def calculate_dissolved_volatiles(self, temperature, pressure, X_fluid=1, print_status=True, model='MagmaSat', record_errors=False, **kwargs):
"""
Calculates the amount of H2O and CO2 dissolved in a magma at the given P/T conditions and fluid composition. Fluid composition
will be matched to within 0.0001 mole fraction.
Parameters
----------
temperature: float, int, or str
Temperature, in degrees C. Can be passed as float, in which case the
passed value is used as the temperature for all samples. Alternatively, temperature information for each individual
sample may already be present in the BatchFile object. If so, pass the str value corresponding to the column
title in the BatchFile object.
presure: float, int, or str
Pressure, in bars. Can be passed as float or int, in which case the
passed value is used as the pressure for all samples. Alternatively, pressure information for each individual
sample may already be present in the BatchFile object. If so, pass the str value corresponding to the column
title in the BatchFile object.
X_fluid: float, int, or str
OPTIONAL: Default value is 1. The mole fraction of H2O in the H2O-CO2 fluid. X_fluid=1 is a pure H2O fluid. X_fluid=0 is a
pure CO2 fluid. Can be passed as a float or int, in which case the passed value is used as the X_fluid for all samples.
Alternatively, X_fluid information for each individual sample may already be present in the BatchFile object. If so, pass
the str value corresponding to the column title in the BatchFile object.
print_status: bool
OPTIONAL: The default value is True, in which case the progress of the calculation will be printed to the terminal.
If set to False, nothing will be printed. MagmaSat calculations tend to be slow, and so a value of True is recommended
for most use cases.
model: string
OPTIONAL: Default is 'MagmaSat'. Any other model name can be passed here.
record_errors: bool
OPTIONAL: If True, any errors arising during the calculation will be recorded as a column.
Returns
-------
pandas DataFrame
Original data passed plus newly calculated values are returned.
"""
dissolved_data = self.get_data().copy()
if isinstance(temperature, str):
file_has_temp = True
temp_name = temperature
elif isinstance(temperature, float) or isinstance(temperature, int):
file_has_temp = False
else:
raise core.InputError("temp must be type str or float or int")
if isinstance(pressure, str):
file_has_press = True
press_name = pressure
elif isinstance(pressure, float) or isinstance(pressure, int):
file_has_press = False
else:
raise core.InputError("pressure must be type str or float or int")
if isinstance(X_fluid, str):
file_has_X = True
X_name = X_fluid
elif isinstance(X_fluid, float) or isinstance(X_fluid, int):
file_has_X = False
if X_fluid != 0 and X_fluid !=1:
if X_fluid < 0.001 or X_fluid > 0.999:
raise core.InputError("X_fluid is calculated to a precision of 0.0001 mole fraction. \
Value for X_fluid must be between 0.0001 and 0.9999.")
else:
raise core.InputError("X_fluid must be type str or float or int")
# Check if the model passed as the attribute "model_type"
# Currently only implemented for MagmaSat type models
if hasattr(model, 'model_type') is True:
model = model.model_type
H2Ovals = []
CO2vals = []
warnings = []
errors = []
if model in models.get_model_names(model='mixed'):
for index, row in dissolved_data.iterrows():
try:
if file_has_temp == True:
temperature = row[temp_name]
if file_has_press == True:
pressure = row[press_name]
if file_has_X == True:
X_fluid = row[X_name]
# Get sample comp as Sample class with defaults
bulk_comp = self.get_sample_composition(index,
normalization=self.default_normalization,
units='wtpt_oxides',
asSampleClass=True)
bulk_comp.set_default_units(self.default_units)
bulk_comp.set_default_normalization(self.default_normalization)
calc = calculate_classes.calculate_dissolved_volatiles(sample=bulk_comp, pressure=pressure, temperature=temperature,
X_fluid=(X_fluid, 1-X_fluid), model=model,
silence_warnings=True, **kwargs)
H2Ovals.append(calc.result['H2O_liq'])
CO2vals.append(calc.result['CO2_liq'])
warnings.append(calc.calib_check)
errors.append('')
except Exception as inst:
H2Ovals.append(np.nan)
CO2vals.append(np.nan)
warnings.append('Calculation Failed.')
errors.append(sys.exc_info()[0])
dissolved_data["H2O_liq_VESIcal"] = H2Ovals
dissolved_data["CO2_liq_VESIcal"] = CO2vals
if file_has_temp == False:
dissolved_data["Temperature_C_VESIcal"] = temperature
if file_has_press == False:
dissolved_data["Pressure_bars_VESIcal"] = pressure
if file_has_X == False:
dissolved_data["X_fluid_input_VESIcal"] = X_fluid
dissolved_data["Model"] = model
dissolved_data["Warnings"] = warnings
if record_errors == True:
dissolved_data["Errors"] = errors
return dissolved_data
elif model == 'MagmaSat':
XH2Ovals = []
XCO2vals = []
FluidProportionvals = []
iterno = 0
for index, row in dissolved_data.iterrows():
iterno += 1
if print_status == True:
percent = iterno/len(dissolved_data.index)
batchfile.status_bar.status_bar(percent, index)
if file_has_temp == True:
temperature = row[temp_name]
if temperature <= 0:
H2Ovals.append(np.nan)
CO2vals.append(np.nan)
XH2Ovals.append(np.nan)
XCO2vals.append(np.nan)
FluidProportionvals.append(np.nan)
warnings.append("Sample skipped. Bad temperature.")
errors.append(sys.exc_info()[0])
w.warn("Temperature for sample " + str(index) + " is <=0. Skipping sample.", stacklevel=2)
if file_has_press == True:
pressure = row[press_name]
if temperature >0 and pressure <= 0:
H2Ovals.append(np.nan)
CO2vals.append(np.nan)
XH2Ovals.append(np.nan)
XCO2vals.append(np.nan)
FluidProportionvals.append(np.nan)
warnings.append("Sample skipped. Bad pressure.")
errors.append(sys.exc_info()[0])
w.warn("Pressure for sample " + str(index) + " is <=0. Skipping sample.", stacklevel=2)
if file_has_X == True:
X_fluid = row[X_name]
if temperature >0 and pressure >0 and X_fluid <0:
H2Ovals.append(np.nan)
CO2vals.append(np.nan)
XH2Ovals.append(np.nan)
XCO2vals.append(np.nan)
FluidProportionvals.append(np.nan)
warnings.append("Sample skipped. Bad X_fluid.")
errors.append(sys.exc_info()[0])
w.warn("X_fluid for sample " + str(index) + " is <0. Skipping sample.", stacklevel=2)
if temperature >0 and pressure >0 and X_fluid >1:
H2Ovals.append(np.nan)
CO2vals.append(np.nan)
XH2Ovals.append(np.nan)
XCO2vals.append(np.nan)
FluidProportionvals.append(np.nan)
warnings.append("Sample skipped. Bad X_fluid.")
errors.append(sys.exc_info()[0])
w.warn("X_fluid for sample " + str(index) + " is >1. Skipping sample.", stacklevel=2)
if temperature > 0 and pressure > 0 and X_fluid >=0 and X_fluid <=1:
try:
# Get sample comp as Sample class with defaults
bulk_comp = self.get_sample_composition(index,
normalization=self.default_normalization,
units='wtpt_oxides',
asSampleClass=True)
bulk_comp.set_default_units(self.default_units)
bulk_comp.set_default_normalization(self.default_normalization)
calc = calculate_classes.calculate_dissolved_volatiles(sample=bulk_comp, pressure=pressure, temperature=temperature,
X_fluid=X_fluid, model=model, silence_warnings=True,
verbose=True)
H2Ovals.append(calc.result['H2O_liq'])
CO2vals.append(calc.result['CO2_liq'])
XH2Ovals.append(calc.result['XH2O_fl'])
XCO2vals.append(calc.result['XCO2_fl'])
FluidProportionvals.append(calc.result['FluidProportion_wt'])
warnings.append(calc.calib_check)
errors.append('')
except Exception as inst:
H2Ovals.append(np.nan)
CO2vals.append(np.nan)
XH2Ovals.append(np.nan)
XCO2vals.append(np.nan)
FluidProportionvals.append(np.nan)
warnings.append('Calculation Failed.')
errors.append(sys.exc_info()[0])
dissolved_data["H2O_liq_VESIcal"] = H2Ovals
dissolved_data["CO2_liq_VESIcal"] = CO2vals
if file_has_temp == False:
dissolved_data["Temperature_C_VESIcal"] = temperature
if file_has_press == False:
dissolved_data["Pressure_bars_VESIcal"] = pressure
if file_has_X == False:
dissolved_data["X_fluid_input_VESIcal"] = X_fluid
dissolved_data["Model"] = model
dissolved_data["Warnings"] = warnings
if record_errors == True:
dissolved_data["Errors"] = errors
return dissolved_data
else:
XH2Ovals = []
XCO2vals = []
FluidProportionvals = []
for index, row in dissolved_data.iterrows():
if file_has_temp == True:
temperature = row[temp_name]
if file_has_press == True:
pressure = row[press_name]
if file_has_X == True:
X_fluid = row[X_name]
# Get sample comp as Sample class with defaults
bulk_comp = self.get_sample_composition(index,
normalization=self.default_normalization,
units='wtpt_oxides',
asSampleClass=True)
bulk_comp.set_default_units(self.default_units)
bulk_comp.set_default_normalization(self.default_normalization)
if 'Water' in model:
try:
calc = calculate_classes.calculate_dissolved_volatiles(sample=bulk_comp, pressure=pressure, temperature=temperature,
X_fluid=X_fluid, model=model, silence_warnings=True)
H2Ovals.append(calc.result)
warnings.append(calc.calib_check)
except:
H2Ovals.append(0)
warnings.append('Calculation Failed #001')
if 'Carbon' in model:
try:
calc = calculate_classes.calculate_dissolved_volatiles(sample=bulk_comp, pressure=pressure, temperature=temperature,
X_fluid=X_fluid, model=model, silence_warnings=True)
CO2vals.append(calc.result)
warnings.append(calc.calib_check)
except:
CO2vals.append(0)
warnings.append('Calculation Failed #002')
if 'Water' in model:
dissolved_data["H2O_liq_VESIcal"] = H2Ovals
if 'Carbon' in model:
dissolved_data["CO2_liq_VESIcal"] = CO2vals
if file_has_temp == False:
dissolved_data["Temperature_C_VESIcal"] = temperature
if file_has_press == False:
dissolved_data["Pressure_bars_VESIcal"] = pressure
if file_has_X == False:
dissolved_data["X_fluid_input_VESIcal"] = X_fluid
dissolved_data["Model"] = model
dissolved_data["Warnings"] = warnings
return dissolved_data
def return_default_units(self, sample, calc_result, **kwargs):
""" Checkes the default units set for the sample_class.Sample
object and returns the result of a calculation in those units.
Parameters
----------
sample: Sample class
The rock composition as a Sample object.
calc_result: dict or float
Result of a calculate_dissolved_volatiles() calculation on a
sample.
"""
default_units = sample.default_units
# get the composition of
bulk_comp = deepcopy(sample)
# check if calculation result is H2O-only, CO2-only, or mixed
# H2O-CO2
if isinstance(self.model_name, str):
if self.model_name in models.get_model_names(model='mixed'):
# set dissolved H2O and CO2 values.
# this action assumes they are input as wt% but updates the
# composition in its default units.
bulk_comp.change_composition({
'H2O': calc_result['H2O_liq'],
'CO2': calc_result['CO2_liq']
})
return {
'H2O_liq':
bulk_comp.get_composition(species='H2O',
units=default_units),
'CO2_liq':
bulk_comp.get_composition(species='CO2',
units=default_units)
}
elif 'Water' in self.model_name:
bulk_comp.change_composition({'H2O': calc_result})
return bulk_comp.get_composition(species='H2O',
units=default_units)
elif 'Carbon' in self.model_name:
bulk_comp.change_composition({'CO2': calc_result})
return bulk_comp.get_composition(species='CO2',
units=default_units)
elif self.model_name == 'MagmaSat':
bulk_comp.change_composition({
'H2O': calc_result['H2O_liq'],
'CO2': calc_result['CO2_liq']
})
# check if verbose method has been chosen
if 'verbose' in kwargs and kwargs['verbose']:
return {
'H2O_liq':
bulk_comp.get_composition(species='H2O',
units=default_units),
'CO2_liq':
bulk_comp.get_composition(species='CO2',
units=default_units),
'XH2O_fl':
calc_result['XH2O_fl'],
'XCO2_fl':
calc_result['XCO2_fl'],
'FluidProportion_wt':
calc_result['FluidProportion_wt']
}
else:
return {
'H2O_liq':
bulk_comp.get_composition(species='H2O',
units=default_units),
'CO2_liq':
bulk_comp.get_composition(species='CO2',
units=default_units)
}
else:
# if self.model_name is not a string, most likely this is a
# user-created model class, and so we cannot interrogate it for
# model type (H2O, CO2, or mixed).
# TODO: create model type parameter so that we can ID model type
# this way instead of via strings in a list!
return calc_result
def calculate_equilibrium_fluid_comp(self, temperature, pressure=None, print_status=False, model='MagmaSat', **kwargs):
"""
Returns H2O and CO2 concentrations in wt% or mole fraction in a fluid in equilibrium with the given sample(s) at the given P/T condition.
Parameters
----------
sample: BatchFile object
Compositional information on samples in oxides.
temperature: float, int, or str
Temperature, in degrees C. Can be passed as float, in which case the
passed value is used as the temperature for all samples. Alternatively, temperature information for each individual
sample may already be present in the BatchFile object. If so, pass the str value corresponding to the column
title in the BatchFile object.
presure: float, int, or str
Pressure, in bars. Can be passed as float or int, in which case the
passed value is used as the pressure for all samples. Alternatively, pressure information for each individual
sample may already be present in the BatchFile object. If so, pass the str value corresponding to the column
title in the BatchFile object.
model: string
OPTIONAL: Default is 'MagmaSat'. Any other model name can be passed here.
Returns
-------
pandas DataFrame
Original data passed plus newly calculated values are returned.
"""
fluid_data = self.get_data().copy()
# Check if the model passed as the attribute "model_type"
# Currently only implemented for MagmaSat type models
if hasattr(model, 'model_type') is True:
model = model.model_type
if isinstance(temperature, str):
file_has_temp = True
temp_name = temperature
elif isinstance(temperature, float) or isinstance(temperature, int):
file_has_temp = False
else:
raise core.InputError("temp must be type str or float or int")
if isinstance(pressure, str):
file_has_press = True
press_name = pressure
elif isinstance(pressure, float) or isinstance(pressure, int) or type(pressure) == type(None):
file_has_press = False
else:
raise core.InputError("pressure must be type str or float or int")
H2Ovals = []
CO2vals = []
warnings = []
if model in models.get_model_names(model='mixed') or model == "MooreWater":
for index, row in fluid_data.iterrows():
try:
if file_has_temp == True:
temperature = row[temp_name]
if file_has_press == True:
pressure = row[press_name]
# Get sample comp as Sample class with defaults
bulk_comp = self.get_sample_composition(index,
normalization=self.default_normalization,
units='wtpt_oxides',
asSampleClass=True)
bulk_comp.set_default_units(self.default_units)
bulk_comp.set_default_normalization(self.default_normalization)
calc = calculate_classes.calculate_equilibrium_fluid_comp(sample=bulk_comp, pressure=pressure, temperature=temperature,
model=model, silence_warnings=True, **kwargs)
H2Ovals.append(calc.result['H2O'])
CO2vals.append(calc.result['CO2'])
if calc.result['H2O'] == 0 and calc.result['CO2'] == 0:
warnings.append(calc.calib_check + "Sample not saturated at these conditions")
else:
warnings.append(calc.calib_check)
except:
H2Ovals.append(np.nan)
CO2vals.append(np.nan)
warnings.append("Calculation Failed.")
fluid_data["XH2O_fl_VESIcal"] = H2Ovals
fluid_data["XCO2_fl_VESIcal"] = CO2vals
if file_has_temp == False:
fluid_data["Temperature_C_VESIcal"] = temperature
if file_has_press == False:
fluid_data["Pressure_bars_VESIcal"] = pressure
fluid_data["Model"] = model
fluid_data["Warnings"] = warnings
return fluid_data
elif model == 'MagmaSat':
iterno = 0
for index, row in fluid_data.iterrows():
iterno += 1
if print_status == True:
percent = iterno/len(fluid_data.index)
batchfile.status_bar.status_bar(percent, index)
if file_has_temp == True:
temperature = row[temp_name]
if temperature <= 0:
H2Ovals.append(np.nan)
CO2vals.append(np.nan)
warnings.append("Calculation skipped. Bad temperature.")
w.warn("Temperature for sample " + str(index) + " is <=0. Skipping sample.", stacklevel=2)
if file_has_press == True:
pressure = row[press_name]
if temperature >0 and pressure <= 0:
H2Ovals.append(np.nan)
CO2vals.append(np.nan)
warnings.append("Calculation skipped. Bad pressure.")
w.warn("Pressure for sample " + str(index) + " is <=0. Skipping sample.", stacklevel=2)
if temperature > 0 and pressure > 0:
try:
# Get sample comp as Sample class with defaults
bulk_comp = self.get_sample_composition(index,
normalization=self.default_normalization,
units='wtpt_oxides',
asSampleClass=True)
bulk_comp.set_default_units(self.default_units)
bulk_comp.set_default_normalization(self.default_normalization)
calc = calculate_classes.calculate_equilibrium_fluid_comp(sample=bulk_comp, pressure=pressure, temperature=temperature, model=model, silence_warnings=True)
H2Ovals.append(calc.result['H2O'])
CO2vals.append(calc.result['CO2'])
if calc.result['H2O'] == 0 and calc.result['CO2'] == 0:
warnings.append(calc.calib_check + "Sample not saturated at these conditions")
else:
warnings.append(calc.calib_check)
except:
H2Ovals.append(np.nan)
CO2vals.append(np.nan)
warnings.append("Calculation Failed.")
fluid_data["XH2O_fl_VESIcal"] = H2Ovals
fluid_data["XCO2_fl_VESIcal"] = CO2vals
if file_has_temp == False:
fluid_data["Temperature_C_VESIcal"] = temperature
if file_has_press == False:
fluid_data["Pressure_bars_VESIcal"] = pressure
fluid_data["Model"] = model
fluid_data["Warnings"] = warnings
return fluid_data
else:
saturated = []
for index, row in fluid_data.iterrows():
try:
if file_has_temp == True:
temperature = row[temp_name]
if file_has_press == True:
pressure = row[press_name]
# Get sample comp as Sample class with defaults
bulk_comp = self.get_sample_composition(index,
normalization=self.default_normalization,
units='wtpt_oxides',
asSampleClass=True)
bulk_comp.set_default_units(self.default_units)
bulk_comp.set_default_normalization(self.default_normalization)
calc = calculate_classes.calculate_equilibrium_fluid_comp(sample=bulk_comp, pressure=pressure, temperature=temperature, model=model, silence_warnings=True)
saturated.append(calc.result)
warnings.append(calc.calib_check)
except:
saturated.append(np.nan)
warnings.append("Calculation Failed.")
fluid_data["Saturated_VESIcal"] = saturated
if file_has_temp == False:
fluid_data["Temperature_C_VESIcal"] = temperature
if file_has_press == False:
fluid_data["Pressure_bars_VESIcal"] = pressure
fluid_data["Model"] = model
fluid_data["Warnings"] = warnings
return fluid_data
def get_model_names(model='all'):
return models.get_model_names(model=model)