def setup_rtree(self, ndim, clusters=None):
if self._rtree:
return self._rtree
self._ndim = ndim
if not ndim:
class k(object):
def __init__(self, graph):
self.graph = graph
def insert(self, *args, **kwargs):
pass
def delete(self, *args, **kwargs):
pass
def intersection(self, *args, **kwargs):
return xrange(len(self.graph.clusters))
self._rtree = k(self)
return self._rtree
p = RProp()
p.dimension = max(2, ndim)
p.dat_extension = 'data'
p.idx_extension = 'index'
if clusters:
gen_func = ((i, self.bbox_rtree(c, enlarge=0.005), None)
for i, c in enumerate(clusters))
self._rtree = RTree(gen_func, properties=p)
else:
self._rtree = RTree(properties=p)
return self._rtree
def setup_rtree(self, ndim, clusters=None):
if self._rtree:
return self._rtree
self._ndim = ndim
if not ndim:
class k(object):
def __init__(self, graph):
self.graph = graph
def insert(self, *args, **kwargs):
pass
def delete(self, *args, **kwargs):
pass
def intersection(self, *args, **kwargs):
return xrange(len(self.graph.clusters))
self._rtree = k(self)
return self._rtree
p = RProp()
p.dimension = max(2, ndim)
p.dat_extension = 'data'
p.idx_extension = 'index'
if clusters:
gen_func = ((i, self.bbox_rtree(c, enlarge=0.005), None) for i, c in enumerate(clusters))
self._rtree = RTree(gen_func, properties=p)
else:
self._rtree = RTree(properties=p)
return self._rtree
def __init__(self):
self.obstacles = {}
self.obstacle_index = rtree.index.Index(properties=Property(
dimension=3))
self.vertices = {}
self.edges = {}
self.vertex_index = rtree.index.Index(properties=Property(dimension=3))
def test_tpr(self):
# TODO : this freezes forever on some windows cloud builds
if os.name == 'nt':
return
# Cartesians list for brute force
objects = dict()
tpr_tree = Index(properties=Property(type=RT_TPRTree))
for operation, t_now, object_ in data_generator():
if operation == "INSERT":
tpr_tree.insert(object_.id, object_.get_coordinates())
objects[object_.id] = object_
elif operation == "DELETE":
tpr_tree.delete(object_.id, object_.get_coordinates(t_now))
del objects[object_.id]
elif operation == "QUERY":
tree_intersect = set(
tpr_tree.intersection(object_.get_coordinates()))
# Brute intersect
brute_intersect = set()
for tree_object in objects.values():
x_low, y_low = tree_object.getXY(object_.start_time)
x_high, y_high = tree_object.getXY(object_.end_time)
if intersects(
x_low, y_low, x_high, y_high, # Line
object_.x, object_.y, object_.dx, object_.dy): # Rect
brute_intersect.add(tree_object.id)
# Tree should match brute force approach
assert tree_intersect == brute_intersect
def create_rtree(self, clusters):
if not len(clusters[0].bbox[0]):
class k(object):
def intersection(self, foo):
return xrange(len(clusters))
return k()
ndim = len(clusters[0].bbox[0]) + 1
p = RProp()
p.dimension = ndim
p.dat_extension = 'data'
p.idx_extension = 'index'
rtree = RTree(properties=p)
for idx, c in enumerate(clusters):
rtree.insert(idx, c.bbox[0] + (0,) + c.bbox[1] + (1,))
return rtree
def __init__(self, resolution, basename=None, overwrite=False):
# type: (float) -> None
self._res = resolution
self._cnt = 0
if basename is None:
self._index = Index(interleaved=True)
else:
p = Property(overwrite=overwrite)
self._index = Index(basename, interleaved=True, properties=p)
def create_rtree(self, clusters):
if not len(clusters[0].bbox[0]):
class k(object):
def intersection(self, foo):
return xrange(len(clusters))
return k()
ndim = len(clusters[0].bbox[0]) + 1
p = RProp()
p.dimension = ndim
p.dat_extension = 'data'
p.idx_extension = 'index'
rtree = RTree(properties=p)
for idx, c in enumerate(clusters):
rtree.insert(idx, c.bbox[0] + (0, ) + c.bbox[1] + (1, ))
return rtree
def demo_delete():
seed = 1 # Seed for random points
countries = get_countries()
country_id_to_remove = 170 # United States of America
country_uuids_to_remove = [] # Polygons' ids to remove from the index
properties = Property()
# properties.writethrough = True
# properties.leaf_capacity = 1000
# properties.fill_factor = 0.5
index = Index(properties=properties)
points_per_polygon = 1
points = []
# Inserts countries data to the index
for i, (country_name, geometry) in enumerate(countries):
for polygon in get_polygons(geometry):
temp_uuid = uuid.uuid1().int
index.insert(temp_uuid, polygon.bounds, country_name)
if i == country_id_to_remove:
# Saves index ids of the polygon to be removed later
country_uuids_to_remove.append(temp_uuid)
# Generates random points in every polygon and saves them
random_points = gen_random_point(points_per_polygon, polygon, seed)
points.append((country_name, random_points))
# Checks every generated point has matches
for (country_name, country_points) in points:
for point in country_points:
hits = list(index.intersection(point.bounds, objects=True))
assert any(hit.object == country_name for hit in hits)
# Remove geometry
geometry = countries[country_id_to_remove][1]
for i, polygon in enumerate(get_polygons(geometry)):
index.delete(country_uuids_to_remove[i], polygon.bounds)
points_missing = []
# Checks (again) if every generated point has matches
for (country_name, country_points) in points:
for point in country_points:
hits = list(index.intersection(point.bounds, objects=True))
# Save any point without matches
if not any(hit.object == country_name for hit in hits):
points_missing.append(str(point) + " - " + country_name)
# Print missing points
for point in points_missing:
print(point)
def construct_rtree(self, clusters):
if not len(clusters[0].bbox[0]):
class k(object):
def intersection(self, foo):
return xrange(len(clusters))
return k()
ndim = max(2, len(clusters[0].centroid))
p = RProp()
p.dimension = ndim
p.dat_extension = 'data'
p.idx_extension = 'index'
rtree = RTree(properties=p)
for idx, c in enumerate(clusters):
box = c.bbox #self.scale_box(c.bbox)
if ndim == 1:
rtree.insert(idx, box[0] + [0] + box[1] + [1])
else:
rtree.insert(idx, box[0] + box[1])
return rtree
def make_index(shapes):
"""Creates an index for fast and efficient spatial queries.
Args:
shapes: shapely shapes to bulk-insert bounding boxes for into the spatial index.
Returns:
The spatial index created from the shape's bounding boxes.
"""
# Todo: benchmark these for our use-cases
prop = Property()
prop.dimension = 2
prop.leaf_capacity = 1000
prop.fill_factor = 0.9
def bounded():
for i, shape in enumerate(shapes):
yield (i, shape.bounds, None)
return Index(bounded(), properties=prop)
def make_index(shapes):
'''Creates an index for fast and efficient spatial queries.
Args:
shapes: shapely shapes to bulk-insert bounding boxes for into the spatial index.
Returns:
The spatial index created from the shape's bounding boxes.
'''
# Todo: benchmark these for our use-cases
prop = Property()
prop.dimension = 2
prop.leaf_capacity = 1000
prop.fill_factor = 0.9
def bounded():
for i, shape in enumerate(shapes):
yield (i, shape.bounds, None)
return Index(bounded(), properties=prop)
def build_rtree(self):
'''
Construct an R-tree for the domain. This may reduce the
computational complexity of the methods `intersection_count`,
`contains`, `orient_simplices`, and `snap`.
'''
# create a bounding box for each simplex and add those
# bounding boxes to the R-tree
if self.rtree is not None:
# do nothing because the R-tree already exists
logger.debug('R-tree already exists')
return
smp_min = self.vertices[self.simplices].min(axis=1)
smp_max = self.vertices[self.simplices].max(axis=1)
bounds = np.hstack((smp_min, smp_max))
p = Property()
p.dimension = self.dim
self.rtree = Index(properties=p)
for i, bnd in enumerate(bounds):
self.rtree.add(i, bnd)
return 0
else:
obj.data = data
return page
def deleteByteArray(self, page, returnError):
""" Deletes a page """
try:
RTreePage.objects(name=self.name, page=page).delete(safe=True)
except:
returnError.contents.value = self.InvalidPageError
hasData = property( lambda self: RTreePage.objects(name=self.name).first() is not None )
if __name__=='__main__':
settings = Property()
settings.writethrough= True
settings.buffering_capacity=1
storage = MongoStorage('test')
storage.clear()
r = Rtree( storage, properties=settings)
r.add(123,(0,0,1,1))
print "test 1 should be true"
item = list(r.nearest((0,0), 1, objects=True))[0]
print item.id
print r.valid()
print "test 2 should be true"
obj.data = data
return page
def deleteByteArray(self, page, returnError):
""" Deletes a page """
try:
RTreePage.objects(name=self.name, page=page).delete(safe=True)
except:
returnError.contents.value = self.InvalidPageError
hasData = property(
lambda self: RTreePage.objects(name=self.name).first() is not None)
if __name__ == '__main__':
settings = Property()
settings.writethrough = True
settings.buffering_capacity = 1
storage = MongoStorage('test')
storage.clear()
r = Rtree(storage, properties=settings)
r.add(123, (0, 0, 1, 1))
print "test 1 should be true"
item = list(r.nearest((0, 0), 1, objects=True))[0]
print item.id
print r.valid()
print "test 2 should be true"
def tpr_tree(request):
# Create tree
from rtree.index import Index, Property, RT_TPRTree
return Index(properties=Property(type=RT_TPRTree))