I/O File Details and Format

This section describes various input and output files used by the MC_fit program. Perple_X programs use a root name to identify problem-specific I/O files, the default root name, my_project, is used here. MC_fit requires two problem-specific input files, my_project.dat and my_project.imc:

  • my_project.dat defines the thermodynamic system of interest and is created by the user with the Perple_X program build.

  • my_project.imc defines the inversion problem and is created manually by the user.

Root and/or complete file names may include directory paths, e.g., the root ./my_directory/my_project causes output to be written to the subdirectory my_directory of the current working directory. To change the root name, rename my_project.dat and my_project.imc with the desired name.

Input: my_project.dat

Users of MC_fit should be familiar with the Perple_X program build that generates my_project.dat. If not, consult the tutorials listed on the Perple_X website.

To create my_project.dat, run build as though to setup the calculation of a phase diagram section for the observed assemblage:

  • Specify the components that describe the chemistry of the observed assemblage. These are usually specified as thermodynamic components; however saturated and mobile components may also be specified.

  • Specify the thermodynamic data, solution model, and Perple_X option files to be used by MC_fit.

  • Specify any solution models appropriate for the observed assemblage, as well as solution models for phases that might affect the stability of the observed assemblage.

  • The independent variables selected for the phase diagram section, ordinarily pressure and temperature, define the unknown environmental parameters to be determined by MC_fit. If mobile components have been specified, the chemical potential, activity, or fugacity of the component is included among the unknown environmental parameters to be determined by MC_fit.

  • The bulk composition and variable ranges specified in my_project.dat are ignored by MC_fit, i.e., arbitrary values for these parameters can be entered in response to the prompts from build. MC_fit also ignores the molar vs mass input unit specification my_project.dat.

Note

The thermodynamic data, Perple_X option, and solution model files referenced in my_project.dat are not described here. Refer to the online documentation for details of the thermodynamic data and Perple_X option files. The solution model file, normally solution_model.dat, is to some extent self-documenting.

Note

Specifying component saturation constraints in my_project.dat simplifies the inversion problem by assuring that the corresponding composant is in equilibrium with the predicted assemblage. However, the identity of the composant is not considered as a constraint by MC_fit; therefore, component saturation constraints should not be used when the identity of the composant is critical.

For example, SiO2 should not be saturated if different silica polymorphs are potentially stable over the pressure- temperature range of interest and it is known that a particular polymorph was stable. Conversely, component saturation constraints should be used when it is suspected that a polymorph of a component was stable, but its identity is uncertain (e.g., aragonite vs calcite).

Input: my_project.imc

The my_project.imc file consists of keywords with interspersed data as outlined below, line numbers have been added to facilitate discussion. Although the keywords and data must be entered sequentially, there is no requirement that the data must be on a particular line.

 1  OPTION_FILE_NAME
 2
 3  begin_assemblage
 4
 5  sample_name       TEXT
 6
 7  pressure_range    LO#   HI#
 8  temperature_range LO#   HI#
 9
10  MAF(TEXT)_range   LO#   HI#
11  ...
12
13  unmeasured_component  TEXT
14
15  begin_limits
16  TEXT        LO#   HI#
17  ...
18  end_limits
19
20  ...
21
22  begin_bulk
23  TEXT        VAL#  UNC#
24  ...
25  end_bulk
26
27  phase_name  TEXT
28
29  inversion_weight  VAL#
30
31  phase_mode  VAL#  UNC#
32
33  begin_comp
34  TEXT        VAL#  UNC#
35  ...
36  end_comp
37
38  end_assemblage

—

Line 1 – MC_fit_option.dat

The complete name of the MC_fit option file, e.g., MC_fit_option.dat. This file is distinct from the Perple_X option file specified in my_project.dat.

—

Line 3 – begin_assemblage

Signals the beginning of the inversion problem.

—

Line 5 – sample_name

TEXT is a sample identifier, title, etc.

—

Lines 7-8 – pressure/temperature_range

The LO# HI# pairs on each line are the lower and upper limits on pressure (bar) and temperature (K) for the inversion problem. Currently there is no means of fixing pressure or temperature for an inversion problem. Such an option will be implemented upon request.

—

Line 10 – MAF(TEXT)_range

This optional keyword, and its associated data, must be repeated for each mobile component specified in my_project.dat. If my_project.dat does not specify mobile components then this keyword must be omitted.

TEXT is the name of a mobile component (e.g., O2) and the LO# HI# pair is the lower and upper limit on the chemical potential (J/mol), activity (non-dimensional), or fugacity (bar) of the component depending on which property has been chosen to represent the component in my_project.dat. The chemical potential/activity/fugacity of a mobile component is an independent inversion parameter, the amount of the mobile component in the observed phases is determined as a dependent parameter.

—

Lines 13-18 – unmeasured_component/end_limits

This optional block specifies an unmeasured component, the abundance of which is to be determined by the inversion. The block is repeated as necessary to specify multiple unmeasured components.

On line 13, TEXT following unmeasured_component keyword is the name of an unmeasured thermodynamic component (e.g., O2, C, CO2, H2O, S). The unmeasured_component keyword is followed by a block (lines 15-18) bounded by the begin_limits and end_limits keywords that specifies the range of the unmeasured component. The range of unmeasured components may be specified as either simple or coupled limits.

  • Coupled limits are appropriate when the abundance of an unmeasured component, is strongly dependent on the abundances of other components. Excess O2 (Appendix D) is a prominent example of such a component, because in geologically relevant systems its abundance is stoichiometrically coupled to the redox state of other components.

  • Simple limits are appropriate when the abundance of an unmeasured component, e.g., H2O, is weakly coupled to the abundances of other components and/or is constrained by an indirect observation such as loss-on-ignition (LOI) reported from bulk rock analysis or knowledge of the probable content of the unmeasured component in the observed phases.

—

Simple limits

On line 16, TEXT is simple_mole or simple_mass; and LO# and HI# specify the absolute lower- and upper-limits on the molar or mass amount of the unmeasured component. The choice of simple_mole or simple_mass determines whether the limits are in molar or mass units and is independent of the units used to input the measured compositions specified by the molar_composition_input option, i.e., if simple_mass is specified, molar compositions are converted internally to mass fractions to evaluate the limits. Because the mass of an unmeasured component is not known a priori, the amounts of the unmeasured component must be expressed relative to the normalized mole or mass fractions of the measured components, see the example below.

Example, simple limits for unmeasured H2O

To specify that the mass or mole fraction (the math is the same regardless of units) of H2O must lie in the range [0.01, 0.05], LO# and HI# are computed as:

(6)\[\begin{split}\begin{align} X_{\text{H2O,min}} &= 0.01 = \frac{\text{LO#}}{1 + \text{LO#}} &\Rightarrow \text{LO#} = \frac{X_{\text{H2O,min}}}{1 - X_{\text{H2O,min}}} = 0.01010\\ X_{\text{H2O,max}} &= 0.05 = \frac{\text{HI#}}{1 + \text{HI#}} &\Rightarrow \text{HI#} = \frac{X_{\text{H2O,max}}}{1 - X_{\text{H2O,max}}} = 0.05263 \end{align}\end{split}\]

And the entry in my_project.imc would be:

unmeasured_component H2O

begin_limits
Simple_mass  0.01010  0.05263
end_limits

This example assumes that H2O is the only unmeasured component. When multiple unmeasured components are specified, the limits for unmeasured component i are:

(7)\[\begin{split}\begin{align} \text{LO#}_i = \frac{X_{i\text{,min}}}{1 - \sum{X_{j\text{,min}}}} \\ \text{HI#}_i = \frac{X_{i\text{,max}}}{1 - \sum{X_{j\text{,max}}}} \end{align}\end{split}\]

where the sums are over all unmeasured components.

Given that limits on unmeasured components are intrinsically approximate and that unmeasured components are typically low mass volatiles, it is expedient to simply expand the limits by a factor of, say, ± 20% to avoid using Eq 6 or 7.

Note

If no bulk compositional constraints are specified, the LO# and HI# simple limits should be set to accommodate the lowest and highest amounts of the unmeasured component possible in any phase of the observed assemblage.

For example, if the unmeasured component is H2O and the observed assemblage is garnet + amphibole + serpentine, LO# should be set to 0 (based on garnet), and HI# should be set to approximately 0.15 (0.13/(1-0.13), Eq 6) for a simple_mass constraint and approximately 0.4 (0.29/(1-0.29), Eq 6) for a simple_mole constraint (based on antigorite).

—

Coupled limits

On line 16, TEXT is the name of a component to which the unmeasured component is coupled; and LO# and HI# are the molar stoichiometric coefficients in the linear equations for the lower- and upper-limits on the unmeasured component. If the unmeasured component is coupled to more than one component, line 16 is repeated as necessary. Refer to the examples listed below for further information.

Example, coupled limits for unmeasured O2

For a system described in terms of the components FeO (total iron as FeO) and O2 (Appendix D):

unmeasured_component O2

begin_limits
FeO  0  0.25
end_limits

specifies that the range on the molar content of the unmeasured component O2 is:

\[\begin{split}\begin{align} n_{\text{O2,min}} &= 0 \\ n_{\text{O2,max}} &= 0.25 n_{\text{FeO}} \end{align}\end{split}\]

If iron is the only element in the system with variable redox state, these correspond to all iron being ferrous and ferric, respectively. If the limits on FeO were, instead, -0.5 and 0.25, the lower limit on \(n_{\text{O2}}\) would correspond to all iron being metallic.

In systems with more than one variable redox state component, there is no direct relationship between the bulk composition and redox state of the individual elements. In such cases, the contribution of each element to the bulk redox state must be evaluated from the phase compositions output by MC_fit or meemum (Appendix D). For example, the lines:

unmeasured_component O2

begin_limits
FeO  -0.5  0.25
H2O  -0.5  0.0
C    -2.0  1.0
end_limits

imply that iron, hydrogen, and carbon have variable redox state and define the limits on O2 as

\[\begin{split}\begin{align} n_{\text{O2,min}} &= -0.5 n_{\text{FeO}} - 0.5 n_{\text{H2O}} - 2.0 n_{\text{C}}\\ n_{\text{O2,max}} &= 0.25 n_{\text{FeO}} + 1.0 n_{\text{C}} \end{align}\end{split}\]

Examples, coupled limits for unmeasured volatile components

Unmeasured volatile components, e.g., CO2 and H2O, are less strongly coupled to non-volatile components than is O2; for that reason they are usually better treated with simple limits. When simple limits are inconvenient, coupled limits can be used to reduce the cost resulting from the exploration of unreasonably high or low volatile contents. But the limits must be set based on petrological observation or reasoning. For example in metacarbonate rocks the CO2 content is unlikely to exceed the bulk iron + alkali earth content. In which case, a reasonable specification might be:

unmeasured_component CO2

begin_limits
FeO  0  1.0
CaO  0  1.0
MgO  0  1.0
end_limits

Whereas for H2O in, say, a metapelite the H2O content is unlikely to exceed the bulk alkali + alkaline earth + Al content. In which case, a generous specification might be:

unmeasured_component H2O

begin_limits
Na2O  0  1.0
K2O   0  1.0
CaO   0  1.0
MgO   0  1.0
Al2O3 0  1.0
end_limits

The limits on unmeasured volatile are to some extent a matter of trial and error. To minimize the cost of experimentation, it is advisable to start with generous limits and then narrow them as experience is gained.

—

Lines 22-25 – begin/end_bulk

This optional block specifies the bulk composition in cases where it is reasonable to assume that the bulk composition of the putative equilibrium assemblage is known. This assumption results in a major simplification of the inversion process. Thus, when justified, use of this option is recommended as the first line of attack on the inversion problem. However, particularly for minor elements and/or phases, insignificant variations in the bulk composition can have a significant effect on the predicted mineralogy due to the simplified nature of thermodynamic solution models. For this reason, inversions that make use of the bulk composition option that yield few or no acceptable solutions should be repeated without this option.

The begin_bulk and end_bulk keywords delimit the block. Between these keywords, each line specifies the name (TEXT) of a thermodynamic component, followed by its molar or mass amount (VAL#) and the relative or absolute uncertainty (UNC#). The component names must match those specified in my_project.dat. The bulk composition need not be normalized and need not include the unmeasured thermodynamic components. When uncertainties are not available, MC_fit can be instructed to estimate relative uncertainties using:

(8)\[\epsilon_{j} = \frac{0.25}{X_{j}^{0.7}}\]

where \(X_j\) is the molar fraction of component \(j\), the power-law exponent approximates the dependence suggested by Nerone et al. ([Nerone2025]) for electron microprobe measurement error, and the coefficient (0.25) is chosen to yield relative uncertainties of 2% when \(X_j = 0.5\) and 20% when \(X_j = 0.05\). The use of Eq 8 is signaled to MC_fit by a -1 in place of UNC# for the relevant component. When Eq 8 is used, MC_fit automatically converts the component amounts specified by VAL# to the correct units and normalization.

—

Lines 27-36 – phase_name/end_comp

This block specifies the observed phases of the putative relict equilibrium. The entries differ depending on whether the phase is modeled as a pure phase (e.g., quartz) or a solution phase (e.g., garnet).

—

Solution phases

Line 27, phase_name: TEXT is the name of a solution model specified in my_project.dat that corresponds to an observed phase.

[Optional] Line 29, inversion_weight: VAL# specifies a weighting factor that modifies the contribution of the phase to the overall misfit. The default weighting is unity. A weighting factor greater than unity increases the influence of the phase in the inversion. Conversely, a weighting factor less than unity decreases its influence.

[Optional] Line 31, phase_mode: VAL# is the volume fraction of the phase, and UNC# is the uncertainty in that volume fraction. If modal fractions are provided, they must be provided for all phases. Modal fractions are automatically renormalized by MC_fit.

Note

Modal data and bulk composition are redundant information. Thus, nothing is gained by providing both. In cases where the bulk composition is unknown or inconsistent, modal data can be used to infer the bulk composition of the observed assemblage. Bulk compositions output by MC_fit without modal data are, in general, non-unique.

Lines 33-36: This block, bounded by the begin_comp and end_comp keywords, specifies the composition of the observed phase. Each line within the block specifies the name (NAME) of a thermodynamic, mobile, or saturated component, followed by its molar or mass amount (VAL#) and its relative or absolute uncertainty (UNC#). As in the case of bulk compositions (Lines 22-25 above), when uncertainties are not available, MC_fit can be instructed to estimate the relative uncertainty of a component with Eq 8 by setting UNC# to -1. Neither unmeasured components nor components that are not present in the observed phase need be specified. The component names must match those specified in my_project.dat. The component amounts need not be normalized.

Note

Whether components that are observed in a phase but which cannot be predicted by the corresponding solution model should be included is a matter of judgment. Because such components cannot be predicted by the solution model, their inclusion has the consequence that they must be accommodated by other phases in the predicted assemblage. In general this leads to higher misfit and, in particular, may increase the misfit of the solution model that ultimately accommodates the component. These effects are proportional to the amount of the component. Arguably, when the uncertainty on the abundance of a component includes zero, it should be omitted. When the amount of a component that cannot be predicted by the corresponding solution model is significant, an alternative to simple omission or inclusion is to replace the component by a geochemical proxy that is predicted by the solution model. For example, BaO is a common component of feldspar, but cannot be predicted by current feldspar solution models. As CaO is a reasonable, and thermodynamically well-predicted, proxy for BaO in feldspar, the observed molar amount of CaO in an observed feldspar composition can be augmented by the molar amount of BaO, which is then omitted from the “observed” composition.

—

Pure phases

Line 27, phase_name: TEXT is the name of a stoichiometric compound listed in the thermodynamic data file specified by my_project.dat that approximates the observed phase.

[Optional] Line 29, inversion_weight: is specified as above for solution phases.

[Optional] Line 31, phase_mode: is specified as above for solution phases.

Lines 33-36: This block is omitted for pure phases.

—

Line 36 – end_assemblage

end_assemblage signals the end of the inversion problem specification. Comments may be written after this keyword without using the comment character (|).

Output: my_project.out

The file my_project.out records the progress information and details of the Nelder-Mead optimizations during both the central model analysis and perturbation analysis.

—

Central Model Output

By default, during the central model analysis all successful tries, i.e., Nelder-Mead optimizations that converge to a local minimum, are output. The number of successful tries output can be regulated by the model_output, no_missing_phases, must_fit_all_data and misfit_filter_value options. Additionally, the Nelder-Mead_covariance option can be set to output the correlation-covariance matrix. The output of each successful try is of the form:

 1   --------------------------------------------------------------------------------
 2   Central model Try 44 converged, 42 successes so far.
 3
 4   Misfit function evaluations this try => 259
 5
 6   Misfit this try =  1.011330E-04
 7   Best Misfit so far = 1.011330E-04 obtained on Try 44
 8
 9   Prior probability, PP =  2.253960E-07
10   Bayes score, PP * exp(-Misfit) = 2.253732E-07
11   Best Bayes score so far = 4.084621E-07 obtained on Try 5
12
13                           P_bar         T_K           C_O2          Cpx           Gt
14   Initial coordinates:   3086.20       739.602      0.191001      0.825769      0.174231
15   Final coordinates:     10108.3       1002.02      0.141531      0.260092      0.739908
16
17   This model fits all data within observational uncertainty
18
19   Components of the Misfit Score
20
21        Predicted compositions:       1.011326E-04
22        Extraneous predicted phases:  4.134694E-10
23        Missed observed phases:   0.00000
24
25   The following observed phases are predicted:
26
27                    vol %     Na2O    MgO     Al2O3   CaO     FeO     O2      SiO2
28   Augite(G)
29     predicted*    26.177    0.0134  0.1392  0.0072  0.2164  0.1167  0.0063  0.5008
30     observed*               0.0135  0.1401  0.0073  0.2178  0.1174  0.0000  0.5039
31     residual                0.0001  0.0009  0.0001  0.0014  0.0007 -0.0063  0.0031
32     Composition Misfit:   0.396339E-04
33   Gt(W)
34     predicted*    73.823    0.0000  0.0518  0.1239  0.1561  0.2419  0.0078  0.4185
35     observed*               0.0000  0.0522  0.1249  0.1573  0.2438  0.0000  0.4218
36     residual                0.0000  0.0004  0.0010  0.0012  0.0019 -0.0078  0.0033
37     Composition Misfit:   0.614987E-04
38
39   The following predicted phases are not observed:
40
41                    vol %     Na2O    MgO     Al2O3   CaO     FeO     O2      SiO2
42   q                0.000    0.0000  0.0000  0.0000  0.0000  0.0000  0.0000  1.0000
43
44                Effective Bulk*        Chemical Potentials (J/mol)
45   Na2O              3.507                     -777832.
46   MgO              75.016                     -641782.
47   Al2O3            94.301                    -0.165555E+07
48   CaO             173.054                     -745846.
49   FeO             210.941                     -320589.
50   O2                7.464                     -442446.
51   SiO2            443.182                     -891292.
52
53   *normalized molar units
54   --------------------------------------------------------------------------------

—

Lines 6-7: indicate the misfit of the current result and the current best result. The best central model can be identified by scrolling backward from the end of the my_project.out file to the last central model output to find the number of the try that produced the best result.

—

Lines 9-11: list the prior probability (Eq 17), the current Bayes score for the current result, and the best Bayes score so far.

—

Line 13: the inversion parameters. Parameters indicated by C_X are the fractional value of unmeasured component X, relative to its lower and upper limits as specified in the my_project.imc file. Because these limits are dependent on the effective bulk composition, which itself may be variable, the actual composition of an unmeasured component is best read from the phase or effective bulk compositions listed later in the output. For inversions in which the bulk compositional information is not input, parameters indicated by a phase name, indicate the fractional amount of the observed composition of the phase used to make up the bulk composition.

—

Line 14: the starting (the initial guess) coordinate of the Nelder-Mead optimization.

—

Line 15: the final (converged) coordinate of the Nelder-Mead optimization.

—

Line 17: indicates whether the predicted assemblage fits all data within its analytical uncertainty (uncertainty_multiplier). Whether models fit all data within uncertainty is not directly related to the misfit. Indeed, a model with low misfit may not fit all data within uncertainty, and vice versa. Consequently, it is a matter of judgment whether fitting all data within its uncertainty should be used as a criterion for accepting or rejecting models. This criterion is implemented at the user’s discretion in MC_fit_plot.

—

Lines 19-23: the components of the misfit (Eq 10).

—

Lines 28-38: the predicted and observed compositions, the predicted mode, and misfit, of each successfully predicted observed phase. If observed modal data is available, it is also listed. The predicted modes are only unique if modal and/or bulk compositional observational data has been provided. The phase compositions are normalized to 1 mole.

—

Lines 40-43: the predicted compositions and modes of any predicted phases that are not observed. If no_missing_phases is set to F, the observed composition and, if available, mode of each observed phase that is not predicted is also listed.

—

Lines 45-52: the effective bulk composition and the chemical potential (J/mol) of each component. The chemical potentials are characteristic of the observed assemblage regardless of whether the bulk composition is unique; however, the effective bulk composition is only unique if modal and/or bulk compositional observational data have been provided. The effective bulk composition is normalized to 1000 mole. The composition can be pasted into my_project.dat and used as input for the Perple_X programs meemum or vertex to verify that the predicted assemblage is stable at the inversion coordinates and to obtain additional information about the assemblage. The chemical potential of O2 (\(\mu_{\text{O2}}\)) is easily converted to oxygen fugacity (Appendix C).

—

Perturbation Analysis

The output for each successful try during the perturbation analysis is of the form:

1   --------------------------------------------------------------------------------
2   After 101 successful perturbations:
3                                         P_bar         T_K           C_O2          Cpx           Gt              OBJF
4   Central model parameters:            10108.3       1002.02      0.141531      0.260092      0.739908      1.011330E-04
5   Perturbed central model parameter:   9430.11       1001.87      0.134613      0.221303      0.778697      1.591129E-04
6   Mean perturbed parameters:           10370.6       1007.81      0.139926      0.242894      0.757106      1.636601E-04
7   Parameter standard deviation:        440.918       8.32835      4.849425E-03  3.580837E-02  3.580837E-02  8.408905E-05
8  --------------------------------------------------------------------------------

—

Line 2: the total number of perturbations is 1 + number_of_perturbations, because the best central model result is included in the perturbation analysis statistics. Results are reported only after two successful perturbations.

—

Line 3: the inversion parameters. The parameters have the same significance, and are listed in the same order, as in the central model output (line 13, above). By default, OBJF is the misfit. If Bayes is set to T, OBJF is the Bayes score.

—

Line 4: by default, repeats the best central model parameters. If perturbation analysis has been run with perturbation_hot_start, this line repeats the user specified central model parameters. These coordinates are the starting point for Nelder-Mead optimization with the perturbed analytical and thermodynamic parameters.

—

Line 5: the final coordinates of the Nelder-Mead optimization for the perturbed dataset.

—

Line 6: the mean of the final coordinates of all successful perturbation up to the current iteration.

—

Line 7: the standard deviation of the inversion parameters for all successful perturbations up to the current iteration.

Output: Console

The information written to the my_project.out is echoed to the user console with some additional progress information controlled by the vital_sign and print_level options.

Output: my_project_central.pts

The my_project_central.pts file contains the results of the central model analysis tries formatted for automated processing. Data in the file is of the form:

1   sym fit   P_bar         T_K           C_O2          Cpx           Gt                OBJF        Marker        Misfit         Bayes         Na2O          MgO           Al2O3         CaO           FeO           O2            SiO2
2     3  1    10014.4       999.954      0.164934      0.596088      0.403912      1.030612E-04   999.000      1.030612E-04  2.337938E-07  8.036604E-03  0.104553      5.480211E-02  0.193370      0.168471      6.946660E-03  0.470766
3     3  1    5666.01       912.995      0.214321      0.994931      5.068593E-03  2.037970E-03   999.000      2.037970E-03  3.602763E-07  1.341390E-02  0.139616      7.914999E-03  0.217487      0.118058      6.325581E-03  0.503510
4   ...
5     1  1    10108.3       1002.02      0.141531      0.260092      0.739908      1.011326E-04   999.000       0.00000       0.00000      1.348223E-02  0.140062      7.319146E-03  0.217793      0.117418      1.012418E-02  0.503926
6     9  0    1000.00       700.000       0.00000       0.00000       0.00000      1.011326E-04   999.000       0.00000       0.00000       0.00000       0.00000       0.00000       0.00000       0.00000       0.00000       0.00000
7    10  0    15000.0       1100.00       1.00000       1.00000       1.00000      1.011326E-04   999.000       0.00000       0.00000       0.00000       0.00000       0.00000       0.00000       0.00000       0.00000       0.00000

The header identifies each column of data. The first column is sym, an integer code with the following significance:

  • 1: best central model inversion coordinate.

  • 3: central model inversion coordinate for an inversion where Bayes has been set to default or F, in which case OBJF is the misfit of the model.

  • 6: central model inversion coordinate for an inversion where Bayes has been set to T, in which case OBJF is the Bayes score of the model.

  • 9: lower bounds for the inversion parameter ranges.

  • 10: upper bounds for the inversion parameter ranges.

sym is followed by:

  • fit, an integer code that is 1 if the model fits all data within observational uncertainty (uncertainty_multiplier), and 0 otherwise.

  • the names of the inversion parameters, as on line 13 of my_project.out.

  • OBJF, the misfit or Bayes score.

  • Marker, a numeric marker, 999.000, used to indicate the n+3’th column, where n is the number of inversion parameters.

  • Misfit, the misfit of the model.

  • Bayes, the Bayes score for the model.

  • the components that define the effective bulk composition of the model (molar units).

Note

  • The best central model inversion coordinate (sym = 1) replicates a coordinate (sym = 3 or 6) output earlier in the file.

  • When using programs other than MC_fit_plot for statistical analysis, care should be taken to ignore the best central model coordinate (sym = 1) and the lower and upper bound coordinates (sym = 9 and 10).

  • Symbol codes 3 and 6 are mutually exclusive.

Output: my_project_perturbed.pts

The my_project_perturbed.pts file contains the results of the perturbation analysis formatted for automated processing.

The format of the my_project_perturbed.pts file is identical to that of my_project_central.pts described above except that the mutually exclusive sym codes for the perturbed central models are 2 (misfit) and 5 (Bayes score).