Some test

3 files changed, 34 insertions, 3 deletions

diff --git a/src/python/gudhi/representations/kernel_methods.py b/src/python/gudhi/representations/kernel_methods.py
index 6e4f0619..23fd23c7 100644
--- a/src/python/gudhi/representations/kernel_methods.py
+++ b/src/python/gudhi/representations/kernel_methods.py
@@ -75,7 +75,7 @@ def pairwise_persistence_diagram_kernels(X, Y=None, kernel="sliced_wasserstein",
         numpy array of shape (nxm): kernel matrix.
     """    
     XX = np.reshape(np.arange(len(X)), [-1,1])
-    YY = None if Y is None else np.reshape(np.arange(len(Y)), [-1,1])
+    YY = None if Y is None or Y is X else np.reshape(np.arange(len(Y)), [-1,1])
     if kernel == "sliced_wasserstein":
         return np.exp(-pairwise_persistence_diagram_distances(X, Y, metric="sliced_wasserstein", num_directions=kwargs["num_directions"], n_jobs=n_jobs) / kwargs["bandwidth"])
     elif kernel == "persistence_fisher":
diff --git a/src/python/gudhi/representations/metrics.py b/src/python/gudhi/representations/metrics.py
index 84907160..cf2e0879 100644
--- a/src/python/gudhi/representations/metrics.py
+++ b/src/python/gudhi/representations/metrics.py
@@ -164,7 +164,7 @@ def pairwise_persistence_diagram_distances(X, Y=None, metric="bottleneck", n_job
         numpy array of shape (nxm): distance matrix
     """
     XX = np.reshape(np.arange(len(X)), [-1,1])
-    YY = None if Y is None else np.reshape(np.arange(len(Y)), [-1,1]) 
+    YY = None if Y is None or Y is X else np.reshape(np.arange(len(Y)), [-1,1])
     if metric == "bottleneck":
         try: 
             from .. import bottleneck_distance
diff --git a/src/python/test/test_representations.py b/src/python/test/test_representations.py
index dba7f952..589cee00 100755
--- a/src/python/test/test_representations.py
+++ b/src/python/test/test_representations.py
@@ -1,12 +1,43 @@
 import os
 import sys
 import matplotlib.pyplot as plt
+import numpy as np
+import pytest
+
 
 def test_representations_examples():
     # Disable graphics for testing purposes
-    plt.show = lambda:None
+    plt.show = lambda: None
     here = os.path.dirname(os.path.realpath(__file__))
     sys.path.append(here + "/../example")
     import diagram_vectorizations_distances_kernels
 
     return None
+
+
+from gudhi.representations.metrics import *
+from gudhi.representations.kernel_methods import *
+
+
+def _n_diags(n):
+    l = []
+    for _ in range(n):
+        a = np.random.rand(50, 2)
+        a[:, 1] += a[:, 0]  # So that y >= x
+        l.append(a)
+    return l
+
+
+def test_multiple():
+    l1 = _n_diags(9)
+    l2 = _n_diags(11)
+    l1b = l1.copy()
+    d1 = pairwise_persistence_diagram_distances(l1, e=0.00001, n_jobs=4)
+    d2 = BottleneckDistance(epsilon=0.00001).fit_transform(l1)
+    d3 = pairwise_persistence_diagram_distances(l1, l1b, e=0.00001, n_jobs=4)
+    assert d1 == pytest.approx(d2)
+    assert d3 == pytest.approx(d2, abs=1e-5) # Because of 0 entries (on the diagonal)
+    d1 = pairwise_persistence_diagram_distances(l1, l2, metric="wasserstein", order=2, internal_p=2)
+    d2 = WassersteinDistance(order=2, internal_p=2, n_jobs=4).fit(l2).transform(l1)
+    print(d1.shape, d2.shape)
+    assert d1 == pytest.approx(d2, rel=.02)