def QueryNC(dbfile, staname=None, yearrange=None, cons=None):
"""
Query the tidal station data
"""
outvar = ["NetCDF_Filename", "NetCDF_GroupID", "StationName", "StationID"]
tablename = "observations"
# condition = "Variable_Name = '%s' and (StationName = '%s' or StationName = '%s' or StationName = '%s')" % (varname,staname1,staname2,staname3 )
# Create the query
varname1 = "ssh_amp"
varname2 = "ssh_phs"
if staname == None and yearrange == None:
condition = "(Variable_Name = '%s' or Variable_Name = '%s')" % (varname1, varname2)
ydim = None
elif not staname == None and yearrange == None:
condition = "(Variable_Name = '%s' or Variable_Name = '%s') and StationName = '%s'" % (
varname1,
varname2,
staname,
)
ydim = "year"
elif not staname == None and not yearrange == None:
t1 = "%s-01-01 00:00:00" % yearrange[0]
t2 = "%4d-01-01 00:00:00" % yearrange[1]
condition = (
"(Variable_Name = '%s' or Variable_Name = '%s') and StationName = '%s' and time_start > %s and time_start < %s"
% (varname1, varname2, staname, t1, t2)
)
ydim = None
elif staname == None and not yearrange == None:
t1 = "%s-01-01 00:00:00" % yearrange[0]
t2 = "%4d-01-01 00:00:00" % yearrange[1]
condition = "(Variable_Name = '%s' or Variable_Name = '%s') and time_start > '%s' and time_start < '%s'" % (
varname1,
varname2,
t1,
t2,
)
ydim = "station"
data, query = netcdfio.queryNC(dbfile, outvar, tablename, condition, fastmode=True)
# Read the constituents from the netcdf file
ncfile = query["NetCDF_Filename"][0]
nc = Dataset(ncfile, "r")
# names = nc.__dict__.keys()
names = nc.Tidal_Constituents.split(", ")
# print nc.['Tidal Constituents']
nc.close()
# Find the constituent indices
if cons == None:
cons = names
ind = []
for nn in cons:
ind.append((i for i, j in enumerate(names) if j == nn).next())
# Output the query data into a nicer format
# amp = [if dd.has_key('ssh_amp'): dd['ssh_amp'][[1,3,8]].ravel() for dd in data]
amp = []
phs = []
time = []
lon = []
lat = []
StationName = []
for ii, dd in enumerate(data):
if dd.has_key("ssh_amp"):
amp.append(dd["ssh_amp"][ind].ravel())
if ydim == "year":
time.append(dd["time"][0])
elif ydim == "station":
lon.append(dd["longitude"])
lat.append(dd["latitude"])
StationName.append(query["StationName"][ii])
else:
lon.append(dd["longitude"])
lat.append(dd["latitude"])
StationName.append(query["StationName"][ii])
time.append(dd["time"][0])
if dd.has_key("ssh_phs"):
phs.append(dd["ssh_phs"][ind].ravel())
amp = np.array(amp)
phs = np.array(phs)
# Get the time and station coordinates
if ydim == "station":
time = data[0]["time"][0]
lon = np.array(lon)
lat = np.array(lat)
elif ydim == "year":
lon = data[0]["longitude"]
lat = data[0]["latitude"]
StationName = query["StationName"][0]
time = np.array(time)
return amp, phs, time, lon, lat, StationName, cons
def loadDBstation(dbfile, stationName, varname, timeinfo=None, \
filttype=None,cutoff=3600.0,output_meta=False,method='linear'):
"""
Load station data from a database file
Inputs:
dbfile - location of database file
stationName - StationName in database
varname - variable name e.g. 'waterlevel', 'discharge', 'salinity'
timeinfo (optional) - tuple with (starttime,endtime,dt). Format 'yyyymmdd.HHMMSS'
Use this to interpolate onto a constant time vector
filttype (optional) - 'low' or 'high'
Set this to filter data
Returns:
timeseries object
-1 on error
"""
outvar = ['NetCDF_Filename','NetCDF_GroupID','StationName']
tablename = 'observations'
#condition = 'Variable_Name = "%s" and StationID = "%s"' % (varname,stationID)
condition = 'Variable_Name = "%s" and StationName LIKE "%%%s%%"' % (varname,stationName)
print 'Querying database...'
print condition
data, query = queryNC(dbfile,outvar,tablename,condition)
yout = data[0][varname].squeeze()
# Zero nan
yout[np.isnan(yout)] = 0.0
if len(data)==0:
print '!!! Warning - Did not find any stations matching query. Returning -1 !!!'
return -1
else:
ts = timeseries(data[0]['time'],yout)
if not timeinfo==None:
print 'Interpolating station data between %s and %s\n'%(timeinfo[0],timeinfo[1])
tnew,ynew =\
ts.interp((timeinfo[0],timeinfo[1],timeinfo[2]),method=method)
ts = timeseries(tnew,ynew)
ts.dt = timeinfo[2] # This needs updating
if not filttype==None:
print '%s-pass filtering output data. Cutoff period = %f [s].'%(filttype,cutoff)
yfilt = ts.filt(cutoff,btype=filttype,axis=-1)
ts.y = yfilt.copy()
if output_meta:
if data[0].has_key('elevation'):
ele = data[0]['elevation']
else:
ele = np.array([0.0])
meta = {'longitude':data[0]['longitude'],'latitude':data[0]['latitude'],'elevation':ele,'StationName':query['StationName'][0]}
return ts, meta
else:
return ts
def QueryNC(dbfile,staname=None,yearrange=None,cons=None):
"""
Query the tidal station data
"""
outvar = ['NetCDF_Filename','NetCDF_GroupID','StationName','StationID']
tablename = 'observations'
#condition = "Variable_Name = '%s' and (StationName = '%s' or StationName = '%s' or StationName = '%s')" % (varname,staname1,staname2,staname3 )
# Create the query
varname1 = 'ssh_amp'
varname2 = 'ssh_phs'
if staname == None and yearrange == None:
condition = "(Variable_Name = '%s' or Variable_Name = '%s')"%(varname1,varname2)
ydim = None
elif not staname == None and yearrange == None:
condition = "(Variable_Name = '%s' or Variable_Name = '%s') and StationName = '%s'"%(varname1,varname2, staname)
ydim = 'year'
elif not staname == None and not yearrange == None:
t1 = '%s-01-01 00:00:00'%yearrange[0]
t2 = '%4d-01-01 00:00:00'%yearrange[1]
condition = "(Variable_Name = '%s' or Variable_Name = '%s') and StationName = '%s' and time_start > %s and time_start < %s"%(varname1,varname2,staname,t1,t2)
ydim = None
elif staname == None and not yearrange == None:
t1 = '%s-01-01 00:00:00'%yearrange[0]
t2 = '%4d-01-01 00:00:00'%yearrange[1]
condition = "(Variable_Name = '%s' or Variable_Name = '%s') and time_start > '%s' and time_start < '%s'"%(varname1,varname2,t1,t2)
ydim = 'station'
data, query = netcdfio.queryNC(dbfile,outvar,tablename,condition,fastmode=True)
# Read the constituents from the netcdf file
ncfile = query['NetCDF_Filename'][0]
nc = Dataset(ncfile,'r')
#names = nc.__dict__.keys()
names = nc.Tidal_Constituents.split(', ')
#print nc.['Tidal Constituents']
nc.close()
# Find the constituent indices
if cons == None:
cons=names
ind = []
for nn in cons:
ind.append(next((i for i, j in enumerate(names) if j == nn)))
# Output the query data into a nicer format
#amp = [if dd.has_key('ssh_amp'): dd['ssh_amp'][[1,3,8]].ravel() for dd in data]
amp = []
phs = []
time = []
lon = []
lat = []
StationName=[]
for ii,dd in enumerate(data):
if 'ssh_amp' in dd:
amp.append(dd['ssh_amp'][ind].ravel())
if ydim == 'year':
time.append(dd['time'][0])
elif ydim == 'station':
lon.append(dd['longitude'])
lat.append(dd['latitude'])
StationName.append(query['StationName'][ii])
else:
lon.append(dd['longitude'])
lat.append(dd['latitude'])
StationName.append(query['StationName'][ii])
time.append(dd['time'][0])
if 'ssh_phs' in dd:
phs.append(dd['ssh_phs'][ind].ravel())
amp = np.array(amp)
phs = np.array(phs)
# Get the time and station coordinates
if ydim == 'station':
time = data[0]['time'][0]
lon = np.array(lon)
lat = np.array(lat)
elif ydim == 'year':
lon = data[0]['longitude']
lat = data[0]['latitude']
StationName = query['StationName'][0]
time = np.array(time)
return amp, phs, time, lon, lat, StationName, cons
