Reusable Python utilities to work with geospatial regions.
Project description
pyregeon
Reusable Python utilities to work with geospatial regions.
pyregeon stands for Python Region Geospatial utilities
Usage
The main idea of pyregeon is to make it as easy as possible to associate any Python object to a geospatial region. The first approach is with the object-oriented RegionMixin. We can set the region property attribute to any object that inherits from RegionMixin, e.g.:
from pyregeon import RegionMixin
class MyAnalysisCase(..., RegionMixin):
# optionally define a `crs` or `CRS` attribute
pass
analysis = MyAnalysisCase(...)
analysis.region = "Lausanne, Switzerland"
The region property setter accepts the following values:
- A string with a place name (Nominatim query) to geocode (requires osmnx).
- A sequence with the west, south, east and north bounds.
- A geometric object, e.g., shapely geometry, or a sequence of geometric objects (polygon or multi-polygon). In such a case, the value is passed as the
dataargument of the GeoSeries constructor, and needs to be in the same CRS as the one provided through thecrsargument. - A geopandas geo-series or geo-data frame.
- A filename or URL, a file-like object opened in binary ('rb') mode, or a Path object that will be passed to
geopandas.read_file.
Then, the processed region attribute can be accessed as a geo-data frame:
analysis.region
| geometry | bbox_west | bbox_south | bbox_east | bbox_north | place_id | osm_type | osm_id | lat | lon | class | type | place_rank | importance | addresstype | name | display_name | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | MULTIPOLYGON (((6.58387 46.55187, 6.58632 46.5... | 6.583868 | 46.454873 | 6.720814 | 46.602577 | 83952532 | relation | 1685018 | 46.521827 | 6.632702 | boundary | administrative | 16 | 0.6941 | city | Lausanne | Lausanne, District de Lausanne, Vaud, Switzerland |
Note that when setting region to a naive geometry, i.e, without associated coordinate reference system (CRS), the setter will try to retrieve a CRS by looking whether the object has a crs or CRS attribute (in that order). In absence of these, a ValueError will be raised.
With the region attribute properly set, we can also generate regular grids using the generate_regular_grid_gser method:
import contextily as cx
res = 0.05
ax = analysis.generate_regular_grid_gser(res).plot(alpha=0.5, edgecolor="black")
cx.add_basemap(ax, crs=analysis.region.crs, attribution=False)
Alternatively, it is possible to use the standalone pyregeon.generate_regular_grid_gser function without any class by prepending a geo-series with the region as first positional argument (and optionally providing the crs keyword argument if the provided geo-series is naive).
See the API documentation for more details or the multiurbanpy library for an example use case of pyregeon.
Installation
pip install pyregeon
Acknowledgements
- This package was created with the martibosch/cookiecutter-geopy-package project template.
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