def load_definow_aeds():
bounds = util.get_bounds()
out = {}
url = "http://definow.org/de/map/node"
print("Downloading URL '%s'..." % url)
r = requests.post(url)
if r.status_code != 200:
return
exp = r'"rmt":"([0-9]+)\\/0","latitude":"([\.0-9]+)","longitude":"([\.0-9]+)",'
for item in re.findall(exp, r.text):
#print item
y = float(item[1])
x = float(item[2])
definow_id = int(item[0])
position = Point([x, y])
if not bounds.contains(position):
continue
out[str(definow_id)] = {
"id": definow_id,
"x": x,
"y": y
}
# write CSV version
with open("definow.csv", "wb") as csvfile:
writer = csv.writer(csvfile)
writer.writerow(["id", "x", "y"])
for aedid in out.keys():
writer.writerow([
str(out[aedid]["id"]),
str(out[aedid]["x"]),
str(out[aedid]["y"])
])
return out
def generate_nearest_neighbor(pop_pts, fac_pts):
"""
Nearest Neighbor via QuadTree.
Faster than "naive" approach for large number of
facilities (i.e. > 1000)
arguments:
pop_pts: an iterable of x,y pairs
fac_pts: iterable of x,y pairs
return: A list of pop_pt index, fac_pt index, & distance
representing facilities closest to pop pts & the distance between
"""
edges = []
bounds = util.get_bounds(pop_pts + fac_pts)
qt = quad_tree.QuadTree(10, bounds[:2], bounds[2:],
lambda x: x['pt'], True)
for n in range(0, len(fac_pts)):
fac_dict = {'id': n, 'pt': fac_pts[n]}
qt.add(fac_dict)
for m in range(0, len(pop_pts)):
pop_pt = pop_pts[m]
fac_dict = qt.find_nearest(pop_pt)
dist = util.compute_spherical_distance(pop_pt, fac_dict['pt'])
edge = [m, fac_dict['id'], dist]
edges.append(edge)
return edges
def load_definow_aeds():
bounds = util.get_bounds()
out = {}
url = "http://definow.org/de/map/node"
print("Downloading URL '%s'..." % url)
r = requests.post(url)
if r.status_code != 200:
return
exp = r'"rmt":"([0-9]+)\\/0","latitude":"([\.0-9]+)","longitude":"([\.0-9]+)",'
for item in re.findall(exp, r.text):
#print item
y = float(item[1])
x = float(item[2])
definow_id = int(item[0])
position = Point([x, y])
if not bounds.contains(position):
continue
out[str(definow_id)] = {"id": definow_id, "x": x, "y": y}
# write CSV version
with open("definow.csv", "wb") as csvfile:
writer = csv.writer(csvfile)
writer.writerow(["id", "x", "y"])
for aedid in out.keys():
writer.writerow([
str(out[aedid]["id"]),
str(out[aedid]["x"]),
str(out[aedid]["y"])
])
return out
def load_osm_aeds():
xml = """<osm-script output="json" timeout="25">
<query type="node">
<has-kv k="emergency" v="defibrillator"/>
<bbox-query n="51.2" e="7.2" s="50.8" w="6.7" />
</query>
<print mode="meta"/>
</osm-script>"""
bounds = util.get_bounds()
out = {}
r = requests.post("http://overpass-api.de/api/interpreter", data=xml)
for item in r.json()["elements"]:
position = Point([item["lon"], item["lat"]])
if bounds.contains(position):
out[str(item["id"])] = item
return out
def load_osm_aeds():
xml = """<osm-script output="json" timeout="25">
<query type="node">
<has-kv k="emergency" v="defibrillator"/>
<bbox-query n="51.2" e="7.2" s="50.8" w="6.7" />
</query>
<print mode="meta"/>
</osm-script>"""
bounds = util.get_bounds()
out = {}
r = requests.post("http://overpass-api.de/api/interpreter", data=xml)
for item in r.json()["elements"]:
position = Point([item["lon"], item["lat"]])
if bounds.contains(position):
out[str(item["id"])] = item
return out
def CIO(goals,
world,
p,
single=False,
start_stage=0,
traj_data=None,
gif_tag=''):
if single:
# FOR TESTING A SINGLE traj
S = world.traj_func(world, goals, p, traj_data)
S = add_noise(S)
visualize_result(world, goals, p, 'initial' + gif_tag + '.gif', S)
tot_cost = L(S, goals, world, p, start_stage)
print_final(*function_costs)
return {}
S = world.traj_func(world, goals, p, traj_data)
if start_stage == 0:
S = add_noise(S)
visualize_result(world, goals, p, 'initial' + gif_tag + '.gif', S)
tot_cost = L(S, goals, world, p)
print_final(*function_costs)
bounds = get_bounds(world, p)
ret_info = {}
x_init = S
for stage in range(start_stage, len(p.stage_weights)):
print('BEGINNING PHASE:', stage)
p.print_stage_weights(stage)
res = minimize(fun=L,
x0=x_init,
args=(goals, world, p, stage),
method='L-BFGS-B',
bounds=bounds,
options={'eps': 10**-3})
x_final = res['x']
nit = res['nit']
final_cost = res['fun']
visualize_result(world, goals, p,
'stage_{}'.format(stage) + gif_tag + '.gif', x_final)
print_final(*function_costs)
all_final_costs = function_costs
ret_info[stage] = world.s0, x_final, final_cost, nit, all_final_costs
x_init = x_final
return ret_info
def get_image(self, feat, radius=0.02, scale=30):
moves = [(radius, radius), (radius, -radius), (-radius, -radius),
(-radius, radius)]
feat = ee.Feature(feat)
region = self.get_image_region(feat)
data = feat.getInfo()
type = data['geometry']['type']
coords = data['geometry']['coordinates']
if type == 'Point':
bounds = [[coords[0] + r0, coords[1] + r1] for r0, r1 in moves]
elif type == 'Polygon':
bounds = coords
else:
xmin, ymin, xmax, ymax = get_bounds(
[c[0] for c in data['geometry']['coordinates']])
bounds = [[xmin, ymax], [xmax, ymax], [xmax, ymin], [xmin, ymin]]
image = ee.Image(region)
params = {'region': bounds, 'scale': scale}
return image, params
def load_aedkataster_aeds():
bounds = util.get_bounds()
out = {}
url = "http://aed-kataster.net/nw.html"
print("Downloading URL '%s'..." % url)
r = requests.post(url)
if r.status_code != 200:
return
exp = r'GLatLng\(([\.0-9]+),([\.0-9]+)\);\s+SobiCatOverMap\.addOverlay\(\s+createSobiMarker\(\s+MarkerPoint,\s+\'<div><a href="[^\?]+\?sobi2Task=sobi2Details&sobi2Id=([0-9]+)">'
for item in re.findall(exp, r.text):
#print item
y = float(item[0])
x = float(item[1])
aedk_id = int(item[2])
position = Point([x, y])
if bounds.contains(position):
out[str(aedk_id)] = {
"id": aedk_id,
"x": x,
"y": y
}
return out
def get_bounds(self):
return get_bounds(list(self.blocks.keys()))
