def calc_myami_Csys(dat):
cols = ['pHtot', 'DIC', 'HCO3', 'CO3', 'TA']
dic = dat.loc[:, 'DIC'].copy()
# pHNBS and DIC
ind = ~np.isnan(dat.loc[:, 'pHNBS']) & ~np.isnan(dic)
if any(ind):
cs = cb.Csys(
pHNBS=dat.loc[ind, 'pHNBS'],
DIC=dic.loc[ind],
BT=dat.loc[ind, 'B umol/kg'],
Ca=dat.loc[ind, '[Ca]sw'] * 1e-3,
Mg=dat.loc[ind, '[Mg]sw'] * 1e-3,
T_in=dat.loc[ind, 'Temp'],
S_in=dat.loc[ind, 'Salinity'],
)
for c in cols:
dat.loc[ind, c.replace('_out', '')] = cs[c]
dat.loc[ind, 'omega'] = cs.CO3 * 1e-6 * cs.Ca / cs.Ks.KspC
# pHTOT and DIC
ind = ~np.isnan(dat.loc[:, 'pHTOTAL']) & ~np.isnan(dic)
if any(ind):
cs = cb.Csys(
pHtot=dat.loc[ind, 'pHTOTAL'],
DIC=dic.loc[ind],
BT=dat.loc[ind, 'B umol/kg'],
Ca=dat.loc[ind, '[Ca]sw'] * 1e-3,
Mg=dat.loc[ind, '[Mg]sw'] * 1e-3,
T_in=dat.loc[ind, 'Temp'],
S_in=dat.loc[ind, 'Salinity'],
)
for c in cols:
dat.loc[ind, c.replace('_out', '')] = cs[c]
dat.loc[ind, 'omega'] = cs.CO3 * 1e-6 * cs.Ca / cs.Ks.KspC
# pHTOT and TA
ind = ~np.isnan(dat.loc[:, 'pHTOTAL']) & ~np.isnan(dat.loc[:, 'Alk'])
if any(ind):
cs = cb.Csys(
pHtot=dat.loc[ind, 'pHTOTAL'],
TA=dat.loc[ind, 'Alk'],
BT=dat.loc[ind, 'B umol/kg'],
Ca=dat.loc[ind, '[Ca]sw'] * 1e-3,
Mg=dat.loc[ind, '[Mg]sw'] * 1e-3,
T_in=dat.loc[ind, 'Temp'],
S_in=dat.loc[ind, 'Salinity'],
)
for c in cols:
dat.loc[ind, c.replace('_out', '')] = cs[c]
dat.loc[ind, 'omega'] = cs.CO3 * 1e-6 * cs.Ca / cs.Ks.KspC
# pHNBS and TA
ind = ~np.isnan(dat.loc[:, 'pHNBS']) & ~np.isnan(dat.loc[:, 'Alk'])
if any(ind):
cs = cb.Csys(
pHNBS=dat.loc[ind, 'pHNBS'],
TA=dat.loc[ind, 'Alk'],
BT=dat.loc[ind, 'B umol/kg'],
Ca=dat.loc[ind, '[Ca]sw'] * 1e-3,
Mg=dat.loc[ind, '[Mg]sw'] * 1e-3,
T_in=dat.loc[ind, 'Temp'],
S_in=dat.loc[ind, 'Salinity'],
)
for c in cols:
dat.loc[ind, c.replace('_out', '')] = cs[c]
dat.loc[ind, 'omega'] = cs.CO3 * 1e-6 * cs.Ca / cs.Ks.KspC
return dat
Si : `numpy.array` or `xarray.DataArray` or `pd.core.series.Series`
Silicate (umol/kg)
AOU : `numpy.array` or `xarray.DataArray` or `pd.core.series.Series`
Apparent Oxygen Utilization (umol/kg)
Returns
-------
dcstar : `numpy.array` or `xarray.DataArray` or `pd.core.series.Series`
An array of ∆C* values (umol/kg)
"""
if Gruber == True:
Alk_pre_calc = 367.5 + 54.9*S + 0.074*PO(P,O)
out = cb.Csys(fCO2=280,TA=Alk_pre_calc.ravel(),T=theta.ravel(),S=S.ravel())
DICpi_eq = np.reshape(out.DIC,DIC.shape)
dcstar = DIC-R_co*AOU-0.5*(Alk-Alk_pre_calc+(16/170)*(AOU))-DICpi_eq
else:
Alk_pre_calc = Alk_pre(N,O,P,Si,S,theta,AOU,Alk_pre_eomp)
out = cb.Csys(fCO2=280,TA=Alk_pre_calc.ravel(),T=theta.ravel())
DICpi_eq = np.reshape(out.DIC,DIC.shape)
dcstar = DIC-R_co*AOU-dCa(N,O,P,Si,Alk,S,theta)-DICpi_eq
def calc_pitzer_Csys(
dat,
database='/home/oscar/phreeqc/iphreeqc-3.3.9-11951/database/pitzer.dat',
phreeq_path='/usr/local/lib/libiphreeqc.so'):
"""
Function to calculate C specitation, corrected for [Mg] and [Ca] using PHREEQC.
Parameters
----------
d : pandas.DataFrame
Output of mg_data load function.
database : str
Path to PITZER database file.
phreeq_path : str
Path to PHREEQC executable.
"""
# remove data without [Mg] and [Ca]
dat = dat.loc[~dat.loc[:, ['[Mg]sw', '[Ca]sw']].isnull().any(1)]
# create working copy
d = dat.copy()
# rename columns
d.columns = pd.MultiIndex.from_product([['Measured'], d.columns])
# define standard seawater composition (mol/kg SW)
# ================================================
sw = {
'pH': 8.2,
'Temp': 25,
'units': 'mol/kgw',
'density': 1.026,
'Ca': 10.28e-3,
'Cl': 0.54586,
'K': 10.21e-3,
'Mg': 52.82e-3,
'Na': 0.46906,
'S(6)': 0.02824,
'B': 416e-6,
'C': 2.3e-3,
'Br': 0.84e-3,
'F': 0.7e-4
}
# calculate ambient Ks at 25C (measurement temperature)
# =====================================================
ks = {}
TempC = 25
TempK = TempC + 273.15
Sal = d.loc[:, ('Measured', 'Salinity')]
par = cb.MyAMI_V2.start_params
fns = cb.MyAMI_V2.fn_dict
for k in ['K0', 'K1', 'K2', 'KB', 'KW', 'KspC', 'KspA', 'KSO4']:
ks[k] = fns[k]((TempK, Sal), *par[k])
# calculate other Ks
ks.update(cb.non_MyAMI_constants.calc_KF(TempC, Sal))
ks.update(cb.non_MyAMI_constants.calc_KPs(TempC, Sal))
ks.update(cb.non_MyAMI_constants.calc_KSi(TempC, Sal))
# calculate correction factors at 25C
# ===================================
fKs = {}
isw = sw.copy()
salsc = ['Cl', 'K', 'Na', 'S(6)', 'Br', 'F']
for i, v in tqdm(d.iterrows(),
total=d.shape[0],
desc='Calculating 25C Corrections'):
v = v.Measured
isw.update({
'Mg': v.loc['[Mg]sw'] * 1e-3,
'Ca': v.loc['[Ca]sw'] * 1e-3,
'Temp': 25,
'B': v.loc['B umol/kg'] * 1e-6
})
sal_f = v.Salinity / 35.
isw.update({k: sw[k] * sal_f for k in salsc})
fks = ph.calc_pitzer_fKs(sw,
isw,
database=database,
phreeq_path=phreeq_path)
for k, f in fks.items():
if k not in fKs:
fKs[k] = []
fKs[k].append(f)
# apply correction factors to 25C Ks
# ==================================
cKs = ks.copy()
for k, f in fKs.items():
cKs[k] = ks[k] * f
# convert all pH scales to Total
# ==============================
pHs = cb.helpers.calc_pH_scales(pHtot=None,
pHfree=None,
pHsws=None,
pHNBS=d.loc[:, ('Measured', 'pHNBS')],
TS=cb.calc_TS(Sal),
TF=cb.calc_TF(Sal),
TempK=TempK,
Sal=Sal,
Ks=cb.Bunch(cKs))
ind = d.loc[:, ('Measured', 'pHTOTAL')].isnull()
d.loc[ind, ('Measured', 'pHTOTAL')] = pHs['pHtot'][ind]
# Calculate DIC/Alk at MEASURED conditions (25C)
# ==============================================
# calculate carbon system using 25C Ks, pH and either DIC or Alk
carb = cb.Csys(d.loc[:, ('Measured', 'pHTOTAL')],
TA=d.loc[:, ('Measured', 'Alk')],
BT=d.loc[:, ('Measured', 'B umol/kg')],
Ks=cKs)
d.loc[:, ('pitzer_25C', 'DIC')] = carb.DIC
carb = cb.Csys(d.loc[:, ('Measured', 'pHTOTAL')],
DIC=d.loc[:, ('Measured', 'DIC')],
BT=d.loc[:, ('Measured', 'B umol/kg')],
Ks=cKs)
d.loc[:, ('pitzer_25C', 'Alk')] = carb.TA
# whichever of DIC or Alk wasn't calculated, transfer the
# measured value to the pitzer_25C column for in-situ condition calculation
dicnull = d.loc[:, ('pitzer_25C', 'DIC')].isnull()
d.loc[dicnull, ('pitzer_25C', 'DIC')] = d.loc[dicnull, ('Measured', 'DIC')]
alknull = d.loc[:, ('pitzer_25C', 'Alk')].isnull()
d.loc[alknull, ('pitzer_25C', 'Alk')] = d.loc[alknull, ('Measured', 'Alk')]
# calculate empirical Ks for ambient Mg and Ca, and experiment Sal and Temp
# =========================================================================
eKs = cb.calc_Ks(d.loc[:, ('Measured', 'Temp')],
d.loc[:, ('Measured', 'Salinity')], 0, sw['Mg'], sw['Ca'],
cb.calc_TS(d.loc[:, ('Measured', 'Salinity')]),
cb.calc_TF(d.loc[:, ('Measured', 'Salinity')]))
# calculate correction factors at experimental temperature
# ========================================================
fKs = {}
isw = sw.copy()
salsc = ['Cl', 'K', 'Na', 'S(6)', 'Br', 'F']
for i, v in tqdm(d.iterrows(),
total=d.shape[0],
desc='Calculating Experimental T Corrections'):
v = v.Measured
isw.update({
'Mg': v.loc['[Mg]sw'] * 1e-3,
'Ca': v.loc['[Ca]sw'] * 1e-3,
'Temp': v.Temp,
'B': v.loc['B umol/kg'] * 1e-6
})
sal_f = v.Salinity / 35.
isw.update({k: sw[k] * sal_f for k in salsc})
fks = ph.calc_pitzer_fKs(sw,
isw,
database=database,
phreeq_path=phreeq_path)
for k, f in fks.items():
if k not in fKs:
fKs[k] = []
fKs[k].append(f)
# apply correction factors
for k, f in fKs.items():
eKs[k] = ks[k] * f
# calculate carbon system at experimental conditions using pitzer-calculated DIC/Alk pairs
carb = cb.Csys(DIC=d.loc[:, ('pitzer_25C', 'DIC')],
TA=d.loc[:, ('pitzer_25C', 'Alk')],
BT=d.loc[:, ('Measured', 'B umol/kg')],
Ks=cKs)
# store outputs!
for c in ['DIC', 'TA', 'CO3', 'HCO3', 'CO2', 'pHtot']:
d.loc[:, ('pitzer_expT', c)] = carb[c]
dat.loc[:, c] = carb[c]
return dat
def GLODAPv2_comparison(figdir='.'):
print("\n********************************************")
print("Generating GLODAPv2 Comparison Plots")
print("********************************************")
# if the data file is missing, get it.
if not os.path.exists('./GLODAPv2_pH_DIC_ALK_subset.csv'):
print('Getting GLODAPv2 Data...')
from get_GLODAP_data import get_GLODAP
get_GLODAP()
# Load data
print('Importing GLODAPv2 Data...')
gd = pd.read_csv('./GLODAPv2_pH_DIC_ALK_subset.csv')
gd.dropna(subset=[
'phtsinsitutp', 'temperature', 'salinity', 'tco2', 'talk', 'pressure',
'phosphate', 'silicate'
],
inplace=True)
gd.pressure /= 10 # convert pressure to bar
# exclude weird cruise 270 data
gd = gd.loc[gd.cruise != 270]
# Do the work...
print('Calculating pH from DIC and TA...')
cpH = cb.Csys(TA=gd.talk,
DIC=gd.tco2,
T=gd.temperature,
S=gd.salinity,
P=gd.pressure,
TP=gd.phosphate,
TSi=gd.silicate,
BT=415.7)
print(' Making plots...')
fig, axs = cplot(gd.phtsinsitutp, cpH.pH, 'pH', 'Depth', gd.depth)
fig.savefig(figdir + '/Figures/pH_comparison.png', dpi=200)
print('Calculating TA from pH and DIC...')
cTA = cb.Csys(pH=gd.phtsinsitutp,
DIC=gd.tco2,
T=gd.temperature,
S=gd.salinity,
P=gd.pressure,
TP=gd.phosphate,
TSi=gd.silicate,
BT=415.7)
print(' Making plots...')
fig, ax = cplot(gd.talk, cTA.TA, 'Alk', 'Depth', gd.depth)
fig.savefig('Figures/TA_comparison.png', dpi=200)
print('Calculating DIC from pH and TA...')
cDIC = cb.Csys(pH=gd.phtsinsitutp,
TA=gd.talk,
T=gd.temperature,
S=gd.salinity,
P=gd.pressure,
TP=gd.phosphate,
TSi=gd.silicate,
BT=415.7)
print(' Making plots...')
fig, ax = cplot(gd.tco2, cDIC.DIC, 'DIC', 'Depth', gd.depth)
fig.savefig('Figures/DIC_comparison.png', dpi=200)
print("Done.")
print()
print(' > Plots are saved in : ' + figdir + '/Figures/')
print("********************************************")
def GLODAPv2_comparison(figdir="."):
print("\n********************************************")
print("Generating GLODAPv2 Comparison Plots")
print("********************************************")
# if the data file is missing, get it.
if not os.path.exists("./GLODAPv2_pH_DIC_ALK_subset.csv"):
print("Getting GLODAPv2 Data...")
from get_GLODAP_data import get_GLODAP
get_GLODAP()
# Load data
print("Importing GLODAPv2 Data...")
gd = pd.read_csv("./GLODAPv2_pH_DIC_ALK_subset.csv")
gd.dropna(
subset=[
"phtsinsitutp",
"temperature",
"salinity",
"tco2",
"talk",
"pressure",
"phosphate",
"silicate",
],
inplace=True,
)
gd.pressure /= 10 # convert pressure to bar
# exclude weird cruise 270 data
gd = gd.loc[gd.cruise != 270]
# Do the work...
print("Calculating pH from DIC and TA...")
cpH = cb.Csys(
TA=gd.talk,
DIC=gd.tco2,
T=gd.temperature,
S=gd.salinity,
P=gd.pressure,
TP=gd.phosphate,
TSi=gd.silicate,
BT=415.7,
)
print(" Making plots...")
fig, axs = cplot(gd.phtsinsitutp, cpH.pH, "pH", "Depth", gd.depth)
fig.savefig(figdir + "/Figures/pH_comparison.png", dpi=200)
print("Calculating TA from pH and DIC...")
cTA = cb.Csys(
pH=gd.phtsinsitutp,
DIC=gd.tco2,
T=gd.temperature,
S=gd.salinity,
P=gd.pressure,
TP=gd.phosphate,
TSi=gd.silicate,
BT=415.7,
)
print(" Making plots...")
fig, ax = cplot(gd.talk, cTA.TA, "Alk", "Depth", gd.depth)
fig.savefig("Figures/TA_comparison.png", dpi=200)
print("Calculating DIC from pH and TA...")
cDIC = cb.Csys(
pH=gd.phtsinsitutp,
TA=gd.talk,
T=gd.temperature,
S=gd.salinity,
P=gd.pressure,
TP=gd.phosphate,
TSi=gd.silicate,
BT=415.7,
)
print(" Making plots...")
fig, ax = cplot(gd.tco2, cDIC.DIC, "DIC", "Depth", gd.depth)
fig.savefig("Figures/DIC_comparison.png", dpi=200)
print("Done.")
print()
print(" > Plots are saved in : " + figdir + "/Figures/")
print("********************************************")
def calc_pitzer_Csys(d,
database='./mg_funks/db_phreeqc/pitzer.dat',
phreeq_path='/usr/local/lib/libiphreeqc.so'):
# define standard seawater composition (mol/kg SW)
# ================================================
sw = {
'pH': 8.2,
'Temp': 25,
'units': 'mol/kgw',
'density': 1.026,
'Ca': 10.28e-3,
'Cl': 0.54586,
'K': 10.21e-3,
'Mg': 52.82e-3,
'Na': 0.46906,
'S(6)': 0.02824,
'B': 416e-6,
'C': 2.3e-3,
'Br': 0.84e-3,
'F': 0.7e-4
}
# calculate ambient Ks at measurement temperatures
# =====================================================
ks = {}
TempC = d.loc[:, ('Measured', 'pH_Temp')]
TempK = TempC + 273.15
Sal = d.loc[:, ('Measured', 'Salinity')]
par = cb.MyAMI_V2.start_params
fns = cb.MyAMI_V2.fn_dict
for k in ['K0', 'K1', 'K2', 'KB', 'KW', 'KspC', 'KspA', 'KSO4']:
ks[k] = fns[k]((TempK, Sal), *par[k])
# calculate other Ks
ks.update(cb.non_MyAMI_constants.calc_KF(TempC, Sal))
ks.update(cb.non_MyAMI_constants.calc_KPs(TempC, Sal))
ks.update(cb.non_MyAMI_constants.calc_KSi(TempC, Sal))
# calculate correction factors at 25C
# ===================================
fKs = {}
isw = sw.copy()
salsc = ['Cl', 'K', 'Na', 'S(6)', 'Br', 'F']
for i, v in tqdm(d.iterrows(),
total=d.shape[0],
desc='Calculating 25C Corrections'):
v = v.Measured
isw.update({
'Mg': v.loc['[Mg]sw'] * 1e-3,
'Ca': v.loc['[Ca]sw'] * 1e-3,
'Temp': v.loc['pH_Temp'],
'B': v.loc['B umol/kg'] * 1e-6
})
sal_f = v.Salinity / 35.
isw.update({k: sw[k] * sal_f for k in salsc})
fks = calc_pitzer_fKs(sw,
isw,
database=database,
phreeq_path=phreeq_path)
for k, f in fks.items():
if k not in fKs:
fKs[k] = []
fKs[k].append(f)
# apply correction factors to measurement temperature Ks
# ==================================
cKs = ks.copy()
for k, f in fKs.items():
cKs[k] = ks[k] * f
# convert all pH scales to Total
# ==============================
pHs = cb.helpers.calc_pH_scales(pHtot=None,
pHfree=None,
pHsws=None,
pHNBS=d.loc[:, ('Measured', 'pHNBS')],
TS=cb.calc_TS(Sal),
TF=cb.calc_TF(Sal),
TempK=TempK,
Sal=Sal,
Ks=cb.Bunch(cKs))
d.loc[:, ('pitzer_25C', 'pHTOTAL')] = d.loc[:, ('Measured', 'pHTOTAL')]
ind = d.loc[:, ('Measured', 'pHTOTAL')].isnull()
d.loc[ind, ('pitzer_25C', 'pHTOTAL')] = pHs['pHtot'][ind]
# Calculate DIC/Alk at MEASURED conditions
# ==============================================
# calculate carbon system using measured temp Ks, pH and either DIC or Alk
carb = cb.Csys(d.loc[:, ('pitzer_25C', 'pHTOTAL')],
TA=d.loc[:, ('Measured', 'Alk')],
BT=d.loc[:, ('Measured', 'B umol/kg')],
Ks=cKs)
d.loc[:, ('pitzer_25C', 'DIC')] = carb.DIC
carb = cb.Csys(d.loc[:, ('pitzer_25C', 'pHTOTAL')],
DIC=d.loc[:, ('Measured', 'DIC')],
BT=d.loc[:, ('Measured', 'B umol/kg')],
Ks=cKs)
d.loc[:, ('pitzer_25C', 'Alk')] = carb.TA
# whichever of DIC or Alk wasn't calculated, transfer the
# measured value to the pitzer_25C column for in-situ condition calculation
dicnull = d.loc[:, ('pitzer_25C', 'DIC')].isnull()
d.loc[dicnull, ('pitzer_25C', 'DIC')] = d.loc[dicnull, ('Measured', 'DIC')]
alknull = d.loc[:, ('pitzer_25C', 'Alk')].isnull()
d.loc[alknull, ('pitzer_25C', 'Alk')] = d.loc[alknull, ('Measured', 'Alk')]
# calculate empirical Ks for ambient Mg and Ca, and experiment Sal and Temp
# =========================================================================
eKs = cb.calc_Ks(d.loc[:, ('Measured', 'Temp')],
d.loc[:, ('Measured', 'Salinity')], 0, sw['Mg'], sw['Ca'],
cb.calc_TS(d.loc[:, ('Measured', 'Salinity')]),
cb.calc_TF(d.loc[:, ('Measured', 'Salinity')]))
# calculate correction factors at experimental temperature
# ========================================================
fKs = {}
isw = sw.copy()
salsc = ['Cl', 'K', 'Na', 'S(6)', 'Br', 'F']
for i, v in tqdm(d.iterrows(),
total=d.shape[0],
desc='Calculating Experimental T Corrections'):
v = v.Measured
isw.update({
'Mg': v.loc['[Mg]sw'] * 1e-3,
'Ca': v.loc['[Ca]sw'] * 1e-3,
'Temp': v.Temp,
'B': v.loc['B umol/kg'] * 1e-6
})
sal_f = v.Salinity / 35.
isw.update({k: sw[k] * sal_f for k in salsc})
fks = calc_pitzer_fKs(sw,
isw,
database=database,
phreeq_path=phreeq_path)
for k, f in fks.items():
if k not in fKs:
fKs[k] = []
fKs[k].append(f)
# apply correction factors
for k, f in fKs.items():
eKs[k] = ks[k] * f
# calculate carbon system at experimental conditions using pitzer-calculated DIC/Alk pairs
carb = cb.Csys(DIC=d.loc[:, ('pitzer_25C', 'DIC')],
TA=d.loc[:, ('pitzer_25C', 'Alk')],
BT=d.loc[:, ('Measured', 'B umol/kg')],
Ks=eKs)
# store outputs!
for c in ['DIC', 'TA', 'CO3', 'HCO3', 'CO2', 'pHtot']:
d.loc[:, ('pitzer', c)] = carb[c]
return d
def calc_MyAMI_Csys(d):
out_cols = ['DIC', 'TA', 'CO3', 'HCO3', 'CO2', 'pHtot']
# for pHNBS and Alk
ind = ~d.loc[:, ('Measured', 'pHNBS')].isnull() & ~d.loc[:,
('Measured',
'Alk')].isnull()
if any(ind):
cs = cb.Csys(pHNBS=d.loc[ind, ('Measured', 'pHNBS')],
TA=d.loc[ind, ('Measured', 'Alk')],
T_in=d.loc[ind, ('Measured', 'pH_Temp')],
T_out=d.loc[ind, ('Measured', 'Temp')],
S_in=d.loc[ind, ('Measured', 'Salinity')],
Mg=d.loc[ind, ('Measured', '[Mg]sw')] / 1e3,
Ca=d.loc[ind, ('Measured', '[Ca]sw')] / 1e3,
BT=d.loc[ind, ('Measured', 'B umol/kg')])
for c in out_cols:
d.loc[ind, ('MyAMI', c)] = cs[c]
d.loc[ind, ('MyAMI', 'KspC')] = cs['Ks']['KspC']
# for pHNBS and DIC
ind = ~d.loc[:, ('Measured', 'pHNBS')].isnull() & ~d.loc[:,
('Measured',
'DIC')].isnull()
if any(ind):
cs = cb.Csys(pHNBS=d.loc[ind, ('Measured', 'pHNBS')],
DIC=d.loc[ind, ('Measured', 'DIC')],
T_in=d.loc[ind, ('Measured', 'pH_Temp')],
T_out=d.loc[ind, ('Measured', 'Temp')],
S_in=d.loc[ind, ('Measured', 'Salinity')],
Mg=d.loc[ind, ('Measured', '[Mg]sw')] / 1e3,
Ca=d.loc[ind, ('Measured', '[Ca]sw')] / 1e3,
BT=d.loc[ind, ('Measured', 'B umol/kg')])
for c in out_cols:
d.loc[ind, ('MyAMI', c)] = cs[c]
d.loc[ind, ('MyAMI', 'KspC')] = cs['Ks']['KspC']
# for pHTOTAL and Alk
ind = ~d.loc[:,
('Measured', 'pHTOTAL')].isnull() & ~d.loc[:,
('Measured',
'Alk')].isnull()
if any(ind):
cs = cb.Csys(pHtot=d.loc[ind, ('Measured', 'pHTOTAL')],
TA=d.loc[ind, ('Measured', 'Alk')],
T_in=d.loc[ind, ('Measured', 'pH_Temp')],
T_out=d.loc[ind, ('Measured', 'Temp')],
S_in=d.loc[ind, ('Measured', 'Salinity')],
Mg=d.loc[ind, ('Measured', '[Mg]sw')] / 1e3,
Ca=d.loc[ind, ('Measured', '[Ca]sw')] / 1e3,
BT=d.loc[ind, ('Measured', 'B umol/kg')])
for c in out_cols:
d.loc[ind, ('MyAMI', c)] = cs[c]
d.loc[ind, ('MyAMI', 'KspC')] = cs['Ks']['KspC']
# for pHTOTAL and DIC
ind = ~d.loc[:,
('Measured', 'pHTOTAL')].isnull() & ~d.loc[:,
('Measured',
'DIC')].isnull()
if any(ind):
cs = cb.Csys(pHtot=d.loc[ind, ('Measured', 'pHTOTAL')],
DIC=d.loc[ind, ('Measured', 'DIC')],
T_in=d.loc[ind, ('Measured', 'pH_Temp')],
T_out=d.loc[ind, ('Measured', 'Temp')],
S_in=d.loc[ind, ('Measured', 'Salinity')],
Mg=d.loc[ind, ('Measured', '[Mg]sw')] / 1e3,
Ca=d.loc[ind, ('Measured', '[Ca]sw')] / 1e3,
BT=d.loc[ind, ('Measured', 'B umol/kg')])
for c in out_cols:
d.loc[ind, ('MyAMI', c)] = cs[c]
d.loc[ind, ('MyAMI', 'KspC')] = cs['Ks']['KspC']
return d