base_network: use GeoSeries.voronoi_polygons instead of custom solution (#1172)
* base_network: use GeoSeries.voronoi_polygons instead of custom solution * [pre-commit.ci] auto fixes from pre-commit.com hooks for more information, see https://pre-commit.ci * base_network: move voronoi calculations into separate function * [pre-commit.ci] auto fixes from pre-commit.com hooks for more information, see https://pre-commit.ci * base_network: fix typo in function voronoi() * base_network: refine voronoi function * add release note [no ci] --------- Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>
This commit is contained in:
Fabian Neumann
GitHub
parent
eab315291e
commit
0470f119cf
@ -55,6 +55,9 @@ Upcoming Release
|
||||
excess power) at every AC bus. This can speed up the solving process as the
|
||||
curtailment decision is aggregated into a single generator per region.
|
||||
|
||||
* In :mod:`base_network`, replace own voronoi polygon calculation function with
|
||||
Geopandas `gdf.voronoi_polygons` method.
|
||||
|
||||
PyPSA-Eur 0.11.0 (25th May 2024)
|
||||
=====================================
|
||||
|
||||
|
||||
@ -72,6 +72,7 @@ Creates the network topology from an ENTSO-E map extract, and create Voronoi sha
|
||||
"""
|
||||
|
||||
import logging
|
||||
import warnings
|
||||
from itertools import product
|
||||
|
||||
import geopandas as gpd
|
||||
@ -85,9 +86,9 @@ import shapely.wkt
|
||||
import yaml
|
||||
from _helpers import REGION_COLS, configure_logging, get_snapshots, set_scenario_config
|
||||
from packaging.version import Version, parse
|
||||
from scipy import spatial
|
||||
from scipy.sparse import csgraph
|
||||
from shapely.geometry import LineString, Point, Polygon
|
||||
from scipy.spatial import KDTree
|
||||
from shapely.geometry import LineString, Point
|
||||
|
||||
PD_GE_2_2 = parse(pd.__version__) >= Version("2.2")
|
||||
|
||||
@ -118,7 +119,7 @@ def _find_closest_links(links, new_links, distance_upper_bound=1.5):
|
||||
querycoords = np.vstack(
|
||||
[new_links[["x1", "y1", "x2", "y2"]], new_links[["x2", "y2", "x1", "y1"]]]
|
||||
)
|
||||
tree = spatial.KDTree(treecoords)
|
||||
tree = KDTree(treecoords)
|
||||
dist, ind = tree.query(querycoords, distance_upper_bound=distance_upper_bound)
|
||||
found_b = ind < len(links)
|
||||
found_i = np.arange(len(new_links) * 2)[found_b] % len(new_links)
|
||||
@ -273,7 +274,7 @@ def _add_links_from_tyndp(buses, links, links_tyndp, europe_shape):
|
||||
return buses, links
|
||||
|
||||
tree_buses = buses.query("carrier=='AC'")
|
||||
tree = spatial.KDTree(tree_buses[["x", "y"]])
|
||||
tree = KDTree(tree_buses[["x", "y"]])
|
||||
_, ind0 = tree.query(links_tyndp[["x1", "y1"]])
|
||||
ind0_b = ind0 < len(tree_buses)
|
||||
links_tyndp.loc[ind0_b, "bus0"] = tree_buses.index[ind0[ind0_b]]
|
||||
@ -788,59 +789,26 @@ def base_network(
|
||||
return n
|
||||
|
||||
|
||||
def voronoi_partition_pts(points, outline):
|
||||
def voronoi(points, outline, crs=4326):
|
||||
"""
|
||||
Compute the polygons of a voronoi partition of `points` within the polygon
|
||||
`outline`. Taken from
|
||||
https://github.com/FRESNA/vresutils/blob/master/vresutils/graph.py.
|
||||
|
||||
Attributes
|
||||
----------
|
||||
points : Nx2 - ndarray[dtype=float]
|
||||
outline : Polygon
|
||||
Returns
|
||||
-------
|
||||
polygons : N - ndarray[dtype=Polygon|MultiPolygon]
|
||||
Create Voronoi polygons from a set of points within an outline.
|
||||
"""
|
||||
points = np.asarray(points)
|
||||
pts = gpd.GeoSeries(
|
||||
gpd.points_from_xy(points.x, points.y),
|
||||
index=points.index,
|
||||
crs=crs,
|
||||
)
|
||||
voronoi = pts.voronoi_polygons(extend_to=outline).clip(outline)
|
||||
|
||||
if len(points) == 1:
|
||||
polygons = [outline]
|
||||
else:
|
||||
xmin, ymin = np.amin(points, axis=0)
|
||||
xmax, ymax = np.amax(points, axis=0)
|
||||
xspan = xmax - xmin
|
||||
yspan = ymax - ymin
|
||||
# can be removed with shapely 2.1 where order is preserved
|
||||
# https://github.com/shapely/shapely/issues/2020
|
||||
with warnings.catch_warnings():
|
||||
warnings.filterwarnings("ignore", category=UserWarning)
|
||||
pts = gpd.GeoDataFrame(geometry=pts)
|
||||
voronoi = gpd.GeoDataFrame(geometry=voronoi)
|
||||
joined = gpd.sjoin_nearest(pts, voronoi, how="right")
|
||||
|
||||
# to avoid any network positions outside all Voronoi cells, append
|
||||
# the corners of a rectangle framing these points
|
||||
vor = spatial.Voronoi(
|
||||
np.vstack(
|
||||
(
|
||||
points,
|
||||
[
|
||||
[xmin - 3.0 * xspan, ymin - 3.0 * yspan],
|
||||
[xmin - 3.0 * xspan, ymax + 3.0 * yspan],
|
||||
[xmax + 3.0 * xspan, ymin - 3.0 * yspan],
|
||||
[xmax + 3.0 * xspan, ymax + 3.0 * yspan],
|
||||
],
|
||||
)
|
||||
)
|
||||
)
|
||||
|
||||
polygons = []
|
||||
for i in range(len(points)):
|
||||
poly = Polygon(vor.vertices[vor.regions[vor.point_region[i]]])
|
||||
|
||||
if not poly.is_valid:
|
||||
poly = poly.buffer(0)
|
||||
|
||||
with np.errstate(invalid="ignore"):
|
||||
poly = poly.intersection(outline)
|
||||
|
||||
polygons.append(poly)
|
||||
|
||||
return polygons
|
||||
return joined.dissolve(by="Bus").squeeze()
|
||||
|
||||
|
||||
def build_bus_shapes(n, country_shapes, offshore_shapes, countries):
|
||||
@ -870,9 +838,7 @@ def build_bus_shapes(n, country_shapes, offshore_shapes, countries):
|
||||
"name": onshore_locs.index,
|
||||
"x": onshore_locs["x"],
|
||||
"y": onshore_locs["y"],
|
||||
"geometry": voronoi_partition_pts(
|
||||
onshore_locs.values, onshore_shape
|
||||
),
|
||||
"geometry": voronoi(onshore_locs, onshore_shape),
|
||||
"country": country,
|
||||
},
|
||||
crs=n.crs,
|
||||
@ -888,7 +854,7 @@ def build_bus_shapes(n, country_shapes, offshore_shapes, countries):
|
||||
"name": offshore_locs.index,
|
||||
"x": offshore_locs["x"],
|
||||
"y": offshore_locs["y"],
|
||||
"geometry": voronoi_partition_pts(offshore_locs.values, offshore_shape),
|
||||
"geometry": voronoi(offshore_locs, offshore_shape),
|
||||
"country": country,
|
||||
},
|
||||
crs=n.crs,
|
||||
|
||||
Loading…
Reference in New Issue
Block a user