Visualising Cumulate Compositions

First we’ll import a set of example data tables:

from pyrolite_meltsutil.util.general import get_data_example
from pyrolite_meltsutil.tables.load import import_tables

hsh = "3149b39eee"  # the hash index of our experiment
batchdir = get_data_example("montecarlo")  # let's use the example batch data for this
system, phases = import_tables(batchdir / hsh)  # let's import the tables

The cumulate composition is automatically calculated and added to the phase table:

phases.loc[phases.phase == "cumulate", :].head(3).T

	(5000, 1300)	(5000, 1295)	(5000, 1290)
step	0	1	2
pressure	NaN	NaN	NaN
temperature	NaN	NaN	NaN
mass	NaN	NaN	NaN
entropy	NaN	NaN	NaN
enthalpy	NaN	NaN	NaN
volume	NaN	NaN	NaN
Cp	NaN	NaN	NaN
viscosity	NaN	NaN	NaN
SiO2	NaN	NaN	NaN
TiO2	NaN	NaN	NaN
Al2O3	NaN	NaN	NaN
Fe2O3	NaN	NaN	NaN
FeO	NaN	NaN	NaN
MnO	NaN	NaN	NaN
MgO	NaN	NaN	NaN
CaO	NaN	NaN	NaN
Na2O	NaN	NaN	NaN
K2O	NaN	NaN	NaN
P2O5	NaN	NaN	NaN
Mg#	NaN	NaN	NaN
phaseID	NaN	NaN	NaN
phase	cumulate	cumulate	cumulate
structure	NaN	NaN	NaN
formula	NaN	NaN	NaN
mass%	NaN	NaN	NaN
volume%	NaN	NaN	NaN

We can also manually calculate the phase mass proportions for the cumulate pile:

from pyrolite_meltsutil.util.tables import integrate_solid_proportions

cumulate_phases = integrate_solid_proportions(phases, frac=False)
cumulate_phases.tail(3).T

	(5000, 745)	(5000, 740)	(5000, 735)
pressure	5000.000000	5000.000000	5000.000000
temperature	745.000000	740.000000	735.000000
step	111.000000	112.000000	113.000000
clinopyroxene_0	22.560717	22.569348	22.578173
clinopyroxene_1	25.775885	25.773038	25.770461
clinopyroxene_2	8.750804	8.759462	8.767811
feldspar_0	41.084019	41.068917	41.053587
olivine_0	0.802876	0.803690	0.804486
quartz	1.025699	1.025545	1.025482
rhm-oxide_0	0.000000	0.000000	0.000000
whitlockite	0.000000	0.000000	0.000000

Ternary diagrams can be useful to visualise how the overal/fractional cumulates change during the experiment:

import matplotlib.pyplot as plt
import pyrolite.plot
from pyrolite.util.plot.style import mappable_from_values

chemvars = ["MgO", "Al2O3", "FeO"]
cumulate_comp = phases.loc[phases.phase == "cumulate", :]
ax = cumulate_comp.loc[:, chemvars].pyroplot.scatter(
    c=cumulate_comp.temperature, cmap="magma"
)
plt.colorbar(
    mappable_from_values(cumulate_comp.temperature.dropna(), cmap="magma"),
    label="Temperature (C)",
    ax=ax,
    shrink=0.7,
)
plt.show()

Similarly, we can plot the phase proportions:

phaselist = ["clinopyroxene_0", "clinopyroxene_1", "feldspar_0"]
ax = cumulate_phases.loc[:, phaselist].pyroplot.scatter(
    c=cumulate_phases.temperature, cmap="magma"
)
plt.colorbar(
    mappable_from_values(cumulate_phases.temperature, cmap="magma"),
    label="Temperature (C)",
    ax=ax,
    shrink=0.7,
)
plt.show()