prettymaps.plot(your_query)

import prettymaps

plot = prettymaps.plot("Stad van de Zon, Heerhugowaard, Netherlands")

plot = prettymaps.plot(
    "Stad van de Zon, Heerhugowaard, Netherlands",
    preset = "minimal"
)

prettymaps.presets()

prettymaps.preset("default")

plot = prettymaps.plot(
    # Your query. Example: "Porto Alegre" or (-30.0324999, -51.2303767) (GPS coords)
    your_query,
    # Dict of OpenStreetMap Layers to plot. Example:
    # {"building": {"tags": {"building": True}}, "water": {"tags": {"natural": "water"}}}
    # Check the /presets folder for more examples
    layers,
    # Dict of style parameters for matplotlib. Example:
    # {"building": {"palette": ["#f00","#0f0","#00f"], "edge_color": "#333"}}
    style,
    # Preset to load. Options include:
    # ["default", "minimal", "macao", "tijuca"]
    preset,
    # Save current parameters to a preset file.
    # Example: "my-preset" will save to "presets/my-preset.json"
    save_preset,
    # Whether to update loaded preset with additional provided parameters. Boolean
    update_preset,
    # Plot with circular boundary. Boolean
    circle,
    # Plot area radius. Float
    radius,
    # Dilate the boundary by this amount. Float
    dilate
)

@dataclass
class Plot:
    # A dictionary of GeoDataFrames (one for each plot layer)
    geodataframes: Dict[str, gp.GeoDataFrame]
    # A matplotlib figure
    fig: matplotlib.figure.Figure
    # A matplotlib axis object
    ax: matplotlib.axes.Axes

plot = prettymaps.plot(
    "Praça Ferreira do Amaral, Macau",
    circle = True,
    radius = 1100,
    layers = {
        "green": {
            "tags": {
                "landuse": "grass",
                "natural": ["island", "wood"],
                "leisure": "park"
            }
        },
        "forest": {
            "tags": {
                "landuse": "forest"
            }
        },
        "water": {
            "tags": {
                "natural": ["water", "bay"]
            }
        },
        "parking": {
            "tags": {
                "amenity": "parking",
                "highway": "pedestrian",
                "man_made": "pier"
            }
        },
        "streets": {
            "width": {
                "motorway": 5,
                "trunk": 5,
                "primary": 4.5,
                "secondary": 4,
                "tertiary": 3.5,
                "residential": 3,
            }
        },
        "building": {
            "tags": {"building": True},
        },
    },
    style = {
        "background": {
            "fc": "#F2F4CB",
            "ec": "#dadbc1",
            "hatch": "ooo...",
        },
        "perimeter": {
            "fc": "#F2F4CB",
            "ec": "#dadbc1",
            "lw": 0,
            "hatch": "ooo...",
        },
        "green": {
            "fc": "#D0F1BF",
            "ec": "#2F3737",
            "lw": 1,
        },
        "forest": {
            "fc": "#64B96A",
            "ec": "#2F3737",
            "lw": 1,
        },
        "water": {
            "fc": "#a1e3ff",
            "ec": "#2F3737",
            "hatch": "ooo...",
            "hatch_c": "#85c9e6",
            "lw": 1,
        },
        "parking": {
            "fc": "#F2F4CB",
            "ec": "#2F3737",
            "lw": 1,
        },
        "streets": {
            "fc": "#2F3737",
            "ec": "#475657",
            "alpha": 1,
            "lw": 0,
        },
        "building": {
            "palette": [
                "#FFC857",
                "#E9724C",
                "#C5283D"
            ],
            "ec": "#2F3737",
            "lw": 0.5,
        }
    }
)

radius = False

plot = prettymaps.plot(
    "Bom Fim, Porto Alegre, Brasil", radius = False,
)

# Run prettymaps in show = False mode (we"re only interested in obtaining the GeoDataFrames)
plot = prettymaps.plot("Centro Histórico, Porto Alegre", show = False)
plot.geodataframes["building"]

plot.geodataframes["building"][
        plot.geodataframes["building"].name == "Catedral Metropolitana Nossa Senhora Mãe de Deus"
].geometry[0]

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")

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()

plot = prettymaps.plot(
    (41.39491,2.17557),
    mode = "plotter",
    layers = dict(perimeter = {}),
    preset = "barcelona-plotter",
    scale_x = .6,
    scale_y = -.6,
)

plot = prettymaps.plot(
    # City name
    "Barra da Tijuca",
    dilate = 0,
    figsize = (22,10),
    preset = "tijuca",
)

plot = prettymaps.plot(
    "Stad van de Zon, Heerhugowaard, Netherlands",
    preset = "heerhugowaard",
)

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")

# 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())

# 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)
)