tests(IHmethod): add test for handling inadequate input data

aleaf · aleaf · commit 358ddd2a7b11 · 2020-09-30T12:02:13.000-05:00
diff --git a/pydrograph/baseflow.py b/pydrograph/baseflow.py
@@ -120,8 +120,8 @@ def IHmethod(Qseries, block_length=5, tp=0.9, interp_semilog=True, freq='D'):
     freq : str or DateOffset, default ‘D’
         Any `pandas frequency alias <https://pandas.pydata.org/pandas-docs/stable/user_guide/timeseries.html#timeseries-offset-aliases>`_
         Regular time interval that forms the basis for base-flow separation. Input data are
-        resampled to this frequency, and block lengths represent N repetitions
-        of the time increment. By default, days ('D'), which is what all previous BFI methods
+        resampled to this frequency, and block lengths represent the number of time increments
+        of the frequency. By default, days ('D'), which is what all previous BFI methods
         are based on. Note that this is therefore an experimental option; it is up to the user t
         o verify any results produced by other frequencies.
 
@@ -144,6 +144,11 @@ def IHmethod(Qseries, block_length=5, tp=0.9, interp_semilog=True, freq='D'):
     will differ from those produced by the BFI program.
     
     """
+    if len(Qseries) < 2 * block_length:
+        raise ValueError('Input Series must be at '
+                         'least two block lengths\nblock_length: '
+                         '{}\n{}'.format(block_length, Qseries))
+
     # convert flow values to numeric if they are objects
     # (pandas will cast column as objects if there are strings such as "ICE")
     # coerce any strings into np.nan values
diff --git a/pydrograph/tests/test_baseflow.py b/pydrograph/tests/test_baseflow.py
@@ -20,3 +20,23 @@ def test_IHmethod(test_data, block_length, interp_semilog, freq):
                        interp_semilog=interp_semilog)
     minimum_points = ~results.block_Qmin.isna()
     assert np.all(results.loc[minimum_points, 'block_Qmin'] <= results.loc[minimum_points, 'Q'])
+
+
+@pytest.mark.parametrize('data', (pytest.param(pd.Series(),
+                                               marks=pytest.mark.xfail(reason="index isn't datetime")),
+                                  pytest.param(pd.Series(index=pd.to_datetime([])),
+                                               marks=pytest.mark.xfail(reason="index isn't datetime")),
+                                  pytest.param(pd.Series([15.2, 14.8, 14.5, 14.2],
+                                                         index=pd.date_range('2020-09-30', '2020-10-03')),
+                                               marks=pytest.mark.xfail(reason="index isn't datetime")),
+                                  pd.Series([15.2, 14.8, 14.5, 14.2, 13.9, 13.8, 13.8, 13.8, 13.8, 13.8],
+                                            index=pd.date_range('2020-01-01', '2020-01-10'))
+                                  )
+                         )
+def test_IHmethod_with_not_enough_data(data):
+    results = IHmethod(data)
+    j=2
+
+
+
+
