def generate_residential_zone(centers, models, terrain, map, json_out):
houses = models['houses']
# for testing
# houses = [h for h in houses if 'kittyvision/house11.dae' in h['full_path']]
# assert len(houses) == 1
num_gen = 0
models = []
for x, y, z in iterate_poisson_samples(centers, map,
'Residential Buildings', 15, 1):
pt = numpy.array([x, y, z], dtype=numpy.float32)
pt = scene.mapgen_coords_to_sirikata(pt, terrain)
scale = random.uniform(4.0, 8.0)
m = scene.SceneModel(random.choice(houses)['full_path'],
x=float(pt[0]),
y=float(pt[1]),
z=float(pt[2]),
scale=scale,
model_type='house')
models.append(m)
models = remove_overlapping(models)
for m in models:
json_out.append(m.to_json())
num_gen += 1
print 'Generated (%d) Residential Buildings' % num_gen
def generate_commercial_zone(centers, models, terrain, map, json_out):
commercial = models['commercial_buildings']
# for testing
# commercial = [c for c in commercial if 'emily2e/models/cityimport.dae' in c['full_path']]
# assert len(commercial) == 1
num_gen = 0
models = []
for x, y, z in iterate_poisson_samples(centers, map,
'Commercial Buildings', 20, 2):
pt = numpy.array([x, y, z], dtype=numpy.float32)
pt = scene.mapgen_coords_to_sirikata(pt, terrain)
scale = random.uniform(6.0, 10.0)
m = scene.SceneModel(random.choice(commercial)['full_path'],
x=float(pt[0]),
y=float(pt[1]),
z=float(pt[2]),
scale=scale,
model_type='commercial')
models.append(m)
models = remove_overlapping(models)
for m in models:
json_out.append(m.to_json())
num_gen += 1
print 'Generated (%d) Commercial Buildings' % num_gen
def generate_winter(models, terrain, map, json_out):
winter = models['winter']
snow = [c for c in map.centers.values() if c.biome == 'SNOW']
random.shuffle(snow)
winter = winter + winter
snow = snow[:len(winter)]
for center, winter_model in progress.bar(
zip(snow, winter), label='Generating winter objects...'):
center_pt = numpy.array(
[center.x, center.y, center.elevation * Z_SCALE],
dtype=numpy.float32)
center_pt = scene.mapgen_coords_to_sirikata(center_pt, terrain)
scale = random.uniform(3.0, 10.0)
m = scene.SceneModel(winter_model['full_path'],
x=float(center_pt[0]),
y=float(center_pt[1]),
z=float(center_pt[2]),
scale=scale,
model_type='winter')
json_out.append(m.to_json())
print 'Generated (%d) winter objects' % len(winter)
def generate_forest(centers, models, terrain, map, json_out, name, radius,
num_samples):
trees = models['trees']
# for testing
# trees = [t for t in trees if 'jterrace/palm.dae' in t['full_path']]
# assert len(trees) == 1
num_gen = 0
for x, y, z in iterate_poisson_samples(centers, map, name, radius,
num_samples):
pt = numpy.array([x, y, z], dtype=numpy.float32)
pt = scene.mapgen_coords_to_sirikata(pt, terrain)
scale = random.uniform(3.0, 10.0)
m = scene.SceneModel(random.choice(trees)['full_path'],
x=float(pt[0]),
y=float(pt[1]),
z=float(pt[2]),
scale=scale,
model_type='tree')
json_out.append(m.to_json())
num_gen += 1
print 'Generated (%d) %s' % (num_gen, name)
def generate_flying(models, terrain, map, json_out):
terrain_bounds = scene.sirikata_bounds(terrain.boundsInfo)
minpt, maxpt = terrain_bounds
minpt *= terrain.scale
maxpt *= terrain.scale
height_max = (maxpt[2] - minpt[2]) * 1.20
flying_models = models['flying']
centers = map.centers.values()
random.shuffle(centers)
centers = centers[:len(flying_models)]
for center, flying_model in progress.bar(
zip(centers,
flying_models), label='Generating flying objects... '):
center_pt = numpy.array(
[center.x, center.y, center.elevation * Z_SCALE],
dtype=numpy.float32)
center_pt = scene.mapgen_coords_to_sirikata(center_pt, terrain)
rand_height = random.uniform(center_pt[2], height_max) * 1.10
m = scene.SceneModel(flying_model['full_path'],
x=float(center_pt[0]),
y=float(center_pt[1]),
z=rand_height,
scale=random.uniform(1.0, 8.0),
model_type='flying')
json_out.append(m.to_json())
print 'Generated (%d) flying objects' % len(flying_models)
def generate_boats(models, terrain, map, json_out):
boats = models['boats']
oceans = [c for c in map.centers.values() if c.biome == 'OCEAN']
lakes = [c for c in map.centers.values() if c.biome == 'LAKE']
random.shuffle(lakes)
random.shuffle(oceans)
lakes = lakes[:len(boats)]
oceans = oceans[:len(boats) * 2]
centers = oceans + lakes
boats = boats + boats + boats
for center, boat_model in progress.bar(zip(centers, boats),
label='Generating boats...'):
center_pt = numpy.array(
[center.x, center.y, center.elevation * Z_SCALE],
dtype=numpy.float32)
center_pt = scene.mapgen_coords_to_sirikata(center_pt, terrain)
scale = random.uniform(5.0, 15.0)
m = scene.SceneModel(boat_model['full_path'],
x=float(center_pt[0]),
y=float(center_pt[1]),
z=float(center_pt[2]) - scale * 2 * 0.05,
scale=scale,
model_type='boat')
json_out.append(m.to_json())
print 'Generated (%d) boat objects' % len(boats)
def generate_commercial_zone(centers, models, terrain, map, json_out):
commercial = models['commercial_buildings']
# for testing
# commercial = [c for c in commercial if 'emily2e/models/cityimport.dae' in c['full_path']]
# assert len(commercial) == 1
num_gen = 0
models = []
for x, y, z in iterate_poisson_samples(centers, map, 'Commercial Buildings', 20, 2):
pt = numpy.array([x,y,z], dtype=numpy.float32)
pt = scene.mapgen_coords_to_sirikata(pt, terrain)
scale = random.uniform(6.0, 10.0)
m = scene.SceneModel(random.choice(commercial)['full_path'],
x=float(pt[0]),
y=float(pt[1]),
z=float(pt[2]),
scale=scale,
model_type='commercial')
models.append(m)
models = remove_overlapping(models)
for m in models:
json_out.append(m.to_json())
num_gen += 1
print 'Generated (%d) Commercial Buildings' % num_gen
def generate_residential_zone(centers, models, terrain, map, json_out):
houses = models['houses']
# for testing
# houses = [h for h in houses if 'kittyvision/house11.dae' in h['full_path']]
# assert len(houses) == 1
num_gen = 0
models = []
for x, y, z in iterate_poisson_samples(centers, map, 'Residential Buildings', 15, 1):
pt = numpy.array([x,y,z], dtype=numpy.float32)
pt = scene.mapgen_coords_to_sirikata(pt, terrain)
scale = random.uniform(4.0, 8.0)
m = scene.SceneModel(random.choice(houses)['full_path'],
x=float(pt[0]),
y=float(pt[1]),
z=float(pt[2]),
scale=scale,
model_type='house')
models.append(m)
models = remove_overlapping(models)
for m in models:
json_out.append(m.to_json())
num_gen += 1
print 'Generated (%d) Residential Buildings' % num_gen
def generate_forest(centers, models, terrain, map, json_out, name, radius, num_samples):
trees = models['trees']
# for testing
# trees = [t for t in trees if 'jterrace/palm.dae' in t['full_path']]
# assert len(trees) == 1
num_gen = 0
for x, y, z in iterate_poisson_samples(centers, map, name, radius, num_samples):
pt = numpy.array([x,y,z], dtype=numpy.float32)
pt = scene.mapgen_coords_to_sirikata(pt, terrain)
scale = random.uniform(3.0, 10.0)
m = scene.SceneModel(random.choice(trees)['full_path'],
x=float(pt[0]),
y=float(pt[1]),
z=float(pt[2]),
scale=scale,
model_type='tree')
json_out.append(m.to_json())
num_gen += 1
print 'Generated (%d) %s' % (num_gen, name)
def generate_boats(models, terrain, map, json_out):
boats = models['boats']
oceans = [c for c in map.centers.values() if c.biome == 'OCEAN']
lakes = [c for c in map.centers.values() if c.biome == 'LAKE']
random.shuffle(lakes)
random.shuffle(oceans)
lakes = lakes[:len(boats)]
oceans = oceans[:len(boats)*2]
centers = oceans + lakes
boats = boats + boats + boats
for center, boat_model in progress.bar(zip(centers, boats), label='Generating boats...'):
center_pt = numpy.array([center.x, center.y, center.elevation * Z_SCALE], dtype=numpy.float32)
center_pt = scene.mapgen_coords_to_sirikata(center_pt, terrain)
scale = random.uniform(5.0, 15.0)
m = scene.SceneModel(boat_model['full_path'],
x=float(center_pt[0]),
y=float(center_pt[1]),
z=float(center_pt[2]) - scale * 2 * 0.05,
scale=scale,
model_type='boat')
json_out.append(m.to_json())
print 'Generated (%d) boat objects' % len(boats)
def generate_flying(models, terrain, map, json_out):
terrain_bounds = scene.sirikata_bounds(terrain.boundsInfo)
minpt, maxpt = terrain_bounds
minpt *= terrain.scale
maxpt *= terrain.scale
height_max = (maxpt[2] - minpt[2]) * 1.20
flying_models = models['flying']
centers = map.centers.values()
random.shuffle(centers)
centers = centers[:len(flying_models)]
for center, flying_model in progress.bar(zip(centers, flying_models), label='Generating flying objects... '):
center_pt = numpy.array([center.x, center.y, center.elevation * Z_SCALE], dtype=numpy.float32)
center_pt = scene.mapgen_coords_to_sirikata(center_pt, terrain)
rand_height = random.uniform(center_pt[2], height_max) * 1.10
m = scene.SceneModel(flying_model['full_path'],
x=float(center_pt[0]),
y=float(center_pt[1]),
z=rand_height,
scale=random.uniform(1.0, 8.0),
model_type='flying')
json_out.append(m.to_json())
print 'Generated (%d) flying objects' % len(flying_models)
def generate_winter(models, terrain, map, json_out):
winter = models['winter']
snow = [c for c in map.centers.values() if c.biome == 'SNOW']
random.shuffle(snow)
winter = winter + winter
snow = snow[:len(winter)]
for center, winter_model in progress.bar(zip(snow, winter), label='Generating winter objects...'):
center_pt = numpy.array([center.x, center.y, center.elevation * Z_SCALE], dtype=numpy.float32)
center_pt = scene.mapgen_coords_to_sirikata(center_pt, terrain)
scale = random.uniform(3.0, 10.0)
m = scene.SceneModel(winter_model['full_path'],
x=float(center_pt[0]),
y=float(center_pt[1]),
z=float(center_pt[2]),
scale=scale,
model_type='winter')
json_out.append(m.to_json())
print 'Generated (%d) winter objects' % len(winter)
def generate_roads(models, terrain, map, json_out):
numroads = 0
for center in progress.bar(map.centers.values(),
label='Generating roads... '):
road_edges = [
e for e in center.edges
if e.is_road and e.corner0 is not None and e.corner1 is not None
]
if len(road_edges) != 2:
continue
e1, e2 = road_edges
e1_0 = numpy.array(
[e1.corner0.x, e1.corner0.y, e1.corner0.elevation * Z_SCALE],
dtype=numpy.float32)
e1_1 = numpy.array(
[e1.corner1.x, e1.corner1.y, e1.corner1.elevation * Z_SCALE],
dtype=numpy.float32)
e2_0 = numpy.array(
[e2.corner0.x, e2.corner0.y, e2.corner0.elevation * Z_SCALE],
dtype=numpy.float32)
e2_1 = numpy.array(
[e2.corner1.x, e2.corner1.y, e2.corner1.elevation * Z_SCALE],
dtype=numpy.float32)
region_center = numpy.array(
[center.x, center.y, center.elevation * Z_SCALE])
for end1, edge1, edge2 in [(region_center, e1_0, e1_1),
(region_center, e2_0, e2_1)]:
end2 = v3mid(edge1, edge2)
midpt = v3mid(end1, end2)
midpt = scene.mapgen_coords_to_sirikata(midpt, terrain)
kata_pt1 = scene.mapgen_coords_to_sirikata(end1, terrain)
kata_pt2 = scene.mapgen_coords_to_sirikata(end2, terrain)
scale = v3dist(kata_pt1, kata_pt2) / 2
m = scene.SceneModel(ROAD_PATH,
x=float(midpt[0]),
y=float(midpt[1]),
z=float(midpt[2]),
scale=scale,
model_type='road')
kataboundmin, kataboundmax = scene.sirikata_bounds(m.boundsInfo)
scenemin = kataboundmin * scale + midpt
scenemax = kataboundmax * scale + midpt
xmid = (scenemax[0] - scenemin[0]) / 2.0 + scenemin[0]
road_edge1 = numpy.array([xmid, scenemin[1], scenemin[2]],
dtype=numpy.float32)
road_edge2 = numpy.array([xmid, scenemax[1], scenemin[2]],
dtype=numpy.float32)
midv3 = Vec3(midpt[0], midpt[1], midpt[2])
src = Vec3(road_edge2[0], road_edge2[1], road_edge2[2])
src -= midv3
src_copy = Vec3(src)
target = Vec3(kata_pt1[0], kata_pt1[1], kata_pt1[2])
target -= midv3
cross = src.cross(target)
w = math.sqrt(
src.lengthSquared() * target.lengthSquared()) + src.dot(target)
q = Quat(w, cross)
q.normalize()
orig_up = q.getUp()
orig_up.normalize()
edge1_kata = scene.mapgen_coords_to_sirikata(edge1, terrain)
edge2_kata = scene.mapgen_coords_to_sirikata(edge2, terrain)
new_up = normal_vector(kata_pt1, edge1_kata, edge2_kata)
new_up = Vec3(new_up[0], new_up[1], new_up[2])
rotate_about = orig_up.cross(new_up)
rotate_about.normalize()
angle_between = orig_up.angleDeg(new_up)
r = Quat()
r.setFromAxisAngle(angle_between, rotate_about)
r.normalize()
q *= r
q.normalize()
m.orient_x = q.getI()
m.orient_y = q.getJ()
m.orient_z = q.getK()
m.orient_w = q.getR()
numroads += 1
json_out.append(m.to_json())
print 'Generated (%d) road objects' % numroads
def generate_roads(models, terrain, map, json_out):
numroads = 0
for center in progress.bar(map.centers.values(), label='Generating roads... '):
road_edges = [e for e in center.edges if e.is_road and e.corner0 is not None and e.corner1 is not None]
if len(road_edges) != 2:
continue
e1, e2 = road_edges
e1_0 = numpy.array([e1.corner0.x, e1.corner0.y, e1.corner0.elevation * Z_SCALE], dtype=numpy.float32)
e1_1 = numpy.array([e1.corner1.x, e1.corner1.y, e1.corner1.elevation * Z_SCALE], dtype=numpy.float32)
e2_0 = numpy.array([e2.corner0.x, e2.corner0.y, e2.corner0.elevation * Z_SCALE], dtype=numpy.float32)
e2_1 = numpy.array([e2.corner1.x, e2.corner1.y, e2.corner1.elevation * Z_SCALE], dtype=numpy.float32)
region_center = numpy.array([center.x, center.y, center.elevation * Z_SCALE])
for end1, edge1, edge2 in [(region_center, e1_0, e1_1), (region_center, e2_0, e2_1)]:
end2 = v3mid(edge1, edge2)
midpt = v3mid(end1, end2)
midpt = scene.mapgen_coords_to_sirikata(midpt, terrain)
kata_pt1 = scene.mapgen_coords_to_sirikata(end1, terrain)
kata_pt2 = scene.mapgen_coords_to_sirikata(end2, terrain)
scale = v3dist(kata_pt1, kata_pt2) / 2
m = scene.SceneModel(ROAD_PATH,
x=float(midpt[0]),
y=float(midpt[1]),
z=float(midpt[2]),
scale=scale,
model_type='road')
kataboundmin, kataboundmax = scene.sirikata_bounds(m.boundsInfo)
scenemin = kataboundmin * scale + midpt
scenemax = kataboundmax * scale + midpt
xmid = (scenemax[0] - scenemin[0]) / 2.0 + scenemin[0]
road_edge1 = numpy.array([xmid, scenemin[1], scenemin[2]], dtype=numpy.float32)
road_edge2 = numpy.array([xmid, scenemax[1], scenemin[2]], dtype=numpy.float32)
midv3 = Vec3(midpt[0], midpt[1], midpt[2])
src = Vec3(road_edge2[0], road_edge2[1], road_edge2[2])
src -= midv3
src_copy = Vec3(src)
target = Vec3(kata_pt1[0], kata_pt1[1], kata_pt1[2])
target -= midv3
cross = src.cross(target)
w = math.sqrt(src.lengthSquared() * target.lengthSquared()) + src.dot(target)
q = Quat(w, cross)
q.normalize()
orig_up = q.getUp()
orig_up.normalize()
edge1_kata = scene.mapgen_coords_to_sirikata(edge1, terrain)
edge2_kata = scene.mapgen_coords_to_sirikata(edge2, terrain)
new_up = normal_vector(kata_pt1, edge1_kata, edge2_kata)
new_up = Vec3(new_up[0], new_up[1], new_up[2])
rotate_about = orig_up.cross(new_up)
rotate_about.normalize()
angle_between = orig_up.angleDeg(new_up)
r = Quat()
r.setFromAxisAngle(angle_between, rotate_about)
r.normalize()
q *= r
q.normalize()
m.orient_x = q.getI()
m.orient_y = q.getJ()
m.orient_z = q.getK()
m.orient_w = q.getR()
numroads += 1
json_out.append(m.to_json())
print 'Generated (%d) road objects' % numroads
