def getClosest(elat, elon, etime, eventlist):
dmin = 9999999
tmin = 9999999
azmin = 9999999
imin = -1
for i in range(0, len(eventlist)):
event = eventlist[i]
lon, lat, depth = event['geometry']['coordinates']
time = datetime.utcfromtimestamp(event['properties']['time'] / 1000)
dd = distance.sdist(elat, elon, lat, lon) / 1000.0
azim = distance.getAzimuth(elat, elon, lat, lon)
if time > etime:
dt = (time - etime).seconds
else:
dt = (etime - time).seconds
if dd < dmin and dt < dmin:
dmin = dd
tmin = dt
azmin = azim
imin = i
event = eventlist[imin]
idlist = event['properties']['ids'].split(',')[1:-1]
eurl = event['properties']['url']
authid = event['id']
idlist.remove(authid)
idlist.append(authid)
idlist = idlist[::-1]
return (idlist, eurl, dmin, tmin, azmin)
def getEventsInCircle(lat, lon, radius, eventlist):
"""
Select earthquakes from a list of events using a lat/lon center and a radius in km.
@param lat: Latitude at center of circle.
@param lon: Longitude at center of circle.
@param radius: Radius of search in km.
@param eventlist: List of event dictionaries, each containing (at least) keys lat,lon,depth,mag.
@return: Filtered list of earthquake dictionaries.
"""
elat = np.array([
e['lat'] for e in eventlist
]) #extract the latitudes from each dictionary in the list
elon = np.array([
e['lon'] for e in eventlist
]) #extract the longitudes from each dictionary in the list
d = sdist(
lat, lon, elat, elon
) / 1000.0 #do vectorized distance calculation from center point to all lat/lon pairs
az = []
for i in range(0, len(elat)):
az.append(getAzimuth(lat, lon, elat[i],
elon[i])) #vectorize the azimuth function someday
for i in range(0, len(eventlist)):
eventlist[i]['distance'] = d[
i] #add distance field to each dictionary in the list
eventlist[i]['azimuth'] = az[
i] #add azimuth field to each dictionary in the list
idx = (d <= radius).nonzero()[
0] #array of indices where distance is less than input threshold
newlist = (np.array(eventlist)[idx]).tolist() #return a shortened list
return newlist
def getClosest(elat,elon,etime,eventlist):
dmin = 9999999
tmin = 9999999
azmin = 9999999
imin = -1
for i in range(0,len(eventlist)):
event = eventlist[i]
lon,lat,depth = event['geometry']['coordinates']
time = datetime.utcfromtimestamp(event['properties']['time']/1000)
dd = distance.sdist(elat,elon,lat,lon)/1000.0
azim = distance.getAzimuth(elat,elon,lat,lon)
if time > etime:
dt = (time - etime).seconds
else:
dt = (etime - time).seconds
if dd < dmin and dt < dmin:
dmin = dd
tmin = dt
azmin = azim
imin = i
event = eventlist[imin]
idlist = event['properties']['ids'].split(',')[1:-1]
eurl = event['properties']['url']
authid = event['id']
idlist.remove(authid)
idlist.append(authid)
idlist = idlist[::-1]
return (idlist,eurl,dmin,tmin,azmin)
def getEventsInEllipse(lat, lon, str, aval, bval, eventlist):
"""
Select earthquakes from a list of events using dist/az from a predefined lat/lon, and axes of an ellipse
getEventsInCircle must already have been used
@param str: Strike of slab at center of circle.
@param aval: Long axis of ellipse in km.
@param bval: Short axis of ellipse in km.
@param eventlist: List of event dictionaries, each containing (at least) keys lat,lon,depth,mag.
@return: Filtered list of earthquake dictionaries.
"""
elat = np.array([
e['lat'] for e in eventlist
]) #extract the latitudes from each dictionary in the list
elon = np.array([
e['lon'] for e in eventlist
]) #extract the longitudes from each dictionary in the list
d = sdist(
lat, lon, elat, elon
) / 1000.0 #do vectorized distance calculation from center point to all lat/lon pairs
az = []
for i in range(0, len(elat)):
az.append(getAzimuth(lat, lon, elat[i],
elon[i])) #vectorize the azimuth function someday
for i in range(0, len(eventlist)):
eventlist[i]['distance'] = d[
i] #add distance field to each dictionary in the list
eventlist[i]['azimuth'] = az[
i] #add azimuth field to each dictionary in the list
# print 'Eventlist[1] = %.4f, %.4f, %.4f, %.4f' % (elat[1],elon[1],d[1],az[1])
mdist = []
erta = math.sqrt(1 - ((math.pow(bval, 2)) / (math.pow(aval, 2))))
# print 'ERTA = %.4f' % (erta)
for i in range(0, len(elat)):
mdist.append(getEllipseRad(aval, erta, az[i], str))
# print 'Lon:', (elon[1:-1])
# print 'Lat:', (elat[1:-1])
# print 'Dist:', (d[1:-1])
# print 'Azi:', (az[1:-1])
# print 'Edist:', (mdist[1:-1])
idx = (d <= mdist).nonzero()[
0] #array of indices where distance is less than input threshold
# print 'Indexes:'
# print (idx)[1:-1]
newerlist = (np.array(eventlist)[idx]).tolist() #return a shortened list
return newerlist
def getEventsInEllipse(lat,lon,str,aval,bval,eventlist):
"""
Select earthquakes from a list of events using dist/az from a predefined lat/lon, and axes of an ellipse
getEventsInCircle must already have been used
@param str: Strike of slab at center of circle.
@param aval: Long axis of ellipse in km.
@param bval: Short axis of ellipse in km.
@param eventlist: List of event dictionaries, each containing (at least) keys lat,lon,depth,mag.
@return: Filtered list of earthquake dictionaries.
"""
elat = np.array([e['lat'] for e in eventlist]) #extract the latitudes from each dictionary in the list
elon = np.array([e['lon'] for e in eventlist]) #extract the longitudes from each dictionary in the list
d = sdist(lat,lon,elat,elon)/1000.0 #do vectorized distance calculation from center point to all lat/lon pairs
az = []
for i in range(0,len(elat)):
az.append(getAzimuth(lat,lon,elat[i],elon[i])) #vectorize the azimuth function someday
for i in range(0,len(eventlist)):
eventlist[i]['distance'] = d[i] #add distance field to each dictionary in the list
eventlist[i]['azimuth'] = az[i] #add azimuth field to each dictionary in the list
# print 'Eventlist[1] = %.4f, %.4f, %.4f, %.4f' % (elat[1],elon[1],d[1],az[1])
mdist = []
erta = math.sqrt(1-((math.pow(bval,2))/(math.pow(aval,2))))
# print 'ERTA = %.4f' % (erta)
for i in range(0,len(elat)):
mdist.append(getEllipseRad(aval,erta,az[i],str))
# print 'Lon:', (elon[1:-1])
# print 'Lat:', (elat[1:-1])
# print 'Dist:', (d[1:-1])
# print 'Azi:', (az[1:-1])
# print 'Edist:', (mdist[1:-1])
idx = (d <= mdist).nonzero()[0] #array of indices where distance is less than input threshold
# print 'Indexes:'
# print (idx)[1:-1]
newerlist = (np.array(eventlist)[idx]).tolist() #return a shortened list
return newerlist
def getEventsInCircle(lat,lon,radius,eventlist):
"""
Select earthquakes from a list of events using a lat/lon center and a radius in km.
@param lat: Latitude at center of circle.
@param lon: Longitude at center of circle.
@param radius: Radius of search in km.
@param eventlist: List of event dictionaries, each containing (at least) keys lat,lon,depth,mag.
@return: Filtered list of earthquake dictionaries.
"""
elat = np.array([e['lat'] for e in eventlist]) #extract the latitudes from each dictionary in the list
elon = np.array([e['lon'] for e in eventlist]) #extract the longitudes from each dictionary in the list
d = sdist(lat,lon,elat,elon)/1000.0 #do vectorized distance calculation from center point to all lat/lon pairs
az = []
for i in range(0,len(elat)):
az.append(getAzimuth(lat,lon,elat[i],elon[i])) #vectorize the azimuth function someday
for i in range(0,len(eventlist)):
eventlist[i]['distance'] = d[i] #add distance field to each dictionary in the list
eventlist[i]['azimuth'] = az[i] #add azimuth field to each dictionary in the list
idx = (d <= radius).nonzero()[0] #array of indices where distance is less than input threshold
newlist = (np.array(eventlist)[idx]).tolist() #return a shortened list
return newlist