Metadata-Version: 2.1
Name: wktplot
Version: 2.3.2
Summary: Well-known-text and shapely object visualiation library
Home-page: https://github.com/FuzzFoundation/WKTPlot
Author: Michael Simpson, Gerald Sornsen
Author-email: mikeysimpson4@gmail.com, gerald@sornsen.io
License: MIT
Keywords: well-known-text,shapely,bokeh,geo-spatial,visualization
Platform: any
Classifier: License :: OSI Approved :: MIT License
Classifier: Programming Language :: Python
Classifier: Programming Language :: Python :: 3.7
Classifier: Programming Language :: Python :: 3.8
Classifier: Programming Language :: Python :: 3.9
Classifier: Programming Language :: Python :: 3.10
Classifier: Natural Language :: English
Classifier: Operating System :: OS Independent
Classifier: Development Status :: 5 - Production/Stable
Classifier: Intended Audience :: Developers
Classifier: Topic :: Software Development :: Libraries
Requires-Python: >=3.7
Description-Content-Type: text/markdown
License-File: LICENSE
Requires-Dist: bokeh (==2.4.2)
Requires-Dist: jinja2 (==3.0.3)
Requires-Dist: markupsafe (==2.0.1)
Requires-Dist: numpy (==1.21.5)
Requires-Dist: packaging (==21.3)
Requires-Dist: pillow (==8.4.0)
Requires-Dist: pyparsing (==3.0.6)
Requires-Dist: pyyaml (==6.0)
Requires-Dist: shapely (>=1.8.1)
Requires-Dist: tornado (==6.1)
Requires-Dist: typing-extensions (==4.0.1)
Provides-Extra: test
Requires-Dist: flake8 (>=4.0.1) ; extra == 'test'
Requires-Dist: pytest (>=6.1.2) ; extra == 'test'
Requires-Dist: pytest-cov (>=2.10.1) ; extra == 'test'
Requires-Dist: pytest-mock (>=3.8.2) ; extra == 'test'

# WKTPlot

Wrapper around the [Bokeh](https://github.com/bokeh/bokeh) library for plotting well-known-text strings and shapely geometries!



## Badges

[![PyPi Python Versions](https://img.shields.io/pypi/pyversions/wktplot.svg)](https://pypi.org/project/wktplot/)

[![codecov](https://codecov.io/gh/FuzzFoundation/WKTPlot/branch/main/graph/badge.svg?token=E1BJVWQLRE)](https://codecov.io/gh/FuzzFoundation/WKTPlot)

[![Codacy Badge](https://app.codacy.com/project/badge/Grade/19fe4574645d492e8677c4b06152dd9d)](https://www.codacy.com/gh/FuzzFoundation/WKTPlot/dashboard?utm_source=github.com&amp;utm_medium=referral&amp;utm_content=FuzzFoundation/WKTPlot&amp;utm_campaign=Badge_Grade)



## Installation



```bash

pip install wktplot

```



## Description

The [well-known-text](https://en.wikipedia.org/wiki/Well-known_text_representation_of_geometry) standard is very common for working with and representing geospatial data, however it is painful to visualize them programatically. The [Shapely](https://github.com/shapely/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 that provides an easy-to-use API for visualizing well-known-text strings and shapely objects programatically. This library wraps around the [Bokeh](https://github.com/bokeh/bokeh) library, which is a powerful plotting library for generating interactive visualizations. Bokeh also provides a rich assortment of [stylizing options](https://docs.bokeh.org/en/latest/docs/user_guide/styling.html) which are all usable through WKTPlot's `add_shape` method.



---



### Supported datatypes

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

* Point

* MultiPoint

* LineString

* MultiLineString

* LinearRing

* Polygon

* MultiPolygon

* GeometryCollection



---



## Basic Usage

``` python

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()

```



![Output](https://i.imgur.com/aajbppI.png)



---

## 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.



If your shape data has already been projected, you can disable the Mercator calculation by setting the `disable_mercator` parameter when creating the plot object. See [Advanced Usage](#advanced-usage) for an example.

```python

# 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()

```

![Output](https://i.imgur.com/JdUDMh7.png)



---



## Advanced Usage

Example for plotting from shapefile. Shapefile is of California's county boundaries, download from [here](https://data.ca.gov/dataset/ca-geographic-boundaries).

```python

import shapefile  # pyshp module



from bokeh.palettes import Magma6

from pathlib import Path

from random import choice

from shapely.geometry import Polygon

from wktplot.plots.osm import OpenStreetMapsPlot





COUNTIES_PATH = Path("/path/to/CA_Counties_TIGER2016.shp")



# Create plot and disable mercator calculation

# because data has already been projected

plot = OpenStreetMapsPlot(

    title="California Counties 2016",

    height=1000,

    width=1000,

    disable_mercator=True,

)



# Read shapefile data points from file

with shapefile.Reader(COUNTIES_PATH) as shp:

    for shape in shp.shapes():

        plot.add_shape(

            shape=Polygon(shape.points),

            fill_color=choice(Magma6),

            fill_alpha=0.75,

        )



# Save plot to disk [./california_counties_2016.html]

plot.save()

```

Which will result in this output:

![CaliforniaCounties2016](https://i.imgur.com/lxac0JL.png)



---



## Development

### Bugs / Feature Requests

Please 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.

    ```sh

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

    ```

2. Create the Python virtual environment and install module's development / testing dependencies. This will also install WKTPlot in [develop mode](https://setuptools.pypa.io/en/latest/userguide/development_mode.html).

    ```sh

    make develop

    ```

3. Activate virtual environment

    ```sh

    source venv/bin/activate

    ```

4. Run linting and unittests.

    ```sh

    make test

    ```

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

    ```sh

    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.
