def waternode(self, lon, lat, depth, url):
'''
return points
'''
data = self.get_data(url)
nodes = dict(temp=[])
mask = data['mask_rho'][:]
lon_rho = data['lon_rho'][:]
lat_rho = data['lat_rho'][:]
lons = jata.shrink(lon_rho, mask[1:,1:].shape)
lats = jata.shrink(lat_rho, mask[1:,1:].shape)
print 'finding the nearest node ...'
index, nearestdistance = self.nearest_point_index(lon,lat,lons,lats)
index=[index[0][0],index[1][0]]
depth_layers = data['h'][index[0]][index[1]]*data['s_rho']
layer = np.argmin(abs(depth_layers-depth))
print 'extracting modeled time'
ot=data['ocean_time'][:]
print len(ot)
otdt=[] # datetime version of ocean_time
for k in range(len(ot)):
otdt.append(dt(2006,1,1,0,0)+td(seconds=ot[k]))
print 'extracting modeled temperature for this depth and site'
nodes=data['temp'][:,layer,index[0],index[1]]
modtso=pd.DataFrame(nodes, index=otdt)
return modtso
def __waternode(self, lon, lat, url):
'''
return points
'''
self.data = self.get_data(url)
nodes = dict(lon=lon, lat=lat)
mask = self.data['mask_rho'][:]
lon_rho = self.data['lon_rho'][:]
lat_rho = self.data['lat_rho'][:]
u = self.data['u'][:,-1]
v = self.data['v'][:,-1]
lons = jata.shrink(lon_rho, mask[1:,1:].shape)
lats = jata.shrink(lat_rho, mask[1:,1:].shape)
print 'lons', len(lons),len(lons[0])
for i in range(0, self.hours):
print 'roms',i
u_t = jata.shrink(u[i], mask[1:,1:].shape)
v_t = jata.shrink(v[i], mask[1:,1:].shape)
index, nearestdistance = self.nearest_point_index(lon,lat,lons,lats)
print 'index', index
print 'u_t', len(u_t), len(u_t[0])
u_p = u_t[index[0]][index[1]]
v_p = v_t[index[0]][index[1]]
'''
for ut, vt in zip(u_p, v_p):
if ut:
break
if not ut:
# raise Exception('point hit the land')
print 'point hit the land'
break
if not ut:
print 'point hit the land'
break
u_p = u_t[index[0]][index[1]]
v_p = v_t[index[0]][index[1]]
'''
if not u_p:
print 'point hit the land'
break
dx = 60*60*float(u_p)
dy = 60*60*float(v_p)
lon = lon + dx/(111111*np.cos(lat*np.pi/180))
lat = lat + dy/111111
nodes['lon'] = np.append(nodes['lon'],lon)
nodes['lat'] = np.append(nodes['lat'],lat)
return nodes
