formats, lints, pytest pt. 2 -- test_adbscan.py

esda/tests/test_adbscan.py

@@ -1,14 +1,13 @@
-import unittest
-
 import numpy as np
 import pandas
-import sklearn
 import pytest
+import sklearn
+
 from .. import adbscan
 
 
-class ADBSCAN_Tester(unittest.TestCase):
- def setUp(self):
+class TestADBSCAN:
+ def setup_method(self):
  np.random.seed(10)
  self.db = pandas.DataFrame(
  {"x": np.random.random(25), "y": np.random.random(25)}
@@ -82,14 +81,14 @@ def test_adbscan(self):
  ads = adbscan.ADBSCAN(0.03, 3, reps=10, keep_solus=True)
  _ = ads.fit(self.db, xy=["x", "y"])
  # Params
- self.assertAlmostEqual(ads.eps, 0.03)
- self.assertEqual(ads.min_samples, 3)
- self.assertEqual(ads.algorithm, "auto")
- self.assertEqual(ads.n_jobs, 1)
- self.assertEqual(ads.pct_exact, 0.1)
- self.assertEqual(ads.reps, 10)
- self.assertEqual(ads.keep_solus, True)
- self.assertEqual(ads.pct_thr, 0.9)
+ assert pytest.approx(ads.eps) == 0.03
+ assert ads.min_samples == 3
+ assert ads.algorithm == "auto"
+ assert ads.n_jobs == 1
+ assert ads.pct_exact == 0.1
+ assert ads.reps == 10
+ assert ads.keep_solus is True
+ assert ads.pct_thr == 0.9
  # Labels
  np.testing.assert_equal(ads.labels_, self.lbls)
  # Votes
@@ -109,9 +108,16 @@ def test_adbscan(self):
  # ------------------------#
  np.random.seed(10)
  ads = adbscan.ADBSCAN(0.03, 3, reps=10, keep_solus=True, n_jobs=-1)
- _ = ads.fit(self.db, xy=["x", "y"])
+ with pytest.warns(
+ UserWarning,
+ match=(
+ "Multi-core implementation only works on relabelling solutions. "
+ "Execution of draws is still sequential."
+ ),
+ ):
+ _ = ads.fit(self.db, xy=["x", "y"])
  # Params
- self.assertEqual(ads.n_jobs, -1)
+ assert ads.n_jobs == -1
  # Labels
  np.testing.assert_equal(ads.labels_, self.lbls)
  # Votes
@@ -128,8 +134,8 @@ def test_adbscan(self):
  np.testing.assert_equal(ads.solus.astype(int).sum(axis=1).values, i_sum)
 
 
-class Remap_lbls_Tester(unittest.TestCase):
- def setUp(self):
+class TestRemapLBLS:
+ def setup_method(self):
  self.db = pandas.DataFrame({"X": [0, 0.1, 4, 6, 5], "Y": [0, 0.2, 5, 7, 5]})
  self.solus = pandas.DataFrame(
  {
@@ -159,8 +165,8 @@ def test_remap_lbls(self):
  np.testing.assert_equal(lbls.values, vals)
 
 
-class Ensemble_Tester(unittest.TestCase):
- def setUp(self):
+class TestEnsemble:
+ def setup_method(self):
  self.db = pandas.DataFrame(
  {"X": [0, 0.1, 4, 6, 5], "Y": [0, 0.2, 5, 7, 5]}
  ).rename(lambda i: "i_" + str(i))
@@ -192,8 +198,8 @@ def test_ensemble(self):
  np.testing.assert_almost_equal(ensemble_solu.values, vals)
 
 
-class Get_Cluster_Boundary_Tester(unittest.TestCase):
- def setUp(self):
+class TestGetClusterBoundary:
+ def setup_method(self):
  np.random.seed(10)
  self.db = pandas.DataFrame(
  {"x": np.random.random(25), "y": np.random.random(25)}
@@ -275,7 +281,7 @@ def test_get_cluster_boundary(self):
  "0.5475861559192435, 0.5425443680112613 0.7546476915298572, "
  "0.7217553174317995 0.8192869956700687))"
  )
- self.assertEqual(polys[0].wkt, wkt)
+ assert polys.iloc[0].wkt == wkt
 
  # ------------------------#
  # # Multi Core #
@@ -290,15 +296,4 @@ def test_get_cluster_boundary(self):
  "0.5475861559192435, 0.5425443680112613 0.7546476915298572, "
  "0.7217553174317995 0.8192869956700687))"
  )
- self.assertEqual(polys[0].wkt, wkt)
-
-
-suite = unittest.TestSuite()
-test_classes = [ADBSCAN_Tester, Remap_lbls_Tester, Ensemble_Tester]
-for i in test_classes:
- a = unittest.TestLoader().loadTestsFromTestCase(i)
- suite.addTest(a)
-
-if __name__ == "__main__":
- runner = unittest.TextTestRunner()
- runner.run(suite)
+ assert polys.iloc[0].wkt == wkt