Merge pull request #249 from jGaboardi/GH245_pytest

convert from `unittest` to `pytest` and `ruff`en tests

Author: weikang9009

giddy/tests/test_directional.py

@@ -1,14 +1,14 @@
-import unittest
 import libpysal as ps
-from .. import directional
 import numpy as np
+import pytest
+
+from .. import directional
 
 
-class Rose_Tester(unittest.TestCase):
-    def setUp(self):
-        f = open(ps.examples.get_path("spi_download.csv"), "r")
-        lines = f.readlines()
-        f.close()
+class TestRose:
+    def setup_method(self):
+        with open(ps.examples.get_path("spi_download.csv")) as f:
+            lines = f.readlines()
         lines = [line.strip().split(",") for line in lines]
         names = [line[2] for line in lines[1:-5]]
         data = np.array([list(map(int, line[3:])) for line in lines[1:-5]])
@@ -43,8 +43,8 @@ def test_rose(self):
         exp = [0.0, 1.57079633, 3.14159265, 4.71238898, 6.28318531]
         obs = list(r4.cuts)
         for i in range(k + 1):
-            self.assertAlmostEqual(exp[i], obs[i])
-        self.assertEqual(list(r4.counts), [32, 5, 9, 2])
+            assert pytest.approx(exp[i]) == obs[i]
+        assert list(r4.counts) == [32, 5, 9, 2]
 
         import matplotlib.pyplot as plt
 
@@ -61,14 +61,3 @@ def test_rose(self):
         # customize plot
         fig, _ = r4.plot_vectors(arrows=False)
         plt.close(fig)
-
-
-suite = unittest.TestSuite()
-test_classes = [Rose_Tester]
-for i in test_classes:
-    a = unittest.TestLoader().loadTestsFromTestCase(i)
-    suite.addTest(a)
-
-if __name__ == "__main__":
-    runner = unittest.TextTestRunner()
-    runner.run(suite)

giddy/tests/test_ergodic.py

@@ -1,11 +1,11 @@
+import numpy as np
 import pytest
-import unittest
+
 from .. import ergodic
-import numpy as np
 
 
-class SteadyState_Tester(unittest.TestCase):
-    def setUp(self):
+class TestSteadyState:
+    def setup_method(self):
         self.p = np.array([[0.5, 0.25, 0.25], [0.5, 0, 0.5], [0.25, 0.25, 0.5]])
         self.p2 = np.array([[0.5, 0.5, 0], [0.3, 0.7, 0], [0, 0, 1]])
         self.p3 = np.array([[0.5, 0.5, 0], [0.3, 0.7, 0], [0, 0, 0]])
@@ -28,11 +28,12 @@ def test_steady_state(self):
         exp = np.array([[0.375, 0.625, 0.0], [0.0, 0.0, 1.0]])
         np.testing.assert_array_almost_equal(exp, obs)
 
-        self.assertRaises(ValueError, ergodic.steady_state, self.p3, False)
+        with pytest.raises(ValueError, match="Input transition probability matrix"):
+            ergodic.steady_state(self.p3)
 
 
-class Mfpt_Tester(unittest.TestCase):
-    def setUp(self):
+class TestMfpt:
+    def setup_method(self):
         self.p = np.array([[0.5, 0.25, 0.25], [0.5, 0, 0.5], [0.25, 0.25, 0.5]])
         self.p2 = np.array([[0.5, 0.5, 0], [0.3, 0.7, 0], [0, 0, 1]])
         self.p3 = np.array([[0.5, 0.5, 0], [0.3, 0.7, 0], [0, 0, 0]])
@@ -81,8 +82,8 @@ def test_mfpt(self):
         np.testing.assert_array_almost_equal(exp, obs)
 
 
-class VarMfpt_Tester(unittest.TestCase):
-    def setUp(self):
+class TestVarMfpt:
+    def setup_method(self):
         self.p = np.array([[0.5, 0.25, 0.25], [0.5, 0, 0.5], [0.25, 0.25, 0.5]])
 
     def test_var_mfpt(self):
@@ -95,14 +96,3 @@ def test_var_mfpt(self):
             ]
         )
         np.testing.assert_array_almost_equal(exp, obs)
-
-
-suite = unittest.TestSuite()
-test_classes = [SteadyState_Tester, Mfpt_Tester, VarMfpt_Tester]
-for i in test_classes:
-    a = unittest.TestLoader().loadTestsFromTestCase(i)
-    suite.addTest(a)
-
-if __name__ == "__main__":
-    runner = unittest.TextTestRunner()
-    runner.run(suite)

giddy/tests/test_markov.py

@@ -1,22 +1,22 @@
-import unittest
 import libpysal as ps
-import numpy as np
 import mapclassify as mc
+import numpy as np
+
 from ..markov import (
+    FullRank_Markov,
+    GeoRank_Markov,
+    LISA_Markov,
     Markov,
+    Spatial_Markov,
     kullback,
     prais,
-    Spatial_Markov,
-    LISA_Markov,
-    FullRank_Markov,
     sojourn_time,
-    GeoRank_Markov,
 )
 
 RTOL = 0.00001
 
 
-class test_Markov(unittest.TestCase):
+class TestMarkov:
     def test___init__(self):
         # markov = Markov(class_ids, classes)
         f = ps.io.open(ps.examples.get_path("usjoin.csv"))
@@ -106,8 +106,8 @@ def test___init__(self):
         np.testing.assert_array_almost_equal(m.sojourn_time, expected)
 
 
-class test_Spatial_Markov(unittest.TestCase):
-    def setUp(self):
+class TestSpatialMarkov:
+    def setup_method(self):
         f = ps.io.open(ps.examples.get_path("usjoin.csv"))
         pci = np.array([f.by_col[str(y)] for y in range(1929, 2010)])
         pci = pci.transpose()
@@ -273,7 +273,7 @@ def test_discretized(self):
         np.testing.assert_array_equal(sm.T, answer)
 
 
-class test_chi2(unittest.TestCase):
+class TestChi2:
     def test_chi2(self):
         f = ps.io.open(ps.examples.get_path("usjoin.csv"))
         pci = np.array([f.by_col[str(y)] for y in range(1929, 2010)])
@@ -305,7 +305,7 @@ def test_chi2(self):
         np.testing.assert_array_almost_equal(obs, np.array(sm.shtest))
 
 
-class test_LISA_Markov(unittest.TestCase):
+class TestLISAMarkov:
     def test___init__(self):
         f = ps.io.open(ps.examples.get_path("usjoin.csv"))
         pci = np.array([f.by_col[str(y)] for y in range(1929, 2010)]).transpose()
@@ -348,7 +348,7 @@ def test___init__(self):
         np.testing.assert_allclose(lm_random.chi_2, c, RTOL)
 
 
-class test_kullback(unittest.TestCase):
+class TestKullback:
     def test___init__(self):
         s1 = np.array(
             [
@@ -382,7 +382,7 @@ def test___init__(self):
         np.testing.assert_array_almost_equal(0.0, p_value)
 
 
-class test_prais(unittest.TestCase):
+class TestPrais:
     def test___init__(self):
         f = ps.io.open(ps.examples.get_path("usjoin.csv"))
         pci = np.array([f.by_col[str(y)] for y in range(1929, 2010)])
@@ -392,7 +392,7 @@ def test___init__(self):
         np.testing.assert_array_almost_equal(prais(m.p), res)
 
 
-class FullRank_Markov_Tester(unittest.TestCase):
+class TestFullRankMarkov:
     def test___init__(self):
         f = ps.io.open(ps.examples.get_path("usjoin.csv"))
         pci = np.array([f.by_col[str(y)] for y in range(1929, 2010)]).transpose()
@@ -664,7 +664,7 @@ def test___init__(self):
         np.testing.assert_array_almost_equal(m.sojourn_time, expected)
 
 
-class GeoRank_Markov_Tester(unittest.TestCase):
+class TestGeoRankMarkov:
     def test___init__(self):
         f = ps.io.open(ps.examples.get_path("usjoin.csv"))
         pci = np.array([f.by_col[str(y)] for y in range(1929, 2010)]).transpose()
@@ -707,8 +707,8 @@ def test___init__(self):
         np.testing.assert_array_almost_equal(gm.sojourn_time[:10], expected)
 
 
-class Sojourn_time_Tester(unittest.TestCase):
-    def setUp(self):
+class TestSojournTime:
+    def setup_method(self):
         self.p = np.array([[0.5, 0.25, 0.25], [0.5, 0, 0.5], [0.25, 0.25, 0.5]])
         self.p2 = np.array([[0.5, 0.5, 0], [0.3, 0.7, 0], [0, 0, 1]])
 
@@ -719,7 +719,3 @@ def test_sojourn_time(self):
 
         exp = np.array([2.0, 3.33333333, np.inf])
         np.testing.assert_array_almost_equal(exp, sojourn_time(self.p2))
-
-
-if __name__ == "__main__":
-    unittest.main()

giddy/tests/test_mobility.py

@@ -1,15 +1,13 @@
-import unittest
 import libpysal as ps
-import numpy as np
 import mapclassify as mc
+import numpy as np
+
 from ..markov import Markov
 from ..mobility import markov_mobility
 
 
-class Shorrock_Tester(unittest.TestCase):
+class TestShorrock:
     def test___init__(self):
-        import numpy as np
-
         f = ps.io.open(ps.examples.get_path("usjoin.csv"))
         pci = np.array([f.by_col[str(y)] for y in range(1929, 2010)])
         q5 = np.array([mc.Quantiles(y).yb for y in pci]).transpose()
@@ -19,7 +17,7 @@ def test___init__(self):
         )
 
 
-class MarkovMobility_Tester(unittest.TestCase):
+class TestMarkovMobility:
     def test___init__(self):
         pi = np.array([0.1, 0.2, 0.2, 0.4, 0.1])
         f = ps.io.open(ps.examples.get_path("usjoin.csv"))
@@ -41,7 +39,3 @@ def test___init__(self):
         np.testing.assert_array_almost_equal(
             markov_mobility(m.p, measure="B2", ini=pi), 0.046366601194789261
         )
-
-
-if __name__ == "__main__":
-    unittest.main()

giddy/tests/test_rank.py

@@ -1,44 +1,45 @@
-import unittest
 import libpysal as ps
-from .. import rank
 import numpy as np
+import pytest
+
+from .. import rank
 
 
-class Theta_Tester(unittest.TestCase):
-    def setUp(self):
+class TestTheta:
+    def setup_method(self):
         f = ps.io.open(ps.examples.get_path("mexico.csv"))
-        vnames = ["pcgdp%d" % dec for dec in range(1940, 2010, 10)]
+        vnames = [f"pcgdp{dec}" for dec in range(1940, 2010, 10)]
         self.y = np.transpose(np.array([f.by_col[v] for v in vnames]))
         self.regime = np.array(f.by_col["esquivel99"])
 
-    def test_Theta(self):
+    def test_defaults(self):
         np.random.seed(10)
         t = rank.Theta(self.y, self.regime, 999)
         k = self.y.shape[1]
         obs = t.theta.tolist()
         exp = [[0.41538462, 0.28070175, 0.61363636, 0.62222222, 0.33333333, 0.47222222]]
         for i in range(k - 1):
-            self.assertAlmostEqual(exp[0][i], obs[0][i])
+            assert pytest.approx(exp[0][i]) == obs[0][i]
         obs = t.pvalue_left.tolist()
         exp = [0.307, 0.077, 0.823, 0.552, 0.045, 0.735]
         for i in range(k - 1):
-            self.assertAlmostEqual(exp[i], obs[i])
+            assert pytest.approx(exp[i]) == obs[i]
         obs = t.total.tolist()
         exp = [130.0, 114.0, 88.0, 90.0, 90.0, 72.0]
         for i in range(k - 1):
-            self.assertAlmostEqual(exp[i], obs[i])
-        self.assertEqual(t.max_total, 512)
+            assert pytest.approx(exp[i]) == obs[i]
+        assert t.max_total == 512
 
 
-class SpatialTau_Tester(unittest.TestCase):
-    def setUp(self):
+class TestSpatialTau:
+    def setup_method(self):
         f = ps.io.open(ps.examples.get_path("mexico.csv"))
-        vnames = ["pcgdp%d" % dec for dec in range(1940, 2010, 10)]
+        vnames = [f"pcgdp{dec}" for dec in range(1940, 2010, 10)]
         self.y = np.transpose(np.array([f.by_col[v] for v in vnames]))
         regime = np.array(f.by_col["esquivel99"])
         self.w = ps.weights.block_weights(regime)
 
-    def test_SpatialTau(self):
+    def test_defaults(self):
         np.random.seed(12345)
         k = self.y.shape[1]
         obs = [
@@ -49,35 +50,24 @@ def test_SpatialTau(self):
         ev_tau_s = [0.659, 0.706, 0.772, 0.752, 0.705, 0.819]
         p_vals = [0.010, 0.010, 0.020, 0.210, 0.270, 0.280]
         for i in range(k - 1):
-            self.assertAlmostEqual(tau_s[i], obs[i].tau_spatial, 3)
-            self.assertAlmostEqual(ev_tau_s[i], obs[i].taus.mean(), 3)
-            self.assertAlmostEqual(p_vals[i], obs[i].tau_spatial_psim, 3)
+            assert pytest.approx(tau_s[i], 3) == obs[i].tau_spatial
+            assert pytest.approx(ev_tau_s[i], 3) == obs[i].taus.mean()
+            assert pytest.approx(p_vals[i], 3) == obs[i].tau_spatial_psim
         st12 = rank.SpatialTau(self.y[:, 1], self.y[:, 2], self.w)
         st21 = rank.SpatialTau(self.y[:, 2], self.y[:, 1], self.w)
-        self.assertEqual(st12.tau_spatial, st21.tau_spatial)
+        assert pytest.approx(st12.tau_spatial) == st21.tau_spatial
 
 
-class Tau_Tester(unittest.TestCase):
-    def test_Tau(self):
+class TestTau:
+    def test_defaults(self):
         x1 = [12, 2, 1, 12, 2]
         x2 = [1, 4, 7, 1, 0]
         kt = rank.Tau(x1, x2)
-        self.assertAlmostEqual(kt.tau, -0.47140452079103173, 5)
-        self.assertAlmostEqual(kt.tau_p, 0.24821309157521476, 5)
+        assert pytest.approx(kt.tau, 5) == -0.47140452079103173
+        assert pytest.approx(kt.tau_p, 5) == 0.24821309157521476
         x1 = [0, 0, 0, 1, 0, 0, 0, 1, 0, 0, 0, 1, 0, 0, 0, 1]
         x2 = [1, 4, 7, 1, 1, 3, 1, 6, 7, 7, 3, 6, 2, 7, 2, 8]
         kt12 = rank.Tau(x1, x2)
         kt21 = rank.Tau(x2, x1)
-        self.assertEqual(kt12.tau, kt21.tau)
-        self.assertAlmostEqual(kt12.tau, 0.15494494670022804)
-
-
-suite = unittest.TestSuite()
-test_classes = [Theta_Tester, SpatialTau_Tester, Tau_Tester]
-for i in test_classes:
-    a = unittest.TestLoader().loadTestsFromTestCase(i)
-    suite.addTest(a)
-
-if __name__ == "__main__":
-    runner = unittest.TextTestRunner()
-    runner.run(suite)
+        assert kt12.tau == kt21.tau
+        assert pytest.approx(kt12.tau) == 0.15494494670022804