Example plotting ternary diagrams in python using image files as source data.

PlotUFGTernary.py

from matplotlib import pyplot
import ternary
import numpy as np

## Boundary and Gridlines
scale = 100
figure, tax = ternary.figure(scale=scale)

# Draw Boundary and Gridlines
tax.boundary(linewidth=2.0)
tax.gridlines(color="blue", multiple=10) # Every 5th gridline, can be a float

# Set Axis labels and Title
fontsize = 20
tax.set_title("Simplex Boundary and Gridlines", fontsize=fontsize)
tax.left_axis_label("Mg", fontsize=fontsize)
tax.bottom_axis_label("Fe", fontsize=fontsize)
tax.right_axis_label("Si", fontsize=fontsize)

# Set ticks
tax.ticks(axis='lbr', linewidth=1)

# Remove default Matplotlib Axes
tax.clear_matplotlib_ticks()

#Points = (19.2,22.0,9.5)
#tax.scatter(Points, color='red')

Fe=pyplot.imread('Fe-K.tif')
Mg=pyplot.imread('Mg-K.tif')
Si=pyplot.imread('SiMask.tif')

points=np.array([np.ravel(Mg), np.ravel(Fe), np.ravel(Si)]).T.astype('float')

#Points = [p[0]/np.sum(p[0]) for p in points]
Points = [p/np.sum(p)*100 for p in points if p[2] < 7000]#if p[0] > 2000]

v1 = Points[0]/(Points[0]+Points[1])
print 'mean Mg/(Mg+Fe): %g \n' % np.mean(v1)
print 'std Mg/(Mg+Fe): %g \n' % np.std(v1)

v2 = (Points[0]+Points[1])/Points[2]
print 'mean (Mg+Fe)/Si: %g \n' % np.mean(v2)
print 'std (Mg+Fe)/Si: %g \n' % np.std(v2)

#print Points

CenterPoint = [(19.2,9.5,22.0)]
#CenterPoint = [(10,30,60)]
CenterPoint = CenterPoint/np.sum(CenterPoint)*100
#print points
tax.scatter(Points, marker='s', color='red', label="Point analyses")
tax.scatter(CenterPoint, marker='s', color='blue', label="Whole object")

pyplot.show()