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Update of get_data and calc_ref_state: running version to read data

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Gabriel Wolf 2018-09-17 09:43:16 +01:00
parent 83e22a0440
commit 3b698337d6
3 changed files with 72 additions and 28 deletions
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6
calc_ref_state.py
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@ -26,6 +26,7 @@ variables = {'s':{},'theta':{},'grd':[],'valid':[]}
# Input 1 ####################################################################################
# Physical constants
# input : None
# output : r_earth, rho0, grav, gbuo
# r_earth : earth radis [m]
# rho0 : reference density [kg m**-3]
@ -33,10 +34,7 @@ variables = {'s':{},'theta':{},'grd':[],'valid':[]}
# gbuo :
# PHYSICAL CONSTATS MISSING
# ############################################################################################
r_earth = 6.4e06
rho0 = 1027.0
grav = 9.81
gbuo = -grav/rho0
# constants stored in myconstants.py
# step a #####################################################################################
# Read necessary data to calculate reference state

94
get_data.py
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@ -1,5 +1,5 @@
def get_data_woa2009(variables):
# get_data_woa2009(variables) ############################################################
def get_data_woa2009(variables,grid_order=('lon','lat','z','time',)):
# get_data_woa2009(variables,grid_order) #################################################
# written by : Gabriel Wolf, g.a.wolf@reading.ac.uk
# adapted from get_woa2009_data.m of Remi Tailleux
# last modified : 13.09.2018
@ -16,14 +16,19 @@ def get_data_woa2009(variables):
# Johnson, 2010: World Ocean Atlas 2009, Volume 2: Salinity. S. Levitus,
# Ed. NOAA Atlas NESDIS 69, 184 pp.
# -> PDF : https://www.nodc.noaa.gov/OC5/indpub.html#woa09
# #######################################################################################
# ########################################################################################
print 'Use of get_data_woa2009 in get_data.py'
dir_data = '/glusterfs/inspect/users/xg911182/data/WOA2009/'
grid_names = ('lon','lat','depth','time',)
# import modules
import numpy as np
from netCDF4 import Dataset # to read netcdf files
from mydata_classes import Grid
from netCDF4 import Dataset # to read netcdf files
from mydata_classes import Grid # class containing grid information
import myconstants as my_const # my own defined constants
from mycalc_ocean import calc_theta_from_temp
# define grid_order (used for data permutation)
find_index = lambda searchlist, elem: [[i for i, x in enumerate(searchlist) if x == e] for e in elem]
grid_order = np.squeeze(np.array(find_index(('lon','lat','z','time',),grid_order)))
# Allocation
data = {}
grd = []
@ -42,35 +47,76 @@ def get_data_woa2009(variables):
Uz = nc_fid.variables[grid_names[2]].units
Ut = nc_fid.variables[grid_names[3]].units
grd = Grid(LON,LAT,Z,TIME,len(LON),len(LAT),len(Z),len(TIME), Ulon, Ulat, Uz, Ut)
# define data permutation to match input dimensions
nc_fid.variables['t_an'].dimensions
# read salinity data
if 's' in list_allkeys:
print 'Load salinity data'
fn = dir_data + 'salinity_annual_1deg.nc'
nc_fid = Dataset(fn,'r')
# read salinity data
DATA_d = nc_fid.variables['s_an']
MASK = np.array(DATA_d)!=DATA_d._FillValue
data_perm = np.squeeze(np.asarray(find_index(DATA_d.dimensions,[grid_names[i] for i in grid_order])))
varname = 's'
data[varname] = {}
data[varname]['val'] = np.array(DATA_d).transpose(data_perm)
data[varname]['units'] = DATA_d.units
data[varname]['fill_value'] = DATA_d._FillValue
data[varname]['standard_name'] = DATA_d.standard_name
data[varname]['valid'] = MASK.transpose(data_perm)
# Read temperature data
if 'temp' or 'theta' in list_allkeys:
print 'Load temperature data'
fn = dir_data + 'temperature_annual_1deg.nc'
nc_fid = Dataset(fn,'r')
# read temperature data
DATA_d = nc_fid.variables['t_an']
DATA_d = nc_fid.variables['t_an']
data_perm = np.squeeze(np.asarray(find_index(DATA_d.dimensions,[grid_names[i] for i in grid_order])))
TEMP = np.array(DATA_d)
MASK = TEMP!=DATA_d._FillValue
if 'temp' in list_allkeys:
varname = 'temp'
data[varname] = {}
data[varname]['val'] = np.array(DATA_d)
data[varname]['units'] = DATA_d.units
data[varname]['fill_value'] = DATA_d._FillValue
data[varname] = {}
data[varname]['val'] = TEMP.transpose(data_perm)
data[varname]['units'] = DATA_d.units
data[varname]['fill_value'] = DATA_d._FillValue
data[varname]['standard_name'] = DATA_d.standard_name
data[varname]['valid'] = MASK.transpose(data_perm)
if 'theta' in list_allkeys:
# compute pot. temp. for valid points
print DATA_d.dimensions
print data_perm
THETA = TEMP.transpose(data_perm)
SA = data['s']['val']
SA = SA[data['s']['valid']]
print DATA_d.dimensions[data_perm[0]]
print DATA_d.dimensions[data_perm[1]]
print DATA_d.dimensions[data_perm[2]]
print DATA_d.dimensions[data_perm[3]]
wvar = nc_fid.variables[DATA_d.dimensions[data_perm[0]]]
xvar = nc_fid.variables[DATA_d.dimensions[data_perm[1]]]
yvar = nc_fid.variables[DATA_d.dimensions[data_perm[2]]]
zvar = nc_fid.variables[DATA_d.dimensions[data_perm[3]]]
w3d, x3d, y3d, z3d = np.meshgrid(xvar,wvar,yvar,zvar)
p = y3d*(my_const.rho0*my_const.grav/1e4) # in dbar
print 'Doesnt work automatically - p_xyz'
del w3d, x3d, y3d, z3d, wvar, xvar, yvar, zvar
pr = p*0
print 'SA.shape: ',SA.shape
print 'THETA.shape',THETA[data[varname]['valid']].shape
print 'p.shape, ',p[data[varname]['valid']].shape
dummy = input('Press enter to continue')
MASK_mesh = data[varname]['valid']
THETA[MASK_mesh] = calc_theta_from_temp(SA,THETA[MASK_mesh],p[MASK_mesh],pr[MASK_mesh])
varname = 'theta'
data[varname] = {}
data[varname]['val'] = THETA
data[varname]['units'] = DATA_d.units
data[varname]['fill_value'] = DATA_d._FillValue
data[varname]['standard_name'] = 'sea_water_potential_temperature'
data[varname]['valid'] = MASK.transpose(data_perm)
print 'MISSING: Calculate pot. temp. from temperature data'
# read salinity data
if 's' in list_allkeys:
print 'Load salinity data'
fn = dir_data + 'salinity_annual_1deg.nc'
nc_fid = Dataset(fn,'r')
# read salinity data
DATA_d = nc_fid.variables['s_an']
varname = 's'
data[varname] = {}
data[varname]['val'] = np.array(DATA_d)
data[varname]['units'] = DATA_d.units
data[varname]['fill_value'] = DATA_d._FillValue
# return data
if 'grd' in list_allkeys:
return grd, data

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