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-rw-r--r--src/python/test/test_diff.py78
-rwxr-xr-xsrc/python/test/test_dtm.py16
-rw-r--r--src/python/test/test_remote_datasets.py87
-rwxr-xr-xsrc/python/test/test_representations.py21
-rwxr-xr-xsrc/python/test/test_simplex_tree.py6
-rwxr-xr-xsrc/python/test/test_subsampling.py4
6 files changed, 200 insertions, 12 deletions
diff --git a/src/python/test/test_diff.py b/src/python/test/test_diff.py
new file mode 100644
index 00000000..dca001a9
--- /dev/null
+++ b/src/python/test/test_diff.py
@@ -0,0 +1,78 @@
+from gudhi.tensorflow import *
+import numpy as np
+import tensorflow as tf
+import gudhi as gd
+
+def test_rips_diff():
+
+ Xinit = np.array([[1.,1.],[2.,2.]], dtype=np.float32)
+ X = tf.Variable(initial_value=Xinit, trainable=True)
+ rl = RipsLayer(maximum_edge_length=2., homology_dimensions=[0])
+
+ with tf.GradientTape() as tape:
+ dgm = rl.call(X)[0][0]
+ loss = tf.math.reduce_sum(tf.square(.5*(dgm[:,1]-dgm[:,0])))
+ grads = tape.gradient(loss, [X])
+ assert tf.norm(grads[0]-tf.constant([[-.5,-.5],[.5,.5]]),1) <= 1e-6
+
+def test_cubical_diff():
+
+ Xinit = np.array([[0.,2.,2.],[2.,2.,2.],[2.,2.,1.]], dtype=np.float32)
+ X = tf.Variable(initial_value=Xinit, trainable=True)
+ cl = CubicalLayer(homology_dimensions=[0])
+
+ with tf.GradientTape() as tape:
+ dgm = cl.call(X)[0][0]
+ loss = tf.math.reduce_sum(tf.square(.5*(dgm[:,1]-dgm[:,0])))
+ grads = tape.gradient(loss, [X])
+ assert tf.norm(grads[0]-tf.constant([[0.,0.,0.],[0.,.5,0.],[0.,0.,-.5]]),1) <= 1e-6
+
+def test_nonsquare_cubical_diff():
+
+ Xinit = np.array([[-1.,1.,0.],[1.,1.,1.]], dtype=np.float32)
+ X = tf.Variable(initial_value=Xinit, trainable=True)
+ cl = CubicalLayer(homology_dimensions=[0])
+
+ with tf.GradientTape() as tape:
+ dgm = cl.call(X)[0][0]
+ loss = tf.math.reduce_sum(tf.square(.5*(dgm[:,1]-dgm[:,0])))
+ grads = tape.gradient(loss, [X])
+ assert tf.norm(grads[0]-tf.constant([[0.,0.5,-0.5],[0.,0.,0.]]),1) <= 1e-6
+
+def test_st_diff():
+
+ st = gd.SimplexTree()
+ st.insert([0])
+ st.insert([1])
+ st.insert([2])
+ st.insert([3])
+ st.insert([4])
+ st.insert([5])
+ st.insert([6])
+ st.insert([7])
+ st.insert([8])
+ st.insert([9])
+ st.insert([10])
+ st.insert([0, 1])
+ st.insert([1, 2])
+ st.insert([2, 3])
+ st.insert([3, 4])
+ st.insert([4, 5])
+ st.insert([5, 6])
+ st.insert([6, 7])
+ st.insert([7, 8])
+ st.insert([8, 9])
+ st.insert([9, 10])
+
+ Finit = np.array([6.,4.,3.,4.,5.,4.,3.,2.,3.,4.,5.], dtype=np.float32)
+ F = tf.Variable(initial_value=Finit, trainable=True)
+ sl = LowerStarSimplexTreeLayer(simplextree=st, homology_dimensions=[0])
+
+ with tf.GradientTape() as tape:
+ dgm = sl.call(F)[0][0]
+ loss = tf.math.reduce_sum(tf.square(.5*(dgm[:,1]-dgm[:,0])))
+ grads = tape.gradient(loss, [F])
+
+ assert tf.math.reduce_all(tf.math.equal(grads[0].indices, tf.constant([2,4])))
+ assert tf.math.reduce_all(tf.math.equal(grads[0].values, tf.constant([-1.,1.])))
+
diff --git a/src/python/test/test_dtm.py b/src/python/test/test_dtm.py
index e46d616c..b276f041 100755
--- a/src/python/test/test_dtm.py
+++ b/src/python/test/test_dtm.py
@@ -91,11 +91,11 @@ def test_density():
def test_dtm_overflow_warnings():
pts = numpy.array([[10., 100000000000000000000000000000.], [1000., 100000000000000000000000000.]])
-
- with warnings.catch_warnings(record=True) as w:
- # TODO Test "keops" implementation as well when next version of pykeops (current is 1.5) is released (should fix the problem (cf. issue #543))
- dtm = DistanceToMeasure(2, implementation="hnsw")
- r = dtm.fit_transform(pts)
- assert len(w) == 1
- assert issubclass(w[0].category, RuntimeWarning)
- assert "Overflow" in str(w[0].message)
+ impl_warn = ["keops", "hnsw"]
+ for impl in impl_warn:
+ with warnings.catch_warnings(record=True) as w:
+ dtm = DistanceToMeasure(2, implementation=impl)
+ r = dtm.fit_transform(pts)
+ assert len(w) == 1
+ assert issubclass(w[0].category, RuntimeWarning)
+ assert "Overflow" in str(w[0].message)
diff --git a/src/python/test/test_remote_datasets.py b/src/python/test/test_remote_datasets.py
new file mode 100644
index 00000000..e5d2de82
--- /dev/null
+++ b/src/python/test/test_remote_datasets.py
@@ -0,0 +1,87 @@
+# This file is part of the Gudhi Library - https://gudhi.inria.fr/ - which is released under MIT.
+# See file LICENSE or go to https://gudhi.inria.fr/licensing/ for full license details.
+# Author(s): Hind Montassif
+#
+# Copyright (C) 2021 Inria
+#
+# Modification(s):
+# - YYYY/MM Author: Description of the modification
+
+from gudhi.datasets import remote
+
+import shutil
+import io
+import sys
+import pytest
+
+from os.path import isdir, expanduser, exists
+from os import remove, environ
+
+def test_data_home():
+ # Test _get_data_home and clear_data_home on new empty folder
+ empty_data_home = remote._get_data_home(data_home="empty_folder_for_test")
+ assert isdir(empty_data_home)
+
+ remote.clear_data_home(data_home=empty_data_home)
+ assert not isdir(empty_data_home)
+
+def test_fetch_remote():
+ # Test fetch with a wrong checksum
+ with pytest.raises(OSError):
+ remote._fetch_remote("https://raw.githubusercontent.com/GUDHI/gudhi-data/main/points/spiral_2d/spiral_2d.npy", "tmp_spiral_2d.npy", file_checksum = 'XXXXXXXXXX')
+ assert not exists("tmp_spiral_2d.npy")
+
+def _get_bunny_license_print(accept_license = False):
+ capturedOutput = io.StringIO()
+ # Redirect stdout
+ sys.stdout = capturedOutput
+
+ bunny_arr = remote.fetch_bunny("./tmp_for_test/bunny.npy", accept_license)
+ assert bunny_arr.shape == (35947, 3)
+ del bunny_arr
+ remove("./tmp_for_test/bunny.npy")
+
+ # Reset redirect
+ sys.stdout = sys.__stdout__
+ return capturedOutput
+
+def test_print_bunny_license():
+ # Test not printing bunny.npy LICENSE when accept_license = True
+ assert "" == _get_bunny_license_print(accept_license = True).getvalue()
+ # Test printing bunny.LICENSE file when fetching bunny.npy with accept_license = False (default)
+ with open("./tmp_for_test/bunny.LICENSE") as f:
+ assert f.read().rstrip("\n") == _get_bunny_license_print().getvalue().rstrip("\n")
+ shutil.rmtree("./tmp_for_test")
+
+def test_fetch_remote_datasets_wrapped():
+ # Test fetch_spiral_2d and fetch_bunny wrapping functions with data directory different from default (twice, to test case of already fetched files)
+ # Default case is not tested because it would fail in case the user sets the 'GUDHI_DATA' environment variable locally
+ for i in range(2):
+ spiral_2d_arr = remote.fetch_spiral_2d("./another_fetch_folder_for_test/spiral_2d.npy")
+ assert spiral_2d_arr.shape == (114562, 2)
+
+ bunny_arr = remote.fetch_bunny("./another_fetch_folder_for_test/bunny.npy")
+ assert bunny_arr.shape == (35947, 3)
+
+ # Check that the directory was created
+ assert isdir("./another_fetch_folder_for_test")
+ # Check downloaded files
+ assert exists("./another_fetch_folder_for_test/spiral_2d.npy")
+ assert exists("./another_fetch_folder_for_test/bunny.npy")
+ assert exists("./another_fetch_folder_for_test/bunny.LICENSE")
+
+ # Remove test folders
+ del spiral_2d_arr
+ del bunny_arr
+ shutil.rmtree("./another_fetch_folder_for_test")
+
+def test_gudhi_data_env():
+ # Set environment variable "GUDHI_DATA"
+ environ["GUDHI_DATA"] = "./test_folder_from_env_var"
+ bunny_arr = remote.fetch_bunny()
+ assert bunny_arr.shape == (35947, 3)
+ assert exists("./test_folder_from_env_var/points/bunny/bunny.npy")
+ assert exists("./test_folder_from_env_var/points/bunny/bunny.LICENSE")
+ # Remove test folder
+ del bunny_arr
+ shutil.rmtree("./test_folder_from_env_var")
diff --git a/src/python/test/test_representations.py b/src/python/test/test_representations.py
index 5f29740f..2ca72d07 100755
--- a/src/python/test/test_representations.py
+++ b/src/python/test/test_representations.py
@@ -152,7 +152,26 @@ def test_vectorization_empty_diagrams():
scv = Entropy(mode="vector", normalized=False, resolution=random_resolution)(empty_diag)
assert not np.any(scv)
assert scv.shape[0] == random_resolution
-
+
+def test_entropy_miscalculation():
+ diag_ex = np.array([[0.0,1.0], [0.0,1.0], [0.0,2.0]])
+ def pe(pd):
+ l = pd[:,1] - pd[:,0]
+ l = l/sum(l)
+ return -np.dot(l, np.log(l))
+ sce = Entropy(mode="scalar")
+ assert [[pe(diag_ex)]] == sce.fit_transform([diag_ex])
+ sce = Entropy(mode="vector", resolution=4, normalized=False)
+ pef = [-1/4*np.log(1/4)-1/4*np.log(1/4)-1/2*np.log(1/2),
+ -1/4*np.log(1/4)-1/4*np.log(1/4)-1/2*np.log(1/2),
+ -1/2*np.log(1/2),
+ 0.0]
+ assert all(([pef] == sce.fit_transform([diag_ex]))[0])
+ sce = Entropy(mode="vector", resolution=4, normalized=True)
+ pefN = (sce.fit_transform([diag_ex]))[0]
+ area = np.linalg.norm(pefN, ord=1)
+ assert area==1
+
def test_kernel_empty_diagrams():
empty_diag = np.empty(shape = [0, 2])
assert SlicedWassersteinDistance(num_directions=100)(empty_diag, empty_diag) == 0.
diff --git a/src/python/test/test_simplex_tree.py b/src/python/test/test_simplex_tree.py
index 688f4fd6..54bafed5 100755
--- a/src/python/test/test_simplex_tree.py
+++ b/src/python/test/test_simplex_tree.py
@@ -320,6 +320,10 @@ def test_extend_filtration():
]
dgms = st.extended_persistence(min_persistence=-1.)
+ assert len(dgms) == 4
+ # Sort by (death-birth) descending - we are only interested in those with the longest life span
+ for idx in range(4):
+ dgms[idx] = sorted(dgms[idx], key=lambda x:(-abs(x[1][0]-x[1][1])))
assert dgms[0][0][1][0] == pytest.approx(2.)
assert dgms[0][0][1][1] == pytest.approx(3.)
@@ -528,7 +532,7 @@ def test_expansion_with_blocker():
def blocker(simplex):
try:
- # Block all simplices that countains vertex 6
+ # Block all simplices that contain vertex 6
simplex.index(6)
print(simplex, ' is blocked')
return True
diff --git a/src/python/test/test_subsampling.py b/src/python/test/test_subsampling.py
index 4019852e..3431f372 100755
--- a/src/python/test/test_subsampling.py
+++ b/src/python/test/test_subsampling.py
@@ -91,7 +91,7 @@ def test_simple_choose_n_farthest_points_randomed():
assert gudhi.choose_n_farthest_points(points=[], nb_points=1) == []
assert gudhi.choose_n_farthest_points(points=point_set, nb_points=0) == []
- # Go furter than point set on purpose
+ # Go further than point set on purpose
for iter in range(1, 10):
sub_set = gudhi.choose_n_farthest_points(points=point_set, nb_points=iter)
for sub in sub_set:
@@ -117,7 +117,7 @@ def test_simple_pick_n_random_points():
assert gudhi.pick_n_random_points(points=[], nb_points=1) == []
assert gudhi.pick_n_random_points(points=point_set, nb_points=0) == []
- # Go furter than point set on purpose
+ # Go further than point set on purpose
for iter in range(1, 10):
sub_set = gudhi.pick_n_random_points(points=point_set, nb_points=iter)
for sub in sub_set:
generated by cgit v1.2.3 (git 2.39.1) at 2024-07-15 03:30:38 +0000