def cities_on_map(A, distance_limit=100):
"""Put selected cities on map.
Ensure that cities shown are at least dis_lim km apart.
Input
A: Selected cities sorted by intensity and population.
distance_limit: Minimum distance [km] between cities shown on map (default is 100 km)
Output
Generates text file for use by GMT to plot cities on map
"""
# Always take the first city (which is the one with the highest intensity)
index = [0]
# Indices of all remaining cities
T = range(1, len(A))
# Loop through remaining cities and determine which to plot
T2 = []
b = 0
while True:
# Find cities more than distance_limit km away from city b (anchor city)
for i in range(len(T)):
k = T[i] # Index of other city
start = Point(latitude=A['lat'][b], longitude=A['lon'][b]) # Anchor city
end = Point(latitude=A['lat'][k], longitude=A['lon'][k]) # Other city
r = start.distance_to(end)/1000 # Calculate distance and convert to km
if r >= distance_limit:
# Select city i because it is sufficiently far away from anchor city
T2 += [(k)]
# Determine whether to use more cities or not
if len(T2) > 1:
# If more than one candidate exist pick the first of the selected cities as new anchor city
b = T2[0]
index += [(b)]
# Replace T with what now remains and reset T2
T = T2[1:]
T2 = []
elif len(T2) == 1:
# If only one city exists add it and exit loop
index += [(T2[0])]
break
else:
# If no cities were found exit loop
break
# Make sure there is no old file hanging around
cmd = '/bin/rm -rf city.txt'
os.system(cmd)
# Record selected cities in GMT file
city_filename = 'city.txt'
for i in index:
cmd = 'cat << END >> %s' % city_filename + '\n'+''+str(A['lon'][i])+' '+str(A['lat'][i])+' 15 0 0 BR '+A['name'][i]+'\n'+'END'
os.system(cmd)
def setUp(self):
self.eps = 0.001 # Accept 0.1 % relative error
self.RSISE = Point(-35.27456, 149.12065)
self.Home = Point(-35.25629, 149.12494) # 28 Scrivener Street, ACT
self.Syd = Point(-33.93479, 151.16794) # Sydney Airport
self.Nadi = Point(-17.75330, 177.45148) # Nadi Airport
self.Kobenhavn = Point(55.70248, 12.58364) # Kobenhavn, Denmark
self.Muncar = Point(-8.43, 114.33) # Muncar, Indonesia
def testBearingNorth(self):
"""Bearing due north (0 deg) correct within double precision
"""
eps = 1.0e-12
p1 = Point(0.0, 0.0)
p2 = Point(1.0, 0.0)
b = p1.bearing_to(p2)
msg = 'Computed northward bearing: %d, Should have been: %d' % (b, 0)
assert numpy.allclose(b, 0, rtol=eps, atol=eps), msg
def testBearingNorth(self):
"""Bearing due north (0 deg) correct within double precision
"""
eps = 1.0e-12
p1 = Point(0.0, 0.0)
p2 = Point(1.0, 0.0)
b = p1.bearing_to(p2)
msg = 'Computed northward bearing: %d, Should have been: %d' % (b, 0)
assert numpy.allclose(b, 0, rtol=eps, atol=eps), msg
def testBearingWest(self):
"""Bearing due west (270 deg) is correct within double precision
"""
eps = 1.0e-12
B = 270 # True bearing
p1 = Point(0.0, 0.0)
p3 = Point(0.0, 1.0)
b = p3.bearing_to(p1)
msg = 'Computed southward bearing %d. Expected %d' % (b, B)
assert numpy.allclose(b, B, rtol=eps, atol=eps), msg
def test_equator_example(self):
"""Distance and bearing of real example (near equator) are correct
"""
# Test data from http://www.movable-type.co.uk/scripts/latlong.html
D = 11448.0959593 # True Distance [m]
p1 = Point(latitude=-0.59, longitude=117.10)
p2 = Point(latitude=-0.50, longitude=117.15)
d = p1.distance_to(p2)
msg = 'Dist to point failed %f. Expected %f' % (d, D)
assert numpy.allclose(d, D, rtol=1.0e-3), msg
def testBearingWest(self):
"""Bearing due west (270 deg) is correct within double precision
"""
eps = 1.0e-12
B = 270 # True bearing
p1 = Point(0.0, 0.0)
p3 = Point(0.0, 1.0)
b = p3.bearing_to(p1)
msg = 'Computed southward bearing %d. Expected %d' % (b, B)
assert numpy.allclose(b, B, rtol=eps, atol=eps), msg
def test_equator_example(self):
"""Distance and bearing of real example (near equator) are correct
"""
# Test data from http://www.movable-type.co.uk/scripts/latlong.html
D = 11448.0959593 # True Distance [m]
p1 = Point(latitude=-0.59, longitude=117.10)
p2 = Point(latitude=-0.50, longitude=117.15)
d = p1.distance_to(p2)
msg = 'Dist to point failed %f. Expected %f' % (d, D)
assert numpy.allclose(d, D, rtol=1.0e-3), msg
def calculate_location_info(event_info, city_info):
"""Calculate distance from earthquake to most affected city
Input
event_info: Information about earthquake
city_info: List of cities sorted by intensity
Note all information is passed in to allow future modifications such
as options for calculating
* distance to nearest city
* distance to most affected city
* distance to biggest city
* etc
"""
# Get location of earthquake FIXME: Should store these as floats
earthquake_location = Point(float(event_info['lat']),
float(event_info['lon']))
# Select city (in this case, take the most affected)
city = city_info[0]
# Get location and name of selected city
city_name = city[0]
city_location = Point(city[4], city[3])
# Compute distance [m] and bearing [deg from city]
d = city_location.distance_to(earthquake_location)
b = city_location.bearing_to(earthquake_location)
# Create string and update event_info
if 5 <= b < 85:
direction = 'Timur Laut' # North East
elif 85 <= b < 95:
direction = 'Timur' # East
elif 95 <= b < 175:
direction = 'Tenggara' # South East
elif 175 <= b < 185:
direction = 'Selatan' # South
elif 185 <= b < 265:
direction = 'Barat Daya' # South West
elif 265 <= b < 275:
direction = 'Barat' # West
elif 275 <= b < 355:
direction = 'Barat Laut' # North West
else:
direction = 'Utara' # North
s = 'Berjarak %i km, %i$^\circ$ Arah %s %s' % (d/1000, b,
direction, city_name)
event_info['location_string'] = s
def setUp(self):
self.eps = 0.001 # Accept 0.1 % relative error
self.RSISE = Point(-35.27456, 149.12065)
self.Home = Point(-35.25629, 149.12494) # 28 Scrivener Street, ACT
self.Syd = Point(-33.93479, 151.16794) # Sydney Airport
self.Nadi = Point(-17.75330, 177.45148) # Nadi Airport
self.Kobenhavn = Point(55.70248, 12.58364) # Kobenhavn, Denmark
self.Muncar = Point(-8.43, 114.33) # Muncar, Indonesia
def testEarthquake2Muncar(self):
"""Distance and bearing of real example (quake -> Muncar) are correct
"""
# Test data from http://www.movable-type.co.uk/scripts/latlong.html
D = 151318 # True Distance [m]
B = 26 # 26 19 42 / 26 13 57 # Bearing to between points (start, end)
p1 = Point(latitude=-9.65, longitude=113.72)
d = p1.distance_to(self.Muncar)
msg = 'Dist to Muncar failed %f. Expected %f' % (d, D)
assert numpy.allclose(d, D), msg
b = p1.bearing_to(self.Muncar)
msg = 'Bearing to Muncar %i. Expected %i' % (b, B)
assert b == B, msg
def testEarthquake2Muncar(self):
"""Distance and bearing of real example (quake -> Muncar) are correct
"""
# Test data from http://www.movable-type.co.uk/scripts/latlong.html
D = 151318 # True Distance [m]
B = 26 # 26 19 42 / 26 13 57 # Bearing to between points (start, end)
p1 = Point(latitude=-9.65, longitude=113.72)
d = p1.distance_to(self.Muncar)
msg = 'Dist to Muncar failed %f. Expected %f' % (d, D)
assert numpy.allclose(d, D), msg
b = p1.bearing_to(self.Muncar)
msg = 'Bearing to Muncar %i. Expected %i' % (b, B)
assert b == B, msg
def test_generate_circle(self):
"""A circle with a given radius can be generated correctly
"""
# Generate a circle around Sydney airport with radius 3km
radius = 3000
C = self.Syd.generate_circle(radius)
# Check distance around the circle
# Note that not every point will be exactly 3000m
# because the circle in defined in geographic coordinates
for c in C:
p = Point(c[1], c[0])
d = self.Syd.distance_to(p)
msg = ('Radius %f not with in expected tolerance. Expected %d' %
(d, radius))
assert numpy.allclose(d, radius, rtol=2.0e-1), msg
class TestCase(unittest.TestCase):
def setUp(self):
self.eps = 0.001 # Accept 0.1 % relative error
self.RSISE = Point(-35.27456, 149.12065)
self.Home = Point(-35.25629, 149.12494) # 28 Scrivener Street, ACT
self.Syd = Point(-33.93479, 151.16794) # Sydney Airport
self.Nadi = Point(-17.75330, 177.45148) # Nadi Airport
self.Kobenhavn = Point(55.70248, 12.58364) # Kobenhavn, Denmark
self.Muncar = Point(-8.43, 114.33) # Muncar, Indonesia
def testBearingNorth(self):
"""Bearing due north (0 deg) correct within double precision
"""
eps = 1.0e-12
p1 = Point(0.0, 0.0)
p2 = Point(1.0, 0.0)
b = p1.bearing_to(p2)
msg = 'Computed northward bearing: %d, Should have been: %d' % (b, 0)
assert numpy.allclose(b, 0, rtol=eps, atol=eps), msg
def testBearingSouth(self):
"""Bearing due south (180 deg) is correct within double precision
"""
eps = 1.0e-12
B = 180 # True bearing
p1 = Point(0.0, 0.0)
p2 = Point(1.0, 0.0)
b = p2.bearing_to(p1)
msg = 'Computed southward bearing %d. Expected %d' % (b, B)
assert numpy.allclose(b, B, rtol=eps, atol=eps), msg
def testBearingEast(self):
"""Bearing due west (270 deg) is correct within double precision
"""
eps = 1.0e-12
B = 90 # True bearing
p1 = Point(0.0, 0.0)
p3 = Point(0.0, 1.0)
b = p1.bearing_to(p3)
msg = 'Computed southward bearing %d. Expected %d' % (b, B)
assert numpy.allclose(b, B, rtol=eps, atol=eps), msg
def testBearingWest(self):
"""Bearing due west (270 deg) is correct within double precision
"""
eps = 1.0e-12
B = 270 # True bearing
p1 = Point(0.0, 0.0)
p3 = Point(0.0, 1.0)
b = p3.bearing_to(p1)
msg = 'Computed southward bearing %d. Expected %d' % (b, B)
assert numpy.allclose(b, B, rtol=eps, atol=eps), msg
def testRSISE2Home(self):
"""Distance and bearing of real example (RSISE -> Home) are correct
"""
D = 2068.855 # True Distance to Home
B = 11 # True Bearing to Home
d = self.RSISE.distance_to(self.Home)
msg = 'Dist from RSISE to Home %f. Expected %f' % (d, D)
assert numpy.allclose(d, D, rtol=1.0e-6), msg
b = self.RSISE.bearing_to(self.Home)
msg = 'Bearing from RSISE to Home %i. Expected %i' % (b, B)
assert b == B, msg
def testRSISE2Sydney(self):
"""Distance and bearing of real example (RSISE -> Syd) are correct
"""
D = 239407.67 # True Distance to Sydney Airport
B = 52 # True Bearing to Sydney Airport
d = self.RSISE.distance_to(self.Syd)
msg = 'Dist from RSISE to Sydney airport %f. Expected %f' % (d, D)
assert numpy.allclose(d, D, rtol=1.0e-6), msg
b = self.RSISE.bearing_to(self.Syd)
msg = 'Bearing from RSISE to Sydney airport %i. Expected %i' % (b, B)
assert b == B, msg
def testRSISE2Nadi(self):
"""Distance and bearing of real example (RSISE -> Nadi) are correct
"""
D = 3406100 # True Distance to Nadi Airport
B = 63 # True Bearing to Nadi Airport
d = self.RSISE.distance_to(self.Nadi)
msg = 'Dist from RSISE to Nadi airport %f. Expected %f' % (d, D)
assert numpy.allclose(d, D, rtol=1.0e-4), msg
b = self.RSISE.bearing_to(self.Nadi)
msg = 'Bearing from RSISE to Nadi airport %i. Expected %i' % (b, B)
assert b == B, msg
def testRSISE2Kobenhavn(self):
"""Distance and bearing of real example (RSISE -> Kbh) are correct
"""
D = 16025 * 1000 # True Distance to Kobenhavn
B = 319 # True Bearing to Kobenhavn
d = self.RSISE.distance_to(self.Kobenhavn)
msg = 'Dist from RSISE to Kobenhavn %f. Expected %f' % (d, D)
assert numpy.allclose(d, D, rtol=1.0e-3), msg
b = self.RSISE.bearing_to(self.Kobenhavn)
msg = 'Bearing from RSISE to Nadi airport %i. Expected %i' % (b, B)
assert b == B, msg
def testEarthquake2Muncar(self):
"""Distance and bearing of real example (quake -> Muncar) are correct
"""
# Test data from http://www.movable-type.co.uk/scripts/latlong.html
D = 151318 # True Distance [m]
B = 26 # 26 19 42 / 26 13 57 # Bearing to between points (start, end)
p1 = Point(latitude=-9.65, longitude=113.72)
d = p1.distance_to(self.Muncar)
msg = 'Dist to Muncar failed %f. Expected %f' % (d, D)
assert numpy.allclose(d, D), msg
b = p1.bearing_to(self.Muncar)
msg = 'Bearing to Muncar %i. Expected %i' % (b, B)
assert b == B, msg
def test_equator_example(self):
"""Distance and bearing of real example (near equator) are correct
"""
# Test data from http://www.movable-type.co.uk/scripts/latlong.html
D = 11448.0959593 # True Distance [m]
p1 = Point(latitude=-0.59, longitude=117.10)
p2 = Point(latitude=-0.50, longitude=117.15)
d = p1.distance_to(p2)
msg = 'Dist to point failed %f. Expected %f' % (d, D)
assert numpy.allclose(d, D, rtol=1.0e-3), msg
class TestCase(unittest.TestCase):
def setUp(self):
self.eps = 0.001 # Accept 0.1 % relative error
self.RSISE = Point(-35.27456, 149.12065)
self.Home = Point(-35.25629, 149.12494) # 28 Scrivener Street, ACT
self.Syd = Point(-33.93479, 151.16794) # Sydney Airport
self.Nadi = Point(-17.75330, 177.45148) # Nadi Airport
self.Kobenhavn = Point(55.70248, 12.58364) # Kobenhavn, Denmark
self.Muncar = Point(-8.43, 114.33) # Muncar, Indonesia
def testBearingNorth(self):
"""Bearing due north (0 deg) correct within double precision
"""
eps = 1.0e-12
p1 = Point(0.0, 0.0)
p2 = Point(1.0, 0.0)
b = p1.bearing_to(p2)
msg = 'Computed northward bearing: %d, Should have been: %d' % (b, 0)
assert numpy.allclose(b, 0, rtol=eps, atol=eps), msg
def testBearingSouth(self):
"""Bearing due south (180 deg) is correct within double precision
"""
eps = 1.0e-12
B = 180 # True bearing
p1 = Point(0.0, 0.0)
p2 = Point(1.0, 0.0)
b = p2.bearing_to(p1)
msg = 'Computed southward bearing %d. Expected %d' % (b, B)
assert numpy.allclose(b, B, rtol=eps, atol=eps), msg
def testBearingEast(self):
"""Bearing due west (270 deg) is correct within double precision
"""
eps = 1.0e-12
B = 90 # True bearing
p1 = Point(0.0, 0.0)
p3 = Point(0.0, 1.0)
b = p1.bearing_to(p3)
msg = 'Computed southward bearing %d. Expected %d' % (b, B)
assert numpy.allclose(b, B, rtol=eps, atol=eps), msg
def testBearingWest(self):
"""Bearing due west (270 deg) is correct within double precision
"""
eps = 1.0e-12
B = 270 # True bearing
p1 = Point(0.0, 0.0)
p3 = Point(0.0, 1.0)
b = p3.bearing_to(p1)
msg = 'Computed southward bearing %d. Expected %d' % (b, B)
assert numpy.allclose(b, B, rtol=eps, atol=eps), msg
def testRSISE2Home(self):
"""Distance and bearing of real example (RSISE -> Home) are correct
"""
D = 2068.855 # True Distance to Home
B = 11 # True Bearing to Home
d = self.RSISE.distance_to(self.Home)
msg = 'Dist from RSISE to Home %f. Expected %f' % (d, D)
assert numpy.allclose(d, D, rtol=1.0e-6), msg
b = self.RSISE.bearing_to(self.Home)
msg = 'Bearing from RSISE to Home %i. Expected %i' % (b, B)
assert b == B, msg
def testRSISE2Sydney(self):
"""Distance and bearing of real example (RSISE -> Syd) are correct
"""
D = 239407.67 # True Distance to Sydney Airport
B = 52 # True Bearing to Sydney Airport
d = self.RSISE.distance_to(self.Syd)
msg = 'Dist from RSISE to Sydney airport %f. Expected %f' % (d, D)
assert numpy.allclose(d, D, rtol=1.0e-6), msg
b = self.RSISE.bearing_to(self.Syd)
msg = 'Bearing from RSISE to Sydney airport %i. Expected %i' % (b, B)
assert b == B, msg
def testRSISE2Nadi(self):
"""Distance and bearing of real example (RSISE -> Nadi) are correct
"""
D = 3406100 # True Distance to Nadi Airport
B = 63 # True Bearing to Nadi Airport
d = self.RSISE.distance_to(self.Nadi)
msg = 'Dist from RSISE to Nadi airport %f. Expected %f' % (d, D)
assert numpy.allclose(d, D, rtol=1.0e-4), msg
b = self.RSISE.bearing_to(self.Nadi)
msg = 'Bearing from RSISE to Nadi airport %i. Expected %i' % (b, B)
assert b == B, msg
def testRSISE2Kobenhavn(self):
"""Distance and bearing of real example (RSISE -> Kbh) are correct
"""
D = 16025 * 1000 # True Distance to Kobenhavn
B = 319 # True Bearing to Kobenhavn
d = self.RSISE.distance_to(self.Kobenhavn)
msg = 'Dist from RSISE to Kobenhavn %f. Expected %f' % (d, D)
assert numpy.allclose(d, D, rtol=1.0e-3), msg
b = self.RSISE.bearing_to(self.Kobenhavn)
msg = 'Bearing from RSISE to Nadi airport %i. Expected %i' % (b, B)
assert b == B, msg
def testEarthquake2Muncar(self):
"""Distance and bearing of real example (quake -> Muncar) are correct
"""
# Test data from http://www.movable-type.co.uk/scripts/latlong.html
D = 151318 # True Distance [m]
B = 26 # 26 19 42 / 26 13 57 # Bearing to between points (start, end)
p1 = Point(latitude=-9.65, longitude=113.72)
d = p1.distance_to(self.Muncar)
msg = 'Dist to Muncar failed %f. Expected %f' % (d, D)
assert numpy.allclose(d, D), msg
b = p1.bearing_to(self.Muncar)
msg = 'Bearing to Muncar %i. Expected %i' % (b, B)
assert b == B, msg
def test_equator_example(self):
"""Distance and bearing of real example (near equator) are correct
"""
# Test data from http://www.movable-type.co.uk/scripts/latlong.html
D = 11448.0959593 # True Distance [m]
p1 = Point(latitude=-0.59, longitude=117.10)
p2 = Point(latitude=-0.50, longitude=117.15)
d = p1.distance_to(p2)
msg = 'Dist to point failed %f. Expected %f' % (d, D)
assert numpy.allclose(d, D, rtol=1.0e-3), msg
def test_generate_circle(self):
"""A circle with a given radius can be generated correctly
"""
# Generate a circle around Sydney airport with radius 3km
radius = 3000
C = self.Syd.generate_circle(radius)
# Check distance around the circle
# Note that not every point will be exactly 3000m
# because the circle in defined in geographic coordinates
for c in C:
p = Point(c[1], c[0])
d = self.Syd.distance_to(p)
msg = ('Radius %f not with in expected tolerance. Expected %d' %
(d, radius))
assert numpy.allclose(d, radius, rtol=2.0e-1), msg
def city_info(R, B, path, eve_info):
"""List cities exposed sorted by MMI experienced
Input
R: Bounding box of interest
B: MMI point values from shakemap
path: Location of library data
eve_info: Event info (in this case get epicentre)
"""
# Load raw city information
path = path + "/cities/Indonesia.txt"
A = np.loadtxt(path, dtype={"names": ("lon", "lat", "pop", "name"), "formats": (float, float, float, "S10")})
# Mask of those cities that are inside region of interest (1D boolean array)
mask = (A["lon"] > R[0]) & (A["lon"] < R[1]) & (A["lat"] > R[2]) & (A["lat"] < R[3])
# Get indices of cities in region of interest (1D array of integers)
index = np.nonzero(mask)[0] # Get single array from tuple output
if len(index) == 0:
# No cities were found in region of interest.
# Search entire database for the nearest city
eve_lon = float(eve_info["lon"])
eve_lat = float(eve_info["lat"])
min_dist = sys.maxint
for i in range(len(A)):
start = Point(latitude=A["lat"][i], longitude=A["lon"][i])
end = Point(latitude=eve_lat, longitude=eve_lon)
dis = start.distance_to(end) / 1000
if dis < min_dist:
min_dist = dis
index = i
# Assign MMI 0 to nearest city outside region of interest
A = A[index]
city = [(A["name"], A["pop"], 1, A["lon"], A["lat"])]
else:
# One or more cities were found in region of interest
A = A[index]
# Create grid of MMI values (FIXME: More explanation in here please)
points = B[:, 0:2]
values = B[:, 4]
I = make_grid(points, values, (A["lon"], A["lat"]))
# Create city list with entries: Name, population, MMI, lon, lat
intensity = I.tolist()
name = A["name"].tolist()
pop = A["pop"].tolist()
lon = A["lon"].tolist()
lat = A["lat"].tolist()
city = zip(name, pop, intensity, lon, lat)
# Convert to array and sort by intensity
# (and population if intensity is the same)
city = np.array(city, dtype=city_dtype)
city = np.sort(city, order=["intensity", "population"])
city = np.flipud(city)
return city
