How to create ternary contour plot in Python?

Question

I have a data set as follows (in Python):

import numpy as np
A = np.array([0.1, 0.2, 0.3, 0.4, 0.5, 0.6, 0.7, 0.8, 0.9, 0, 0.1, 0.2, 0.3, 0.4, 0.2, 0.2, 0.05         


        

Answer 1

Just to add in another option (though probably too late to help the OP, but maybe someone else). You can pip install using pip install samternary. The github link is https://github.com/samueljmcameron/samternary.

For the original post, you can follow the example examples/flatdata.py from the source code fairly closely, i.e.

import matplotlib.pyplot as plt
import numpy as np

from samternary.ternary import Ternary

# OP's data                                                             
A = np.array([0.1, 0.2, 0.3, 0.4, 0.5, 0.6, 0.7, 0.8, 0.9, 0,
              0.1, 0.2, 0.3, 0.4, 0.2, 0.2, 0.05, 0.1])
B = np.array([0.9, 0.7, 0.5, 0.3, 0.1, 0.2, 0.1, 0.15, 0, 0.1,
              0.2, 0.3, 0.4, 0.5, 0.6, 0.7, 0.8, 0.9])
C = np.array([0, 0.1, 0.2, 0.3, 0.4, 0.2, 0.2, 0.05, 0.1, 0.9,
              0.7, 0.5, 0.3, 0.1, 0.2, 0.1, 0.15, 0])
D = np.array([1, 2, 3, 4, 5, 6, 7, 8, 7, 6, 5, 4, 3, 2, 1, 0,
              1, 2])
# note that the array C above is not necessary since A+B+C=1            


# plot the data in two ways, in cartesian coordinates (ax_norm)         
# and in ternary-plot coordinates (ax_trans)                            

# create the figure and the two sets of axes                            
fig, (ax_norm,ax_trans) = plt.subplots(1,2,
                                       figsize=[5,2.8])


# plot data in normal way first using tricontourf                       
ax_norm.tricontourf(A,B,D)
ax_norm.set_xlabel(r'$\phi_1$')
ax_norm.set_ylabel(r'$\phi_2$')

# transform ax_trans to ternary-plot style, which includes              
# building axes and labeling the axes                                   
cob = Ternary(ax_trans, bottom_ax = 'bottom', left_ax = 'left',
              right_ax = 'right',labelpad=20)

# use change of bases method within Ternary() to                        
points = cob.B1_to_B2(A,B)

# affine transform x,y points to ternary-plot basis                     
cs = ax_trans.tricontourf(points[0],points[1],D)


ax_norm.set_title("Cartesian "
                  "(basis " + r"$\mathcal{B}_1$" + ")")
ax_trans.set_title("flattened-grid "
                   "(basis " + r"$\mathcal{B}_2$" + ")")

cbar = fig.colorbar(cs,ax=ax_trans,shrink=0.6)
fig.subplots_adjust(bottom=0.2,hspace=0.01)
plt.show()

The result is (white spaces are due to the sparsity of the data from the OP):

image of data in cartesian coordinates vs ternary plot