pnum = 0
CNP_parms = ['ks_sorption', 'r_desorp', 'r_weather', 'r_adsorp', 'k_s1_biochem', 'smax', 'k_s3_biochem', \
'r_occlude', 'k_s4_biochem', 'k_s2_biochem']
fates_seed_zeroed = [False, False]
for p in parm_names:
if ('INI' in p):
if ('BGC' in casename):
scalevars = ['soil3c_vr', 'soil3n_vr', 'soil3p_vr']
else:
scalevars = ['soil4c_vr', 'soil4n_vr', 'soil4p_vr']
sumvars = ['totsomc', 'totsomp', 'totcolc', 'totcoln', 'totcolp']
for v in scalevars:
myvar = nffun.getvar(finidat_file_new, v)
myvar = parm_values[pnum] * myvar
ierr = nffun.putvar(finidat_file_new, v, myvar)
elif (p == 'lai'):
myfile = surffile
param = nffun.getvar(myfile, 'MONTHLY_LAI')
param[:, :, :, :] = parm_values[pnum]
ierr = nffun.putvar(myfile, 'MONTHLY_LAI', param)
elif (p != 'co2'):
if (p in CNP_parms):
myfile = CNPfile
elif ('fates' in p):
myfile = fates_paramfile
else:
myfile = pftfile
param = nffun.getvar(myfile, p)
if (('fates_prt' in p and 'stoich' in p)
or ('fates_turnover' in p and 'retrans' in p)):
pnum = 0
CNP_parms = ['ks_sorption', 'r_desorp', 'r_weather', 'r_adsorp', 'k_s1_biochem', 'smax', 'k_s3_biochem', \
'r_occlude', 'k_s4_biochem', 'k_s2_biochem']
fates_seed_zeroed=[False,False]
for p in parm_names:
if ('INI' in p):
if ('BGC' in casename):
scalevars = ['soil3c_vr','soil3n_vr','soil3p_vr']
else:
scalevars = ['soil4c_vr','soil4n_vr','soil4p_vr']
sumvars = ['totsomc','totsomp','totcolc','totcoln','totcolp']
for v in scalevars:
myvar = nffun.getvar(finidat_file_new, v)
myvar = parm_values[pnum] * myvar
ierr = nffun.putvar(finidat_file_new, v, myvar)
elif (p == 'lai'):
myfile = surffile
param = nffun.getvar(myfile, 'MONTHLY_LAI')
param[:,:,:,:] = parm_values[pnum]
ierr = nffun.putvar(myfile, 'MONTHLY_LAI', param)
elif (p != 'co2'):
if (p in CNP_parms):
myfile= CNPfile
elif ('fates' in p):
myfile = fates_paramfile
else:
myfile = pftfile
param = nffun.getvar(myfile,p)
if ('fates_prt_nitr_stoich_p1' in p):
#this is a 2D parameter.
area = nffun.getvar(domainfile_new, 'area')
frac[0] = 1.0
mask[0] = 1
if (options.site != ''):
xc[0] = lon[n]
yc[0] = lat[n]
xv[0][0][0] = lon[n] - resx / 2
xv[0][0][1] = lon[n] + resx / 2
xv[0][0][2] = lon[n] - resx / 2
xv[0][0][3] = lon[n] + resx / 2
yv[0][0][0] = lat[n] - resy / 2
yv[0][0][1] = lat[n] - resy / 2
yv[0][0][2] = lat[n] + resy / 2
yv[0][0][3] = lat[n] + resy / 2
area[0] = resx * resy * math.pi / 180 * math.pi / 180
ierr = nffun.putvar(domainfile_new, 'xc', xc)
ierr = nffun.putvar(domainfile_new, 'yc', yc)
ierr = nffun.putvar(domainfile_new, 'xv', xv)
ierr = nffun.putvar(domainfile_new, 'yv', yv)
ierr = nffun.putvar(domainfile_new, 'area', area)
ierr = nffun.putvar(domainfile_new, 'frac', frac)
ierr = nffun.putvar(domainfile_new, 'mask', mask)
os.system('ncks -O --mk_rec_dim nj ' + domainfile_new + ' ' +
domainfile_new)
elif (options.mymask != ''):
print 'Applying mask from ' + options.mymask
os.system('ncks -d lon,'+str(xgrid_min[n])+','+str(xgrid_max[n])+' -d lat,'+str(ygrid_min[n])+ \
','+str(ygrid_max[n])+' '+options.mymask+' mask_temp.nc')
newmask = nffun.getvar('mask_temp.nc', 'PNW_mask')
ierr = nffun.putvar(domainfile_new, 'mask', newmask)
for v in range(0,len(var_names_harvest)):
rest_vals = nffun.getvar(fname_restart, var_names_harvest[v].lower())
#Loop through all valid values in the restart file.
n_rest = len(rest_vals)
for i in range(0,n_rest):
rest_vals[i] = rest_vals[i]*0.05
if (var_names_harvest[v] == 'LEAFC'):
rest_vals[i] = 0.33/0.03
print(rest_vals[i])
elif (var_names_harvest[v] == 'FROOTC'):
rest_vals[i] = 0.33/0.03*0.666
elif (var_names_harvest[v] == 'LEAFN'):
rest_vals[i] = 0.33/0.03/25.0
elif (var_names_harvest[v] == 'FROOTN'):
rest_vals[i] = 0.33/0.03/42.0
ierr = nffun.putvar(fname_restart, var_names_harvest[v].lower(), rest_vals)
else:
for v in range(0,len(var_names)):
hist_vals = nffun.getvar(fname_hist, var_names[v])
rest_vals = nffun.getvar(fname_restart, var_names[v].lower())
#Loop through all valid values in the restart file.
n_rest = len(rest_vals)
for i in range(0,n_rest):
if (float(rest_vals[i]) > 0.0 and float(hist_vals[0][i]) < 1.0e10 and float(hist_vals[0][i]) > 0.001):
rest_vals[i] = hist_vals[0][i]
ierr = nffun.putvar(fname_restart, var_names[v].lower(), rest_vals)
#get a single, non-depth dependent variable to count # of columns
rest_vals = nffun.getvar(fname_restart, 'fpg')
n_rest = len(rest_vals)
for v in range(0,len(var_names2d)):