PlotVisualizer¶

Render a PlotReport as an interactive HTML map or a static PNG/JPG image.

Optional dependency — not included in the base install.
pip install plot-finder[viz]
This installs folium (interactive maps) and Pillow (static images).

Quick Start¶

from plot_finder import Plot, PlotAnalyzer, PlotReporter
from plot_finder.visualizer import PlotVisualizer

plot = Plot(plot_id="141201_1.0001.6509")
analyzer = PlotAnalyzer(plot, radius=2000)
report = PlotReporter(analyzer).report()

viz = PlotVisualizer(report)

viz.save("map.html")   # interactive map
viz.save("map.png")    # static image

Constructor¶

PlotVisualizer(report, *, colors=None, plot_color="red")

Parameter	Type	Default	Description
`report`	`PlotReport`	required	Report to visualize
`colors`	`dict[str, str] \\| None`	`None`	Override category colours
`plot_color`	`str`	`"red"`	Centre marker and radius circle colour

Default Category Colours¶

Category	Colour	Icon (HTML)
`education`	blue	graduation-cap
`finance`	green	university
`transport`	orange	bus
`infrastructure`	purple	building
`parks`	darkgreen	tree
`water`	cadetblue	tint

Override any of them:

viz = PlotVisualizer(report, colors={
    "education": "#1f77b4",
    "parks": "#2ca02c",
    "transport": "darkred",
})

Methods¶

`map() -> folium.Map`¶

Returns an interactive folium map with:

Red centre marker with plot ID popup
Dashed circle showing search radius
Colour-coded markers per category (as FeatureGroups)
LayerControl to toggle categories on/off
Popups with name, kind, distance, walk/bike/car time

m = viz.map()
m.save("map.html")

# Or use in Jupyter
m

Requires: folium

`image(width=800, height=600, zoom=None, marker_radius=6) -> PIL.Image.Image`¶

Renders a static map image from OpenStreetMap tiles.

Parameter	Type	Default	Description
`width`	`int`	`800`	Image width in pixels
`height`	`int`	`600`	Image height in pixels
`zoom`	`int \\| None`	`None`	Zoom level (1–18). Auto-detected from radius if `None`
`marker_radius`	`int`	`6`	Size of place markers in pixels

img = viz.image(width=1200, height=800)
img.save("map.png")

# Custom zoom
img = viz.image(zoom=14)

# Bigger markers
img = viz.image(marker_radius=10)

The image contains:

OpenStreetMap base tiles
Circle outline showing search radius
Colour-coded dot markers per category
Larger centre marker for the plot

Requires: Pillow

`save(path)`¶

Auto-detects format by file extension:

Extension	Output
`.html`	Interactive folium map
`.png`	Static PNG image
`.jpg` / `.jpeg`	Static JPEG image

viz.save("map.html")   # folium
viz.save("map.png")    # PIL → PNG
viz.save("map.jpg")    # PIL → JPEG

Colour Reference¶

Colours accepted by image() (PIL) — any CSS colour name or hex string:

"red", "#FF0000", "darkgreen", "#2ca02c", "cornflowerblue"

Colours accepted by map() (folium icons) — limited set:

red, blue, green, purple, orange, darkred, darkblue,
darkgreen, cadetblue, darkpurple, pink, lightblue,
lightgreen, beige, white, lightgray, gray, black, lightred

For best results, use colours that work in both systems (named colours like red, blue, green, purple, orange, darkgreen).

Examples¶

Custom colours¶

viz = PlotVisualizer(
    report,
    colors={"education": "darkblue", "transport": "darkred"},
    plot_color="black",
)
viz.save("custom.png")

High-resolution image¶

img = viz.image(width=1920, height=1080, zoom=16, marker_radius=8)
img.save("hd.png")

Folium in Jupyter¶

viz.map()  # displays inline