updated test_stats.py to include a testcase for hourly frequency data…

… and type(lags)==int

tests/test_stats.py

@@ -6,10 +6,14 @@
 
 def acf_func(**kwargs):
     index = pd.to_datetime(np.arange(0, 100, 1), unit="D", origin="2000")
+    index = kwargs.pop("index", index)
     data = np.sin(np.linspace(0, 10 * np.pi, 100))
     r = pd.Series(data=data, index=index)
-    acf_true = np.cos(np.linspace(0.0, np.pi, 11))[1:]
-    acf = ps.stats.acf(r, lags=np.arange(1.0, 11.0), min_obs=1, **kwargs).values
+    lags = np.arange(1.0, 11.0)
+    lags = kwargs.pop("lags", lags)
+    acf_true_len = lags + 1 if isinstance(lags, int) else len(lags) + 1
+    acf_true = np.cos(np.linspace(0.0, np.pi, acf_true_len))[1:]
+    acf = ps.stats.acf(r, lags=lags, min_obs=1, **kwargs).values
     return acf, acf_true
 
 
@@ -23,6 +27,13 @@ def test_acf_gaussian():
     assert abs((acf - acf_true)).max() < 0.05
 
 
+def test_acf_hourly():
+    index = pd.to_datetime(np.arange(0, 100, 1), unit="h", origin="2000")
+    lags = 10
+    acf, acf_true = acf_func(index=index, lags=lags)
+    assert abs((acf - acf_true)).max() < 0.05
+
+
 def test_runs_test():
     """
     http://www.itl.nist.gov/div898/handbook/eda/section3/eda35d.htm