A django library that generates SLD documents from geographic models.
- django Required for models and spatial fields.
- python-sld Required for reading and generating SLD XML files.
- pysal Required for classification algorithms.
To install these requirements, you may use pip to install these packages (except for django) with this command:
> sudo pip install -r requirements.txt
> easy_install django-sld OR > pip install django-sld
This library implements a single module named "generator" that contains all the methods of interacting with the classification algorithms. Assuming that you have a geographic model in geodjango, you may classify your distribution with by constructing a queryset, and feeding it to the generator.
Assuming you have a spatial model named MySpatialModel, with a data field of population, you can classify all your data into 10 quantile classes with:
from djsld import generator qs = MySpatialModel.objects.all() sld = generator.as_quantiles(qs, 'population', 10)
You may also any queryset to generate classes, such as a filtered queryset:
qs = MySpatialModel.objects.filter(owner__name = 'David') sld = generator.as_quantiles(qs, 'population', 10)
If your spatial model has a different geometry column name other than 'geom', you may specify that field as the geofield keyword:
sld = generator.as_quantiles(qs, 'population', 10, geofield='state')
The data field may also be distantly related to the queryset in question. For this example, assume that MySpatialModel has a foreign key to a model named Route, and that the data value you would like to classify is a field of the Route model:
sld = generater.as_quantiles(qs, 'route__traffic', 10)
If you have any problems, questions, or comments, please visit the django-sld project on github: https://github.com/dzwarg/django-sld/