></th>
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<th></th>
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<th>addr:housenumber</th>
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<th>addr:street</th>
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<th>amenity</th>
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<th>operator</th>
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<th>website</th>
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<th>geometry</th>
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<th>addr:postcode</th>
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<th>name</th>
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<th>office</th>
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<th>opening_hours</th>
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<th>...</th>
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<th>contact:phone</th>
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<th>bus</th>
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<th>public_transport</th>
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<th>source:name</th>
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<th>government</th>
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<th>ways</th>
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<th>name:fr</th>
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<th>type</th>
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<th>building:part</th>
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<th>architect</th>
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</tr>
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<tr>
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<th>element_type</th>
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<th>osmid</th>
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<th></th>
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<th></th>
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<th></th>
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<th></th>
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<th></th>
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<th></th>
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<th></th>
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<th></th>
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<th></th>
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<th></th>
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<th></th>
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<th></th>
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<th></th>
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<th></th>
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<th></th>
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<th></th>
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<th></th>
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<th></th>
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<th></th>
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<th></th>
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<th></th>
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</tr>
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</thead>
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<tbody>
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<tr>
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<th>node</th>
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<th>2407915698</th>
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<td>820</td>
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<td>Rua Washington Luiz</td>
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<td>NaN</td>
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<td>NaN</td>
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<td>NaN</td>
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<td>POINT (-51.23212 -30.03670)</td>
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<td>90010-460</td>
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<td>NaN</td>
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<td>NaN</td>
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<td>NaN</td>
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<td>...</td>
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<td>NaN</td>
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||
<td>NaN</td>
|
||
<td>NaN</td>
|
||
<td>NaN</td>
|
||
<td>NaN</td>
|
||
<td>NaN</td>
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||
<td>NaN</td>
|
||
<td>NaN</td>
|
||
<td>NaN</td>
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||
<td>NaN</td>
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||
</tr>
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<tr>
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<th rowspan="4" valign="top">way</th>
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<th>126665330</th>
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<td>387</td>
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<td>Rua dos Andradas</td>
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<td>place_of_worship</td>
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<td>NaN</td>
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<td>NaN</td>
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<td>POLYGON ((-51.23518 -30.03275, -51.23512 -30.0...</td>
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<td>90020-002</td>
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<td>Igreja Nossa Senhora das Dores</td>
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<td>NaN</td>
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||
<td>NaN</td>
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||
<td>...</td>
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||
<td>NaN</td>
|
||
<td>NaN</td>
|
||
<td>NaN</td>
|
||
<td>NaN</td>
|
||
<td>NaN</td>
|
||
<td>NaN</td>
|
||
<td>NaN</td>
|
||
<td>NaN</td>
|
||
<td>NaN</td>
|
||
<td>NaN</td>
|
||
</tr>
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||
<tr>
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||
<th>126665331</th>
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||
<td>1001</td>
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||
<td>Rua dos Andradas</td>
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||
<td>NaN</td>
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||
<td>NaN</td>
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||
<td>http://www.ruadapraiashopping.com.br</td>
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<td>POLYGON ((-51.23167 -30.03066, -51.23160 -30.0...</td>
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||
<td>90020-015</td>
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||
<td>Rua da Praia Shopping</td>
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||
<td>NaN</td>
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||
<td>Mo-Fr 09:00-21:00; Sa 08:00-20:00</td>
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||
<td>...</td>
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||
<td>NaN</td>
|
||
<td>NaN</td>
|
||
<td>NaN</td>
|
||
<td>NaN</td>
|
||
<td>NaN</td>
|
||
<td>NaN</td>
|
||
<td>NaN</td>
|
||
<td>NaN</td>
|
||
<td>NaN</td>
|
||
<td>NaN</td>
|
||
</tr>
|
||
<tr>
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||
<th>129176990</th>
|
||
<td>1020</td>
|
||
<td>Rua 7 de Setembro</td>
|
||
<td>NaN</td>
|
||
<td>NaN</td>
|
||
<td>http://www.memorial.rs.gov.br</td>
|
||
<td>POLYGON ((-51.23117 -30.02891, -51.23120 -30.0...</td>
|
||
<td>90010-191</td>
|
||
<td>Memorial do Rio Grande do Sul</td>
|
||
<td>NaN</td>
|
||
<td>Tu-Sa 10:00-18:00</td>
|
||
<td>...</td>
|
||
<td>NaN</td>
|
||
<td>NaN</td>
|
||
<td>NaN</td>
|
||
<td>NaN</td>
|
||
<td>NaN</td>
|
||
<td>NaN</td>
|
||
<td>NaN</td>
|
||
<td>NaN</td>
|
||
<td>NaN</td>
|
||
<td>NaN</td>
|
||
</tr>
|
||
<tr>
|
||
<th>129176991</th>
|
||
<td>NaN</td>
|
||
<td>Praça da Alfândega</td>
|
||
<td>NaN</td>
|
||
<td>NaN</td>
|
||
<td>http://www.margs.rs.gov.br</td>
|
||
<td>POLYGON ((-51.23153 -30.02914, -51.23156 -30.0...</td>
|
||
<td>90010-150</td>
|
||
<td>Museu de Arte do Rio Grande do Sul</td>
|
||
<td>NaN</td>
|
||
<td>Tu-Su 10:00-19:00</td>
|
||
<td>...</td>
|
||
<td>NaN</td>
|
||
<td>NaN</td>
|
||
<td>NaN</td>
|
||
<td>NaN</td>
|
||
<td>NaN</td>
|
||
<td>NaN</td>
|
||
<td>NaN</td>
|
||
<td>NaN</td>
|
||
<td>NaN</td>
|
||
<td>NaN</td>
|
||
</tr>
|
||
<tr>
|
||
<th>...</th>
|
||
<th>...</th>
|
||
<td>...</td>
|
||
<td>...</td>
|
||
<td>...</td>
|
||
<td>...</td>
|
||
<td>...</td>
|
||
<td>...</td>
|
||
<td>...</td>
|
||
<td>...</td>
|
||
<td>...</td>
|
||
<td>...</td>
|
||
<td>...</td>
|
||
<td>...</td>
|
||
<td>...</td>
|
||
<td>...</td>
|
||
<td>...</td>
|
||
<td>...</td>
|
||
<td>...</td>
|
||
<td>...</td>
|
||
<td>...</td>
|
||
<td>...</td>
|
||
<td>...</td>
|
||
</tr>
|
||
<tr>
|
||
<th rowspan="5" valign="top">relation</th>
|
||
<th>6760281</th>
|
||
<td>NaN</td>
|
||
<td>NaN</td>
|
||
<td>NaN</td>
|
||
<td>NaN</td>
|
||
<td>NaN</td>
|
||
<td>POLYGON ((-51.23238 -30.03337, -51.23223 -30.0...</td>
|
||
<td>NaN</td>
|
||
<td>NaN</td>
|
||
<td>NaN</td>
|
||
<td>NaN</td>
|
||
<td>...</td>
|
||
<td>NaN</td>
|
||
<td>NaN</td>
|
||
<td>NaN</td>
|
||
<td>NaN</td>
|
||
<td>NaN</td>
|
||
<td>[457506887, 457506886]</td>
|
||
<td>NaN</td>
|
||
<td>multipolygon</td>
|
||
<td>NaN</td>
|
||
<td>NaN</td>
|
||
</tr>
|
||
<tr>
|
||
<th>6760282</th>
|
||
<td>NaN</td>
|
||
<td>NaN</td>
|
||
<td>NaN</td>
|
||
<td>NaN</td>
|
||
<td>NaN</td>
|
||
<td>POLYGON ((-51.23203 -30.03340, -51.23203 -30.0...</td>
|
||
<td>NaN</td>
|
||
<td>Atheneu Espírita Cruzeiro do Sul</td>
|
||
<td>NaN</td>
|
||
<td>NaN</td>
|
||
<td>...</td>
|
||
<td>NaN</td>
|
||
<td>NaN</td>
|
||
<td>NaN</td>
|
||
<td>NaN</td>
|
||
<td>NaN</td>
|
||
<td>[457506875, 457506889, 457506888]</td>
|
||
<td>NaN</td>
|
||
<td>multipolygon</td>
|
||
<td>NaN</td>
|
||
<td>NaN</td>
|
||
</tr>
|
||
<tr>
|
||
<th>6760283</th>
|
||
<td>NaN</td>
|
||
<td>NaN</td>
|
||
<td>NaN</td>
|
||
<td>NaN</td>
|
||
<td>NaN</td>
|
||
<td>POLYGON ((-51.23284 -30.03367, -51.23288 -30.0...</td>
|
||
<td>NaN</td>
|
||
<td>Palacete Chaves</td>
|
||
<td>NaN</td>
|
||
<td>NaN</td>
|
||
<td>...</td>
|
||
<td>NaN</td>
|
||
<td>NaN</td>
|
||
<td>NaN</td>
|
||
<td>NaN</td>
|
||
<td>NaN</td>
|
||
<td>[457506897, 457506896]</td>
|
||
<td>NaN</td>
|
||
<td>multipolygon</td>
|
||
<td>NaN</td>
|
||
<td>Theodor Wiederspahn</td>
|
||
</tr>
|
||
<tr>
|
||
<th>6760284</th>
|
||
<td>NaN</td>
|
||
<td>NaN</td>
|
||
<td>NaN</td>
|
||
<td>NaN</td>
|
||
<td>NaN</td>
|
||
<td>POLYGON ((-51.23499 -30.03412, -51.23498 -30.0...</td>
|
||
<td>NaN</td>
|
||
<td>NaN</td>
|
||
<td>NaN</td>
|
||
<td>NaN</td>
|
||
<td>...</td>
|
||
<td>NaN</td>
|
||
<td>NaN</td>
|
||
<td>NaN</td>
|
||
<td>NaN</td>
|
||
<td>NaN</td>
|
||
<td>[457506910, 457506913]</td>
|
||
<td>NaN</td>
|
||
<td>multipolygon</td>
|
||
<td>NaN</td>
|
||
<td>NaN</td>
|
||
</tr>
|
||
<tr>
|
||
<th>14393526</th>
|
||
<td>1044</td>
|
||
<td>Rua Siqueira Campos</td>
|
||
<td>NaN</td>
|
||
<td>NaN</td>
|
||
<td>https://www.sefaz.rs.gov.br</td>
|
||
<td>POLYGON ((-51.23125 -30.02813, -51.23128 -30.0...</td>
|
||
<td>NaN</td>
|
||
<td>Secretaria Estadual da Fazenda</td>
|
||
<td>NaN</td>
|
||
<td>NaN</td>
|
||
<td>...</td>
|
||
<td>NaN</td>
|
||
<td>NaN</td>
|
||
<td>NaN</td>
|
||
<td>NaN</td>
|
||
<td>NaN</td>
|
||
<td>[236213286, 1081974882]</td>
|
||
<td>NaN</td>
|
||
<td>multipolygon</td>
|
||
<td>NaN</td>
|
||
<td>NaN</td>
|
||
</tr>
|
||
</tbody>
|
||
</table>
|
||
<p>2423 rows × 105 columns</p>
|
||
</div>
|
||
|
||
|
||
|
||
Search a building by name and display it:
|
||
|
||
|
||
```python
|
||
plot.geodataframes['building'][
|
||
plot.geodataframes['building'].name == 'Catedral Metropolitana Nossa Senhora Mãe de Deus'
|
||
].geometry[0]
|
||
```
|
||
|
||
|
||
|
||
|
||
|
||
|
||
|
||
|
||
|
||
|
||
Plot mosaic of building footprints
|
||
|
||
|
||
```python
|
||
import numpy as np
|
||
import osmnx as ox
|
||
from matplotlib import pyplot as plt
|
||
from matplotlib.font_manager import FontProperties
|
||
|
||
# Run prettymaps in show = False mode (we're only interested in obtaining the GeoDataFrames)
|
||
plot = prettymaps.plot('Porto Alegre', show = False)
|
||
# Get list of buildings from plot's geodataframes dict
|
||
buildings = plot.geodataframes['building']
|
||
# Project from lat / long
|
||
buildings = ox.project_gdf(buildings)
|
||
buildings = [b for b in buildings.geometry if b.area > 0]
|
||
|
||
# Draw Matplotlib mosaic of n x n building footprints
|
||
n = 6
|
||
fig,axes = plt.subplots(n,n, figsize = (7,6))
|
||
# Set background color
|
||
fig.patch.set_facecolor('#5cc0eb')
|
||
# Figure title
|
||
fig.suptitle(
|
||
'Buildings of Porto Alegre',
|
||
size = 25,
|
||
color = '#fff',
|
||
fontproperties = FontProperties(fname = '../assets/PermanentMarker-Regular.ttf')
|
||
)
|
||
# Draw each building footprint on a separate axis
|
||
for ax,building in zip(np.concatenate(axes),buildings):
|
||
ax.plot(*building.exterior.xy, c = '#ffffff')
|
||
ax.autoscale(); ax.axis('off'); ax.axis('equal')
|
||
```
|
||
|
||
|
||
|
||
|
||
|
||
|
||
|
||
Access plot.ax or plot.fig to add new elements to the matplotlib plot:
|
||
|
||
|
||
```python
|
||
from matplotlib.font_manager import FontProperties
|
||
|
||
plot = prettymaps.plot(
|
||
(41.39491,2.17557),
|
||
preset = 'barcelona',
|
||
)
|
||
|
||
# Change background color
|
||
plot.fig.patch.set_facecolor('#F2F4CB')
|
||
# Add title
|
||
plot.ax.set_title(
|
||
'Barcelona',
|
||
fontproperties = FontProperties(
|
||
fname = '../assets/PermanentMarker-Regular.ttf',
|
||
size = 50
|
||
)
|
||
)
|
||
|
||
plt.show()
|
||
```
|
||
|
||
|
||
|
||
|
||
|
||
|
||
|
||
Use **plotter** mode to export a pen plotter-compatible SVG (thanks to abey79's amazing [vsketch](https://github.com/abey79/vsketch) library)
|
||
|
||
|
||
```python
|
||
plot = prettymaps.plot(
|
||
(41.39491,2.17557),
|
||
mode = 'plotter',
|
||
layers = dict(perimeter = {}),
|
||
preset = 'barcelona-plotter',
|
||
scale_x = .6,
|
||
scale_y = -.6,
|
||
)
|
||
```
|
||
|
||
|
||
|
||
|
||
|
||
|
||
|
||
Some other examples
|
||
|
||
|
||
```python
|
||
plot = prettymaps.plot(
|
||
# City name
|
||
'Barra da Tijuca',
|
||
dilate = 0,
|
||
figsize = (22,10),
|
||
preset = 'tijuca',
|
||
)
|
||
```
|
||
|
||
|
||
|
||
|
||
|
||
|
||
|
||
|
||
```python
|
||
plot = prettymaps.plot(
|
||
'Stad van de Zon, Heerhugowaard, Netherlands',
|
||
preset = 'heerhugowaard',
|
||
)
|
||
```
|
||
|
||
|
||
|
||
|
||
|
||
|
||
|
||
Use prettymaps.create_preset() to create a preset:
|
||
|
||
|
||
```python
|
||
prettymaps.create_preset(
|
||
"my-preset",
|
||
layers = {
|
||
"building": {
|
||
"tags": {
|
||
"building": True,
|
||
"leisure": [
|
||
"track",
|
||
"pitch"
|
||
]
|
||
}
|
||
},
|
||
"streets": {
|
||
"width": {
|
||
"trunk": 6,
|
||
"primary": 6,
|
||
"secondary": 5,
|
||
"tertiary": 4,
|
||
"residential": 3.5,
|
||
"pedestrian": 3,
|
||
"footway": 3,
|
||
"path": 3
|
||
}
|
||
},
|
||
},
|
||
style = {
|
||
"perimeter": {
|
||
"fill": False,
|
||
"lw": 0,
|
||
"zorder": 0
|
||
},
|
||
"streets": {
|
||
"fc": "#F1E6D0",
|
||
"ec": "#2F3737",
|
||
"lw": 1.5,
|
||
"zorder": 3
|
||
},
|
||
"building": {
|
||
"palette": [
|
||
"#fff"
|
||
],
|
||
"ec": "#2F3737",
|
||
"lw": 1,
|
||
"zorder": 4
|
||
}
|
||
}
|
||
)
|
||
|
||
prettymaps.preset('my-preset')
|
||
```
|
||
|
||
|
||
| | layers | style | circle | radius | dilate |
|
||
|:----------|:--------------------------------------------------------------------------------------------------------------------------------------------------|:----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|:----------------|:----------------|:----------------|
|
||
| building | tags:<br> building: true<br> leisure:<br> - track<br> - pitch<br> | ec: '<span style="background-color:#2F3737; color:<span style="background-color:#fff; color:#000">#fff</span>">#2F3737</span>'<br>lw: 1<br>palette:<br>- '<span style="background-color:#fff; color:#000">#fff</span>'<br>zorder: 4<br> | null<br>...<br> | null<br>...<br> | null<br>...<br> |
|
||
| streets | width:<br> footway: 3<br> path: 3<br> pedestrian: 3<br> primary: 6<br> residential: 3.5<br> secondary: 5<br> tertiary: 4<br> trunk: 6<br> | ec: '<span style="background-color:#2F3737; color:#fff">#2F3737</span>'<br>fc: '<span style="background-color:#F1E6D0; color:#000">#F1E6D0</span>'<br>lw: 1.5<br>zorder: 3<br> | | | |
|
||
| perimeter | .nan<br>...<br> | fill: false<br>lw: 0<br>zorder: 0<br> | | | |
|
||
|
||
|
||
Use prettymaps.delete_preset() to delete presets:
|
||
|
||
|
||
```python
|
||
# Show presets before deletion
|
||
print('Before deletion:')
|
||
display(prettymaps.presets())
|
||
# Delete 'my-preset'
|
||
prettymaps.delete_preset('my-preset')
|
||
# Show presets after deletion
|
||
print('After deletion:')
|
||
display(prettymaps.presets())
|
||
```
|
||
|
||
Before deletion:
|
||
|
||
|
||
|
||
<div>
|
||
<table border="1" class="dataframe">
|
||
<thead>
|
||
<tr style="text-align: right;">
|
||
<th></th>
|
||
<th>preset</th>
|
||
<th>params</th>
|
||
</tr>
|
||
</thead>
|
||
<tbody>
|
||
<tr>
|
||
<th>0</th>
|
||
<td>barcelona</td>
|
||
<td>{'layers': {'perimeter': {'circle': False}, 's...</td>
|
||
</tr>
|
||
<tr>
|
||
<th>1</th>
|
||
<td>barcelona-plotter</td>
|
||
<td>{'layers': {'streets': {'width': {'primary': 5...</td>
|
||
</tr>
|
||
<tr>
|
||
<th>2</th>
|
||
<td>cb-bf-f</td>
|
||
<td>{'layers': {'streets': {'width': {'trunk': 6, ...</td>
|
||
</tr>
|
||
<tr>
|
||
<th>3</th>
|
||
<td>default</td>
|
||
<td>{'layers': {'perimeter': {}, 'streets': {'widt...</td>
|
||
</tr>
|
||
<tr>
|
||
<th>4</th>
|
||
<td>heerhugowaard</td>
|
||
<td>{'layers': {'perimeter': {}, 'streets': {'widt...</td>
|
||
</tr>
|
||
<tr>
|
||
<th>5</th>
|
||
<td>macao</td>
|
||
<td>{'layers': {'perimeter': {}, 'streets': {'cust...</td>
|
||
</tr>
|
||
<tr>
|
||
<th>6</th>
|
||
<td>minimal</td>
|
||
<td>{'layers': {'perimeter': {}, 'streets': {'widt...</td>
|
||
</tr>
|
||
<tr>
|
||
<th>7</th>
|
||
<td>my-preset</td>
|
||
<td>{'layers': {'building': {'tags': {'building': ...</td>
|
||
</tr>
|
||
<tr>
|
||
<th>8</th>
|
||
<td>tijuca</td>
|
||
<td>{'layers': {'perimeter': {}, 'streets': {'widt...</td>
|
||
</tr>
|
||
</tbody>
|
||
</table>
|
||
</div>
|
||
|
||
|
||
After deletion:
|
||
|
||
|
||
|
||
<div>
|
||
<table border="1" class="dataframe">
|
||
<thead>
|
||
<tr style="text-align: right;">
|
||
<th></th>
|
||
<th>preset</th>
|
||
<th>params</th>
|
||
</tr>
|
||
</thead>
|
||
<tbody>
|
||
<tr>
|
||
<th>0</th>
|
||
<td>barcelona</td>
|
||
<td>{'layers': {'perimeter': {'circle': False}, 's...</td>
|
||
</tr>
|
||
<tr>
|
||
<th>1</th>
|
||
<td>barcelona-plotter</td>
|
||
<td>{'layers': {'streets': {'width': {'primary': 5...</td>
|
||
</tr>
|
||
<tr>
|
||
<th>2</th>
|
||
<td>cb-bf-f</td>
|
||
<td>{'layers': {'streets': {'width': {'trunk': 6, ...</td>
|
||
</tr>
|
||
<tr>
|
||
<th>3</th>
|
||
<td>default</td>
|
||
<td>{'layers': {'perimeter': {}, 'streets': {'widt...</td>
|
||
</tr>
|
||
<tr>
|
||
<th>4</th>
|
||
<td>heerhugowaard</td>
|
||
<td>{'layers': {'perimeter': {}, 'streets': {'widt...</td>
|
||
</tr>
|
||
<tr>
|
||
<th>5</th>
|
||
<td>macao</td>
|
||
<td>{'layers': {'perimeter': {}, 'streets': {'cust...</td>
|
||
</tr>
|
||
<tr>
|
||
<th>6</th>
|
||
<td>minimal</td>
|
||
<td>{'layers': {'perimeter': {}, 'streets': {'widt...</td>
|
||
</tr>
|
||
<tr>
|
||
<th>7</th>
|
||
<td>tijuca</td>
|
||
<td>{'layers': {'perimeter': {}, 'streets': {'widt...</td>
|
||
</tr>
|
||
</tbody>
|
||
</table>
|
||
</div>
|
||
|
||
|
||
Use **prettymaps.multiplot** and **prettymaps.Subplot** to draw multiple regions on the same canvas
|
||
|
||
|
||
```python
|
||
# Draw several regions on the same canvas
|
||
prettymaps.multiplot(
|
||
prettymaps.Subplot(
|
||
'Cidade Baixa, Porto Alegre',
|
||
style={'building': {'palette': ['#49392C', '#E1F2FE', '#98D2EB']}}
|
||
),
|
||
prettymaps.Subplot(
|
||
'Bom Fim, Porto Alegre',
|
||
style={'building': {'palette': ['#BA2D0B', '#D5F2E3', '#73BA9B', '#F79D5C']}}
|
||
),
|
||
prettymaps.Subplot(
|
||
'Farroupilha, Porto Alegre',
|
||
style={'building': {'palette': ['#EEE4E1', '#E7D8C9', '#E6BEAE']}}
|
||
),
|
||
# Load a global preset
|
||
preset='cb-bf-f',
|
||
# Figure size
|
||
figsize=(12, 12)
|
||
)
|
||
|
||
```
|
||
|
||
|
||
|
||
|
||
|
||
|