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-rwxr-xr-xsrc/python/test/test_wasserstein_distance.py134
1 files changed, 122 insertions, 12 deletions
diff --git a/src/python/test/test_wasserstein_distance.py b/src/python/test/test_wasserstein_distance.py
index e3b521d6..42bf3299 100755
--- a/src/python/test/test_wasserstein_distance.py
+++ b/src/python/test/test_wasserstein_distance.py
@@ -5,25 +5,105 @@
Copyright (C) 2019 Inria
Modification(s):
+ - 2020/07 Théo Lacombe: Added tests about handling essential parts in diagrams.
- YYYY/MM Author: Description of the modification
"""
-from gudhi.wasserstein.wasserstein import _proj_on_diag
+from gudhi.wasserstein.wasserstein import _proj_on_diag, _finite_part, _handle_essential_parts, _get_essential_parts
+from gudhi.wasserstein.wasserstein import _warn_infty
from gudhi.wasserstein import wasserstein_distance as pot
from gudhi.hera import wasserstein_distance as hera
import numpy as np
import pytest
+
__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 test_finite_part():
+ diag = np.array([[0, 1], [3, 5], [2, np.inf], [3, np.inf], [-np.inf, 8], [-np.inf, 12], [-np.inf, -np.inf],
+ [np.inf, np.inf], [-np.inf, np.inf], [-np.inf, np.inf]])
+ assert np.array_equal(_finite_part(diag), [[0, 1], [3, 5]])
+
+
+def test_handle_essential_parts():
+ diag1 = np.array([[0, 1], [3, 5],
+ [2, np.inf], [3, np.inf],
+ [-np.inf, 8], [-np.inf, 12],
+ [-np.inf, -np.inf],
+ [np.inf, np.inf],
+ [-np.inf, np.inf], [-np.inf, np.inf]])
+
+ diag2 = np.array([[0, 2], [3, 5],
+ [2, np.inf], [4, np.inf],
+ [-np.inf, 8], [-np.inf, 11],
+ [-np.inf, -np.inf],
+ [np.inf, np.inf],
+ [-np.inf, np.inf], [-np.inf, np.inf]])
+
+ diag3 = np.array([[0, 2], [3, 5],
+ [2, np.inf], [4, np.inf], [6, np.inf],
+ [-np.inf, 8], [-np.inf, 11],
+ [-np.inf, -np.inf],
+ [np.inf, np.inf],
+ [-np.inf, np.inf], [-np.inf, np.inf]])
+
+ c, m = _handle_essential_parts(diag1, diag2, order=1)
+ assert c == pytest.approx(2, 0.0001) # Note: here c is only the cost due to essential part (thus 2, not 3)
+ # Similarly, the matching only corresponds to essential parts.
+ # Note that (-inf,-inf) and (+inf,+inf) coordinates are matched to the diagonal.
+ assert np.array_equal(m, [[4, 4], [5, 5], [2, 2], [3, 3], [8, 8], [9, 9], [6, -1], [7, -1], [-1, 6], [-1, 7]])
+
+ c, m = _handle_essential_parts(diag1, diag3, order=1)
+ assert c == np.inf
+ assert (m is None)
+
+
+def test_get_essential_parts():
+ diag1 = np.array([[0, 1], [3, 5], [2, np.inf], [3, np.inf], [-np.inf, 8], [-np.inf, 12], [-np.inf, -np.inf],
+ [np.inf, np.inf], [-np.inf, np.inf], [-np.inf, np.inf]])
+
+ diag2 = np.array([[0, 1], [3, 5], [2, np.inf], [3, np.inf]])
+
+ res = _get_essential_parts(diag1)
+ res2 = _get_essential_parts(diag2)
+ assert np.array_equal(res[0], [4, 5])
+ assert np.array_equal(res[1], [2, 3])
+ assert np.array_equal(res[2], [8, 9])
+ assert np.array_equal(res[3], [6] )
+ assert np.array_equal(res[4], [7] )
+
+ assert np.array_equal(res2[0], [] )
+ assert np.array_equal(res2[1], [2, 3])
+ assert np.array_equal(res2[2], [] )
+ assert np.array_equal(res2[3], [] )
+ assert np.array_equal(res2[4], [] )
+
+
+def test_warn_infty():
+ with pytest.warns(UserWarning):
+ assert _warn_infty(matching=False)==np.inf
+ c, m = _warn_infty(matching=True)
+ assert (c == np.inf)
+ assert (m is None)
+
+
+def _to_set(X):
+ return { (i, j) for i, j in X }
+
+def _same_permuted(X, Y):
+ return _to_set(X) == _to_set(Y)
+
+
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]])
@@ -64,20 +144,46 @@ def _basic_wasserstein(wasserstein_distance, delta, test_infinity=True, test_mat
assert wasserstein_distance(diag4, diag5) == np.inf
assert wasserstein_distance(diag5, diag6, order=1, internal_p=np.inf) == approx(4.)
-
+ assert wasserstein_distance(diag5, emptydiag) == np.inf
if test_matching:
match = wasserstein_distance(emptydiag, emptydiag, matching=True, internal_p=1., order=2)[1]
- assert np.array_equal(match, [])
+ # Accept [] or np.array of shape (2, 0)
+ assert len(match) == 0
match = wasserstein_distance(emptydiag, emptydiag, matching=True, internal_p=np.inf, order=2.24)[1]
- assert np.array_equal(match, [])
+ assert len(match) == 0
match = wasserstein_distance(emptydiag, diag2, matching=True, internal_p=np.inf, order=2.)[1]
- assert np.array_equal(match , [[-1, 0], [-1, 1]])
+ assert _same_permuted(match, [[-1, 0], [-1, 1]])
match = wasserstein_distance(diag2, emptydiag, matching=True, internal_p=np.inf, order=2.24)[1]
- assert np.array_equal(match , [[0, -1], [1, -1]])
+ assert _same_permuted(match, [[0, -1], [1, -1]])
match = wasserstein_distance(diag1, diag2, matching=True, internal_p=2., order=2.)[1]
- assert np.array_equal(match, [[0, 0], [1, 1], [2, -1]])
-
+ assert _same_permuted(match, [[0, 0], [1, 1], [2, -1]])
+
+ if test_matching and test_infinity:
+ diag7 = np.array([[0, 3], [4, np.inf], [5, np.inf]])
+ diag8 = np.array([[0,1], [0, np.inf], [-np.inf, -np.inf], [np.inf, np.inf]])
+ diag9 = np.array([[-np.inf, -np.inf], [np.inf, np.inf]])
+ diag10 = np.array([[0,1], [-np.inf, -np.inf], [np.inf, np.inf]])
+
+ match = wasserstein_distance(diag5, diag6, matching=True, internal_p=2., order=2.)[1]
+ assert _same_permuted(match, [[0, -1], [-1,0], [-1, 1], [1, 2]])
+ match = wasserstein_distance(diag5, diag7, matching=True, internal_p=2., order=2.)[1]
+ assert (match is None)
+ cost, match = wasserstein_distance(diag7, emptydiag, matching=True, internal_p=2., order=2.3)
+ assert (cost == np.inf)
+ assert (match is None)
+ cost, match = wasserstein_distance(emptydiag, diag7, matching=True, internal_p=2.42, order=2.)
+ assert (cost == np.inf)
+ assert (match is None)
+ cost, match = wasserstein_distance(diag8, diag9, matching=True, internal_p=2., order=2.)
+ assert (cost == np.inf)
+ assert (match is None)
+ cost, match = wasserstein_distance(diag9, diag10, matching=True, internal_p=1., order=1.)
+ assert (cost == 1)
+ assert _same_permuted(match, [[0, -1],[1, -1],[-1, 0], [-1, 1], [-1, 2]]) # type 4 and 5 are match to the diag anyway.
+ cost, match = wasserstein_distance(diag9, emptydiag, matching=True, internal_p=2., order=2.)
+ assert (cost == 0.)
+ assert _same_permuted(match, [[0, -1], [1, -1]])
def hera_wrap(**extra):
@@ -85,15 +191,19 @@ def hera_wrap(**extra):
return hera(*kargs,**kwargs,**extra)
return fun
+
def pot_wrap(**extra):
def fun(*kargs,**kwargs):
return pot(*kargs,**kwargs,**extra)
return fun
+
def test_wasserstein_distance_pot():
- _basic_wasserstein(pot, 1e-15, test_infinity=False, test_matching=True)
- _basic_wasserstein(pot_wrap(enable_autodiff=True), 1e-15, test_infinity=False, test_matching=False)
+ _basic_wasserstein(pot, 1e-15, test_infinity=False, test_matching=True) # pot with its standard args
+ _basic_wasserstein(pot_wrap(enable_autodiff=True, keep_essential_parts=False), 1e-15, test_infinity=False, test_matching=False)
+
def test_wasserstein_distance_hera():
- _basic_wasserstein(hera_wrap(delta=1e-12), 1e-12, test_matching=False)
- _basic_wasserstein(hera_wrap(delta=.1), .1, test_matching=False)
+ _basic_wasserstein(hera_wrap(delta=1e-12), 1e-12, test_matching=True)
+ _basic_wasserstein(hera_wrap(delta=.1), .1, test_matching=True)
+