def getFVCOM_depth(lati, loni): # vname='temp'or'salinity'
"""
Function written by Jim Manning
generates model depth data as a DataFrame
"""
urlfvcom = "http://www.smast.umassd.edu:8080/thredds/dodsC/fvcom/hindcasts/30yr_gom3"
nc = netCDF4.Dataset(urlfvcom)
nc.variables
lat = nc.variables["lat"][:]
lon = nc.variables["lon"][:]
dep = nc.variables["h"][:]
inode = nearlonlat(lon, lat, loni, lati)
return dep[inode]
def getFVCOM_bottom_tempsalt_netcdf(lati, loni, starttime, endtime, layer, vname): # vname='temp'or'salinity'
"""
Function written by Yacheng Wang
generates model data as a DataFrame
according to time and local position
different from getFVCOM_bottom_temp:
this function only return time-temp dataframe and ues netcdf4
getFVCOM_bottom_temp return depth and temp
"""
urlfvcom = "http://www.smast.umassd.edu:8080/thredds/dodsC/fvcom/hindcasts/30yr_gom3"
nc = netCDF4.Dataset(urlfvcom)
nc.variables
lat = nc.variables["lat"][:]
lon = nc.variables["lon"][:]
times = nc.variables["time"]
jd = netCDF4.num2date(times[:], times.units)
var = nc.variables[vname]
inode = nearlonlat(lon, lat, loni, lati)
modindex = netCDF4.date2index([starttime, endtime], times, select="nearest")
modtso = pd.DataFrame(var[modindex[0] : modindex[1], layer, inode], index=jd[modindex[0] : modindex[1]])
return modtso
def getFVCOM_bottom_tempsalt_netcdf(lati,loni,starttime,endtime,layer,vname):#vname='temp'or'salinity'
'''
generate mod data as a DataFrame
according to time and local position
different from getFVCOM_bottom_temp:
this function only return time-temp dataframe and ues netcdf4
getFVCOM_bottom_temp return depth and temp
'''
urlfvcom = 'http://www.smast.umassd.edu:8080/thredds/dodsC/fvcom/hindcasts/30yr_gom3'
nc = netCDF4.Dataset(urlfvcom)
nc.variables
lat = nc.variables['lat'][:]
lon = nc.variables['lon'][:]
times = nc.variables['time']
jd = netCDF4.num2date(times[:],times.units)
var = nc.variables[vname]
print 'Now find the coincide timestample'
inode = nearlonlat(lon,lat,loni,lati)
print inode
modindex=netCDF4.date2index([starttime,endtime],times,select='nearest')
modtso=pd.DataFrame(var[modindex[0]:modindex[1],layer,inode],index=jd[modindex[0]:modindex[1]])
return modtso
