adds documentation

nolds/test_measures.py

@@ -552,16 +552,19 @@ class RegressionTests(unittest.TestCase):
   """
 
   def test_sampen(self):
+    """Test hypothesis: The exact output of sampen() on random data hasn't changed since the last version."""
     data = datasets.load_qrandom()[:1000]
     se = nolds.sampen(data, emb_dim=2, tolerance=None, lag=1, dist=nolds.rowwise_chebyshev, closed=False)
     self.assertAlmostEqual(2.1876999522832743, se, places=15)
 
   def test_corr_dim(self):
+    """Test hypothesis: The exact output of corr_dim() with `fit=poly` on random data hasn't changed since the last version."""
     data = datasets.load_qrandom()[:1000]
     cd = nolds.corr_dim(data, emb_dim=5, lag=1, rvals=None, dist=nolds.rowwise_euclidean, fit="poly")
     self.assertAlmostEqual(1.303252839255068, cd, places=15)
 
   def test_corr_dim_RANSAC(self):
+    """Test hypothesis: The exact output of corr_dim() with `fit=RANSAC` on random data hasn't changed since the last version."""
     data = datasets.load_qrandom()[:1000]
     sd = np.std(data, ddof=1)
     # fix seed
@@ -572,19 +575,22 @@ def test_corr_dim_RANSAC(self):
     self.assertAlmostEqual(0.44745494643404665, cd, places=15)
 
   def test_lyap_e(self):
+    """Test hypothesis: The exact output of lyap_e() on random data hasn't changed since the last version."""
     data = datasets.load_qrandom()[:1000]
     le = nolds.lyap_e(data, emb_dim=10, matrix_dim=4, min_nb=10, min_tsep=1, tau=1)
     expected = np.array([ 0.03779942603329712,  -0.014314012551504982, -0.08436867977030214, -0.22316730257003717])
     for i in range(le.shape[0]):
       self.assertAlmostEqual(expected[i], le[i], places=15, msg=f"{i+1}th Lyapunov exponent doesn't match")
 
   def test_lyap_r(self):
+    """Test hypothesis: The exact output of lyap_r() with `fit=poly` on random data hasn't changed since the last version."""
     data = datasets.load_qrandom()[:1000]
     le = nolds.lyap_r(data, emb_dim=10, lag=1, min_tsep=1, tau=1, min_neighbors=10, trajectory_len=10, fit="poly")
     expected = 0.094715945307378
     self.assertAlmostEqual(expected, le, places=15)
 
   def test_lyap_r_RANSAC(self):
+    """Test hypothesis: The exact output of lyap_r() with `fit=RANSAC` on random data hasn't changed since the last version."""
     data = datasets.load_qrandom()[:1000]
     np.random.seed(42)
     # set lag to 2 for weird duplicate lines
@@ -594,12 +600,14 @@ def test_lyap_r_RANSAC(self):
     self.assertAlmostEqual(expected, le, places=15)
 
   def test_hurst_rs(self):
+    """Test hypothesis: The exact output of hurst_rs() with `fit=poly` on random data hasn't changed since the last version."""
     data = datasets.load_qrandom()[:1000]
     rs = nolds.hurst_rs(data, nvals=None, fit="poly", corrected=True, unbiased=True)
     expected = 0.5123887964986258
     self.assertAlmostEqual(expected, rs, places=15)
 
   def test_hurst_rs_RANSAC(self):
+    """Test hypothesis: The exact output of hurst_rs() with `fit=RANSAC` on random data hasn't changed since the last version."""
     data = datasets.load_qrandom()[:1000]
     np.random.seed(42)
     # increase nsteps in nvals to have more data points for RANSAC to choose from
@@ -609,12 +617,14 @@ def test_hurst_rs_RANSAC(self):
     self.assertAlmostEqual(expected, rs, places=15)
 
   def test_dfa(self):
+    """Test hypothesis: The exact output of dfa() with `fit_exp=poly` on random data hasn't changed since the last version."""
     data = datasets.load_qrandom()[:1000]
     h = nolds.dfa(data, nvals=None, overlap=True, order=1, fit_trend="poly", fit_exp="poly")
     expected = 0.5450874638765073
     self.assertAlmostEqual(expected, h, places=15)
 
   def test_dfa_RANSAC(self):
+    """Test hypothesis: The exact output of dfa() with `fit_exp=RANSAC` on random data hasn't changed since the last version."""
     # adds trend to data to introduce a less clear line for fitting
     data = datasets.load_qrandom()[:1000] + np.arange(1000) * 100
     np.random.seed(42)
@@ -625,25 +635,29 @@ def test_dfa_RANSAC(self):
     self.assertAlmostEqual(expected, h, places=15)
 
   def test_mfhurst_b(self):
+    """Test hypothesis: The exact output of mfhurst_b() with `fit=poly` on random data hasn't changed since the last version."""
     data = datasets.load_qrandom()[:1000]
     h = nolds.mfhurst_b(data, qvals=[1], dists=None, fit="poly")
     expected = [-0.00559398934417339]
     self.assertAlmostEqual(expected[0], h[0], places=15)
 
   def test_mfhurst_b_RANSAC(self):
+    """Test hypothesis: The exact output of mfhurst_b() with `fit=RANSAC` on random data hasn't changed since the last version."""
     data = datasets.load_qrandom()[:1000]
     np.random.seed(42)
     h = nolds.mfhurst_b(data, qvals=[1], dists=None, fit="RANSAC")
     expected = [-0.009056463064211057]
     self.assertAlmostEqual(expected[0], h[0], places=15)
 
   def test_mfhurst_dm(self):
+    """Test hypothesis: The exact output of mfhurst_dm() with `fit=poly` on random data hasn't changed since the last version."""
     data = datasets.load_qrandom()[:1000]
     h, _ = nolds.mfhurst_dm(data, qvals=[1], max_dists=range(5, 20), detrend=True, fit="poly")
     expected = [0.008762803881203145]
     self.assertAlmostEqual(expected[0], h[0], places=15)
 
   def test_mfhurst_dm_RANSAC(self):
+    """Test hypothesis: The exact output of mfhurst_dm() with `fit=RANSAC` on random data hasn't changed since the last version."""
     data = datasets.load_qrandom()[:1000]
     np.random.seed(42)
     h, _ = nolds.mfhurst_dm(data, qvals=[1], max_dists=range(5, 20), detrend=True, fit="RANSAC")