Reintroduce _proj_on_diag, with a unit test

2 files changed, 18 insertions, 0 deletions

diff --git a/src/python/gudhi/wasserstein/wasserstein.py b/src/python/gudhi/wasserstein/wasserstein.py
index 5df66cf9..efc851a0 100644
--- a/src/python/gudhi/wasserstein/wasserstein.py
+++ b/src/python/gudhi/wasserstein/wasserstein.py
@@ -15,6 +15,17 @@ try:
 except ImportError:
     print("POT (Python Optimal Transport) package is not installed. Try to run $ conda install -c conda-forge pot ; or $ pip install POT")
 
+
+# Currently unused, but Théo says it is likely to be used again.
+def _proj_on_diag(X):
+    '''
+    :param X: (n x 2) array encoding the points of a persistent diagram.
+    :returns: (n x 2) array encoding the (respective orthogonal) projections of the points onto the diagonal
+    '''
+    Z = (X[:,0] + X[:,1]) / 2.
+    return np.array([Z , Z]).T
+
+
 def _dist_to_diag(X, internal_p):
     '''
     :param X: (n x 2) array encoding the points of a persistent diagram.
diff --git a/src/python/test/test_wasserstein_distance.py b/src/python/test/test_wasserstein_distance.py
index 7e0d0f5f..1a4acc1d 100755
--- a/src/python/test/test_wasserstein_distance.py
+++ b/src/python/test/test_wasserstein_distance.py
@@ -8,6 +8,7 @@
       - YYYY/MM Author: Description of the modification
 """
 
+from gudhi.wasserstein.wasserstein import _proj_on_diag
 from gudhi.wasserstein import wasserstein_distance as pot
 from gudhi.hera import wasserstein_distance as hera
 import numpy as np
@@ -17,6 +18,12 @@ __author__ = "Theo Lacombe"
 __copyright__ = "Copyright (C) 2019 Inria"
 __license__ = "MIT"
 
+def test_proj_on_diag():
+    dgm = np.array([[1., 1.], [1., 2.], [3., 5.]])
+    assert np.array_equal(_proj_on_diag(dgm), [[1., 1.], [1.5, 1.5], [4., 4.]])
+    empty = np.empty((0, 2))
+    assert np.array_equal(_proj_on_diag(empty), empty)
+
 def _basic_wasserstein(wasserstein_distance, delta, test_infinity=True, test_matching=True):
     diag1 = np.array([[2.7, 3.7], [9.6, 14.0], [34.2, 34.974]])
     diag2 = np.array([[2.8, 4.45], [9.5, 14.1]])