-
Notifications
You must be signed in to change notification settings - Fork 902
/
sindex.py
482 lines (409 loc) · 16.8 KB
/
sindex.py
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
198
199
200
201
202
203
204
205
206
207
208
209
210
211
212
213
214
215
216
217
218
219
220
221
222
223
224
225
226
227
228
229
230
231
232
233
234
235
236
237
238
239
240
241
242
243
244
245
246
247
248
249
250
251
252
253
254
255
256
257
258
259
260
261
262
263
264
265
266
267
268
269
270
271
272
273
274
275
276
277
278
279
280
281
282
283
284
285
286
287
288
289
290
291
292
293
294
295
296
297
298
299
300
301
302
303
304
305
306
307
308
309
310
311
312
313
314
315
316
317
318
319
320
321
322
323
324
325
326
327
328
329
330
331
332
333
334
335
336
337
338
339
340
341
342
343
344
345
346
347
348
349
350
351
352
353
354
355
356
357
358
359
360
361
362
363
364
365
366
367
368
369
370
371
372
373
374
375
376
377
378
379
380
381
382
383
384
385
386
387
388
389
390
391
392
393
394
395
396
397
398
399
400
401
402
403
404
405
406
407
408
409
410
411
412
413
414
415
416
417
418
419
420
421
422
423
424
425
426
427
428
429
430
431
432
433
434
435
436
437
438
439
440
441
442
443
444
445
446
447
448
449
450
451
452
453
454
455
456
457
458
459
460
461
462
463
464
465
466
467
468
469
470
471
472
473
474
475
476
477
478
479
480
481
482
import numpy as np
import shapely
from shapely.geometry.base import BaseGeometry
from . import array, geoseries
from . import _compat as compat
PREDICATES = {p.name for p in shapely.strtree.BinaryPredicate} | {None}
if compat.GEOS_GE_310:
PREDICATES.update(["dwithin"])
class SpatialIndex:
"""A simple wrapper around Shapely's STRTree.
Parameters
----------
geometry : np.array of Shapely geometries
Geometries from which to build the spatial index.
"""
def __init__(self, geometry):
# set empty geometries to None to avoid segfault on GEOS <= 3.6
# see:
# https://github.com/pygeos/pygeos/issues/146
# https://github.com/pygeos/pygeos/issues/147
non_empty = geometry.copy()
non_empty[shapely.is_empty(non_empty)] = None
# set empty geometries to None to maintain indexing
self._tree = shapely.STRtree(non_empty)
# store geometries, including empty geometries for user access
self.geometries = geometry.copy()
@property
def valid_query_predicates(self):
"""Returns valid predicates for the spatial index.
Returns
-------
set
Set of valid predicates for this spatial index.
Examples
--------
>>> from shapely.geometry import Point
>>> s = geopandas.GeoSeries([Point(0, 0), Point(1, 1)])
>>> s.sindex.valid_query_predicates # doctest: +SKIP
{None, "contains", "contains_properly", "covered_by", "covers", \
"crosses", "dwithin", "intersects", "overlaps", "touches", "within"}
"""
return PREDICATES
def query(self, geometry, predicate=None, sort=False, distance=None):
"""
Return the integer indices of all combinations of each input geometry
and tree geometries where the bounding box of each input geometry
intersects the bounding box of a tree geometry.
If the input geometry is a scalar, this returns an array of shape (n, ) with
the indices of the matching tree geometries. If the input geometry is an
array_like, this returns an array with shape (2,n) where the subarrays
correspond to the indices of the input geometries and indices of the
tree geometries associated with each. To generate an array of pairs of
input geometry index and tree geometry index, simply transpose the
result.
If a predicate is provided, the tree geometries are first queried based
on the bounding box of the input geometry and then are further filtered
to those that meet the predicate when comparing the input geometry to
the tree geometry: ``predicate(geometry, tree_geometry)``.
The 'dwithin' predicate requires GEOS >= 3.10.
Bounding boxes are limited to two dimensions and are axis-aligned
(equivalent to the ``bounds`` property of a geometry); any Z values
present in input geometries are ignored when querying the tree.
Any input geometry that is None or empty will never match geometries in
the tree.
Parameters
----------
geometry : shapely.Geometry or array-like of geometries \
(numpy.ndarray, GeoSeries, GeometryArray)
A single shapely geometry or array of geometries to query against
the spatial index. For array-like, accepts both GeoPandas geometry
iterables (GeoSeries, GeometryArray) or a numpy array of Shapely
geometries.
predicate : {None, "contains", "contains_properly", "covered_by", "covers", \
"crosses", "intersects", "overlaps", "touches", "within", "dwithin"}, optional
If predicate is provided, the input geometries are tested
using the predicate function against each item in the tree
whose extent intersects the envelope of the input geometry:
``predicate(input_geometry, tree_geometry)``.
If possible, prepared geometries are used to help speed up the
predicate operation.
sort : bool, default False
If True, the results will be sorted in ascending order. In case
of 2D array, the result is sorted lexicographically using the
geometries' indexes as the primary key and the sindex's indexes
as the secondary key.
If False, no additional sorting is applied (results are often
sorted but there is no guarantee).
distance : number or array_like, optional
Distances around each input geometry within which to query the tree for
the 'dwithin' predicate. If array_like, shape must be broadcastable to shape
of geometry. Required if ``predicate='dwithin'``.
Returns
-------
ndarray with shape (n,) if geometry is a scalar
Integer indices for matching geometries from the spatial index
tree geometries.
OR
ndarray with shape (2, n) if geometry is an array_like
The first subarray contains input geometry integer indices.
The second subarray contains tree geometry integer indices.
Examples
--------
>>> from shapely.geometry import Point, box
>>> s = geopandas.GeoSeries(geopandas.points_from_xy(range(10), range(10)))
>>> s
0 POINT (0 0)
1 POINT (1 1)
2 POINT (2 2)
3 POINT (3 3)
4 POINT (4 4)
5 POINT (5 5)
6 POINT (6 6)
7 POINT (7 7)
8 POINT (8 8)
9 POINT (9 9)
dtype: geometry
Querying the tree with a scalar geometry:
>>> s.sindex.query(box(1, 1, 3, 3))
array([1, 2, 3])
>>> s.sindex.query(box(1, 1, 3, 3), predicate="contains")
array([2])
Querying the tree with an array of geometries:
>>> s2 = geopandas.GeoSeries([box(2, 2, 4, 4), box(5, 5, 6, 6)])
>>> s2
0 POLYGON ((4 2, 4 4, 2 4, 2 2, 4 2))
1 POLYGON ((6 5, 6 6, 5 6, 5 5, 6 5))
dtype: geometry
>>> s.sindex.query(s2)
array([[0, 0, 0, 1, 1],
[2, 3, 4, 5, 6]])
>>> s.sindex.query(s2, predicate="contains")
array([[0],
[3]])
>>> s.sindex.query(box(1, 1, 3, 3), predicate="dwithin", distance=0)
array([1, 2, 3])
>>> s.sindex.query(box(1, 1, 3, 3), predicate="dwithin", distance=2)
array([0, 1, 2, 3, 4])
Notes
-----
In the context of a spatial join, input geometries are the "left"
geometries that determine the order of the results, and tree geometries
are "right" geometries that are joined against the left geometries. This
effectively performs an inner join, where only those combinations of
geometries that can be joined based on overlapping bounding boxes or
optional predicate are returned.
"""
if predicate not in self.valid_query_predicates:
if predicate == "dwithin":
raise ValueError("predicate = 'dwithin' requires GEOS >= 3.10.0")
raise ValueError(
"Got predicate='{}'; ".format(predicate)
+ "`predicate` must be one of {}".format(self.valid_query_predicates)
)
# distance argument requirement of predicate `dwithin`
# and only valid for predicate `dwithin`
kwargs = {}
if predicate == "dwithin":
if distance is None:
# the distance parameter is needed
raise ValueError(
"'distance' parameter is required for 'dwithin' predicate"
)
# add distance to kwargs
kwargs["distance"] = distance
elif distance is not None:
# distance parameter is invalid
raise ValueError(
"'distance' parameter is only supported in combination with "
"'dwithin' predicate"
)
geometry = self._as_geometry_array(geometry)
indices = self._tree.query(geometry, predicate=predicate, **kwargs)
if sort:
if indices.ndim == 1:
return np.sort(indices)
else:
# sort by first array (geometry) and then second (tree)
geo_idx, tree_idx = indices
sort_indexer = np.lexsort((tree_idx, geo_idx))
return np.vstack((geo_idx[sort_indexer], tree_idx[sort_indexer]))
return indices
@staticmethod
def _as_geometry_array(geometry):
"""Convert geometry into a numpy array of Shapely geometries.
Parameters
----------
geometry
An array-like of Shapely geometries, a GeoPandas GeoSeries/GeometryArray,
shapely.geometry or list of shapely geometries.
Returns
-------
np.ndarray
A numpy array of Shapely geometries.
"""
if isinstance(geometry, np.ndarray):
return array.from_shapely(geometry)._data
elif isinstance(geometry, geoseries.GeoSeries):
return geometry.values._data
elif isinstance(geometry, array.GeometryArray):
return geometry._data
elif isinstance(geometry, BaseGeometry):
return geometry
elif geometry is None:
return None
else:
return np.asarray(geometry)
def nearest(
self,
geometry,
return_all=True,
max_distance=None,
return_distance=False,
exclusive=False,
):
"""
Return the nearest geometry in the tree for each input geometry in
``geometry``.
If multiple tree geometries have the same distance from an input geometry,
multiple results will be returned for that input geometry by default.
Specify ``return_all=False`` to only get a single nearest geometry
(non-deterministic which nearest is returned).
In the context of a spatial join, input geometries are the "left"
geometries that determine the order of the results, and tree geometries
are "right" geometries that are joined against the left geometries.
If ``max_distance`` is not set, this will effectively be a left join
because every geometry in ``geometry`` will have a nearest geometry in
the tree. However, if ``max_distance`` is used, this becomes an
inner join, since some geometries in ``geometry`` may not have a match
in the tree.
For performance reasons, it is highly recommended that you set
the ``max_distance`` parameter.
Parameters
----------
geometry : {shapely.geometry, GeoSeries, GeometryArray, numpy.array of Shapely \
geometries}
A single shapely geometry, one of the GeoPandas geometry iterables
(GeoSeries, GeometryArray), or a numpy array of Shapely geometries to query
against the spatial index.
return_all : bool, default True
If there are multiple equidistant or intersecting nearest
geometries, return all those geometries instead of a single
nearest geometry.
max_distance : float, optional
Maximum distance within which to query for nearest items in tree.
Must be greater than 0. By default None, indicating no distance limit.
return_distance : bool, optional
If True, will return distances in addition to indexes. By default False
exclusive : bool, optional
if True, the nearest geometries that are equal to the input geometry
will not be returned. By default False. Requires Shapely >= 2.0.
Returns
-------
Indices or tuple of (indices, distances)
Indices is an ndarray of shape (2,n) and distances (if present) an
ndarray of shape (n).
The first subarray of indices contains input geometry indices.
The second subarray of indices contains tree geometry indices.
Examples
--------
>>> from shapely.geometry import Point, box
>>> s = geopandas.GeoSeries(geopandas.points_from_xy(range(10), range(10)))
>>> s.head()
0 POINT (0 0)
1 POINT (1 1)
2 POINT (2 2)
3 POINT (3 3)
4 POINT (4 4)
dtype: geometry
>>> s.sindex.nearest(Point(1, 1))
array([[0],
[1]])
>>> s.sindex.nearest([box(4.9, 4.9, 5.1, 5.1)])
array([[0],
[5]])
>>> s2 = geopandas.GeoSeries(geopandas.points_from_xy([7.6, 10], [7.6, 10]))
>>> s2
0 POINT (7.6 7.6)
1 POINT (10 10)
dtype: geometry
>>> s.sindex.nearest(s2)
array([[0, 1],
[8, 9]])
"""
geometry = self._as_geometry_array(geometry)
if isinstance(geometry, BaseGeometry) or geometry is None:
geometry = [geometry]
result = self._tree.query_nearest(
geometry,
max_distance=max_distance,
return_distance=return_distance,
all_matches=return_all,
exclusive=exclusive,
)
if return_distance:
indices, distances = result
else:
indices = result
if return_distance:
return indices, distances
else:
return indices
def intersection(self, coordinates):
"""Compatibility wrapper for rtree.index.Index.intersection,
use ``query`` instead.
Parameters
----------
coordinates : sequence or array
Sequence of the form (min_x, min_y, max_x, max_y)
to query a rectangle or (x, y) to query a point.
Examples
--------
>>> from shapely.geometry import Point, box
>>> s = geopandas.GeoSeries(geopandas.points_from_xy(range(10), range(10)))
>>> s
0 POINT (0 0)
1 POINT (1 1)
2 POINT (2 2)
3 POINT (3 3)
4 POINT (4 4)
5 POINT (5 5)
6 POINT (6 6)
7 POINT (7 7)
8 POINT (8 8)
9 POINT (9 9)
dtype: geometry
>>> s.sindex.intersection(box(1, 1, 3, 3).bounds)
array([1, 2, 3])
Alternatively, you can use ``query``:
>>> s.sindex.query(box(1, 1, 3, 3))
array([1, 2, 3])
"""
# TODO: we should deprecate this
# convert bounds to geometry
# the old API uses tuples of bound, but Shapely uses geometries
try:
iter(coordinates)
except TypeError:
# likely not an iterable
# this is a check that rtree does, we mimic it
# to ensure a useful failure message
raise TypeError(
"Invalid coordinates, must be iterable in format "
"(minx, miny, maxx, maxy) (for bounds) or (x, y) (for points). "
"Got `coordinates` = {}.".format(coordinates)
)
# need to convert tuple of bounds to a geometry object
if len(coordinates) == 4:
indexes = self._tree.query(shapely.box(*coordinates))
elif len(coordinates) == 2:
indexes = self._tree.query(shapely.points(*coordinates))
else:
raise TypeError(
"Invalid coordinates, must be iterable in format "
"(minx, miny, maxx, maxy) (for bounds) or (x, y) (for points). "
"Got `coordinates` = {}.".format(coordinates)
)
return indexes
@property
def size(self):
"""Size of the spatial index
Number of leaves (input geometries) in the index.
Examples
--------
>>> from shapely.geometry import Point
>>> s = geopandas.GeoSeries(geopandas.points_from_xy(range(10), range(10)))
>>> s
0 POINT (0 0)
1 POINT (1 1)
2 POINT (2 2)
3 POINT (3 3)
4 POINT (4 4)
5 POINT (5 5)
6 POINT (6 6)
7 POINT (7 7)
8 POINT (8 8)
9 POINT (9 9)
dtype: geometry
>>> s.sindex.size
10
"""
return len(self._tree)
@property
def is_empty(self):
"""Check if the spatial index is empty
Examples
--------
>>> from shapely.geometry import Point
>>> s = geopandas.GeoSeries(geopandas.points_from_xy(range(10), range(10)))
>>> s
0 POINT (0 0)
1 POINT (1 1)
2 POINT (2 2)
3 POINT (3 3)
4 POINT (4 4)
5 POINT (5 5)
6 POINT (6 6)
7 POINT (7 7)
8 POINT (8 8)
9 POINT (9 9)
dtype: geometry
>>> s.sindex.is_empty
False
>>> s2 = geopandas.GeoSeries()
>>> s2.sindex.is_empty
True
"""
return len(self._tree) == 0
def __len__(self):
return len(self._tree)