def cruiseSelector(self, var,Cruisename):
'''
Returns a profile list by selecting for
variable (string) and
Cruisename (string)
Returns a profile list
'''
iCruise = find_index(Cruisename, self.CRUISES)
ivar = find_index(var, self.VARIABLES)
values= self.DATA[ivar,:]
good = (values < 1e+19) & (values > 0)
ii = self.DATA[-1,:] == (iCruise+1)
Selected = good & ii
year = self.DATA[ 0,Selected]
month = self.DATA[ 1,Selected]
day = self.DATA[ 2,Selected]
lat = self.DATA[ 3,Selected]
lon = self.DATA[ 4,Selected]
depth = self.DATA[ 5,Selected]
dataset = self.DATA[-1,Selected]
values = values[Selected]
nValues=values.size
TIME = np.zeros((nValues), dtype=np.int32)
for i in range(nValues):
time = datetime.datetime(year[i],month[i],day[i])
TIME[i] = time.toordinal()
return self.profileGenerator(TIME, lon, lat, values, depth, dataset)
def stationSelector(self, var,stationname):
'''
Returns a profile list by selecting for
variable (string) and
stationname(string)
Returns a profile list
'''
print('-------------------------------------------')
print('NON ancora testato, potrebbe NON funzionare')
print('-------------------------------------------')
iStation= find_index(stationname, self.STATIONS)
ivar = find_index(var, self.VARIABLES)
values= self.DATA[ivar,:]
good = (values < 1e+19) & (values > 0)
ii = self.DATA[-1,:] == (iStation+1)
Selected = good & ii
year = self.DATA[ 0,Selected]
month = self.DATA[ 1,Selected]
day = self.DATA[ 2,Selected]
lat = self.DATA[ 3,Selected]
lon = self.DATA[ 4,Selected]
depth = self.DATA[ 5,Selected]
dataset = self.DATA[-1,Selected]
values = values[Selected]
nValues=values.size
TIME = np.zeros((nValues), dtype=np.int32)
for i in range(nValues):
time = datetime.datetime(year[i],month[i],day[i])
TIME[i] = time.toordinal()
return self.profileGenerator(TIME, lon, lat, values, depth, dataset)
def __init__(self):
'''
Reads the NetCDF Dataset
'''
self.filename="/gss/gss_work/DRES_OGS_BiGe/Observations/TIME_RAW_DATA/STATIC/Carbon/Dataset_Med_CarbSys.nc"
self.DataExtractor = DatasetExtractor(self.filename)
# DATA ELIMINATION in order to not duplicate values with nutrients dataset
for cruisename in ['METEOR','METEOR51', 'METEOR95','PROSOPE']:
iCruise = find_index(cruisename, self.DataExtractor.CRUISES)
for var in ['nitrate','phosphate','silicate','oxygen']:
ivar = find_index(var, self.DataExtractor.VARIABLES)
ii = self.DataExtractor.DATA[-1,:] == (iCruise+1)
self.DataExtractor.DATA[ivar,ii] = -999.0
def selector(self,var,T_int, region):
'''
Returns a profile list by selecting for
variable (string),
T_int (TimeInterval object)
region (region object)
'''
ivar = find_index(var, self.VARIABLES)
values= self.DATA[ivar,:]
units = self.UNITS[ivar,:].tostring()
if units =="\\mumol/kg":
itemp = find_index('temp' , self.VARIABLES)
ipsal = find_index('salinity', self.VARIABLES)
idens = find_index('density' , self.VARIABLES)
temp = self.DATA[itemp,:]
sali = self.DATA[ipsal,:]
pres = self.DATA[5,:]
dens = self.DATA[idens,:]
good_rho = (sali < 1.e+19 ) & (sali>0) & (temp < 1.e+19 ) & (temp>0) & (pres < 1.e+19 ) & (pres>0)
t = T90conv(temp)
n = len(values)
calculated_rho = np.ones((n),np.float32)*np.nan
assumed_density = np.ones((n),np.float32)*np.nan
calculated_rho[good_rho] = seawater.dens(sali[good_rho],t[good_rho],pres[good_rho])
good_dens = (dens < 1.e+19 ) & (dens>0)
for i in range(n):
if good_dens[i]:
assumed_density[i] = dens[i]
else:
if good_rho[i]:
assumed_density[i] = calculated_rho[i]
good = ~np.isnan(assumed_density)
values[good] = values[good] * assumed_density[good] /1000.
values[~good] = 1.e+20
good = (values < 1e+19) & (values > 0)
values = values[good]
year = self.DATA[ 0,good]
month = self.DATA[ 1,good]
day = self.DATA[ 2,good]
lat = self.DATA[ 3,good]
lon = self.DATA[ 4,good]
depth = self.DATA[ 5,good]
dataset = self.DATA[-1,good]
nValues=values.size
Selected = np.zeros((nValues,),dtype=np.bool)
TIME = np.zeros((nValues), dtype=np.int32)
for i in range(nValues):
time = datetime.datetime(year[i],month[i],day[i])
TIME[i] = time.toordinal()
if T_int.contains(time) & region.is_inside(lon[i], lat[i]):
Selected[i] = True
Time = TIME[Selected]
Lon = lon[Selected]
Lat = lat[Selected]
values = values[Selected]
depth = depth[Selected]
dataset = dataset[Selected]
return self.profileGenerator(Time, Lon, Lat, values, depth, dataset)
