Esempio n. 1
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TKE10_W = opennc("nc_files_TKE10_lev75/PAPA_1d_20100615_20110614_grid_W.nc", 0)
TKE30_T = opennc("nc_files_TKE30_lev75/PAPA_1d_20100615_20110614_grid_T.nc", 0)
TKE30_W = opennc("nc_files_TKE30_lev75/PAPA_1d_20100615_20110614_grid_W.nc", 0)

# initial variables
# put in the indexes to map the depth values here: (found from observation)
mapindexsalinity = [1, 8, 11, 13, 14, 15, 17, 19, 22, 24, 25, 28, 30]
#print(len(mapindexsalinity))
mapindextemperature = [
    1, 4, 8, 9, 10, 11, 13, 14, 15, 17, 19, 21, 24, 25, 27, 29, 30, 34
]
#print(len(mapindextemperature))
# initial variables done

# get/open original data variables here:
time_orig = getvar(orig_S, "time",
                   0)  # use one time for all calc, set to 364 days
temp_orig = getvar(orig_T, "T_20", 0)
#print(temp_orig[0,:])# get temperatures and salinities
sal_orig = getvar(orig_S, "S_41", 0)
depth_temp_orig = getvar(orig_T, "depth", 0)  # get the depths
depth_sal_orig = getvar(orig_S, "depth", 0)

# will need to resize from 4 dims to 2 dims otherwise havoc
# it is to exclude the (obvious) 1,1 dimension that s the 3rd and 4th dimension, must include the time steps 364 of them as well as the temp and sal data for each time step.
temp_orig = temp_orig[0:len(time_orig), :].reshape(
    len(time_orig), len(mapindextemperature)
)  #also need to use 364 indexes out of 365 because of the data structures
sal_orig = sal_orig.reshape(len(time_orig), len(mapindexsalinity))
# original data done

# get calculated variables here(for the different closure schemes):
# this code is to analyse the runs from the c1d_PAPA case after modifying the turbulence schemes (TKE,generic,ke,kw,kkl)
#   for a constant number of vertical levels of 75

###########################

# for the original data:

###########################
# Open the netcdf files using the file paths for the files:
# init = opennc("initial_conditions/init_PAPASTATION_m06d15.nc",0)# initial conditions
orig_T = opennc("original_data/t50n145w_dy.cdf", 0)  # original data
orig_S = opennc("original_data/s50n145w_dy.cdf", 0)

# get/open original data variables here:
time_orig = getvar(orig_S, "time",
                   0)  # use one time for all calc, set to 364 days
temp_orig = getvar(orig_T, "T_20", 0)
#print(temp_orig[0,:])# get temperatures and salinities
sal_orig = getvar(orig_S, "S_41", 0)
temp_depth_orig = getvar(orig_T, "depth", 0)  # get the depths
sal_depth_orig = getvar(orig_S, "depth", 0)

# plt.plot(temp_orig)
# print(sal_depth_orig)

# process the original Temp and Sal data:
# This will resize and get rid of NaN values from the data
# it is to exclude the (obvious) 1,1 dimension that s the 3rd and 4th dimension, must include the time steps 364 of them as well as the temp and sal data for each time step.
[temp_orig, sal_orig] = processTempandSal(temp_orig, sal_orig, len(time_orig))
# print(temp_orig.shape) # testing
# print(sal_orig.shape)
Esempio n. 3
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# type of turbulence scheme: (change this, ke, kw, generic, kkl, TKE0, TKE10, TKE30)
scheme = "ke"

###########################

# for the original data:

###########################
# Open the netcdf files using the file paths for the files:
# init = opennc("initial_conditions/init_PAPASTATION_m06d15.nc",0)# initial conditions
orig_T = opennc("original_data/t50n145w_dy.cdf", 0)  # original data
orig_S = opennc("original_data/s50n145w_dy.cdf", 0)

# get/open original data variables here:
time_orig = getvar(orig_S, "time",
                   0)  # use one time for all calc, set to 364 days
temp_orig = getvar(orig_T, "T_20", 0)
#print(temp_orig[0,:])# get temperatures and salinities
sal_orig = getvar(orig_S, "S_41", 0)
temp_depth_orig = getvar(orig_T, "depth", 0)  # get the depths
sal_depth_orig = getvar(orig_S, "depth", 0)

# plt.plot(temp_orig)
# print(sal_depth_orig)

# process the original Temp and Sal data:
# This will resize and get rid of NaN values from the data
# it is to exclude the (obvious) 1,1 dimension that s the 3rd and 4th dimension, must include the time steps 364 of them as well as the temp and sal data for each time step.
[temp_orig, sal_orig] = processTempandSal(temp_orig, sal_orig, len(time_orig))
# print(temp_orig.shape) # testing
# print(sal_orig.shape)
Esempio n. 4
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# this code is to analyse the runs from the c1d_PAPA case after modifying the turbulence schemes (TKE,generic,ke,kw,kkl)
#   for a constant number of vertical levels of 75

###########################

# for the original data:

###########################
# Open the netcdf files using the file paths for the files:
# init = opennc("initial_conditions/init_PAPASTATION_m06d15.nc",0)# initial conditions
orig_T = opennc("original_data/t50n145w_dy.cdf", 0)  # original data
orig_S = opennc("original_data/s50n145w_dy.cdf", 0)

# get/open original data variables here:
time_orig = getvar(orig_S, "time",
                   0)  # use one time for all calc, set to 364 days
temp_orig = getvar(orig_T, "T_20", 0)
#print(temp_orig[0,:])# get temperatures and salinities
sal_orig = getvar(orig_S, "S_41", 0)
temp_depth_orig = getvar(orig_T, "depth", 0)  # get the depths
sal_depth_orig = getvar(orig_S, "depth", 0)

# plt.plot(temp_orig)
# print(sal_depth_orig)

# process the original Temp and Sal data:
# This will resize and get rid of NaN values from the data
# it is to exclude the (obvious) 1,1 dimension that s the 3rd and 4th dimension, must include the time steps 364 of them as well as the temp and sal data for each time step.
[temp_orig, sal_orig] = processTempandSal(temp_orig, sal_orig, len(time_orig))
# print(temp_orig.shape) # testing
# print(sal_orig.shape)
Esempio n. 5
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from opennc import opennc
from getvar import getvar
from zgrid import zgrid
from scipy.interpolate import interp1d
from pinitgraph import pinitgraph
from netCDF4 import Dataset as netcdffile
import matplotlib.pyplot as plt
import numpy as np
from mpl_toolkits.basemap import Basemap
import pylab
from scipy.optimize import curve_fit

infile4 = 'nc_files/init_PAPASTATION_m06d15.nc'
fh_init = opennc(infile4, 1)

init_dept = getvar(fh_init, "deptht", 1)
# C
init_temp = getvar(fh_init, "votemper", 1)
init_temp = init_temp[0, :, 1, 1]  # C
init_sal = getvar(fh_init, "vosaline", 1)
init_sal = init_sal[0, :, 1, 1]  # C

# use the spline interpolation
# gert suggested it and it is found online at:
# http://docs.scipy.org/doc/scipy/reference/tutorial/interpolate.html
# works well for salinity and temperature

# set out the data
xdata = init_dept
ydata_S = init_sal
ydata_T = init_temp
Esempio n. 6
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# from pRMSE import pRMSE
from pvert_grid import pvert_grid
from extractdata import extractdata
from getvar import getvar
from pgraph import pgraph
from netCDF4 import Dataset as netcdffile
import matplotlib.pyplot as plt
import numpy as np
from mpl_toolkits.basemap import Basemap
import pylab

# this code is to analyse the runs from the c1d_PAPA case after modifying the turbulence schemes (TKE,generic,ke,kw,kkl)
#   for a constant number of vertical levels of 75

# Open the netcdf files using the file paths for the files:
ke_T = opennc("ncfiles/PAPA_1d_20100615_20110614_grid_T.nc",
              0)  #output from NEMO, T,W files
# ke_W = opennc("ncfiles_ke_lev75/PAPA_1d_20100615_20110614_grid_W.nc",0)

ke_T_temp = getvar(ke_T, "votemper", 1)
ke_T_sal = getvar(ke_T, "vosaline", 1)
ke_T_dep = getvar(ke_T, "deptht", 1)
ke_T_time = getvar(ke_T, "time_counter", 1)

pgraph(ke_T_time, ke_T_dep, ke_T_temp[0:364, :, 1, 1], "time (days)", "depth",
       35, 1, 0, 1, None, [0, 200])
pgraph(ke_T_time, ke_T_dep, ke_T_sal[0:364, :, 1, 1], "time (days)", "depth",
       35, 1, 0, 1, None, [0, 200])

plt.show()
# a sentimental note, James again proves to have much more luck than I anticipated. A minor error fixed when he poped in the office :-)
Esempio n. 7
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# f2011_lat = getvar(fh_2011,"nav_lat",1) # DC
# f2011_lon = getvar(fh_2011,"nav_lon",1) # DC
# f2011_wndwe = getvar(fh_2011,"wndwe",1) # DC
# f2011_wndsn = getvar(fh_2011,"wndsn",1) # DC
# f2011_tinst = getvar(fh_2011,"time_instant",1) # DC
# f2011_tcount = getvar(fh_2011,"time_counter",1) # DC
# f2011_relhumid = getvar(fh_2011,"humi_r",1) # DC
# f2011_humid = getvar(fh_2011,"humi",1) # DC
# f2011_sw = getvar(fh_2011,"qsr",1) # DC
# f2011_lw = getvar(fh_2011,"qlw",1) # DC
# f2011_airtem = getvar(fh_2011,"tair",1) # DC
# f2011_rain = getvar(fh_2011,"prec",1) # DC
# f2011_snow = getvar(fh_2011,"snow",1) # DC

# for fh_init:
init_lon = getvar(fh_init, "longitude", 1)  # DC
init_lat = getvar(fh_init, "latitude", 1)  # DC
init_time = getvar(fh_init, "time_counter", 1)  # DC

init_dept = getvar(fh_init, "deptht", 1)
# C
init_temp = getvar(fh_init, "votemper", 1)
init_temp = init_temp[0, :, 1, 1]  # C
init_sal = getvar(fh_init, "vosaline", 1)
init_sal = init_sal[0, :, 1, 1]  # C

pinitgraph(init_dept, init_temp, "temperature")
# print(init_temp[:,:,1,1])
print(init_dept)
# print(init_lon)
# print(init_lat)