Added example for ternary contour plot.

examples/ternary_contours.py

@@ -0,0 +1,54 @@
+""" Compute ternary contours using matplotlib.pyplot.contour function """
+import numpy as np
+import matplotlib.pyplot as plt
+import ternary
+import math
+import itertools
+
+
+def shannon_entropy(p):
+    """Computes the Shannon Entropy at a distribution in the simplex."""
+    s = 0.
+    for i in range(len(p)):
+        try:
+            s += p[i] * math.log(p[i])
+        except ValueError:
+            continue
+    return -1. * s
+
+scale = 20
+level = [0.25, 0.5, 0.8, 0.9]       # values for contours
+
+# === prepare coordinate list for contours
+x_range = np.arange(0, 1.01, 0.01)   # ensure that grid spacing is small enough to get smooth contours
+coordinate_list = np.asarray(list(itertools.product(x_range, repeat=2)))
+coordinate_list = np.append(coordinate_list, (1 - coordinate_list[:, 0] - coordinate_list[:, 1]).reshape(-1, 1), axis=1)
+
+# === calculate data with coordinate list
+data_list = []
+for point in coordinate_list:
+    data_list.append(shannon_entropy(point))
+data_list = np.asarray(data_list)
+data_list[np.sum(coordinate_list[:, 0:2], axis=1) > 1] = np.nan  # remove data outside triangle
+
+# === reshape coordinates and data for use with pyplot contour function
+x = coordinate_list[:, 0].reshape(x_range.shape[0], -1)
+y = coordinate_list[:, 1].reshape(x_range.shape[0], -1)
+
+h = data_list.reshape(x_range.shape[0], -1)
+
+# === use pyplot to calculate contours
+contours = plt.contour(x, y, h, level)  # this needs to be BEFORE figure definition
+plt.clf()  # makes sure that contours are not plotted in carthesian plot
+
+fig, tax = ternary.figure(scale=scale)
+
+# === plot contour lines
+for ii, contour in enumerate(contours.allsegs):
+    for jj, seg in enumerate(contour):
+        tax.plot(seg[:, 0:2] * scale, color='r')
+
+# === plot regular data
+tax.heatmapf(shannon_entropy, boundary=True, style='hexagonal', colorbar=True)
+
+plt.show()