Basic Usage

Import mpltern together with Matplotlib as:

import matplotlib.pyplot as plt
import mpltern

With this, the projection "ternary" is registered. Then, make TernaryAxes;

ax = plt.subplot(projection="ternary")

You can use another normalization constant e.g. 100 using ternary_sum. Ternary-axis labels can be given using e.g. ax.set_tlabel. You can also add grids with ax.grid.

ax = plt.subplot(projection="ternary", ternary_sum=100.0)

ax.set_tlabel("Top (%)")
ax.set_llabel("Left (%)")
ax.set_rlabel("Right (%)")

ax.grid()

plt.show()

You can make ternary plots using methods similar to Matplotlib. You can e.g. use ax.plot; the only difference from Matplotlib is that you give three variables i.e. t (top), l (left), r (right) instead of x and y.

from mpltern.datasets import get_spiral

ax = plt.subplot(projection="ternary")

t, l, r = get_spiral()
# t: [0.33333333 0.33357906 0.33430414 ...]
# l: [0.33333333 0.33455407 0.33543547 ...]
# r: [0.33333333 0.33186687 0.33026039 ...]
ax.plot(t, l, r)

plt.show()

You can also make filled contour plots using ax.tricontourf.

from mpltern.datasets import get_shanon_entropies

ax = plt.subplot(projection="ternary")

t, l, r, entropies = get_shanon_entropies()
# t: [ 0. 0.  0.  0.  0.  0.  0.  0.  0.  0.  0.  0.1 0.1 0.1 ...]
# l: [ 0. 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1.  0.  0.1 0.2 ...]
# r: [ 1. 0.9 0.8 0.7 0.6 0.5 0.4 0.3 0.2 0.1 0.  0.9 0.8 0.7 ...]
# v: [-0. 0.32508297  0.50040242  ...]
ax.tricontourf(t, l, r, entropies)

plt.show()

There are more plotting methods and controls. See examples.