wktplot 2.3.1

Well-known-text and shapely object visualiation library

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.

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Supported datatypes

WKTPlot supports the majority of well-known-text primitives, including:

• Point

• MultiPoint

• LineString

• MultiLineString

• LinearRing

• Polygon

• MultiPolygon

• GeometryCollection

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Basic Usage

from shapely.geometry import LineString

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

line_string = LineString([[45, 5], [30, -7], [40, 10]])

polygon = "POLYGON ((35 10, 45 45, 15 40, 10 20, 35 10),(20 30, 35 35, 30 20, 20 30))"

points = "MULTIPOINT (17 11, 13 0, 22 -5, 25 7)"



# Add shapes to the plot with style args

plot.add_shape(line_string, line_color="firebrick", line_alpha=0.5, line_width=20)

plot.add_shape(polygon, fill_color="#6495ED", fill_alpha=0.5)

plot.add_shape(points, fill_color=(50, 205, 50, 0.25), fill_alpha=0.7, size=30)



# Save plot to disk [/path/to/directory/my_first_plot.html]

plot.save()

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OpenStreetMaps

WKTPlot now supports the ability to integrate with OpenStreetMaps. Shape coordinates will be projected to the Mercator coordinate system, which appear to distort shape proportions compared to standard geometric projection.

# Import OpenStreetMaps plotting class

from wktplot.plots.osm import OpenStreetMapsPlot



# Create plot object just like standard WKTPlot class

plot = OpenStreetMapsPlot("Open Street Map Plot", save_dir="/path/to/directory")



shape = "POLYGON ((35 10, 45 45, 15 40, 10 20, 35 10), (20 30, 35 35, 30 20, 20 30))"

plot.add_shape(shape, fill_alpha=0.5, fill_color="firebrick")



plot.save()

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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:

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Development

Bugs / Feature Requests

Plese open an Issue in Github with any bugs found or feature requests, and follow the prompts so that developers can reproduce or implement the necessary changes.

Local development

Development of this model is centered around the Makefile. All you need to spin up a working environment to build and test this module can be done with the Makefile.

1. Clone the repository onto your machine.

   git clone https://github.com/FuzzFoundation/WKTPlot.git
   

2. Create the Python virtaul environment and install module's development / testing dependencies. This will also install WKTPlot in develop mode.

   make develop
   

3. Activate virtual environment

   source venv/bin/activate
   

4. Run linting and unittests.

   make test
   

5. When you want to remove the virtual environment and clean up after development.

   deactivate
   
   make clean  # This will remove all generated files, like .coverage and build/
   
   make sparkling  # This will remove all generate files and the virtual env.