WKTPlot

Wrapper around the Bokeh library for plotting well-known-text strings and shapely geometries!

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Installation

pip install wktplot

Description

The well-known-text standard is very common for working with and representing geospatial data, however it is painful to visualize them programatically. The Shapely library extends the functionality of the well-known-text standard with a rich assortment of geometry objects and operations, but it doesn't make it any easier to visualize.

WKTPlot is a library provides an easy-to-use API for visualizing well-known-text strings and shapely objects programatically. This library wraps around the Bokeh library, which is a powerful plotting library for generating interactive visualizations. Bokeh also provides a rich assortment of stylizing options which are all usable through WKTPlot's add_shape method.

Basic Usage

from shapely.geometry import Polygon
from wktplot import WKTPlot

# Create plot object
plot = WKTPlot(title="My first plot!", save_dir="/path/to/directory")

# Define shapes either through well-known-text (WKT) string, or shapely object
shape_1 = "POINT (30 10)"
shape_2 = Polygon([[30, 10], [40, 40], [20, 40], [10, 20], [30, 10]])

# Add shapes to the plot
plot.add_shape(shape_1, fill_color="green", line_width=3)
plot.add_shape(shape_2, fill_color="cyan", fill_alpha=0.7)

# Save the plot to disk [/path/to/directory/my_first_plot.html]
plot.save()

Supported datatypes

WKTPlot supports majority of shapely objects including:

Point
MultiPoint
LineString
MultiLineString
LinearRing
Polygon
MultiPolygon
GeometryCollection

Advanced Usage

Example for plotting from shapefile. Shapefile is of California's county boundaries from here.

import shapefile  # pyshp module

from random import randrange
from shapely.geometry import Polygon
from wktplot import WKTPlot

def get_rand_color():
    return f"#{randrange(0, 0xffffff):0>6x}"

plot = WKTPlot(title="California Counties", save_dir="~/scratch")
with shapefile.Reader("~/scratch/CA_Counties_TIGER2016.shp") as shp:
    for shape in shp.shapes():
        p = Polygon(shape.points)
        plot.add_shape(p, fill_color=get_rand_color())
plot.save()

Which will result in this output:

Future Plans

Add native support for visualizing GeoDataframes and shapefiles.
Make web view more interactive.

rsmith013/WKTPlot