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new stair interpolation based on dijkstra

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Laura Klünder 2017-08-07 18:12:33 +02:00
parent 2573ffc05b
commit 3c9013220e
1 changed files with 54 additions and 37 deletions
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91
src/c3nav/mapdata/models/geometry/level.py
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@ -1,9 +1,11 @@
import itertools
from operator import attrgetter, itemgetter
import numpy as np
from django.db import models
from django.db.models import F
from django.utils.translation import ugettext_lazy as _
from scipy.sparse.csgraph._shortest_path import dijkstra
from shapely.affinity import scale
from shapely.geometry import JOIN_STYLE, LineString
from shapely.ops import cascaded_union
@ -256,46 +258,61 @@ class AltitudeArea(LevelGeometryMixin, models.Model):
del area_connections[tmpid]
# interpolate altitudes
while areas_without_altitude:
# find a area without an altitude that is connected
# to one with an altitude to start the chain
chain = []
for tmpid in areas_without_altitude:
areas_with_altitude = [i for i in range(len(areas)) if i not in areas_without_altitude]
for i, tmpid in enumerate(areas_with_altitude):
areas[tmpid].i = i
csgraph = np.zeros((len(areas), len(areas)), dtype=bool)
for area in areas:
for connected_tmpid in area.connected_to:
csgraph[area.tmpid, connected_tmpid] = True
repeat = True
while repeat:
repeat = False
distances, predecessors = dijkstra(csgraph, directed=False, return_predecessors=True, unweighted=True)
relevant_distances = distances[np.array(areas_with_altitude)[:, None], np.array(areas_with_altitude)]
# noinspection PyTypeChecker
for from_i, to_i in np.argwhere(np.logical_and(relevant_distances < np.inf, relevant_distances > 1)):
from_area = areas[areas_with_altitude[from_i]]
to_area = areas[areas_with_altitude[to_i]]
if from_area.altitude == to_area.altitude:
continue
path = [to_area.tmpid]
while path[-1] != from_area.tmpid:
path.append(predecessors[from_area.tmpid, path[-1]])
from_altitude = from_area.altitude
delta_altitude = (to_area.altitude-from_altitude)/(len(path)-1)
if set(path[1:-1]).difference(areas_without_altitude):
continue
for i, tmpid in enumerate(reversed(path[1:-1]), start=1):
area = areas[tmpid]
area.altitude = from_altitude+delta_altitude*i
areas_without_altitude.discard(tmpid)
area.i = len(areas_with_altitude)
areas_with_altitude.append(tmpid)
for from_tmpid, to_tmpid in zip(path[:-1], path[1:]):
csgraph[from_tmpid, to_tmpid] = False
csgraph[to_tmpid, from_tmpid] = False
repeat = True
# remaining areas: copy altitude from connected areas if any
repeat = True
while repeat:
repeat = False
for tmpid in tuple(areas_without_altitude):
area = areas[tmpid]
connected_with_altitude = area.connected_to-areas_without_altitude
if connected_with_altitude:
chain = [next(iter(connected_with_altitude)), tmpid]
current = area
break
else:
# there are no more chains possible
break
# continue chain as long as possible
while True:
connected_with_altitude = (current.connected_to-areas_without_altitude).difference(chain)
if connected_with_altitude:
# interpolate
area = areas[next(iter(connected_with_altitude))]
from_altitude = areas[chain[0]].altitude
delta_altitude = area.altitude-from_altitude
for i, tmpid in enumerate(chain[1:], 1):
areas[tmpid].altitude = from_altitude+delta_altitude*i/len(chain)
areas_without_altitude.difference_update(chain)
break
connected = current.connected_to.difference(chain)
if not connected:
# end of chain
altitude = areas[chain[0]].altitude
for i, tmpid in enumerate(chain[1:], 1):
areas[tmpid].altitude = altitude
areas_without_altitude.difference_update(chain)
break
# continue chain
current = areas[next(iter(connected))]
chain.append(current.tmpid)
area.altitude = areas[next(iter(connected_with_altitude))].altitude
areas_without_altitude.discard(tmpid)
repeat = True
# remaining areas which belong to a room that has an altitude somewhere
for contained_areas in space_areas.values():