diff --git a/multiview_platform/mono_multi_view_classifiers/utils/get_multiview_db.py b/multiview_platform/mono_multi_view_classifiers/utils/get_multiview_db.py
index be069e57ba8f6d4d00ce1e5201ca5651ebc4d2ae..d968500a489aa74fe712489d54eace498985a0f0 100644
--- a/multiview_platform/mono_multi_view_classifiers/utils/get_multiview_db.py
+++ b/multiview_platform/mono_multi_view_classifiers/utils/get_multiview_db.py
@@ -310,7 +310,7 @@ def get_classic_db_hdf5(views, path_f, name_DB, nb_class, asked_labels_names,
noise_std)
else:
pass
- return dataset, labels_dictionary, dataset_name
+ return dataset_file, labels_dictionary, dataset_name
def add_gaussian_noise(dataset_file, random_state, path_f, dataset_name,
diff --git a/multiview_platform/tests/test_ExecClassif.py b/multiview_platform/tests/test_ExecClassif.py
index a0c11c76d7969f38aa73efafd2144acc9b586412..6c7dd9719a06f5f1d43dc6e3d343c66006b77f3c 100644
--- a/multiview_platform/tests/test_ExecClassif.py
+++ b/multiview_platform/tests/test_ExecClassif.py
@@ -6,7 +6,7 @@ import numpy as np
from .utils import rm_tmp, tmp_path
-from ..mono_multi_view_classifiers import exec_classif
+from multiview_platform.mono_multi_view_classifiers import exec_classif
class Test_initBenchmark(unittest.TestCase):
@@ -232,7 +232,7 @@ class Test_execBenchmark(unittest.TestCase):
@classmethod
def setUpClass(cls):
rm_tmp()
- os.mkdir("multiview_platform/tests/tmp_tests")
+ os.mkdir("./tests/tmp_tests")
cls.Dataset = h5py.File(
tmp_path+"test_file.hdf5", "w")
cls.labels = cls.Dataset.create_dataset("Labels",
@@ -333,10 +333,10 @@ class FakeKfold():
class Test_execOneBenchmark(unittest.TestCase):
@classmethod
-
def setUp(cls):
rm_tmp()
- os.mkdir("multiview_platform/tests/tmp_tests")
+ print(os.getcwd())
+ os.mkdir("../tests/tmp_tests")
cls.args = {
"Base": {"name": "chicken_is_heaven", "type": "type",
"pathf": "pathF"},
@@ -403,7 +403,7 @@ class Test_execOneBenchmark_multicore(unittest.TestCase):
@classmethod
def setUpClass(cls):
rm_tmp()
- os.mkdir("multiview_platform/tests/tmp_tests")
+ os.mkdir("./tests/tmp_tests")
cls.args = {
"Base": {"name": "chicken_is_heaven", "type": "type",
"pathf": "pathF"},
@@ -809,3 +809,6 @@ class Test_get_path_dict(unittest.TestCase):
# suite.addTest(Test_initBenchmark('test_initKWARGSFunc_no_monoview'))
# # suite.addTest(WidgetTestCase('test_widget_resize'))
# return suite
+
+if __name__ == '__main__':
+ unittest.main()
\ No newline at end of file
diff --git a/multiview_platform/tests/test_multiview_classifiers/test_additions/test_diversity_utils.py b/multiview_platform/tests/test_multiview_classifiers/test_additions/test_diversity_utils.py
index bfb134d7a039ab3400d6e2e772dfa827d6fc2ed6..a7dd8797d18f7b5ce6e9d0c11bcd22de5881f0b9 100644
--- a/multiview_platform/tests/test_multiview_classifiers/test_additions/test_diversity_utils.py
+++ b/multiview_platform/tests/test_multiview_classifiers/test_additions/test_diversity_utils.py
@@ -67,4 +67,8 @@ class Test_DiversityFusion(unittest.TestCase):
clf = FakeDivGlobalClf(self.random_state,
classifier_names=self.classifier_names,
classifiers_config=self.classifiers_config)
- clf.fit(self.X, self.y, self.train_indices, self.views_indices)
\ No newline at end of file
+ clf.fit(self.X, self.y, self.train_indices, self.views_indices)
+
+
+if __name__ == '__main__':
+ unittest.main()
\ No newline at end of file
diff --git a/multiview_platform/tests/test_utils/test_GetMultiviewDB.py b/multiview_platform/tests/test_utils/test_GetMultiviewDB.py
index 862556e2346fa3c77a0dfe8c49418c2423e8666a..bb84359ea450ad8d7b0329a7cab3073947826bf7 100644
--- a/multiview_platform/tests/test_utils/test_GetMultiviewDB.py
+++ b/multiview_platform/tests/test_utils/test_GetMultiviewDB.py
@@ -23,23 +23,23 @@ class Test_copyhdf5Dataset(unittest.TestCase):
0, 100, (10, 20)))
cls.dataset.attrs["test_arg"] = "Am I copied"
- def test_simple_copy(cls):
- get_multiview_db.copyhdf5_dataset(cls.dataset_file, cls.dataset_file,
+ def test_simple_copy(self):
+ get_multiview_db.copyhdf5_dataset(self.dataset_file, self.dataset_file,
"test", "test_copy_1", np.arange(10))
- np.testing.assert_array_equal(cls.dataset_file.get("test").value,
- cls.dataset_file.get("test_copy_1").value)
- cls.assertEqual("Am I copied",
- cls.dataset_file.get("test_copy_1").attrs["test_arg"])
-
- def test_copy_only_some_indices(cls):
- usedIndices = cls.random_state.choice(10, 6, replace=False)
- get_multiview_db.copyhdf5_dataset(cls.dataset_file, cls.dataset_file,
+ np.testing.assert_array_equal(self.dataset_file.get("test").value,
+ self.dataset_file.get("test_copy_1").value)
+ self.assertEqual("Am I copied",
+ self.dataset_file.get("test_copy_1").attrs["test_arg"])
+
+ def test_copy_only_some_indices(self):
+ usedIndices = self.random_state.choice(10, 6, replace=False)
+ get_multiview_db.copyhdf5_dataset(self.dataset_file, self.dataset_file,
"test", "test_copy", usedIndices)
np.testing.assert_array_equal(
- cls.dataset_file.get("test").value[usedIndices, :],
- cls.dataset_file.get("test_copy").value)
- cls.assertEqual("Am I copied",
- cls.dataset_file.get("test_copy").attrs["test_arg"])
+ self.dataset_file.get("test").value[usedIndices, :],
+ self.dataset_file.get("test_copy").value)
+ self.assertEqual("Am I copied",
+ self.dataset_file.get("test_copy").attrs["test_arg"])
@classmethod
def tearDownClass(cls):
@@ -67,30 +67,30 @@ class Test_filterViews(unittest.TestCase):
0, 100, (10, 20)))
cls.dataset.attrs["name"] = "test_view_" + str(i)
- def test_simple_filter(cls):
- cls.temp_dataset_file = h5py.File(
+ def test_simple_filter(self):
+ self.temp_dataset_file = h5py.File(
tmp_path+"test_copy_temp.hdf5", "w")
- cls.dataset_file.copy("Metadata", cls.temp_dataset_file)
- get_multiview_db.filter_views(cls.dataset_file, cls.temp_dataset_file,
- cls.views, np.arange(10))
- cls.assertEqual(cls.dataset_file.get("View1").attrs["name"],
- cls.temp_dataset_file.get("View0").attrs["name"])
- np.testing.assert_array_equal(cls.dataset_file.get("View2").value,
- cls.temp_dataset_file.get("View1").value)
- cls.assertEqual(cls.temp_dataset_file.get("Metadata").attrs["nbView"],
+ self.dataset_file.copy("Metadata", self.temp_dataset_file)
+ get_multiview_db.filter_views(self.dataset_file, self.temp_dataset_file,
+ self.views, np.arange(10))
+ self.assertEqual(self.dataset_file.get("View1").attrs["name"],
+ self.temp_dataset_file.get("View0").attrs["name"])
+ np.testing.assert_array_equal(self.dataset_file.get("View2").value,
+ self.temp_dataset_file.get("View1").value)
+ self.assertEqual(self.temp_dataset_file.get("Metadata").attrs["nbView"],
2)
- def test_filter_view_and_examples(cls):
- cls.temp_dataset_file = h5py.File(
+ def test_filter_view_and_examples(self):
+ self.temp_dataset_file = h5py.File(
tmp_path+"test_copy_temp.hdf5", "w")
- cls.dataset_file.copy("Metadata", cls.temp_dataset_file)
- usedIndices = cls.random_state.choice(10, 6, replace=False)
- get_multiview_db.filter_views(cls.dataset_file, cls.temp_dataset_file,
- cls.views, usedIndices)
+ self.dataset_file.copy("Metadata", self.temp_dataset_file)
+ usedIndices = self.random_state.choice(10, 6, replace=False)
+ get_multiview_db.filter_views(self.dataset_file, self.temp_dataset_file,
+ self.views, usedIndices)
np.testing.assert_array_equal(
- cls.dataset_file.get("View1").value[usedIndices, :],
- cls.temp_dataset_file.get("View0").value)
- cls.temp_dataset_file.close()
+ self.dataset_file.get("View1").value[usedIndices, :],
+ self.temp_dataset_file.get("View0").value)
+ self.temp_dataset_file.close()
@classmethod
def tearDownClass(cls):
@@ -112,60 +112,60 @@ class Test_filterLabels(unittest.TestCase):
"test_label_2", "test_label_3"]
cls.askedLabelsNames = ["test_label_1", "test_label_3"]
- def test_simple(cls):
+ def test_simple(self):
newLabels, \
newLabelsNames, \
- usedIndices = get_multiview_db.filter_labels(cls.labelsSet,
- cls.askedLabelsNamesSet,
- cls.fullLabels,
- cls.availableLabelsNames,
- cls.askedLabelsNames)
- cls.assertEqual(["test_label_1", "test_label_3"], newLabelsNames)
+ usedIndices = get_multiview_db.filter_labels(self.labelsSet,
+ self.askedLabelsNamesSet,
+ self.fullLabels,
+ self.availableLabelsNames,
+ self.askedLabelsNames)
+ self.assertEqual(["test_label_1", "test_label_3"], newLabelsNames)
np.testing.assert_array_equal(usedIndices, np.array([1, 5, 9]))
np.testing.assert_array_equal(newLabels, np.array([1, 1, 0]))
- def test_biclasse(cls):
- cls.labelsSet = {0, 1}
- cls.fullLabels = cls.random_state.randint(0, 2, 10)
- cls.availableLabelsNames = ["test_label_0", "test_label_1"]
+ def test_biclasse(self):
+ self.labelsSet = {0, 1}
+ self.fullLabels = self.random_state.randint(0, 2, 10)
+ self.availableLabelsNames = ["test_label_0", "test_label_1"]
newLabels, \
newLabelsNames, \
- usedIndices = get_multiview_db.filter_labels(cls.labelsSet,
- cls.askedLabelsNamesSet,
- cls.fullLabels,
- cls.availableLabelsNames,
- cls.askedLabelsNames)
- cls.assertEqual(cls.availableLabelsNames, newLabelsNames)
+ usedIndices = get_multiview_db.filter_labels(self.labelsSet,
+ self.askedLabelsNamesSet,
+ self.fullLabels,
+ self.availableLabelsNames,
+ self.askedLabelsNames)
+ self.assertEqual(self.availableLabelsNames, newLabelsNames)
np.testing.assert_array_equal(usedIndices, np.arange(10))
- np.testing.assert_array_equal(newLabels, cls.fullLabels)
+ np.testing.assert_array_equal(newLabels, self.fullLabels)
- def test_asked_too_many_labels(cls):
- cls.askedLabelsNamesSet = {"test_label_0", "test_label_1",
+ def test_asked_too_many_labels(self):
+ self.askedLabelsNamesSet = {"test_label_0", "test_label_1",
"test_label_2", "test_label_3",
"chicken_is_heaven"}
- with cls.assertRaises(get_multiview_db.DatasetError) as catcher:
- get_multiview_db.filter_labels(cls.labelsSet,
- cls.askedLabelsNamesSet,
- cls.fullLabels,
- cls.availableLabelsNames,
- cls.askedLabelsNames)
+ with self.assertRaises(get_multiview_db.DatasetError) as catcher:
+ get_multiview_db.filter_labels(self.labelsSet,
+ self.askedLabelsNamesSet,
+ self.fullLabels,
+ self.availableLabelsNames,
+ self.askedLabelsNames)
exception = catcher.exception
- def test_asked_all_labels(cls):
- cls.askedLabelsNamesSet = {"test_label_0", "test_label_1",
+ def test_asked_all_labels(self):
+ self.askedLabelsNamesSet = {"test_label_0", "test_label_1",
"test_label_2", "test_label_3"}
- cls.askedLabelsNames = ["test_label_0", "test_label_1", "test_label_2",
+ self.askedLabelsNames = ["test_label_0", "test_label_1", "test_label_2",
"test_label_3"]
newLabels, \
newLabelsNames, \
- usedIndices = get_multiview_db.filter_labels(cls.labelsSet,
- cls.askedLabelsNamesSet,
- cls.fullLabels,
- cls.availableLabelsNames,
- cls.askedLabelsNames)
- cls.assertEqual(cls.availableLabelsNames, newLabelsNames)
+ usedIndices = get_multiview_db.filter_labels(self.labelsSet,
+ self.askedLabelsNamesSet,
+ self.fullLabels,
+ self.availableLabelsNames,
+ self.askedLabelsNames)
+ self.assertEqual(self.availableLabelsNames, newLabelsNames)
np.testing.assert_array_equal(usedIndices, np.arange(10))
- np.testing.assert_array_equal(newLabels, cls.fullLabels)
+ np.testing.assert_array_equal(newLabels, self.fullLabels)
class Test_selectAskedLabels(unittest.TestCase):
@@ -179,42 +179,42 @@ class Test_selectAskedLabels(unittest.TestCase):
"test_label_2", "test_label_3"]
cls.askedLabelsNames = ["test_label_1", "test_label_3"]
- def test_simple(cls):
+ def test_simple(self):
newLabels, \
newLabelsNames, \
- usedIndices = get_multiview_db.select_asked_labels(cls.askedLabelsNamesSet,
- cls.availableLabelsNames,
- cls.askedLabelsNames,
- cls.fullLabels)
- cls.assertEqual(["test_label_1", "test_label_3"], newLabelsNames)
+ usedIndices = get_multiview_db.select_asked_labels(self.askedLabelsNamesSet,
+ self.availableLabelsNames,
+ self.askedLabelsNames,
+ self.fullLabels)
+ self.assertEqual(["test_label_1", "test_label_3"], newLabelsNames)
np.testing.assert_array_equal(usedIndices, np.array([1, 5, 9]))
np.testing.assert_array_equal(newLabels, np.array([1, 1, 0]))
- def test_asked_all_labels(cls):
- cls.askedLabelsNamesSet = {"test_label_0", "test_label_1",
+ def test_asked_all_labels(self):
+ self.askedLabelsNamesSet = {"test_label_0", "test_label_1",
"test_label_2", "test_label_3"}
- cls.askedLabelsNames = ["test_label_0", "test_label_1", "test_label_2",
+ self.askedLabelsNames = ["test_label_0", "test_label_1", "test_label_2",
"test_label_3"]
newLabels, \
newLabelsNames, \
- usedIndices = get_multiview_db.select_asked_labels(cls.askedLabelsNamesSet,
- cls.availableLabelsNames,
- cls.askedLabelsNames,
- cls.fullLabels)
- cls.assertEqual(cls.availableLabelsNames, newLabelsNames)
+ usedIndices = get_multiview_db.select_asked_labels(self.askedLabelsNamesSet,
+ self.availableLabelsNames,
+ self.askedLabelsNames,
+ self.fullLabels)
+ self.assertEqual(self.availableLabelsNames, newLabelsNames)
np.testing.assert_array_equal(usedIndices, np.arange(10))
- np.testing.assert_array_equal(newLabels, cls.fullLabels)
+ np.testing.assert_array_equal(newLabels, self.fullLabels)
- def test_asked_unavailable_labels(cls):
- cls.askedLabelsNamesSet = {"test_label_1", "test_label_3",
+ def test_asked_unavailable_labels(self):
+ self.askedLabelsNamesSet = {"test_label_1", "test_label_3",
"chicken_is_heaven"}
- with cls.assertRaises(get_multiview_db.DatasetError) as catcher:
- get_multiview_db.select_asked_labels(cls.askedLabelsNamesSet,
- cls.availableLabelsNames,
- cls.askedLabelsNames,
- cls.fullLabels)
+ with self.assertRaises(get_multiview_db.DatasetError) as catcher:
+ get_multiview_db.select_asked_labels(self.askedLabelsNamesSet,
+ self.availableLabelsNames,
+ self.askedLabelsNames,
+ self.fullLabels)
exception = catcher.exception
- # cls.assertTrue("Asked labels are not all available in the dataset" in exception)
+ # self.assertTrue("Asked labels are not all available in the dataset" in exception)
class Test_getAllLabels(unittest.TestCase):
@@ -226,12 +226,12 @@ class Test_getAllLabels(unittest.TestCase):
cls.availableLabelsNames = ["test_label_0", "test_label_1",
"test_label_2", "test_label_3"]
- def test_simple(cls):
+ def test_simple(self):
newLabels, newLabelsNames, usedIndices = get_multiview_db.get_all_labels(
- cls.fullLabels, cls.availableLabelsNames)
- cls.assertEqual(cls.availableLabelsNames, newLabelsNames)
+ self.fullLabels, self.availableLabelsNames)
+ self.assertEqual(self.availableLabelsNames, newLabelsNames)
np.testing.assert_array_equal(usedIndices, np.arange(10))
- np.testing.assert_array_equal(newLabels, cls.fullLabels)
+ np.testing.assert_array_equal(newLabels, self.fullLabels)
class Test_fillLabelNames(unittest.TestCase):
@@ -243,24 +243,24 @@ class Test_fillLabelNames(unittest.TestCase):
cls.random_state = np.random.RandomState(42)
cls.availableLabelsNames = ["test_label_" + str(_) for _ in range(40)]
- def test_simple(cls):
+ def test_simple(self):
askedLabelsNames, askedLabelsNamesSet = get_multiview_db.fill_label_names(
- cls.NB_CLASS,
- cls.askedLabelsNames,
- cls.random_state,
- cls.availableLabelsNames)
- cls.assertEqual(askedLabelsNames, cls.askedLabelsNames)
- cls.assertEqual(askedLabelsNamesSet, set(cls.askedLabelsNames))
-
- def test_missing_labels_names(cls):
- cls.NB_CLASS = 39
+ self.NB_CLASS,
+ self.askedLabelsNames,
+ self.random_state,
+ self.availableLabelsNames)
+ self.assertEqual(askedLabelsNames, self.askedLabelsNames)
+ self.assertEqual(askedLabelsNamesSet, set(self.askedLabelsNames))
+
+ def test_missing_labels_names(self):
+ self.NB_CLASS = 39
askedLabelsNames, askedLabelsNamesSet = get_multiview_db.fill_label_names(
- cls.NB_CLASS,
- cls.askedLabelsNames,
- cls.random_state,
- cls.availableLabelsNames)
+ self.NB_CLASS,
+ self.askedLabelsNames,
+ self.random_state,
+ self.availableLabelsNames)
- cls.assertEqual(askedLabelsNames,
+ self.assertEqual(askedLabelsNames,
['test_label_1', 'test_label_3', 'test_label_35',
'test_label_38', 'test_label_6', 'test_label_15',
'test_label_32', 'test_label_28', 'test_label_8',
@@ -274,21 +274,21 @@ class Test_fillLabelNames(unittest.TestCase):
'test_label_36', 'test_label_25', 'test_label_33',
'test_label_12', 'test_label_24', 'test_label_20',
'test_label_22', 'test_label_9', 'test_label_16'])
- cls.assertEqual(askedLabelsNamesSet, set(
+ self.assertEqual(askedLabelsNamesSet, set(
["test_label_" + str(_) for _ in range(30)] + [
"test_label_" + str(31 + _) for _ in range(9)]))
- def test_too_many_label_names(cls):
- cls.NB_CLASS = 2
- cls.askedLabelsNames = ["test_label_1", "test_label_3", "test_label_4",
+ def test_too_many_label_names(self):
+ self.NB_CLASS = 2
+ self.askedLabelsNames = ["test_label_1", "test_label_3", "test_label_4",
"test_label_6"]
askedLabelsNames, askedLabelsNamesSet = get_multiview_db.fill_label_names(
- cls.NB_CLASS,
- cls.askedLabelsNames,
- cls.random_state,
- cls.availableLabelsNames)
- cls.assertEqual(askedLabelsNames, ["test_label_3", "test_label_6"])
- cls.assertEqual(askedLabelsNamesSet, {"test_label_3", "test_label_6"})
+ self.NB_CLASS,
+ self.askedLabelsNames,
+ self.random_state,
+ self.availableLabelsNames)
+ self.assertEqual(askedLabelsNames, ["test_label_3", "test_label_6"])
+ self.assertEqual(askedLabelsNamesSet, {"test_label_3", "test_label_6"})
class Test_allAskedLabelsAreAvailable(unittest.TestCase):
@@ -299,17 +299,17 @@ class Test_allAskedLabelsAreAvailable(unittest.TestCase):
cls.availableLabelsNames = ["test_label_0", "test_label_1",
"test_label_2", "test_label_3"]
- def test_asked_available_labels(cls):
- cls.assertTrue(
- get_multiview_db.all_asked_labels_are_available(cls.askedLabelsNamesSet,
- cls.availableLabelsNames))
+ def test_asked_available_labels(self):
+ self.assertTrue(
+ get_multiview_db.all_asked_labels_are_available(self.askedLabelsNamesSet,
+ self.availableLabelsNames))
- def test_asked_unavailable_label(cls):
- cls.askedLabelsNamesSet = {"test_label_1", "test_label_3",
+ def test_asked_unavailable_label(self):
+ self.askedLabelsNamesSet = {"test_label_1", "test_label_3",
"chicken_is_heaven"}
- cls.assertFalse(
- get_multiview_db.all_asked_labels_are_available(cls.askedLabelsNamesSet,
- cls.availableLabelsNames))
+ self.assertFalse(
+ get_multiview_db.all_asked_labels_are_available(self.askedLabelsNamesSet,
+ self.availableLabelsNames))
class Test_getClasses(unittest.TestCase):
@@ -318,21 +318,21 @@ class Test_getClasses(unittest.TestCase):
def setUpClass(cls):
cls.random_state = np.random.RandomState(42)
- def test_multiclass(cls):
+ def test_multiclass(self):
labelsSet = get_multiview_db.get_classes(
- cls.random_state.randint(0, 5, 30))
- cls.assertEqual(labelsSet, {0, 1, 2, 3, 4})
+ self.random_state.randint(0, 5, 30))
+ self.assertEqual(labelsSet, {0, 1, 2, 3, 4})
- def test_biclass(cls):
+ def test_biclass(self):
labelsSet = get_multiview_db.get_classes(
- cls.random_state.randint(0, 2, 30))
- cls.assertEqual(labelsSet, {0, 1})
+ self.random_state.randint(0, 2, 30))
+ self.assertEqual(labelsSet, {0, 1})
- def test_one_class(cls):
- with cls.assertRaises(get_multiview_db.DatasetError) as catcher:
+ def test_one_class(self):
+ with self.assertRaises(get_multiview_db.DatasetError) as catcher:
get_multiview_db.get_classes(np.zeros(30, dtype=int))
exception = catcher.exception
- # cls.assertTrue("Dataset must have at least two different labels" in exception)
+ # self.assertTrue("Dataset must have at least two different labels" in exception)
class Test_getClassicDBhdf5(unittest.TestCase):
@@ -366,86 +366,86 @@ class Test_getClassicDBhdf5(unittest.TestCase):
0, 100, (10, 20)))
cls.dataset.attrs["name"] = "test_view_" + str(i)
- def test_simple(cls):
+ def test_simple(self):
dataset_file, labels_dictionary, dataset_name = get_multiview_db.get_classic_db_hdf5(
- cls.views, cls.pathF, cls.nameDB,
- cls.NB_CLASS, cls.askedLabelsNames,
- cls.random_state)
- cls.assertEqual(dataset_file.get("View1").attrs["name"], "test_view_3")
- cls.assertEqual(labels_dictionary,
+ self.views, self.pathF, self.nameDB,
+ self.NB_CLASS, self.askedLabelsNames,
+ self.random_state)
+ self.assertEqual(dataset_file.get("View1").attrs["name"], "test_view_3")
+ self.assertEqual(labels_dictionary,
{0: "test_label_1", 1: "test_label_3"})
- cls.assertEqual(dataset_file.get("Metadata").attrs["datasetLength"], 3)
- cls.assertEqual(dataset_file.get("Metadata").attrs["nbView"], 2)
- cls.assertEqual(dataset_file.get("Metadata").attrs["nbClass"], 2)
+ self.assertEqual(dataset_file.get("Metadata").attrs["datasetLength"], 3)
+ self.assertEqual(dataset_file.get("Metadata").attrs["nbView"], 2)
+ self.assertEqual(dataset_file.get("Metadata").attrs["nbClass"], 2)
np.testing.assert_array_equal(dataset_file.get("View0").value,
- cls.dataset_file.get("View1").value[
+ self.dataset_file.get("View1").value[
np.array([1, 5, 9]), :])
- def test_all_labels_asked(cls):
+ def test_all_labels_asked(self):
askedLabelsNames = ["test_label_0", "test_label_1", "test_label_2",
"test_label_3"]
NB_CLASS = 4
dataset_file, labels_dictionary, dataset_name = get_multiview_db.get_classic_db_hdf5(
- cls.views, cls.pathF, cls.nameDB,
+ self.views, self.pathF, self.nameDB,
NB_CLASS, askedLabelsNames,
- cls.random_state)
- cls.assertEqual(dataset_name, 'test_dataset_temp_view_label_select')
- cls.assertEqual(dataset_file.get("View1").attrs["name"], "test_view_3")
- cls.assertEqual(labels_dictionary,
+ self.random_state)
+ self.assertEqual(dataset_name, 'test_dataset_temp_view_label_select')
+ self.assertEqual(dataset_file.get("View1").attrs["name"], "test_view_3")
+ self.assertEqual(labels_dictionary,
{0: "test_label_0", 1: "test_label_1",
2: "test_label_2", 3: "test_label_3"})
- cls.assertEqual(dataset_file.get("Metadata").attrs["datasetLength"], 10)
- cls.assertEqual(dataset_file.get("Metadata").attrs["nbView"], 2)
- cls.assertEqual(dataset_file.get("Metadata").attrs["nbClass"], 4)
+ self.assertEqual(dataset_file.get("Metadata").attrs["datasetLength"], 10)
+ self.assertEqual(dataset_file.get("Metadata").attrs["nbView"], 2)
+ self.assertEqual(dataset_file.get("Metadata").attrs["nbClass"], 4)
np.testing.assert_array_equal(dataset_file.get("View0").value,
- cls.dataset_file.get("View1").value)
+ self.dataset_file.get("View1").value)
- def test_all_views_asked(cls):
+ def test_all_views_asked(self):
views = ["test_view_0", "test_view_1", "test_view_2", "test_view_3"]
dataset_file, labels_dictionary, dataset_name = get_multiview_db.get_classic_db_hdf5(views,
- cls.pathF,
- cls.nameDB,
- cls.NB_CLASS,
- cls.askedLabelsNames,
- cls.random_state)
+ self.pathF,
+ self.nameDB,
+ self.NB_CLASS,
+ self.askedLabelsNames,
+ self.random_state)
for viewIndex in range(4):
np.testing.assert_array_equal(
dataset_file.get("View" + str(viewIndex)).value,
- cls.dataset_file.get("View" + str(viewIndex)).value[
+ self.dataset_file.get("View" + str(viewIndex)).value[
np.array([1, 5, 9]), :])
- cls.assertEqual(
+ self.assertEqual(
dataset_file.get("View" + str(viewIndex)).attrs["name"],
"test_view_" + str(viewIndex))
- cls.assertEqual(labels_dictionary,
+ self.assertEqual(labels_dictionary,
{0: "test_label_1", 1: "test_label_3"})
- cls.assertEqual(dataset_file.get("Metadata").attrs["datasetLength"], 3)
- cls.assertEqual(dataset_file.get("Metadata").attrs["nbView"], 4)
- cls.assertEqual(dataset_file.get("Metadata").attrs["nbClass"], 2)
+ self.assertEqual(dataset_file.get("Metadata").attrs["datasetLength"], 3)
+ self.assertEqual(dataset_file.get("Metadata").attrs["nbView"], 4)
+ self.assertEqual(dataset_file.get("Metadata").attrs["nbClass"], 2)
- def test_asked_the_whole_dataset(cls):
+ def test_asked_the_whole_dataset(self):
askedLabelsNames = ["test_label_0", "test_label_1", "test_label_2",
"test_label_3"]
NB_CLASS = 4
views = ["test_view_0", "test_view_1", "test_view_2", "test_view_3"]
dataset_file, labels_dictionary, dataset_name = get_multiview_db.get_classic_db_hdf5(views,
- cls.pathF,
- cls.nameDB,
+ self.pathF,
+ self.nameDB,
NB_CLASS,
askedLabelsNames,
- cls.random_state)
+ self.random_state)
for viewIndex in range(4):
np.testing.assert_array_equal(
dataset_file.get("View" + str(viewIndex)).value,
- cls.dataset_file.get("View" + str(viewIndex)))
- cls.assertEqual(
+ self.dataset_file.get("View" + str(viewIndex)))
+ self.assertEqual(
dataset_file.get("View" + str(viewIndex)).attrs["name"],
"test_view_" + str(viewIndex))
- cls.assertEqual(labels_dictionary,
+ self.assertEqual(labels_dictionary,
{0: "test_label_0", 1: "test_label_1",
2: "test_label_2", 3: "test_label_3"})
- cls.assertEqual(dataset_file.get("Metadata").attrs["datasetLength"], 10)
- cls.assertEqual(dataset_file.get("Metadata").attrs["nbView"], 4)
- cls.assertEqual(dataset_file.get("Metadata").attrs["nbClass"], 4)
+ self.assertEqual(dataset_file.get("Metadata").attrs["datasetLength"], 10)
+ self.assertEqual(dataset_file.get("Metadata").attrs["nbView"], 4)
+ self.assertEqual(dataset_file.get("Metadata").attrs["nbClass"], 4)
@classmethod
def tearDownClass(cls):
@@ -485,87 +485,87 @@ class Test_getClassicDBcsv(unittest.TestCase):
data, delimiter=",")
cls.datas.append(data)
- def test_simple(cls):
+ def test_simple(self):
dataset_file, labels_dictionary, dataset_name = get_multiview_db.get_classic_db_csv(
- cls.views, cls.pathF, cls.nameDB,
- cls.NB_CLASS, cls.askedLabelsNames,
- cls.random_state, delimiter=",")
- cls.assertEqual(dataset_file.get("Metadata").attrs["nbView"], 2)
- cls.assertEqual(dataset_file.get("View1").attrs["name"], "test_view_3")
- cls.assertEqual(dataset_file.get("View0").attrs["name"], "test_view_1")
- cls.assertEqual(labels_dictionary,
+ self.views, self.pathF, self.nameDB,
+ self.NB_CLASS, self.askedLabelsNames,
+ self.random_state, delimiter=",")
+ self.assertEqual(dataset_file.get("Metadata").attrs["nbView"], 2)
+ self.assertEqual(dataset_file.get("View1").attrs["name"], "test_view_3")
+ self.assertEqual(dataset_file.get("View0").attrs["name"], "test_view_1")
+ self.assertEqual(labels_dictionary,
{0: "test_label_1", 1: "test_label_3"})
- cls.assertEqual(dataset_file.get("Metadata").attrs["datasetLength"], 3)
- cls.assertEqual(dataset_file.get("Metadata").attrs["nbClass"], 2)
+ self.assertEqual(dataset_file.get("Metadata").attrs["datasetLength"], 3)
+ self.assertEqual(dataset_file.get("Metadata").attrs["nbClass"], 2)
np.testing.assert_array_equal(dataset_file.get("View0").value,
- cls.datas[1][np.array([1, 5, 9]), :])
+ self.datas[1][np.array([1, 5, 9]), :])
- def test_all_views_asked(cls):
+ def test_all_views_asked(self):
views = ["test_view_0", "test_view_1", "test_view_2", "test_view_3"]
dataset_file, labels_dictionary, dataset_name = get_multiview_db.get_classic_db_csv(views,
- cls.pathF,
- cls.nameDB,
- cls.NB_CLASS,
- cls.askedLabelsNames,
- cls.random_state,
+ self.pathF,
+ self.nameDB,
+ self.NB_CLASS,
+ self.askedLabelsNames,
+ self.random_state,
delimiter=",")
- cls.assertEqual(labels_dictionary,
+ self.assertEqual(labels_dictionary,
{0: "test_label_1", 1: "test_label_3"})
- cls.assertEqual(dataset_file.get("Metadata").attrs["datasetLength"], 3)
- cls.assertEqual(dataset_file.get("Metadata").attrs["nbView"], 4)
- cls.assertEqual(dataset_file.get("Metadata").attrs["nbClass"], 2)
- cls.assertEqual(dataset_name,'test_dataset_temp_view_label_select')
+ self.assertEqual(dataset_file.get("Metadata").attrs["datasetLength"], 3)
+ self.assertEqual(dataset_file.get("Metadata").attrs["nbView"], 4)
+ self.assertEqual(dataset_file.get("Metadata").attrs["nbClass"], 2)
+ self.assertEqual(dataset_name,'test_dataset_temp_view_label_select')
for viewIndex in range(4):
np.testing.assert_array_equal(
dataset_file.get("View" + str(viewIndex)).value,
- cls.datas[viewIndex][np.array([1, 5, 9]), :])
- cls.assertEqual(
+ self.datas[viewIndex][np.array([1, 5, 9]), :])
+ self.assertEqual(
dataset_file.get("View" + str(viewIndex)).attrs["name"],
"test_view_" + str(viewIndex))
- def test_all_labels_asked(cls):
+ def test_all_labels_asked(self):
askedLabelsNames = ["test_label_0", "test_label_1", "test_label_2",
"test_label_3"]
NB_CLASS = 4
dataset_file, labels_dictionary, dataset_name = get_multiview_db.get_classic_db_csv(
- cls.views, cls.pathF, cls.nameDB,
+ self.views, self.pathF, self.nameDB,
NB_CLASS, askedLabelsNames,
- cls.random_state, delimiter=",")
- cls.assertEqual(dataset_file.get("View1").attrs["name"], "test_view_3")
- cls.assertEqual(labels_dictionary,
+ self.random_state, delimiter=",")
+ self.assertEqual(dataset_file.get("View1").attrs["name"], "test_view_3")
+ self.assertEqual(labels_dictionary,
{0: "test_label_0", 1: "test_label_1",
2: "test_label_2", 3: "test_label_3"})
- cls.assertEqual(dataset_file.get("Metadata").attrs["datasetLength"], 10)
- cls.assertEqual(dataset_file.get("Metadata").attrs["nbView"], 2)
- cls.assertEqual(dataset_file.get("Metadata").attrs["nbClass"], 4)
+ self.assertEqual(dataset_file.get("Metadata").attrs["datasetLength"], 10)
+ self.assertEqual(dataset_file.get("Metadata").attrs["nbView"], 2)
+ self.assertEqual(dataset_file.get("Metadata").attrs["nbClass"], 4)
np.testing.assert_array_equal(dataset_file.get("View0").value,
- cls.datas[1])
+ self.datas[1])
- def test_asked_the_whole_dataset(cls):
+ def test_asked_the_whole_dataset(self):
askedLabelsNames = ["test_label_0", "test_label_1", "test_label_2",
"test_label_3"]
NB_CLASS = 4
views = ["test_view_0", "test_view_1", "test_view_2", "test_view_3"]
dataset_file, labels_dictionary, dataset_name = get_multiview_db.get_classic_db_csv(views,
- cls.pathF,
- cls.nameDB,
+ self.pathF,
+ self.nameDB,
NB_CLASS,
askedLabelsNames,
- cls.random_state,
+ self.random_state,
delimiter=",")
for viewIndex in range(4):
np.testing.assert_array_equal(
dataset_file.get("View" + str(viewIndex)).value,
- cls.datas[viewIndex])
- cls.assertEqual(
+ self.datas[viewIndex])
+ self.assertEqual(
dataset_file.get("View" + str(viewIndex)).attrs["name"],
"test_view_" + str(viewIndex))
- cls.assertEqual(labels_dictionary,
+ self.assertEqual(labels_dictionary,
{0: "test_label_0", 1: "test_label_1",
2: "test_label_2", 3: "test_label_3"})
- cls.assertEqual(dataset_file.get("Metadata").attrs["datasetLength"], 10)
- cls.assertEqual(dataset_file.get("Metadata").attrs["nbView"], 4)
- cls.assertEqual(dataset_file.get("Metadata").attrs["nbClass"], 4)
+ self.assertEqual(dataset_file.get("Metadata").attrs["datasetLength"], 10)
+ self.assertEqual(dataset_file.get("Metadata").attrs["nbView"], 4)
+ self.assertEqual(dataset_file.get("Metadata").attrs["nbClass"], 4)
@classmethod
def tearDownClass(cls):
@@ -617,3 +617,5 @@ class Test_get_plausible_db_hdf5(unittest.TestCase):
self.assertEqual(dataset.get_nb_class(), 2)
+if __name__ == '__main__':
+ unittest.main()
\ No newline at end of file
diff --git a/multiview_platform/tests/test_utils/test_configuration.py b/multiview_platform/tests/test_utils/test_configuration.py
index 53f1c6605c268bceb065f5ae3b1e2306e762eade..9285155c817ee91b1e62a694d516b87c99792e27 100644
--- a/multiview_platform/tests/test_utils/test_configuration.py
+++ b/multiview_platform/tests/test_utils/test_configuration.py
@@ -13,7 +13,7 @@ class Test_get_the_args(unittest.TestCase):
def setUpClass(cls):
rm_tmp()
cls.path_to_config_file = tmp_path+"config_temp.yml"
- os.mkdir("multiview_platform/tests/tmp_tests")
+ os.mkdir("./multiview_platform/tests/tmp_tests")
data = {"Base":{"first_arg": 10, "second_arg":[12.5, 1e-06]}, "Classification":{"third_arg":True}}
with open(cls.path_to_config_file, "w") as config_file:
yaml.dump(data, config_file)
@@ -74,3 +74,5 @@ class Test_get_the_args(unittest.TestCase):
# value = configuration.format_raw_arg("list_str ; list string")
# self.assertEqual(value, ["list", "string"])
+if __name__ == '__main__':
+ unittest.main()
\ No newline at end of file
diff --git a/multiview_platform/tests/test_utils/test_dataset.py b/multiview_platform/tests/test_utils/test_dataset.py
index 9b8c002367d69bbb402fe65f00d825c329895f66..23ced56abe8a8102a0d6f4545b7536f1a49a8e6e 100644
--- a/multiview_platform/tests/test_utils/test_dataset.py
+++ b/multiview_platform/tests/test_utils/test_dataset.py
@@ -94,4 +94,7 @@ class Test_Dataset(unittest.TestCase):
labels_names=self.labels_names)
self.assertEqual(dataset_object.get_view_dict(), {"ViewN0":0,
"ViewN1": 1,
- "ViewN2": 2,})
\ No newline at end of file
+ "ViewN2": 2,})
+
+if __name__ == '__main__':
+ unittest.main()
\ No newline at end of file
diff --git a/multiview_platform/tests/test_utils/test_execution.py b/multiview_platform/tests/test_utils/test_execution.py
index e251dd052b23287fd8578c90da75c7140691dfd3..8848dc56907ee1a2bce106c9589b9c775e13ffbc 100644
--- a/multiview_platform/tests/test_utils/test_execution.py
+++ b/multiview_platform/tests/test_utils/test_execution.py
@@ -225,3 +225,6 @@ class Test_genArgumentDictionaries(unittest.TestCase):
np.array([0, 1, -100, 0, 1])]
cls.labelsCombinations = [[0, 1], [0, 2], [1, 2]]
cls.indicesMulticlass = [[[[], []], [[], []], [[], []]], [[], [], []]]
+
+if __name__ == '__main__':
+ unittest.main()
\ No newline at end of file
diff --git a/multiview_platform/tests/test_utils/test_hyper_parameter_search.py b/multiview_platform/tests/test_utils/test_hyper_parameter_search.py
index 17e5290108adbd1e64fb0db9ab180d0f87efd990..2fafecce33551ba555bfe01f97d11988f2198e43 100644
--- a/multiview_platform/tests/test_utils/test_hyper_parameter_search.py
+++ b/multiview_platform/tests/test_utils/test_hyper_parameter_search.py
@@ -56,3 +56,9 @@ class Test_randomized_search(unittest.TestCase):
self.dataset_file, self.labels.value, "multiview", self.random_state, tmp_path,
weighted_linear_early_fusion, "WeightedLinearEarlyFusion", self.k_folds,
1, ["accuracy_score", None], 2, {}, learning_indices=self.learning_indices)
+
+
+if __name__ == '__main__':
+ # unittest.main()
+ suite = unittest.TestLoader().loadTestsFromTestCase(Test_randomized_search)
+ unittest.TextTestRunner(verbosity=2).run(suite)
\ No newline at end of file
diff --git a/multiview_platform/tests/test_utils/test_multiclass.py b/multiview_platform/tests/test_utils/test_multiclass.py
index dcb764267646f224c20ac14468a046d101d07219..52cac2a3c257d4e30903fe7e2ab313abe766cd57 100644
--- a/multiview_platform/tests/test_utils/test_multiclass.py
+++ b/multiview_platform/tests/test_utils/test_multiclass.py
@@ -43,3 +43,6 @@ class Test_genMulticlassLabels(unittest.TestCase):
-100,
1, -100, 0, 0, 1, 0, -100, 0,
-100]))
+
+if __name__ == '__main__':
+ unittest.main()
\ No newline at end of file