def remove_identical_sindex(geosrs: gpd.GeoSeries,
snap_threshold: float) -> gpd.GeoSeries:
"""
Remove stacked nodes by using a search buffer the size of snap_threshold.
"""
geosrs_reset = geosrs.reset_index(inplace=False, drop=True)
assert isinstance(geosrs_reset, gpd.GeoSeries)
geosrs = geosrs_reset
spatial_index = geosrs.sindex
identical_idxs = []
point: Point
for idx, point in enumerate(geosrs.geometry.values):
if idx in identical_idxs:
continue
# point = point.buffer(snap_threshold) if snap_threshold != 0 else point
p_candidate_idxs = (
# list(spatial_index.intersection(point.buffer(snap_threshold).bounds))
spatial_index_intersection(
spatial_index=spatial_index,
coordinates=geom_bounds(
safe_buffer(geom=point, radius=snap_threshold)),
) if snap_threshold != 0 else list(
spatial_index.intersection(point.coords[0])))
p_candidate_idxs.remove(idx)
p_candidates = geosrs.iloc[p_candidate_idxs]
inter = p_candidates.distance(point) < snap_threshold
colliding = inter.loc[inter]
if len(colliding) > 0:
index_to_list = colliding.index.to_list()
assert len(index_to_list) > 0
assert all(isinstance(i, int) for i in index_to_list)
identical_idxs.extend(index_to_list)
geosrs_dropped = geosrs.drop(identical_idxs)
assert isinstance(geosrs_dropped, gpd.GeoSeries)
return geosrs_dropped
def estimate_censoring(self, ) -> float:
"""
Estimate the amount of censoring as area float value.
Censoring is caused by e.g. vegetation.
Returns np.nan if no ``censoring_area`` is passed by the user into
``Network`` creation or if the passed GeoDataFrame is empty.
"""
# Either censoring_area is passed directly or its passed in Network
# creation. Otherwise raise ValueError.
if self.censoring_area is None:
raise ValueError(
"Expected censoring_area as an argument or initialized"
f" as Network (name:{self.name}) attribute.")
if not isinstance(self.censoring_area, gpd.GeoDataFrame):
raise TypeError(
"Expected censoring_area to be of type gpd.GeoDataFrame."
f" Got type={type(self.censoring_area)}")
if self.censoring_area.empty:
return np.nan
# Determine bounds of Network.area_gdf
network_area_bounds = total_bounds(self.area_gdf)
# Use spatial index to filter censoring polygons that are not near the
# network
sindex = pygeos_spatial_index(self.censoring_area)
index_intersection = spatial_index_intersection(
spatial_index=sindex, coordinates=network_area_bounds)
candidate_idxs = list(
index_intersection if index_intersection is not None else [])
if len(candidate_idxs) == 0:
return 0.0
candidates = self.censoring_area.iloc[candidate_idxs]
# Clip the censoring areas with the network area and calculate the area
# sum of leftover area.
clipped = gpd.clip(candidates, self.area_gdf)
if not isinstance(clipped, (gpd.GeoDataFrame, gpd.GeoSeries)):
vals = type(clipped), clipped
raise TypeError(
f"Expected that clipped is of geopandas data type. Got: {vals}."
)
censoring_value = clipped.area.sum()
unpacked_value = numpy_to_python_type(censoring_value)
assert isinstance(unpacked_value, float)
assert unpacked_value >= 0.0
return unpacked_value
def determine_trace_candidates(
geom: LineString,
idx: int,
traces: gpd.GeoDataFrame,
spatial_index: Optional[PyGEOSSTRTreeIndex],
) -> gpd.GeoSeries:
"""
Determine potentially intersecting traces with spatial index.
"""
if spatial_index is None:
logging.error("Expected spatial_index not be None.")
return gpd.GeoSeries()
assert isinstance(traces, (gpd.GeoSeries, gpd.GeoDataFrame))
assert isinstance(spatial_index, PyGEOSSTRTreeIndex)
candidate_idxs = spatial_index_intersection(spatial_index, geom_bounds(geom))
candidate_idxs.remove(idx)
candidate_traces: gpd.GeoSeries = traces.geometry.iloc[candidate_idxs]
candidate_traces = candidate_traces.loc[ # type: ignore
[isinstance(geom, LineString) for geom in candidate_traces.geometry.values]
]
return candidate_traces
def populate_sample_cell(
sample_cell: Polygon,
sample_cell_area: float,
traces_sindex: PyGEOSSTRTreeIndex,
traces: gpd.GeoDataFrame,
nodes: gpd.GeoDataFrame,
snap_threshold: float,
resolve_branches_and_nodes: bool,
) -> Dict[str, float]:
"""
Take a single grid polygon and populate it with parameters.
Mauldon determination requires that E-nodes are defined for
every single sample circle. If correct Mauldon values are
wanted `resolve_branches_and_nodes` must be passed as True.
This will result in much longer analysis time.
"""
_centroid = sample_cell.centroid
if not isinstance(_centroid, Point):
raise TypeError("Expected Point centroid.")
centroid = _centroid
sample_circle = safe_buffer(centroid, np.sqrt(sample_cell_area) * 1.5)
sample_circle_area = sample_circle.area
assert sample_circle_area > 0
# Choose geometries that are either within the sample_circle or
# intersect it
# Use spatial indexing to filter to only spatially relevant traces,
# traces and nodes
trace_candidates_idx = spatial_index_intersection(
traces_sindex, geom_bounds(sample_circle))
trace_candidates = traces.iloc[trace_candidates_idx]
assert isinstance(trace_candidates, gpd.GeoDataFrame)
if len(trace_candidates) == 0:
return determine_topology_parameters(
trace_length_array=np.array([]),
node_counts=determine_node_type_counts(np.array([]),
branches_defined=True),
area=sample_circle_area,
)
if resolve_branches_and_nodes:
# Solve branches and nodes for each cell if wanted
# Only way to make sure Mauldon parameters are correct
_, nodes = branches_and_nodes(
traces=trace_candidates,
areas=gpd.GeoSeries([sample_circle], crs=traces.crs),
snap_threshold=snap_threshold,
)
# node_candidates_idx = list(nodes_sindex.intersection(sample_circle.bounds))
node_candidates_idx = spatial_index_intersection(
spatial_index=pygeos_spatial_index(nodes),
coordinates=geom_bounds(sample_circle),
)
node_candidates = nodes.iloc[node_candidates_idx]
# Crop traces to sample circle
# First check if any geometries intersect
# If not: sample_features is an empty GeoDataFrame
if any(
trace_candidate.intersects(sample_circle)
for trace_candidate in trace_candidates.geometry.values):
sample_traces = crop_to_target_areas(
traces=trace_candidates,
areas=gpd.GeoSeries([sample_circle]),
is_filtered=True,
keep_column_data=False,
)
else:
sample_traces = traces.iloc[0:0]
if any(node.intersects(sample_circle) for node in nodes.geometry.values):
# if any(nodes.intersects(sample_circle)):
# TODO: Is node clipping stable?
sample_nodes = gpd.clip(node_candidates, sample_circle)
assert sample_nodes is not None
assert all(
isinstance(val, Point) for val in sample_nodes.geometry.values)
else:
sample_nodes = nodes.iloc[0:0]
assert isinstance(sample_nodes, gpd.GeoDataFrame)
assert isinstance(sample_traces, gpd.GeoDataFrame)
sample_node_type_values = sample_nodes[CLASS_COLUMN].values
assert isinstance(sample_node_type_values, np.ndarray)
node_counts = determine_node_type_counts(sample_node_type_values,
branches_defined=True)
topology_parameters = determine_topology_parameters(
trace_length_array=sample_traces.geometry.length.values,
node_counts=node_counts,
area=sample_circle_area,
correct_mauldon=resolve_branches_and_nodes,
)
return topology_parameters
def choose_geometries(sindex, sample_circle, geometries):
candidates_idx = spatial_index_intersection(sindex,
geom_bounds(sample_circle))
candidates = geometries.iloc[candidates_idx]
assert isinstance(candidates, gpd.GeoDataFrame)
return candidates
def get_branch_identities(
branches: gpd.GeoSeries,
nodes: gpd.GeoSeries,
node_identities: list,
snap_threshold: float,
) -> List[str]:
"""
Determine the types of branches for a GeoSeries of branches.
i.e. C-C, C-I or I-I, + (C-E, E-E, I-E)
>>> branches = gpd.GeoSeries(
... [
... LineString([(1, 1), (2, 2)]),
... LineString([(2, 2), (3, 3)]),
... LineString([(3, 0), (2, 2)]),
... LineString([(2, 2), (-2, 5)]),
... ]
... )
>>> nodes = gpd.GeoSeries(
... [
... Point(2, 2),
... Point(1, 1),
... Point(3, 3),
... Point(3, 0),
... Point(-2, 5),
... ]
... )
>>> node_identities = ["X", "I", "I", "I", "E"]
>>> snap_threshold = 0.001
>>> get_branch_identities(branches, nodes, node_identities, snap_threshold)
['C - I', 'C - I', 'C - I', 'C - E']
"""
assert len(nodes) == len(node_identities)
node_spatial_index = pygeos_spatial_index(nodes)
branch_identities = []
for branch in branches.geometry.values:
assert isinstance(branch, LineString)
node_candidate_idxs = spatial_index_intersection(
spatial_index=node_spatial_index, coordinates=geom_bounds(branch))
# node_candidate_idxs = list(node_spatial_index.intersection(branch.bounds))
node_candidates = nodes.iloc[node_candidate_idxs]
node_candidate_types = [
node_identities[i] for i in node_candidate_idxs
]
# Use distance instead of two polygon buffers
inter = [
dist < snap_threshold for dist in node_candidates.distance(
MultiPoint(list(get_trace_endpoints(branch)))).values
]
assert len(inter) == len(node_candidates)
# nodes_that_intersect = node_candidates.loc[inter]
nodes_that_intersect_types = list(compress(node_candidate_types,
inter))
number_of_E_nodes = sum(
[inter_id == E_node for inter_id in nodes_that_intersect_types])
number_of_I_nodes = sum(
[inter_id == I_node for inter_id in nodes_that_intersect_types])
number_of_XY_nodes = sum([
inter_id in [X_node, Y_node]
for inter_id in nodes_that_intersect_types
])
branch_identities.append(
determine_branch_identity(number_of_I_nodes, number_of_XY_nodes,
number_of_E_nodes))
return branch_identities
def determine_proximal_traces(
traces: Union[gpd.GeoSeries, gpd.GeoDataFrame],
buffer_value: float,
azimuth_tolerance: float,
) -> gpd.GeoDataFrame:
"""
Determine proximal traces.
Takes an input of GeoSeries or GeoDataFrame
of LineString geometries and returns a GeoDataFrame with a new
column `Merge` which has values of True or False depending on if
nearby proximal traces were found.
E.g.
>>> lines = [
... LineString([(0, 0), (0, 3)]),
... LineString([(1, 0), (1, 3)]),
... LineString([(5, 0), (5, 3)]),
... LineString([(0, 0), (-3, -3)]),
... ]
>>> traces = gpd.GeoDataFrame({"geometry": lines})
>>> buffer_value = 1.1
>>> azimuth_tolerance = 10
>>> determine_proximal_traces(traces, buffer_value, azimuth_tolerance)
geometry Merge
0 LINESTRING (0.00000 0.00000, 0.00000 3.00000) True
1 LINESTRING (1.00000 0.00000, 1.00000 3.00000) True
2 LINESTRING (5.00000 0.00000, 5.00000 3.00000) False
3 LINESTRING (0.00000 0.00000, -3.00000 -3.00000) False
"""
assert isinstance(traces, (gpd.GeoSeries, gpd.GeoDataFrame))
if isinstance(traces, gpd.GeoSeries):
traces_as_gdf: gpd.GeoDataFrame = gpd.GeoDataFrame(geometry=traces)
else:
traces_as_gdf = traces
traces_as_gdf.reset_index(inplace=True, drop=True)
spatial_index = pygeos_spatial_index(traces_as_gdf)
trace: LineString
proximal_traces: List[int] = []
for idx, trace in enumerate(traces_as_gdf.geometry.values):
candidate_idxs = spatial_index_intersection(
spatial_index, geom_bounds(safe_buffer(trace, buffer_value * 5)))
candidate_idxs.remove(idx)
candidate_traces: Union[
gpd.GeoSeries,
gpd.GeoDataFrame] = traces_as_gdf.iloc[candidate_idxs]
candidate_traces = candidate_traces.loc[ # type: ignore
[
is_within_buffer_distance(trace, other, buffer_value) and
is_similar_azimuth(trace, other, tolerance=azimuth_tolerance)
for other in candidate_traces.geometry.values
]]
if len(candidate_traces) > 0:
proximal_traces.extend([
i for i in list(candidate_traces.index) + [idx] # type: ignore
if i not in proximal_traces
])
traces_as_gdf[MERGE_COLUMN] = [
i in proximal_traces for i in traces_as_gdf.index
]
return traces_as_gdf