Julia interface to the MAGEMin C package, which performs thermodynamic equilibrium calculations. See the MAGEMin page for more details on the package & how to use it.
First install julia. We recommend downloading the official binary from the julia webpage.
Next, install the MAGEMin_C
package with:
julia> ]
pkg> add MAGEMin_C
You can check if it works on your system by running the build-in test suite:
pkg> test MAGEMin_C
By pushing backspace
you return from the package manager to the main julia terminal. This will download a compiled version of the library as well as some wrapper functions to your system.
Next, you can do calculations with:
This is an example of how to use it for a predefined bulk rock composition:
julia> using MAGEMin_C
julia> db = "ig" # database: ig, igneous (Holland et al., 2018); mp, metapelite (White et al 2014b)
julia> data = Initialize_MAGEMin(db, verbose=true);
julia> test = 0 #KLB1
julia> data = use_predefined_bulk_rock(data, test);
julia> P = 8.0;
julia> T = 800.0;
julia> out = point_wise_minimization(P,T, data);
which gives
Status : 0
Mass residual : +5.34576e-06
Rank : 0
Point : 1
Temperature : +800.00000 [C]
Pressure : +8.00000 [kbar]
SOL = [G: -797.749] (25 iterations, 39.62 ms)
GAM = [-979.481432,-1774.104523,-795.261024,-673.747244,-375.070247,-917.557241,-829.990582,-1023.656703,-257.019268,-1308.294427]
Phase : spn cpx opx ol
Mode : 0.02799 0.14166 0.24228 0.58807
And here a case in which you specify your own bulk rock composition.
julia> using MAGEMin_C
julia> data = Initialize_MAGEMin("ig", verbose=false);
julia> P,T = 10.0, 1100.0
julia> Xoxides = ["SiO2"; "Al2O3"; "CaO"; "MgO"; "FeO"; "Fe2O3"; "K2O"; "Na2O"; "TiO2"; "Cr2O3"; "H2O"];
julia> X = [48.43; 15.19; 11.57; 10.13; 6.65; 1.64; 0.59; 1.87; 0.68; 0.0; 3.0];
julia> sys_in = "wt"
julia> out = single_point_minimization(P, T, data, X=X, Xoxides=Xoxides, sys_in=sys_in)
which gives:
Pressure : 10.0 [kbar]
Temperature : 1100.0 [Celsius]
Stable phase | Fraction (mol fraction)
liq 0.75133
cpx 0.20987
opx 0.03877
Stable phase | Fraction (wt fraction)
liq 0.73001
cpx 0.22895
opx 0.04096
Gibbs free energy : -916.874646 (45 iterations; 86.53 ms)
Oxygen fugacity : 2.0509883251350577e-8
After the calculation is finished, the structure out
holds all the information about the stable assemblage, including seismic velocities, melt content, melt chemistry, densities etc.
You can show a full overview of that with
julia> print_info(out)
If you are interested in the density or seismic velocity at the point, access it with
julia> out.rho
2755.2995530913095
julia> out.Vp
3.945646731595539
Once you are done with all calculations, release the memory with
julia> Finalize_MAGEMin(data)
To suppress solution phases from the calculation, define a remove list rm_list
using the remove_phases()
function. In the latter, provide a vector of the solution phase(s) you want to remove and the database acronym as a second argument. Then pass the created rm_list
to the single_point_minimization()
function.
julia> using MAGEMin_C
julia> data = Initialize_MAGEMin("mp", verbose=-1, solver=0);
julia> rm_list = remove_phases(["liq","sp"],"mp");
julia> P,T = 10.713125, 1177.34375;
julia> Xoxides = ["SiO2","Al2O3","CaO","MgO","FeO","K2O","Na2O","TiO2","O","MnO","H2O"];
julia> X = [70.999,12.805,0.771,3.978,6.342,2.7895,1.481,0.758,0.72933,0.075,30.0];
julia> sys_in = "mol";
julia> out = single_point_minimization(P, T, data, X=X, Xoxides=Xoxides, sys_in=sys_in,rm_list=rm_list)
which gives:
Pressure : 10.713125 [kbar]
Temperature : 1177.3438 [Celsius]
Stable phase | Fraction (mol fraction)
fsp 0.29236
g 0.13786
ilmm 0.01526
q 0.22534
sill 0.10705
H2O 0.22213
Stable phase | Fraction (wt fraction)
fsp 0.34544
g 0.17761
ilmm 0.0261
q 0.25385
sill 0.12197
H2O 0.07503
Stable phase | Fraction (vol fraction)
fsp 0.31975
g 0.10873
ilmm 0.01307
q 0.23367
sill 0.08991
H2O 0.23487
Gibbs free energy : -920.021202 (25 iterations; 27.45 ms)
Oxygen fugacity : -5.4221261006295105
Delta QFM : 2.506745293747623
Note that if you want to suppress a single phase, you still need to define a vector to be passed to the remove_phases()
function, such as:
julia> using MAGEMin_C
julia> data = Initialize_MAGEMin("mp", verbose=-1, solver=0);
julia> rm_list = remove_phases(["liq"],"mp");
julia> P,T = 10.713125, 1177.34375;
julia> Xoxides = ["SiO2","Al2O3","CaO","MgO","FeO","K2O","Na2O","TiO2","O","MnO","H2O"];
julia> X = [70.999,12.805,0.771,3.978,6.342,2.7895,1.481,0.758,0.72933,0.075,30.0];
julia> sys_in = "mol";
julia> out = single_point_minimization(P, T, data, X=X, Xoxides=Xoxides, sys_in=sys_in,rm_list=rm_list)
which gives:
Pressure : 10.713125 [kbar]
Temperature : 1177.3438 [Celsius]
Stable phase | Fraction (mol fraction)
fsp 0.29337
g 0.12
sp 0.03036
q 0.23953
sill 0.08939
ru 0.00521
H2O 0.22213
Stable phase | Fraction (wt fraction)
fsp 0.34667
g 0.15368
sp 0.04514
q 0.26983
sill 0.10184
ru 0.00781
H2O 0.07503
Stable phase | Fraction (vol fraction)
fsp 0.31981
g 0.09422
sp 0.02492
q 0.24761
sill 0.07484
ru 0.00446
H2O 0.23413
Gibbs free energy : -920.00146 (19 iterations; 27.79 ms)
Oxygen fugacity : -5.760704474307317
Delta QFM : 2.1681669200698166
julia> using MAGEMin_C
julia> db = "ig" # database: ig, igneous (Holland et al., 2018); mp, metapelite (White et al 2014b)
julia> data = Initialize_MAGEMin(db, verbose=false);
julia> test = 0 #KLB1
julia> n = 1000
julia> P = rand(8.0:40,n);
julia> T = rand(800.0:2000.0, n);
julia> out = multi_point_minimization(P,T, data, test=test);
julia> Finalize_MAGEMin(data)
By default, this will show a progressbar (which you can deactivate with the progressbar=false
option).
You can also specify a custom bulk rock for all points (see above), or a custom bulk rock for every point.
in the previous examples the results of the minimization are saved in a structure called out
. To access all the information stored in the structure simply do:
julia> out.
Then press tab
(tabulation key) to display all stored data:
julia> out.
G_system Gamma MAGEMin_ver M_sys PP_vec P_kbar SS_vec T_C V Vp Vp_S Vs Vs_S X
aAl2O3 aFeO aH2O aMgO aSiO2 aTiO2 alpha bulk bulkMod bulkModulus_M bulkModulus_S bulk_F bulk_F_wt bulk_M
bulk_M_wt bulk_S bulk_S_wt bulk_res_norm bulk_wt cp dQFM dataset enthalpy entropy fO2 frac_F frac_F_wt frac_M
frac_M_wt frac_S frac_S_wt iter mSS_vec n_PP n_SS n_mSS oxides ph ph_frac ph_frac_vol ph_frac_wt ph_id
ph_type rho rho_F rho_M rho_S s_cp shearMod shearModulus_S status time_ms
In order to access any of these variables type for instance:
julia> out.fO2
which will give you the oxygen fugacity:
julia> out.fO2
-4.405735414252153
to access the list of stable phases and their fraction in mol
:
julia> out.ph
4-element Vector{String}:
"liq"
"g"
"sp"
"ru"
julia> out.ph_frac
4-element Vector{Float64}:
0.970482189810529
0.003792750364729876
0.020229088594267013
0.0054959712304740085
Chemical potential of the pure components (oxides) of the system is retrieved as:
julia> out.Gamma
11-element Vector{Float64}:
-1017.3138187719679
-1847.7215909497188
-881.3605772634041
-720.5475835413267
-428.1896629304572
-1051.6248892195592
-1008.7336303031074
-1070.7332593397723
-228.07833391903714
-561.1937065530427
-440.764181608507
julia> out.oxides
11-element Vector{String}:
"SiO2"
"Al2O3"
"CaO"
"MgO"
"FeO"
"K2O"
"Na2O"
"TiO2"
"O"
"MnO"
"H2O"
The composition in wt
of the first listed solution phase ("liq") can be accessed as
julia> out.SS_vec[1].Comp_wt
11-element Vector{Float64}:
0.6174962747665693
0.1822124172602761
0.006265730986600257
0.0185105629478801
0.04555393290694774
0.038161590650707795
0.013329583423813463
0.0
0.0
0.0
0.07846990705720527
and the end-member fraction in wt
and their names as
julia> out.SS_vec[1].emFrac_wt
8-element Vector{Float64}:
0.4608062343057727
0.0972375952287159
0.17818888101139307
0.02313962538195582
0.12734359573100587
0.025819902698522926
0.047571646835750894
0.03989251880688298
julia> out.SS_vec[1].emNames
8-element Vector{String}:
"q4L"
"abL"
"kspL"
"anL"
"slL"
"fo2L"
"fa2L"
"h2oL"
Julia can be run in parallel using multi-threading. To take advantage of this, you need to start julia from the terminal with:
$julia -t auto
which will automatically use all threads on your machine. Alternatively, use julia -t 4
to start it on 4 threads.
If you are interested to see what you can do on your machine, type:
julia> versioninfo()
Julia Version 1.9.0
Commit 8e630552924 (2023-05-07 11:25 UTC)
Platform Info:
OS: macOS (arm64-apple-darwin22.4.0)
CPU: 12 × Apple M2 Max
WORD_SIZE: 64
LIBM: libopenlibm
LLVM: libLLVM-14.0.6 (ORCJIT, apple-m1)
Threads: 8 on 8 virtual cores
The function multi_point_minimization
will automatically utilize parallelization if you run it on >1 threads.