full coveragre utils

4 files changed, 65 insertions, 7 deletions

diff --git a/Makefile b/Makefile
index 577bbbe..98f5614 100644
--- a/Makefile
+++ b/Makefile
@@ -38,10 +38,10 @@ pep8 :
 	flake8 examples/ ot/ test/
 
 test : FORCE pep8
-	python -m py.test -v test/
+	python -m py.test -v test/ --cov=ot --cov-report html:cov_html
 	
 pytest : FORCE 
-	python -m py.test -v test/	
+	python -m py.test -v test/ --cov=ot
 
 uploadpypi :
 	#python setup.py register
diff --git a/test/test_gpu.py b/test/test_gpu.py
index 312a2d4..49b98d0 100644
--- a/test/test_gpu.py
+++ b/test/test_gpu.py
@@ -3,8 +3,14 @@ import numpy as np
 import time
 import pytest
 
+try:  # test if cudamat installed
+    import ot.gpu
+    nogpu = False
+except ImportError:
+    nogpu = True
+
 
-@pytest.mark.skip(reason="No way to test GPU on travis yet")
+@pytest.mark.skipif(nogpu, reason="No GPU available")
 def test_gpu_sinkhorn():
     import ot.gpu
 
@@ -12,7 +18,7 @@ def test_gpu_sinkhorn():
         print("min:{:.3E}, max::{:.3E}, mean::{:.3E}, std::{:.3E}".format(
             np.min(r), np.max(r), np.mean(r), np.std(r)))
 
-    for n in [5000]:
+    for n in [50, 100, 500, 1000]:
         print(n)
         a = np.random.rand(n // 4, 100)
         b = np.random.rand(n, 100)
@@ -30,14 +36,16 @@ def test_gpu_sinkhorn():
         print("   GPU sinkhorn, time: {:6.2f} sec ".format(time3 - time2))
         describeRes(G2)
 
+        assert np.allclose(G1, G2, rtol=1e-5, atol=1e-5)
 
-@pytest.mark.skip(reason="No way to test GPU on travis yet")
+
+@pytest.mark.skipif(nogpu, reason="No GPU available")
 def test_gpu_sinkhorn_lpl1():
         def describeRes(r):
             print("min:{:.3E}, max:{:.3E}, mean:{:.3E}, std:{:.3E}"
                   .format(np.min(r), np.max(r), np.mean(r), np.std(r)))
 
-        for n in [5000]:
+        for n in [50, 100, 500, 1000]:
             print(n)
             a = np.random.rand(n // 4, 100)
             labels_a = np.random.randint(10, size=(n // 4))
@@ -57,3 +65,5 @@ def test_gpu_sinkhorn_lpl1():
             print("   GPU sinkhorn lpl1, time: {:6.2f} sec ".format(
                 time3 - time2))
             describeRes(G2)
+
+            assert np.allclose(G1, G2, rtol=1e-5, atol=1e-5)
diff --git a/test/test_ot.py b/test/test_ot.py
index 3fa1bc4..16fd510 100644
--- a/test/test_ot.py
+++ b/test/test_ot.py
@@ -31,9 +31,11 @@ def test_emd_emd2():
 
     # check G is identity
     assert np.allclose(G, np.eye(n) / n)
+    # check constratints
+    assert np.allclose(u, G.sum(1))  # cf convergence sinkhorn
+    assert np.allclose(u, G.sum(0))  # cf convergence sinkhorn
 
     w = ot.emd2(u, u, M)
-
     # check loss=0
     assert np.allclose(w, 0)
 
diff --git a/test/test_utils.py b/test/test_utils.py
index 3219fce..e85e5b7 100644
--- a/test/test_utils.py
+++ b/test/test_utils.py
@@ -71,6 +71,52 @@ def test_dist():
             D[i, j] = np.sum(np.square(x[i, :] - x[j, :]))
 
     D2 = ot.dist(x, x)
+    D3 = ot.dist(x)
 
     # dist shoul return squared euclidean
     assert np.allclose(D, D2)
+    assert np.allclose(D, D3)
+
+
+def test_dist0():
+
+    n = 100
+    M = ot.utils.dist0(n, method='lin_square')
+
+    # dist0 default to linear sampling with quadratic loss
+    assert np.allclose(M[0, -1], (n - 1) * (n - 1))
+
+
+def test_dots():
+
+    n1, n2, n3, n4 = 100, 50, 200, 100
+
+    A = np.random.randn(n1, n2)
+    B = np.random.randn(n2, n3)
+    C = np.random.randn(n3, n4)
+
+    X1 = ot.utils.dots(A, B, C)
+
+    X2 = A.dot(B.dot(C))
+
+    assert np.allclose(X1, X2)
+
+
+def test_clean_zeros():
+
+    n = 100
+    nz = 50
+    nz2 = 20
+    u1 = ot.unif(n)
+    u1[:nz] = 0
+    u1 = u1 / u1.sum()
+    u2 = ot.unif(n)
+    u2[:nz2] = 0
+    u2 = u2 / u2.sum()
+
+    M = ot.utils.dist0(n)
+
+    a, b, M2 = ot.utils.clean_zeros(u1, u2, M)
+
+    assert len(a) == n - nz
+    assert len(b) == n - nz2