else:
grid_mn = []
for Y in range(168, 171):
for X in range(225, 228):
if not mask[Y, X]:
grid_mn.append(grd(X, Y))
def apply_init(grid):
grid.init_caete_dyn(input_path, stime, co2_data, pls_table, tsoil, ssoil)
return grid
# # START GRIDCELLS
print("Starting gridcells")
print_progress(0, len(grid_mn), prefix='Progress:', suffix='Complete')
for i, g in enumerate(grid_mn):
apply_init(g)
print_progress(i + 1, len(grid_mn), prefix='Progress:', suffix='Complete')
# DEFINE HARVERSTERS - funcs that will apply grd methods(run the CAETÊ model) over the instanvces
def apply_spin(grid):
"""pre-spinup use some outputs of daily budget (water, litter C, N and P) to start soil organic pools"""
w, ll, cwd, rl, lnc = grid.bdg_spinup(start_date="19790101",
end_date="19830101")
grid.sdc_spinup(w, ll, cwd, rl, lnc)
return grid
def apply_fun(grid):
def create_ncG3(table, interval):
nc_out = Path("../nc_outputs")
out_data = True if nc_out.exists() else os.mkdir(nc_out)
if out_data is None:
print(f"Creating output folder at{nc_out.resolve()}")
elif out_data:
print(f"Saving outputs in {nc_out.resolve()}")
vars = [
"rcm", "runom", "evapm", "wsoil", "cleaf", "cawood", "cfroot",
"litter_l", "cwd", "litter_fr", "litter_n", "litter_p", "sto_c",
"sto_n", "sto_p", "c_cost"
]
dates = time_queries(interval)
dm1 = len(dates)
rcm = np.zeros(shape=(dm1, 61, 71), dtype=np.float32) - 9999.0
runom = np.zeros(shape=(dm1, 61, 71), dtype=np.float32) - 9999.0
evapm = np.zeros(shape=(dm1, 61, 71), dtype=np.float32) - 9999.0
wsoil = np.zeros(shape=(dm1, 61, 71), dtype=np.float32) - 9999.0
swsoil = np.zeros(shape=(dm1, 61, 71), dtype=np.float32) - 9999.0
cleaf = np.zeros(shape=(dm1, 61, 71), dtype=np.float32) - 9999.0
cawood = np.zeros(shape=(dm1, 61, 71), dtype=np.float32) - 9999.0
cfroot = np.zeros(shape=(dm1, 61, 71), dtype=np.float32) - 9999.0
litter_l = np.zeros(shape=(dm1, 61, 71), dtype=np.float32) - 9999.0
cwd = np.zeros(shape=(dm1, 61, 71), dtype=np.float32) - 9999.0
litter_fr = np.zeros(shape=(dm1, 61, 71), dtype=np.float32) - 9999.0
lnc1 = np.zeros(shape=(dm1, 61, 71), dtype=np.float32) - 9999.0
lnc2 = np.zeros(shape=(dm1, 61, 71), dtype=np.float32) - 9999.0
lnc3 = np.zeros(shape=(dm1, 61, 71), dtype=np.float32) - 9999.0
lnc4 = np.zeros(shape=(dm1, 61, 71), dtype=np.float32) - 9999.0
lnc5 = np.zeros(shape=(dm1, 61, 71), dtype=np.float32) - 9999.0
lnc6 = np.zeros(shape=(dm1, 61, 71), dtype=np.float32) - 9999.0
sto1 = np.zeros(shape=(dm1, 61, 71), dtype=np.float32) - 9999.0
sto2 = np.zeros(shape=(dm1, 61, 71), dtype=np.float32) - 9999.0
sto3 = np.zeros(shape=(dm1, 61, 71), dtype=np.float32) - 9999.0
c_cost = np.zeros(shape=(dm1, 61, 71), dtype=np.float32) - 9999.0
print("\nQuerying data from file FOR", end=': ')
for v in vars:
print(v, end=", ")
print("\nInterval: ", interval)
print_progress(0, len(dates), prefix='Progress:', suffix='Complete')
for i, day in enumerate(dates):
out = table.read_where(day)
rcm[i, :, :] = assemble_layer(out['grid_y'], out['grid_x'], out['rcm'])
runom[i, :, :] = assemble_layer(out['grid_y'], out['grid_x'],
out['runom'])
evapm[i, :, :] = assemble_layer(out['grid_y'], out['grid_x'],
out['evapm'])
wsoil[i, :, :] = assemble_layer(out['grid_y'], out['grid_x'],
out['wsoil'])
swsoil[i, :, :] = assemble_layer(out['grid_y'], out['grid_x'],
out['swsoil'])
cleaf[i, :, :] = assemble_layer(out['grid_y'], out['grid_x'],
out['cleaf'])
cawood[i, :, :] = assemble_layer(out['grid_y'], out['grid_x'],
out['cawood'])
cfroot[i, :, :] = assemble_layer(out['grid_y'], out['grid_x'],
out['cfroot'])
litter_l[i, :, :] = assemble_layer(out['grid_y'], out['grid_x'],
out['litter_l'])
cwd[i, :, :] = assemble_layer(out['grid_y'], out['grid_x'], out['cwd'])
litter_fr[i, :, :] = assemble_layer(out['grid_y'], out['grid_x'],
out['litter_fr'])
lnc1[i, :, :] = assemble_layer(out['grid_y'], out['grid_x'],
out['lnc1'])
lnc2[i, :, :] = assemble_layer(out['grid_y'], out['grid_x'],
out['lnc2'])
lnc3[i, :, :] = assemble_layer(out['grid_y'], out['grid_x'],
out['lnc3'])
lnc4[i, :, :] = assemble_layer(out['grid_y'], out['grid_x'],
out['lnc4'])
lnc5[i, :, :] = assemble_layer(out['grid_y'], out['grid_x'],
out['lnc5'])
lnc6[i, :, :] = assemble_layer(out['grid_y'], out['grid_x'],
out['lnc6'])
sto1[i, :, :] = assemble_layer(out['grid_y'], out['grid_x'],
out['sto1'])
sto2[i, :, :] = assemble_layer(out['grid_y'], out['grid_x'],
out['sto2'])
sto3[i, :, :] = assemble_layer(out['grid_y'], out['grid_x'],
out['sto3'])
c_cost[i, :, :] = assemble_layer(out['grid_y'], out['grid_x'],
out['c_cost'])
print_progress(i + 1,
len(dates),
prefix='Progress:',
suffix='Complete')
# write netcdf
litter_n = lnc1 + lnc2 + lnc3
litter_p = lnc4 + lnc5 + lnc6
wsoil = swsoil + wsoil
vars = [
"rcm", "runom", "evapm", "wsoil", "cleaf", "cawood", "cfroot",
"litter_l", "cwd", "litter_fr", "litter_n", "litter_p", "sto_c",
"sto_n", "sto_p", "c_cost"
]
arr = (rcm, runom, evapm, wsoil, cleaf, cawood, cfroot, litter_l, cwd,
litter_fr, litter_n, litter_p, sto1, sto2, sto3, c_cost)
var_attrs = get_var_metadata(vars)
write_daily_output(arr, vars, var_attrs, interval)
def create_ncG1(table, interval):
nc_out = Path("../nc_outputs")
out_data = True if nc_out.exists() else os.mkdir(nc_out)
if out_data is None:
print(f"Creating output folder at{nc_out.resolve()}")
elif out_data:
print(f"Saving outputs in {nc_out.resolve()}")
vars = [
'photo', 'aresp', 'npp', 'lai', 'wue', 'cue', 'vcmax', 'sla', 'nupt',
'pupt'
]
dates = time_queries(interval)
dm1 = len(dates)
photo = np.zeros(shape=(dm1, 61, 71), dtype=np.float32) - 9999.0
aresp = np.zeros(shape=(dm1, 61, 71), dtype=np.float32) - 9999.0
npp = np.zeros(shape=(dm1, 61, 71), dtype=np.float32) - 9999.0
lai = np.zeros(shape=(dm1, 61, 71), dtype=np.float32) - 9999.0
wue = np.zeros(shape=(dm1, 61, 71), dtype=np.float32) - 9999.0
cue = np.zeros(shape=(dm1, 61, 71), dtype=np.float32) - 9999.0
vcmax = np.zeros(shape=(dm1, 61, 71), dtype=np.float32) - 9999.0
specific_la = np.zeros(shape=(dm1, 61, 71), dtype=np.float32) - 9999.0
nupt1 = np.zeros(shape=(dm1, 61, 71), dtype=np.float32) - 9999.0
nupt2 = np.zeros(shape=(dm1, 61, 71), dtype=np.float32) - 9999.0
pupt1 = np.zeros(shape=(dm1, 61, 71), dtype=np.float32) - 9999.0
pupt2 = np.zeros(shape=(dm1, 61, 71), dtype=np.float32) - 9999.0
pupt3 = np.zeros(shape=(dm1, 61, 71), dtype=np.float32) - 9999.0
# TODO sort G1 table
# if table.col has index: reindex_dirty
# else: create_index(row_id)
# tbl = table.copy(newname="indexed_g1", sortby=table.cols.row_index)
print("\nQuerying data from file FOR", end=': ')
for v in vars:
print(v, end=", ")
print("\nInterval: ", interval)
print_progress(0, len(dates), prefix='Progress:', suffix='Complete')
for i, day in enumerate(dates):
out = table.read_where(day)
photo[i, :, :] = assemble_layer(out['grid_y'], out['grid_x'],
out['photo'])
aresp[i, :, :] = assemble_layer(out['grid_y'], out['grid_x'],
out['aresp'])
npp[i, :, :] = assemble_layer(out['grid_y'], out['grid_x'], out['npp'])
lai[i, :, :] = assemble_layer(out['grid_y'], out['grid_x'], out['lai'])
wue[i, :, :] = assemble_layer(out['grid_y'], out['grid_x'], out['wue'])
cue[i, :, :] = assemble_layer(out['grid_y'], out['grid_x'], out['cue'])
vcmax[i, :, :] = assemble_layer(out['grid_y'], out['grid_x'],
out['vcmax'])
specific_la[i, :, :] = assemble_layer(out['grid_y'], out['grid_x'],
out['specific_la'])
nupt1[i, :, :] = assemble_layer(out['grid_y'], out['grid_x'],
out['nupt1'])
nupt2[i, :, :] = assemble_layer(out['grid_y'], out['grid_x'],
out['nupt2'])
pupt1[i, :, :] = assemble_layer(out['grid_y'], out['grid_x'],
out['pupt1'])
pupt2[i, :, :] = assemble_layer(out['grid_y'], out['grid_x'],
out['pupt2'])
pupt3[i, :, :] = assemble_layer(out['grid_y'], out['grid_x'],
out['pupt3'])
print_progress(i + 1,
len(dates),
prefix='Progress:',
suffix='Complete')
# write netcdf
nupt1 = nupt2 + nupt1
pupt1 = pupt3 + pupt2 + pupt1
vars = [
'photo', 'aresp', 'npp', 'lai', 'wue', 'cue', 'vcmax', 'sla', 'nupt',
'pupt'
]
arr = (photo, aresp, npp, lai, wue, cue, vcmax, specific_la, nupt1, pupt1)
var_attrs = get_var_metadata(vars)
write_daily_output(arr, vars, var_attrs, interval)
def create_ncG2(table, interval):
nc_out = Path("../nc_outputs")
out_data = True if nc_out.exists() else os.mkdir(nc_out)
if out_data is None:
print(f"Creating output folder at{nc_out.resolve()}")
elif out_data:
print(f"Saving outputs in {nc_out.resolve()}")
vars = [
'csoil', 'total_n', 'total_p', 'org_n', 'org_p', 'inorg_n', 'inorg_p',
'sorbed_p', 'hresp', 'nmin', 'pmin'
]
dates = time_queries(interval)
dm1 = len(dates)
csoil1 = np.zeros(shape=(dm1, 61, 71), dtype=np.float32) - 9999.0
csoil2 = np.zeros(shape=(dm1, 61, 71), dtype=np.float32) - 9999.0
csoil3 = np.zeros(shape=(dm1, 61, 71), dtype=np.float32) - 9999.0
csoil4 = np.zeros(shape=(dm1, 61, 71), dtype=np.float32) - 9999.0
sncN1 = np.zeros(shape=(dm1, 61, 71), dtype=np.float32) - 9999.0
sncN2 = np.zeros(shape=(dm1, 61, 71), dtype=np.float32) - 9999.0
sncN3 = np.zeros(shape=(dm1, 61, 71), dtype=np.float32) - 9999.0
sncN4 = np.zeros(shape=(dm1, 61, 71), dtype=np.float32) - 9999.0
sncP1 = np.zeros(shape=(dm1, 61, 71), dtype=np.float32) - 9999.0
sncP2 = np.zeros(shape=(dm1, 61, 71), dtype=np.float32) - 9999.0
sncP3 = np.zeros(shape=(dm1, 61, 71), dtype=np.float32) - 9999.0
sncP4 = np.zeros(shape=(dm1, 61, 71), dtype=np.float32) - 9999.0
inorg_n = np.zeros(shape=(dm1, 61, 71), dtype=np.float32) - 9999.0
inorg_p = np.zeros(shape=(dm1, 61, 71), dtype=np.float32) - 9999.0
sorbed_n = np.zeros(shape=(dm1, 61, 71), dtype=np.float32) - 9999.0
sorbed_p = np.zeros(shape=(dm1, 61, 71), dtype=np.float32) - 9999.0
hresp = np.zeros(shape=(dm1, 61, 71), dtype=np.float32) - 9999.0
nmin = np.zeros(shape=(dm1, 61, 71), dtype=np.float32) - 9999.0
pmin = np.zeros(shape=(dm1, 61, 71), dtype=np.float32) - 9999.0
print("\nQuerying data from file FOR", end=': ')
for v in vars:
print(v, end=", ")
print("\nInterval: ", interval)
print_progress(0, len(dates), prefix='Progress:', suffix='Complete')
for i, day in enumerate(dates):
out = table.read_where(day)
csoil1[i, :, :] = assemble_layer(out['grid_y'], out['grid_x'],
out["csoil1"])
csoil2[i, :, :] = assemble_layer(out['grid_y'], out['grid_x'],
out["csoil2"])
csoil3[i, :, :] = assemble_layer(out['grid_y'], out['grid_x'],
out["csoil3"])
csoil4[i, :, :] = assemble_layer(out['grid_y'], out['grid_x'],
out["csoil4"])
sncN1[i, :, :] = assemble_layer(out['grid_y'], out['grid_x'],
out["sncN1"])
sncN2[i, :, :] = assemble_layer(out['grid_y'], out['grid_x'],
out["sncN2"])
sncN3[i, :, :] = assemble_layer(out['grid_y'], out['grid_x'],
out["sncN3"])
sncN4[i, :, :] = assemble_layer(out['grid_y'], out['grid_x'],
out["sncN4"])
sncP1[i, :, :] = assemble_layer(out['grid_y'], out['grid_x'],
out["sncP1"])
sncP2[i, :, :] = assemble_layer(out['grid_y'], out['grid_x'],
out["sncP2"])
sncP3[i, :, :] = assemble_layer(out['grid_y'], out['grid_x'],
out["sncP3"])
sncP4[i, :, :] = assemble_layer(out['grid_y'], out['grid_x'],
out["sncP4"])
inorg_n[i, :, :] = assemble_layer(out['grid_y'], out['grid_x'],
out["inorg_n"])
inorg_p[i, :, :] = assemble_layer(out['grid_y'], out['grid_x'],
out["inorg_p"])
sorbed_n[i, :, :] = assemble_layer(out['grid_y'], out['grid_x'],
out["sorbed_n"])
sorbed_p[i, :, :] = assemble_layer(out['grid_y'], out['grid_x'],
out["sorbed_p"])
hresp[i, :, :] = assemble_layer(out['grid_y'], out['grid_x'],
out["hresp"])
nmin[i, :, :] = assemble_layer(out['grid_y'], out['grid_x'],
out["nmin"])
pmin[i, :, :] = assemble_layer(out['grid_y'], out['grid_x'],
out["pmin"])
print_progress(i + 1,
len(dates),
prefix='Progress:',
suffix='Complete')
# write netcdf
csoil = csoil1 + csoil2 + csoil3 + csoil4
org_n = sncN1 + sncN2 + sncN3 + sncN4
org_p = sncP1 + sncP2 + sncP3 + sncP4
inorg_n = sorbed_n + inorg_n
vars = [
'csoil', 'org_n', 'org_p', 'inorg_n', 'inorg_p', 'sorbed_p', 'hresp',
'nmin', 'pmin'
]
arr = (csoil, org_n, org_p, inorg_n, inorg_p, sorbed_p, hresp, nmin, pmin)
var_attrs = get_var_metadata(vars)
write_daily_output(arr, vars, var_attrs, interval)
def write_snap_output(arr,
var,
flt_attrs,
time_index,
experiment="TEST RUN HISTORICAL ISIMIP"):
NO_DATA = [-9999.0, -9999.0]
time_units = TIME_UNITS
calendar = CALENDAR
nc_out = Path("../nc_outputs")
time_dim = time_index
longitude_0 = np.arange(-179.75, 180, 0.5)[201:272]
latitude_0 = np.arange(89.75, -90, -0.5)[160:221]
print("\nSaving netCDF4 files")
print_progress(0, len(var), prefix='Progress:', suffix='Complete')
for i, v in enumerate(var):
nc_filename = os.path.join(nc_out, Path(f'{v}.nc4'))
with dt(nc_filename, mode='w', format='NETCDF4') as rootgrp:
# dimensions & variables
rootgrp.createDimension("latitude", latitude_0.size)
rootgrp.createDimension("longitude", longitude_0.size)
rootgrp.createDimension("time", None)
time = rootgrp.createVariable(varname="time",
datatype=np.int32,
dimensions=("time", ))
latitude = rootgrp.createVariable(varname="latitude",
datatype=np.float32,
dimensions=("latitude", ))
longitude = rootgrp.createVariable(varname="longitude",
datatype=np.float32,
dimensions=("longitude", ))
var_ = rootgrp.createVariable(varname=flt_attrs[v][2],
datatype=np.float32,
dimensions=(
"time",
"latitude",
"longitude",
),
zlib=True,
fill_value=NO_DATA[0],
fletcher32=True)
# attributes
# rootgrp
rootgrp.description = flt_attrs[v][0] + " from CAETÊ-CNP OUTPUT"
rootgrp.source = "CAETE model outputs - [email protected]"
rootgrp.experiment = experiment
# time
time.units = time_units
time.calendar = calendar
time.axis = 'T'
# lat
latitude.units = u"degrees_north"
latitude.long_name = u"latitude"
latitude.standart_name = u"latitude"
latitude.axis = u'Y'
# lon
longitude.units = "degrees_east"
longitude.long_name = "longitude"
longitude.standart_name = "longitude"
longitude.axis = u'X'
# var
var_.long_name = flt_attrs[v][0]
var_.units = flt_attrs[v][1]
var_.standard_name = flt_attrs[v][2]
var_.missing_value = NO_DATA[0]
# WRITING DATA
longitude[:] = longitude_0
latitude[:] = latitude_0
time[:] = time_dim
var_[:, :, :] = np.ma.masked_array(arr[i],
mask=arr[i] == NO_DATA[0])
print_progress(i + 1,
len(var),
prefix='Progress:',
suffix='Complete')