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read_plot_n_compare.py
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import iris
import iris.quickplot as qplt
import iris.plot as iplt
import matplotlib.pyplot as plt
import numpy as np
import numpy.ma as ma
### dont want the huge unit var list :
#import warnings
#warnings.filterwarnings('ignore')
#
#%matplotlib inline
'''
def def_var_n_dic(YY) :
################
################
## def file and var : (default have to be updated)
yr = "YY"
### Ancillary files -- Needed by some functions :
reg_grid_file = "../MESH/Data_reg_grid/woa13_all_i00_01.nc"
mesh_mask = "../MESH/eORCA1/NEMO42/mesh_mask.nc"
try:
## running local
meshfile = "../MESH/eORCA1/NEMO42/mesh_mask.nc"
except:
## on NOC system
meshfile = "/noc/users/jpp1m13/WORKING/UKESM/MESH/eORCA1/NEMO42/mesh_mask.nc"
maskfile = "../MESH/eORCA1/NEMO42/eORCA100_masks.nc"
#maskfile = "/noc/users/axy/Matlab/Macros/woa_mask100.mat"
#### #experiment name :
runlist = [ "Init-cond",
"No-olivine",
"surf",
"100m_max",
"200m_max"]
#### Title associated to experiments
ttl_list = ["Init-cond",
"No-olivine",
"surf",
"100m_max",
"200m_max"]
#### Path to experiment output files
rundict = {
runlist[0] : "Out",
runlist[1] : "Out",
runlist[2] : "Out",
runlist[3] : "Out",
runlist[4] : "Out"
}
#### Somme Var lists :
##-----------------------------
#Inv_2d_var = [ "RIV_ALK",
# "TOT_SHALK",
# "CO2FLUX"]
Inv_2d_var = ["CO2FLUX"]
Inv_2d_phys = [ "somxl010",
"tos",
"sos"]
Inv_2d_ZMP_var = ["FRAGDF1",
"FRAGDF2",
"FRAGD",
"GMPDF1",
"GMPDF2",
"GMPD"]
Surf_3d_var = ["ZME",
"CHL",
"ZMI",
"PHN",
"PHD",
"ALK",
"DIC",
"DIN",
"FER",
"SIL"]
Surf_3d_zmp_var = ["ZMP"]
Inv_3d_var = ["ZME_E3T",
"ZMI_E3T",
"PHN_E3T",
"PHD_E3T",
"PHYTO",
"ZOO",
"PLKT",
"ALK_E3T",
"DIC_E3T",
"DIN_E3T",
"FER_E3T",
"SIL_E3T"]
Inv_3d_zmp_var = ["ZMP_E3T"]
Transect_3d_var = ["TPP3",
"DETFLUX3"]
Obs_surf_compare_var = ["CHL",
"ALK",
"DIC",
"DIN",
"SIL"]
Obs_surf_diad_var = ["PP",
"OCN_PCO2",
"CO2FLUX"]
Obs_3D_compare_var = ["OXY",
"ALK",
"DIC",
"DIN",
"SIL"]
monthnm = {
"01" : "Jan",
"02" : "Feb",
"03" : "Mar",
"04" : "Apr",
"05" : "May",
"06" : "Jun",
"07" : "Jul",
"08" : "Aug",
"09" : "Sep",
"10" : "Oct",
"11" : "Nov",
"12" : "Dec" }
'''
def nc_obs2D_varname(var) :
#dimensions:
# x = 362 ;
# y = 332 ;
#variables:
# double nav_lon(y, x) ;
# double nav_lat(y, x) ;
# double obs_din(y, x) ;
# double obs_sil(y, x) ;
# double obs_oxy(y, x) ;
# double obs_dic(y, x) ;
# double obs_alk(y, x) ;
# double obs_chl(y, x) ;
# double obs_npp(y, x) ;
#
if var == 'ALK' :
obsvar = 'obs_alk'
elif var == 'DIC' :
obsvar = 'obs_dic'
elif var == 'DIN' :
obsvar = 'obs_din'
elif var == 'SIL' :
obsvar = 'obs_sil'
elif var == 'PP' :
obsvar = 'obs_npp'
elif var == 'CHL' :
obsvar = 'obs_chl'
else :
print("E R R O R -- No obs for this var -- ")
#
return obsvar
def mat_obs2D_varname(var) :
#'rg_glodap1_surf_alk', 'rg_glodap1_surf_dic', 'rg_glodap1_surf_pidic',
#'rg_glodap2_surf_alk', 'rg_glodap2_surf_dic', 'rg_glodap2_surf_nit',
#'rg_glodap2_surf_pidic', 'rg_glodap2_surf_sil', 'rg_modis_npp',
#'rg_roden_clim_flux', 'rg_roden_clim_pco2', 'rg_seawifs_surf_chl',
#'rg_woa13_surf_nit', 'rg_woa13_surf_oxy', 'rg_woa13_surf_sil'
if var == 'ALK' :
obsvar = 'rg_glodap1_surf_alk'
elif var == 'DIC' :
obsvar = 'rg_glodap1_surf_dic'
elif var == 'DIN' :
obsvar = 'rg_woa13_surf_nit'
elif var == 'SIL' :
obsvar = 'rg_woa13_surf_sil'
elif var == 'PP' :
obsvar = 'rg_modis_npp'
elif var == 'CHL' :
obsvar = 'rg_seawifs_surf_chl'
elif var == 'OCN_PCO2' :
obsvar = 'rg_roden_clim_pco2'
elif var == 'CO2FLUX' :
obsvar = 'rg_roden_clim_flux'
return obsvar
def mat_obs3D_varname(var) :
#'woa75_alk', 'woa75_cfc11', 'woa75_dic', 'woa75_din', 'woa75_oxy', 'woa75_sil'
if var == 'ALK' :
obsvar = 'woa75_alk'
elif var == 'DIC' :
obsvar = 'woa75_dic'
elif var == 'DIN' :
obsvar = 'woa75_din'
elif var == 'SIL' :
obsvar = 'woa75_sil'
elif var == 'CFC11' :
obsvar = 'woa75_cfc11'
elif var == 'OXY' :
obsvar = 'woa75_oxy'
return obsvar
#################
#################
### Read and plot functions - if need to update - update on jupyter, then update back here
class runclass:
def __init__(self, modlist):
#
print(modlist)
#
if modlist == 0 :
name = "Half sink"
exp_name = adddict
dict_ptrc = adddict_ptrc
dict_diad = adddict_diad
dict_grid = adddict_grid
#outfreq = "1M"
outfreq = "5D"
elif modlist == 1 :
name = "Dble sink"
exp_name = rundict
dict_ptrc = rundict_ptrc
dict_diad = rundict_diad
dict_grid = rundict_grid
outfreq = "5D"
elif modlist == 2 :
name = "MEDUSA"
exp_name = rundictold
dict_ptrc = olddict_ptrc
dict_diad = olddict_diad
dict_grid = olddict_grid
outfreq = "5D"
else :
print("modlist out of list")
self.name = name
self.exp_name = exp_name
self.dict_ptrc = dict_ptrc
self.dict_diad = dict_diad
self.dict_grid = dict_grid
self.outfreq = outfreq
def diad_replace(file_name) :
'''
if not the diad file, change file name to make it the diad file
'''
if "diad" not in file_name :
## We need a way to know the diad file (use it for ORCA1 2D cube template)
try :
file_name = file_name.replace("ptrc", "diad")
except :
file_name = file_name.replace("grid", "diad")
return file_name
def ptrc_replace(file_name) :
'''
if not the ptrc file, change file name to make it the ptrc file
'''
if "ptrc" not in file_name :
## We need a way to know the diad file (use it for ORCA1 2D cube template)
try :
file_name = file_name.replace("diad", "ptrc")
except :
file_name = file_name.replace("grid", "ptrc")
return file_name
def grid_replace(file_name) :
'''
if not the grid file, change file name to make it the grid file
'''
if "grid" not in file_name :
## We need a way to know the diad file (use it for ORCA1 2D cube template)
try :
file_name = file_name.replace("ptrc", "grid")
except :
file_name = file_name.replace("diad", "grid")
return file_name
def make_big_average_timeseries (var, runlist, run_exp_list, rundict, out_file="ptrc", MASK=None, region=None, Regrid=False, nemogrid="ORCA1_NEMO42", machine="NOC_linux", year=1850 ):
'''
call as :
make_big_average_timeseries (var, runlist, run_exp_list, out_file="ptrc", year=1850)
where
-- var is the variable to read
-- runlist is the list of possible experiments(used in the dict)
-- run_exp_list is the list of exp to go through
-- out_file can be "ptrc" "diad" or "grid"
-- year the year to treat
'''
from os.path import exists
#from set_runs_input_for_timeseries import rundict_file
from set_runs_input_to_plot import rundict_file
# def file_name for given year and run
# check in saved registered array if year is already here for this run
# if not --> read the file and avg and save it.
#------------------------
### prep regions :
## regional plot :
if region == "Amazon" :
jj_min = 175
jj_max = 220
ii_min = 220
ii_max = 260
elif region == "Bengal" :
jj_min = 200
jj_max = 230
ii_min = 0
ii_max = 30
elif region == "UKshelv" :
jj_min = 250
jj_max = 280
ii_min = 275
ii_max = 295
#ii_min=-7
#ii_max=2
#jj_min=45
#jj_max=55
elif region == "NorthOrtho" or region == "NorthPolarStereo":
jj_min = 275
jj_max = 332
ii_min = 0
ii_max = 361
MASK="arc_msk"
### get the output files name for this year - all experiments
[rundict_ptrc, rundict_diad, rundict_grid] = rundict_file(year, runlist, rundict)
#print(rundict_ptrc)
for rundd in [rundict_ptrc, rundict_diad, rundict_grid] :
for ii in run_exp_list :
if out_file == "ptrc" :
bibi = rundict_ptrc[runlist[ii]]
elif out_file == "diad" :
bibi = rundict_diad[runlist[ii]]
elif out_file == "grid" :
bibi = rundict_grid[runlist[ii]]
if type(bibi) is list :
try :
if out_file == "ptrc" :
rundict_ptrc.update({runlist[ii] : bibi[0]})
if out_file == "diad" :
rundict_diad.update({runlist[ii] : bibi[0]})
if out_file == "grid" :
rundict_grid.update({runlist[ii] : bibi[0]})
except :
print('!! list problem -- probably no file or file corrupted !!')
EXIT = True
##
### run through all runs of the list
TSpath="TIMESERIES/"
for exp in run_exp_list :
EXIT=False
###
##1 - read saved time_serie if exist
if region is None :
tm_name= TSpath + var+"_"+runlist[exp]+"_time_serie"
else :
tm_name= TSpath + var+"_"+runlist[exp]+"_"+region+"_time_serie"
print(tm_name)
if exists(tm_name+".npy") :
tm = np.load(tm_name+".npy")
print(tm.shape)
#print(tm)
NEW = False
### Check if year already filled for this run :
if year in tm[0,:] :
EXIT=True
else :
NEW = True
###
if EXIT is not True :
##2 - read the output
if out_file == "ptrc" :
ref_file_name = rundict_ptrc[runlist[exp]]
elif out_file == "diad" :
ref_file_name = rundict_diad[runlist[exp]]
elif out_file == "grid" :
ref_file_name = rundict_grid[runlist[exp]]
#
ref_ttl = runlist[exp]
#
try :
cube = prep_cube(ref_file_name, var,Obs=False,MASK_ZERO=True )
except :
print(' !! SOMETHING WRONG IN ', ref_file_name )
EXIT = True
### we have the field --> now average :
# need surface only :
if EXIT is not True :
try :
cube = prep_cube_surf(cube)
if cube is None :
print("cube ref surface gives None")
except :
print("already 2D -- ", cube.data.shape ," no need to extract ")
##
## mask if needed :
if MASK is not None :
cube = prep_Masked_cube(cube,MASK,nemogrid=nemogrid, machine=machine)
if cube is None :
print("cube ref Masking gives None")
##
## regrid to get a real average
if Regrid :
print("Regridding cube_ref")
cube = regrid_ORCA(cube, runlist, Meth="Surface", run_nb=exp, MASK=MASK, NEW=True)
if cube is None :
print("cube ref Regrid gives None")
print("Regridded cube : ", cube.shape)
#print("cube_ref : ", cube.shape)
#print(cube)
##
##
## extract region if needed
#if region is not None :
# cubi = cube[...,jj_min:jj_max,ii_min:ii_max].copy()
#else :
# cubi = cube.copy()
### check
#print("cube shape after extractions :", cubi.shape )
### now average :
## can be done proprely, but try first the easy way :
#### we want to regrid the surface, and then cube collapse lat/lon or nanmean. \o/
#### no need for region extraction --
avg = np.mean(cube.data)
#print(year, avg)
ytm=np.empty([2,1])
ytm[0,0]=year
ytm[1,0] = avg
if NEW :
ntm=ytm
else :
ntm=np.empty([2,tm.shape[1]+1])
ntm[:,:-1]=tm
ntm[:,-1]=ytm[:,0]
#print("new array's shape :",ntm.shape)
#print(ntm)
np.save(tm_name, ntm)
##
## should be it
def fix_nemo_cube(src_cubi, mesh_mask="/noc/users/jpp1m13/WORKING/UKESM/MESH/eORCA1/NEMO42/MEDUSA_well_defined.nc") :
## cube badly written - have to fix it...
## there is no x and y and z coord in the 4.2 NEMO files
## get a file with the right coord :
tmp_src= prep_cube(mesh_mask,"PRN")
#print(tmp_src)
# and create new, well defined, cube
###
print(" NO coord... fix NEMO file")
# guess 2D or 3D
regrid2d = False
regrid3d = False
if src_cubi.data.ndim == 4 :
print("-- Fixing 3D --")
regrid3d = True
elif src_cubi.data.ndim == 3 :
## check the first dim is depth (more than one layer)
## if not, no need to extract
if src_cubi.data.shape[0] <= 12 :
print("-- Fixing 2D --")
regrid2d = True
else :
# real 3D
print("-- Fixing 3D --")
regrid3d = True
elif src_cubi.data.ndim == 2 :
# already 2D
print("-- Fixing 2D --")
regrid2d = True
#area = src_cubi.copy(e1t.data[0,:,:] * e2t.data[0,:,:])
else :
print("data shape not understood : ", src_cubi.data.shape)
# create Cube :
#print("area shape : ", area.shape)
xx = tmp_src.coord(axis='x')
#print(xx)
yy = tmp_src.coord(axis='y')
#print(yy)
#tt = src_cubi.coords(axis='t')[0]
#print(tt)
##
#ttdim = src_cubi.shape[0]
#yydim = tmp_src.shape[1]
#xxdim = tmp_src.shape[2]
##
if regrid3d :
src_cubi.add_aux_coord(yy, data_dims=[2, 3])
src_cubi.add_aux_coord(xx, data_dims=[2, 3])
#zz = src_cubi.coord(axis='z')
#print(zz)
#zzdim = src_cubi.shape[1]
#reg_cubi = iris.cube.Cube(np.zeros((ttdim, zzdim, yydim, xxdim)),
# dim_coords_and_dims=[(tt, 0),
# (zz, 1),
# (yy, 2),
# (xx, 3)])
else:
#reg_cubi = iris.cube.Cube(np.zeros((ttdim, yydim, xxdim)))
#reg_cubi.add_dim_coord(tt, 0)
src_cubi.add_aux_coord(yy, data_dims=[1, 2])
src_cubi.add_aux_coord(xx, data_dims=[1, 2])
#reg_cubi.data = src_cubi.data
#reg_cubi.name = src_cubi.name
#reg_cubi.var_name = src_cubi.var_name
#reg_cubi.long_name = src_cubi.long_name
#reg_cubi.units = src_cubi.units
return src_cubi
def regrid_ORCA(src_cubi, runlist, Meth=None, NEW = False, run_nb=None, MASK=None, reg_grid_file = "/noc/users/jpp1m13/WORKING/UKESM/MESH/Data_reg_grid/woa13_all_i00_01.nc") :
'''
regrid_ORCA(src_cubi, Meth=None, NEW = False, run_nb=run_nb) :
regrids on WOA 1x1 grid (if not already here ) and saves it
-- src_cubi : source cube to regrid
-- runlist : same as in subplot_diff -- list of available run names, used to name the regrid file
-- if Meth is Surface : regrid only surface field
-- NEW to reproduce the file -- to regrid again
-- run_nb : run number to get the run name for the file to save.
-- MASK : if you want to mask the file to regrid (mask is the same than in subplot_diff )
-- reg_grid_file : a regrid file used a ref model for the grid -- default WOA 1x1 grid.
'''
import os
dirr="SAVE_NC_FILE" ## Directory with all saved regrided nc files
##
##first check dir exists and create it if needed:
if os.path.isdir(dirr) != True :
os.mkdir(dirr)
##
## regrid :
## Target grid : WOA
reg_cube = prep_cube(reg_grid_file,"i_mn")
#if Meth=="Surface":
reg_cube = prep_cube_surf(reg_cube)
##
if Meth=="Surface":
print("Regrid -- extract surf -- cube shape : ",src_cubi.shape)
src_cubi = prep_cube_surf(src_cubi)
if src_cubi is None :
print("Regrid -- cube Surface gives None")
##
## extra precautions -- mask problematic values
## target -- should not be needed
reg_cube.data = np.ma.masked_invalid(reg_cube.data)
reg_cube.data = np.ma.masked_where(reg_cube.data==0.0, reg_cube.data)
reg_cube_mask = reg_cube.data.mask
## sources
src_cubi.data = np.ma.masked_invalid(src_cubi.data)
src_cubi.data = np.ma.masked_where(src_cubi.data==0.0, src_cubi.data)
#print(reg_cube)
reg_cube.coord(axis='x').coord_system = iris.coord_systems.GeogCS(6371229.0)
reg_cube.coord(axis='y').coord_system = iris.coord_systems.GeogCS(6371229.0)
#reg_grid = reg_cube.coords()
#print(reg_grid)
## Source grid to regrid: NEMO
#src_cubi = prep_cube("Out/medusa_cp799o_sum-1m_20200101-21001231_diad-T.nc","TOT_SHALK")
regrid2d = False
regrid3d = False
print("src cubi shape : ", src_cubi.shape)
print("reg cube shape : ", reg_cube.shape)
src_mask = src_cubi.copy()
src_mask.data[...] = 1
src_mask.data[src_cubi.data.mask] = 0
if src_cubi.data.ndim == 4 :
print("-- 3D Regrid --")
regrid3d = True
elif src_cubi.data.ndim == 3 :
## check the first dim is depth (more than one layer)
## if not, no need to extract
if src_cubi.data.shape[0] <= 12 :
print("-- 2D Regrid --")
regrid2d = True
else :
# real 3D
print("-- 3D Regrid --")
regrid3d = True
elif src_cubi.data.ndim == 2 :
# already 2D
print("-- 2D Regrid --")
regrid2d = True
#area = src_cubi.copy(e1t.data[0,:,:] * e2t.data[0,:,:])
else :
print("data shape not understood : ", src_cubi.data.shape)
###
### need src_cubi coord system (but might need to fix the cubes...)
try:
src_cubi.coord(axis='x').coord_system = reg_cube.coord(axis='x').coord_system
src_cubi.coord(axis='y').coord_system = reg_cube.coord(axis='y').coord_system
except :
src_cubi = fix_nemo_cube(src_cubi)
src_cubi.coord(axis='x').coord_system = reg_cube.coord(axis='x').coord_system
src_cubi.coord(axis='y').coord_system = reg_cube.coord(axis='y').coord_system
##
## Scheme --
#scheme = iris.analysis.AreaWeighted(mdtol=0.5)
#scheme = iris.analysis.PointInCell()
scheme = iris.analysis.UnstructuredNearest()
#scheme = iris.analysis.Nearest()
#scheme = iris.analysis.Linear()
##
isfile = False
if MASK==None :
MASK="no"
##
if regrid2d :
fname = dirr + "/regridded_" + src_cubi.var_name + "_" + runlist[run_nb] + "_" + MASK + "_mask_2D.nc"
print("check if 2D file exists : ", fname)
if os.path.isfile(fname) and not NEW:
# file exists : read it
print("read regridded file : ",fname)
reg_cubi = iris.load_cube(fname)
isfile = True
else :
# create it
print("No file to read : regridding")
reg_cubi=src_cubi.regrid(reg_cube, scheme)
#reg_mask=src_mask.regrid(reg_cube, scheme)
elif regrid3d :
fname = dirr + "/regridded_" + src_cubi.var_name + "_" + runlist[run_nb] + "_" + MASK + "_mask_3D.nc"
print("check if 3D file exists : ", fname)
if os.path.isfile(fname) and not NEW:
# file exists : read it
print("read regridded file : ",fname)
reg_cubi = iris.load_cube(fname)
isfile = True
else :
###
print("No file to read : regridding")
# create Cube :
#print("area shape : ", area.shape)
xx = reg_cube.coord(axis='x')
yy = reg_cube.coord(axis='y')
#print(reg_cube)
tt = src_cubi.coords(axis='t')[0]
zz = src_cubi.coord(axis='z')
#if zz==None :
# zz = src_cubi.coord('Vertical T levels')
#print(cc)
ttdim = src_cubi.shape[0]
zzdim = src_cubi.shape[1]
yydim = reg_cube.shape[1]
xxdim = reg_cube.shape[2]
reg_cubi = iris.cube.Cube(np.zeros((ttdim, zzdim, yydim, xxdim)),
dim_coords_and_dims=[(tt, 0),
(zz, 1),
(yy, 2),
(xx, 3)])
reg_cubi.name = src_cubi.name
reg_cubi.var_name = src_cubi.var_name
reg_cubi.long_name = src_cubi.long_name
reg_cubi.units = src_cubi.units
#reg_mask = reg_cubi.copy()
for ZZZ in np.arange(zzdim) :
print("Regrid Z level --",ZZZ)
print("src cubi slice shape : ", src_cubi[:,ZZZ,:,:].shape)
tcube=src_cubi[:,ZZZ,:,:].regrid(reg_cube, scheme)
reg_cubi.data[:,ZZZ,:,:] = tcube.data
#tmask = src_mask[:,ZZZ,:,:].regrid(reg_cube, scheme)
#reg_mask.data[:,ZZZ,:,:] = tmask.data
if not isfile :
## need a masked array
#bibi = np.ma.masked_where(reg_mask.data == 0, reg_cubi.data)
bibi = np.ma.masked_where(reg_cubi.data > 1e17, reg_cubi.data)
reg_cubi.data = bibi
## Save file :
print("saving file : ",fname)
iris.save(reg_cubi, fname)
else :
print(reg_cubi)
return reg_cubi
def load_meta(datapath, fxpath=None):
"""Load metadata of the netCDF file.
Parameters
----------
datapath: str
path to the netCDF file with data
fxpath: str
path to the netCDF file with fx files
Returns
-------
datafile: instance of netCDF4 Dataset
points to the file
lon2d: numpy array
Two dimentional longitude information
lat2d: numpy array
Two dimentional latitude information
lev: numpy array
depths of the model levels
time: numpy array
dates are converted to datetime objects
areacello: numpy array
values of areacello
"""
from netCDF4 import Dataset
datafile = Dataset(datapath)
if fxpath:
datafile_area = Dataset(fxpath)
areacello = datafile_area.variables['areacello'][:]
else:
areacello = None
lon = datafile.variables['lon'][:]
lat = datafile.variables['lat'][:]
lev = datafile.variables['lev'][:]
time = num2date(datafile.variables['time'][:],
datafile.variables['time'].units)
# hack for HadGEM2-ES
lat[lat > 90] = 90
if lon.ndim == 2:
lon2d, lat2d = lon, lat
elif lon.ndim == 1:
lon2d, lat2d = np.meshgrid(lon, lat)
metadata = {}
metadata['datafile'] = datafile
metadata['lon2d'] = lon2d
metadata['lat2d'] = lat2d
metadata['lev'] = lev
metadata['time'] = time
metadata['areacello'] = areacello
return metadata
def plot_budget_bar(var, xx, globi, exp_names, yr = None, Convert=1.0, ConvUnit = "None", op = "sum", log_scale = False, centered=False, Titre = None, REF_COMP=None, RETURN=False, **attrs) :
print(var)
if op == "sum" :
f_name = "Glub_sum_" + var
elif op == "avg" :
f_name = "Glov_avg_" + var
comp_nb = np.size(globi)
fig = plt.figure(figsize=(7.5,7.5))
ax = fig.add_subplot(1, 1, 1)
#fig = plt.figure(figsize=(5*6,5*6))
## no pac
##
## plot :
print(xx)
print(exp_names)
print(globi)
p1 = ax.bar(xx, globi*Convert, edgecolor="white", linewidth=0.8)
if ConvUnit == "None" :
ax.set_ylabel("-")
else :
ax.set_ylabel(ConvUnit)
ax.bar_label(p1, label_type='center', size=12)
ax.set_xticks(xx, labels= exp_names, size=12 )
#ax.set(xlim=(0, 8), xticks=np.arange(1, 8),
# ylim=(0, 8), yticks=np.arange(1, 8))
if Titre == None :
plt.suptitle( "No title.... add one" , size=16)
else :
plt.suptitle( Titre , size=16)
plt.rcParams.update({'font.size': 12})
plt.savefig(f_name)
plt.show()
if RETURN :
return xx, globi, exp_names
def comp_budget_bar(var, rundict, run_exp_list, Meth="None", yr="None", Convert=1.0, ConvUnit = "None", op = "sum", log_scale = False, centered=False, Diff = False, Titre = None, REF_COMP=None, RETURN=False, **attrs) :
print(var)
if op == "sum" :
f_name = "Glob_sum_" + var
elif op == "avg" :
f_name = "Glob_avg_" + var
if yr != "None" :
f_name = f_name + "_" + yr
if REF_COMP is not None :
runcomp = REF_COMP
ref_comp_fname = rundict[runcomp]
comp_ttl = runcomp
else :
ref_comp_fname = None
comp_nb = np.size(run_exp_list)
fig = plt.figure(figsize=(7.5,7.5))
ax = fig.add_subplot(1, 1, 1)
#fig = plt.figure(figsize=(5*6,5*6))
## no pac
loop = 0
xx = np.arange(comp_nb)
for compref in run_exp_list :
comp_file_name = rundict[runlist[compref]]
comp_ttl = runlist[compref]
cube = prep_cube(comp_file_name, var, REF_COMP=ref_comp_fname)
if log_scale :
## Make sure there are no neg values
cube.data = ma.masked_where(cube.data <= 0.0, cube.data )
if Meth=="Surface":
try :
cube = prep_cube_surf(cube)
except :
print("already 2D -- no need to extract ")
elif Meth=="Vert_Inv":
try :
cube = prep_cube_vert_inv(cube)
except :
print(" already 2D var -- ")
##
if Diff == False :
if loop == 0 :
globi = np.array([glob_budget_2D(cube, op = op)])
exp_names = np.array([comp_ttl])
else :
globi = np.append(globi,[glob_budget_2D(cube, op = op)])
exp_names = np.append(exp_names,[comp_ttl])
else :
if loop == 0 :
globref = np.array([glob_budget_2D(cube, op = op)])
elif loop == 1 :
globi = np.array([glob_budget_2D(cube, op = op) - globref])
exp_names = np.array([comp_ttl])
else :
globi = np.append(globi,[glob_budget_2D(cube, op = op) - globref])
exp_names = np.append(exp_names,[comp_ttl])
loop = loop + 1
##
## plot :
if Diff == True :
xx = xx[1:]
print(xx)
print(exp_names)
print(globi)
p1 = ax.bar(xx, globi*Convert, edgecolor="white", linewidth=0.8)
if ConvUnit == "None" :
ax.set_ylabel(cube.units)
else :
ax.set_ylabel(ConvUnit)
ax.bar_label(p1, label_type='center', size=12)
ax.set_xticks(xx, labels= exp_names, size=12 )
#ax.set(xlim=(0, 8), xticks=np.arange(1, 8),
# ylim=(0, 8), yticks=np.arange(1, 8))
if Diff == False :
if op == "sum" :
tittle = "Global sum of " + cube.long_name
elif op == "avg" :
tittle = "Global avg of " + cube.long_name
else :
if op == "sum" :
tittle = "Global sum of " + cube.long_name + " -- diff with " + runlist[0]
elif op == "avg" :
tittle = "Global avg of " + cube.long_name + " -- diff with " + runlist[0]
if Titre == None :
plt.suptitle( tittle , size=16)
else :
plt.suptitle( Titre , size=16)
plt.rcParams.update({'font.size': 12})
plt.savefig(f_name)
plt.show()
if RETURN :
return xx, globi, exp_names
def glob_budget_2D(cube, op = "sum",meshfile="/noc/users/jpp1m13/WORKING/UKESM/MESH/eORCA1/NEMO42/mesh_mask.nc") :
def glob_sum(cube, area, op = "sum") :
#try :
#cube = read_cube(file_name, var)
area.mask = cube.data.mask
ppp = cube.data.copy()
ppp1 = cube.data.copy()
if op == "sum" :
ppp1 = ppp * area ## mmol--2D
#
ppp2 = ppp1.sum(axis = 1)
ppp3 = ppp2.sum(axis = 1)
gls = ppp3[0] # glob sum Tmol-N
elif op == "avg" :
print("averaging")
ppp2 = ma.masked_where(ppp1 == np.nan, ppp1 )
marea = ma.masked_where(ppp1 == np.nan, area )
ppp3 = ppp2.compressed()
carea = marea.compressed()
gls = np.average(ppp3, weights=carea)
#gls = ppp4[0]
#except :
# ## var not in the file (no pac probably)
# gls = 0.0
print("gls = ",gls)
# #
return gls
## all vars are 2D inventory, only needs 2D area and sum-up
#meshfile="/noc/users/jpp1m13/WORKING/UKESM/MESH/eORCA1/mesh_mask.nc"
e1t = prep_cube(meshfile, "e1t")
e2t = prep_cube(meshfile, "e2t")
area = e1t.data.copy()
area = e1t.data * e2t.data
global_sum = glob_sum(cube, area, op)
return global_sum
def prod_graz_budget(file_name, run_ttl,meshfile="/noc/users/jpp1m13/WORKING/UKESM/MESH/eORCA1/NEMO42/mesh_mask.nc") :