From 5dc55d25f71b16bd1a80f4dc9ebdfad1d861ee0d Mon Sep 17 00:00:00 2001
From: Gard Spreemann <gspr@nonempty.org>
Date: Sun, 20 Dec 2020 15:22:22 +0100
Subject: Add tests for BettiCurve2.

---
 src/python/CMakeLists.txt                          |  5 +++
 .../test/test_betti_curve_representations.py       | 41 ++++++++++++++++++++++
 2 files changed, 46 insertions(+)
 create mode 100755 src/python/test/test_betti_curve_representations.py

diff --git a/src/python/CMakeLists.txt b/src/python/CMakeLists.txt
index 5c1402a6..e0e88880 100644
--- a/src/python/CMakeLists.txt
+++ b/src/python/CMakeLists.txt
@@ -512,6 +512,11 @@ if(PYTHONINTERP_FOUND)
       add_gudhi_py_test(test_representations)
     endif()
 
+    # Betti curves.
+    if(SCIPY_FOUND)
+      add_gudhi_py_test(test_betti_curve_representations)
+    endif()
+
     # Time Delay
     add_gudhi_py_test(test_time_delay)
 
diff --git a/src/python/test/test_betti_curve_representations.py b/src/python/test/test_betti_curve_representations.py
new file mode 100755
index 00000000..779f6d6e
--- /dev/null
+++ b/src/python/test/test_betti_curve_representations.py
@@ -0,0 +1,41 @@
+import numpy as np
+import scipy.interpolate
+
+from gudhi.representations.vector_methods import BettiCurve2
+
+def test_betti_curve_is_irregular_betti_curve_followed_by_interpolation():
+    m = 10
+    n = 1000
+    pinf = 0.05
+    pzero = 0.05
+    res = 100
+    success = True
+    
+    pds = []
+    for i in range(0, m):
+        pd = np.zeros((n, 2))
+        pd[:, 0] = np.random.uniform(0, 10, n)
+        pd[:, 1] = np.random.uniform(pd[:, 0], 10, n)
+        pd[np.random.uniform(0, 1, n) < pzero, 0] = 0
+        pd[np.random.uniform(0, 1, n) < pinf, 1] = np.inf
+        pds.append(pd)
+    
+    bc = BettiCurve2(None)
+    bc.fit(pds)
+    bettis = bc.transform(pds)
+
+    bc2 = BettiCurve2(None)
+    bettis2 = bc2.fit_transform(pds)
+    success = success and (bc2.grid_ == bc.grid_).all()
+    success = success and (bettis2 == bettis).all()
+
+    for i in range(0, m):
+        grid = np.linspace(pds[i].min(), pds[i].max() + 1, res)
+        bc_gridded = BettiCurve2(grid)
+        bettis_gridded = bc_gridded(pds[i])
+
+        interp = scipy.interpolate.interp1d(bc.grid_, bettis[i, :], kind="previous", fill_value="extrapolate")
+        bettis_interp = np.array(interp(grid), dtype=int)
+        success = success and (bettis_interp == bettis_gridded).all()
+
+    assert(success)
-- 
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