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Commit f29599ab authored by Valentin Emiya's avatar Valentin Emiya
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update tests

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Pipeline #14338 passed
Stage: test
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ltfatpy/tests/comp/test_assert_sigreshape_post.py
+ 11
− 12
View file @ f29599ab
......@@ -65,8 +65,7 @@ import unittest
import random
import numpy as np
from ltfatpy.comp.assert_sigreshape_pre import assert_sigreshape_pre as aspre
from ltfatpy.comp.assert_sigreshape_post import assert_sigreshape_post\
as aspost
from ltfatpy.comp.assert_sigreshape_post import assert_sigreshape_post as aspost
import functools
......@@ -74,16 +73,16 @@ class TestAssertSigReshapePost(unittest.TestCase):
# Called before the tests.
def setUp(self):
print('Start TestAssertSigReshapePost')
print("Start TestAssertSigReshapePost")
# Called after the tests.
def tearDown(self):
print('Test done')
print("Test done")
def test_default(self):
""" Basic usual cases """
"""Basic usual cases"""
L = random.randint(5, 200)
f = np.arange(0, L, dtype=np.float_)
f = np.arange(0, L, dtype=np.float64)
(g, L, Ls, W, dim, permutedshape, order) = aspre(f)
fres = aspost(f, dim, permutedshape, order)
mess = "\nL = {0:d}, Ls = {1:d}, W = {2:d}, dim = {3:d}, g.shape = "
......@@ -93,10 +92,10 @@ class TestAssertSigReshapePost(unittest.TestCase):
np.testing.assert_array_equal(f, fres, mess)
def test_twodim(self):
""" Many channels signals """
"""Many channels signals"""
shapef = tuple([random.randint(5, 20) for _ in range(2)])
L = functools.reduce(lambda x, y: x*y, shapef)
f = np.arange(0, L, dtype=np.complex_)
L = functools.reduce(lambda x, y: x * y, shapef)
f = np.arange(0, L, dtype=np.complex128)
f = f.reshape(shapef)
(g, L, Ls, W, dim, permutedshape, order) = aspre(f)
fres = aspost(f, dim, permutedshape, order)
......@@ -106,7 +105,7 @@ class TestAssertSigReshapePost(unittest.TestCase):
mess = mess.format(L, Ls, W, dim)
np.testing.assert_array_equal(f, fres, mess)
if __name__ == '__main__':
suite = unittest.TestLoader().loadTestsFromTestCase(
TestAssertSigReshapePost)
if __name__ == "__main__":
suite = unittest.TestLoader().loadTestsFromTestCase(TestAssertSigReshapePost)
unittest.TextTestRunner(verbosity=2).run(suite)
ltfatpy/tests/comp/test_assert_sigreshape_pre.py
+ 12
− 13
View file @ f29599ab
......@@ -72,16 +72,16 @@ class TestAssertSigReshapePre(unittest.TestCase):
# Called before the tests.
def setUp(self):
print('Start TestAssertSigReshapePre')
print("Start TestAssertSigReshapePre")
# Called after the tests.
def tearDown(self):
print('Test done')
print("Test done")
def test_default(self):
""" Basic usual cases """
"""Basic usual cases"""
L = random.randint(5, 200)
f = np.arange(0, L, dtype=np.float_)
f = np.arange(0, L, dtype=np.float64)
(g, L, Ls, W, dim, _permutedshape, _order) = asp(f)
mess = "\nL = {0:d}, Ls = {1:d}, W = {2:d}, dim = {3:d}, g.shape = "
mess += str(g.shape) + ", f.shape = " + str(f.shape)
......@@ -102,7 +102,7 @@ class TestAssertSigReshapePre(unittest.TestCase):
self.assertEqual(dim, 0, mess)
def test_list(self):
""" Basic signal in a list """
"""Basic signal in a list"""
L = random.randint(5, 200)
f = [x for x in range(0, L)]
(g, L, Ls, W, dim, _permutedshape, _order) = asp(f)
......@@ -113,16 +113,16 @@ class TestAssertSigReshapePre(unittest.TestCase):
self.assertEqual(L, L, mess)
self.assertEqual(W, 1, mess)
self.assertEqual(dim, 0, mess)
self.assertRaises(TypeError, asp, {'a': 1})
self.assertRaises(TypeError, asp, {"a": 1})
self.assertRaises(TypeError, asp, f, L, (1, 0))
self.assertRaises(TypeError, asp, f, L, -4)
self.assertRaises(TypeError, asp, f, 5.5)
def test_twodim(self):
""" Many channels signals """
"""Many channels signals"""
shapef = tuple([random.randint(5, 20) for _ in range(2)])
L = functools.reduce(lambda x, y: x*y, shapef)
f = np.arange(0, L, dtype=np.complex_)
L = functools.reduce(lambda x, y: x * y, shapef)
f = np.arange(0, L, dtype=np.complex128)
f = f.reshape(shapef)
(g, L, Ls, W, dim, _permutedshape, _order) = asp(f)
mess = "\nL = {0:d}, Ls = {1:d}, W = {2:d}, dim = {3:d}, g.shape = "
......@@ -133,7 +133,7 @@ class TestAssertSigReshapePre(unittest.TestCase):
self.assertEqual(W, shapef[1], mess)
self.assertEqual(dim, 0, mess)
L = random.randint(5, 200)
f = np.arange(0, L, dtype=np.float_)
f = np.arange(0, L, dtype=np.float64)
fcol = f.reshape((1, L))
(g, L, Ls, W, dim, _permutedshape, _order) = asp(fcol)
mess = "\nL = {0:d}, Ls = {1:d}, W = {2:d}, dim = {3:d}, g.shape = "
......@@ -145,7 +145,6 @@ class TestAssertSigReshapePre(unittest.TestCase):
self.assertEqual(dim, 1, mess)
if __name__ == '__main__':
suite = unittest.TestLoader().loadTestsFromTestCase(
TestAssertSigReshapePre)
if __name__ == "__main__":
suite = unittest.TestLoader().loadTestsFromTestCase(TestAssertSigReshapePre)
unittest.TextTestRunner(verbosity=2).run(suite)
ltfatpy/tests/comp/test_comp_sigreshape.py
+ 12
− 11
View file @ f29599ab
......@@ -73,11 +73,11 @@ class TestCompSigReshape(unittest.TestCase):
# Called before the tests.
def setUp(self):
print('Start TestCompSigReshape')
print("Start TestCompSigReshape")
# Called after the tests.
def tearDown(self):
print('Test done')
print("Test done")
def test_default(self):
self.assertRaises(ValueError, cpre, "toto", 10)
......@@ -85,9 +85,9 @@ class TestCompSigReshape(unittest.TestCase):
self.assertRaises(ValueError, cpre, np.ones((10, 10, 2)), 1)
def test_onedim(self):
""" One channel """
"""One channel"""
L = random.randint(5, 200)
f = np.arange(0, L, dtype=np.float_)
f = np.arange(0, L, dtype=np.float64)
(fin, fl, W, wasrow, remembershape) = cpre(f, 0)
fres = cpost(fin, fl, wasrow, remembershape)
mess = "\nfl = {:d}, W = {:d}, wasrow = {:d},remembershape.shape = "
......@@ -96,7 +96,7 @@ class TestCompSigReshape(unittest.TestCase):
mess = mess.format(fl, W, wasrow)
np.testing.assert_array_equal(f, fres, mess)
L = random.randint(5, 200)
f = np.arange(0, L, dtype=np.float_)
f = np.arange(0, L, dtype=np.float64)
f.resize((1, L))
(fin, fl, W, wasrow, remembershape) = cpre(f, 0)
fres = cpost(fin, fl, wasrow, remembershape)
......@@ -107,10 +107,10 @@ class TestCompSigReshape(unittest.TestCase):
np.testing.assert_array_equal(f, fres, mess)
def test_twodim(self):
""" Many channels signals """
"""Many channels signals"""
shapef = tuple([random.randint(5, 20) for _ in range(2)])
L = functools.reduce(lambda x, y: x*y, shapef)
f = np.arange(0, L, dtype=np.complex_)
L = functools.reduce(lambda x, y: x * y, shapef)
f = np.arange(0, L, dtype=np.complex128)
f = f.reshape(shapef)
(fin, fl, W, wasrow, remembershape) = cpre(f, 1)
fres = cpost(fin, fl, wasrow, remembershape)
......@@ -121,10 +121,10 @@ class TestCompSigReshape(unittest.TestCase):
np.testing.assert_array_equal(f, fres, mess)
def test_multidim(self):
""" Multidimensionnal signals """
"""Multidimensionnal signals"""
shapef = tuple([random.randint(5, 20) for _ in range(4)])
L = np.prod(shapef)
f = np.arange(0, L, dtype=np.complex_)
f = np.arange(0, L, dtype=np.complex128)
f = f.reshape(shapef)
(fin, fl, W, wasrow, remembershape) = cpre(f, 5)
fres = cpost(fin, fl, wasrow, remembershape)
......@@ -134,6 +134,7 @@ class TestCompSigReshape(unittest.TestCase):
mess = mess.format(fl, W, wasrow)
np.testing.assert_array_equal(f, fres, mess)
if __name__ == '__main__':
if __name__ == "__main__":
suite = unittest.TestLoader().loadTestsFromTestCase(TestCompSigReshape)
unittest.TextTestRunner(verbosity=2).run(suite)
ltfatpy/tests/datasets/read_ref_mat.py
+ 10
− 7
View file @ f29599ab
......@@ -115,13 +115,13 @@ def _adapt_type(val):
"""
res = val
if isinstance(val, np.ndarray):
if np.issubdtype(val.dtype, np.unicode_):
if np.issubdtype(val.dtype, np.str_):
# convert the unicode numpy arrays to standard unicode strings
res = val.tolist()
# convert boolean values
if val == u'_bool_True_':
if val == "_bool_True_":
res = True
elif val == u'_bool_False_':
elif val == "_bool_False_":
res = False
elif val.size == 1:
# convert the single value in the array to the corresponding
......@@ -199,15 +199,18 @@ def read_ref_mat(filename, squeeze_arrays=True, adapt_types=True):
having an integer value, it is converted to int.
"""
data = scipy.io.loadmat(filename, chars_as_strings=True)['data']
data = scipy.io.loadmat(filename, chars_as_strings=True)["data"]
res = list()
for item in data[0, :]:
if item[0, 0].size > 0:
# the tolist in the following is used to convert the unicode array
# to standard unicode string
inputs = dict(((key[0].tolist(), val)
for key, val in zip(item[0, 0][0, :],
item[0, 1][0, :])))
inputs = dict(
(
(key[0].tolist(), val)
for key, val in zip(item[0, 0][0, :], item[0, 1][0, :])
)
)
else:
inputs = dict()
......
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