' ', 'Wind speed(m/s)', 'Wave height(m)', 'Bottom temperature(degC)',
'current'
]
dist_emolt, data_emolt, emolt_name = get_emolt_data(alon, alat)
start_time, end_time = min(data_emolt['time']), max(data_emolt['time'])
if method == 'bottom temperature':
url = 'http://tds.marine.rutgers.edu:8080/thredds/dodsC/roms/mabgom/v6/avg'
try:
nc = netCDF4.Dataset(url)
lons = nc.variables['lon_rho'][:]
lats = nc.variables['lat_rho'][:]
time = nc.variables['ocean_time'][:]
temp = nc.variables['temp']
Dist = []
for i in range(len(lons[:])):
Dist.append(DIST(lons[i], lats[i], alon,
alat)) #calculate distance
index_nearest = np.argmin(Dist) #find index of nearest distance
index_one, index_two = index_nearest / len(
lons[0]), index_nearest % len(lons[0])
depth_model = nc.variables['h'][index_one][
index_two] #get depth of roms
t1 = (start_time - datetime.datetime(1858, 11, 17)).total_seconds()
t2 = (end_time - datetime.datetime(1858, 11, 17)).total_seconds()
print('bb')
nearest_s, nearest_e = np.argmin(abs(time - t1)), np.argmin(
abs(time - t2))
T = []
for i in time[nearest_s:nearest_e]:
t = datetime.datetime(1858, 11, 17) + datetime.timedelta(seconds=i)
T.append(t.date())
TEMP = temp[nearest_s:nearest_e, -1, index_one, index_two]
'current'
]
way = ['', 'wind', 'wave', 'bottom_temp', 'current']
dist_emolt, data_emolt, emolt_name = get_emolt_data(alon, alat)
start_time, end_time = min(data_emolt['time']), max(data_emolt['time'])
if method == 'bottom temperature':
url = 'http://www.smast.umassd.edu:8080/thredds/dodsC/fvcom/hindcasts/30yr_gom3/mean'
try:
nc = netCDF4.Dataset(url)
lons = nc.variables['lon'][:]
lats = nc.variables['lat'][:]
time = nc.variables['time'][:]
temp = nc.variables['temp']
Dist = []
for i in range(len(lons[:])):
Dist.append(DIST(lons[i], lats[i], alon, alat))
index_nearest = np.argmin(Dist)
depth_fvcom = nc.variables['h'][index_nearest] #get depth of fvcom
t1 = (start_time -
datetime.datetime(1858, 11, 17)).total_seconds() / 3600 / 24
t2 = (end_time -
datetime.datetime(1858, 11, 17)).total_seconds() / 3600 / 24
nearest_s, nearest_e = np.argmin(abs(time - t1)), np.argmin(
abs(time - t2))
T = []
for i in time[nearest_s:nearest_e]:
t = datetime.datetime(1858, 11,
17) + datetime.timedelta(days=int(i))
T.append(t.date())
TEMP = temp[nearest_s:nearest_e, -1, index_nearest]
TEMP_f = []
]
way = ['', 'wind', 'wave', 'bottom_temp', 'current']
if method == 'wind':
url = 'http://www.smast.umassd.edu:8080/thredds/dodsC/models/fvcom/NECOFS/Forecasts/NECOFS_MET_FORECAST.nc'
try:
nc = netCDF4.Dataset(url)
lons = nc.variables['XLONG'][:]
lats = nc.variables['XLAT'][:]
time = nc.variables['Times'][:]
u = nc.variables['U10'][:]
v = nc.variables['V10'][:]
Dist = []
for i in range(len(lons[:])):
for j in range(len(lons[0])):
Dist.append(
DIST(lons[i][j], lats[i][j], lon_i[sites[site][0]],
lat_i[sites[site][1]]))
index_nearest = np.argmin(Dist) # get smallest one
index_one, index_two = index_nearest / len(
lons[0]), index_nearest % (len(lons[0]))
wind = []
for i in range(len(time)):
U = u[i][index_one][index_two]
V = v[i][index_one][index_two]
s = np.sqrt(U * U + V * V)
wind.append(s)
T = []
for i in range(len(time)):
t = ''
for j in range(len(time[i])):
t = t + str(time[i][j])
t = datetime.datetime.strptime(t, "%Y-%m-%d_%H:%M:%S")