organicmaps/osm_conflate
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Custom OSM data weights support, also more stable output

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This commit is contained in:
Ilya Zverev 2017-05-16 18:22:09 +03:00
parent e23705d775
commit 7cc8740961
1 changed files with 21 additions and 8 deletions
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29
conflate.py
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@ -27,12 +27,13 @@ class SourcePoint:
self.lat = lat
self.lon = lon
self.tags = {} if tags is None else {k.lower(): str(v) for k, v in tags.items()}
self.dist_offset = 0
def distance(self, other):
"""Calculate distance in meters."""
dx = math.radians(self.lon - other.lon) * math.cos(0.5 * math.radians(self.lat + other.lat))
dy = math.radians(self.lat - other.lat)
return 6378137 * math.sqrt(dx*dx + dy*dy)
return 6378137 * math.sqrt(dx*dx + dy*dy) - self.dist_offset
def __len__(self):
return 2
@ -287,6 +288,10 @@ class OsmConflator:
coord[i] += nodes[nd.get('ref')][i]
ways[way.get('id')] = [coord[0] / count, coord[1] / count]
# For calculating priority of OSM objects
priority_fn = self.profile.get_raw('priority')
max_distance = self.profile.get('max_distance', MAX_DISTANCE)
for el in xml:
tags = {}
for tag in el.findall('tag'):
@ -321,6 +326,10 @@ class OsmConflator:
pt = OSMPoint(el.tag, int(el.get('id')), int(el.get('version')), coord[0], coord[1], tags)
pt.members = members
if pt.is_poi():
if callable(priority_fn):
priority = priority_fn(pt)
if priority:
pt.dist_offset = priority if abs(priority) >= 5 else priority * max_distance
self.osmdata[pt.id] = pt
def register_match(self, dataset_key, osmdata_key, keep=False, retag=None):
@ -431,6 +440,13 @@ class OsmConflator:
But given the small number of objects to match, and that
the average case complexity is ~O(n*log^2 n), this is fine.
"""
def search_nn_fix(kd, point):
nearest = kd.search_knn(point, 10)
if not nearest:
return None, None
nearest = [(n[0], n[0].data.distance(point)) for n in nearest]
return sorted(nearest, key=lambda kv: kv[1])[0]
if not self.osmdata:
return
max_distance = self.profile.get('max_distance', MAX_DISTANCE)
@ -438,8 +454,7 @@ class OsmConflator:
count_matched = 0
dist = []
for sp, v in self.dataset.items():
osm_point, _ = osm_kd.search_nn(v)
distance = None if osm_point is None else v.distance(osm_point.data)
osm_point, distance = search_nn_fix(osm_kd, v)
if osm_point is not None and distance <= max_distance:
dist.append((distance, sp, osm_point.data))
needs_sorting = True
@ -454,11 +469,9 @@ class OsmConflator:
del dist[0]
for i in range(len(dist)-1, -1, -1):
if dist[i][2] == osm_point:
nearest = osm_kd.search_nn(self.dataset[dist[i][1]])
distance = None if nearest is None else self.dataset[dist[i][1]].distance(nearest[0].data)
nearest, distance = search_nn_fix(osm_kd, self.dataset[dist[i][1]])
if nearest and distance <= max_distance:
new_point = nearest[0]
dist[i] = (distance, dist[i][1], new_point.data)
dist[i] = (distance, dist[i][1], nearest.data)
needs_sorting = i == 0 or distance < dist[0][0]
else:
del dist[i]
@ -483,7 +496,7 @@ class OsmConflator:
# Add unmatched dataset points
logging.info('Adding %s unmatched dataset points', len(self.dataset))
for k in list(self.dataset.keys()):
for k in sorted(list(self.dataset.keys())):
self.register_match(k, None)
# And finally delete some or all of the remaining osm objects