increased soil moisture tests test coverage

saqc/funcs/soil_moisture_tests.py

@@ -265,17 +265,17 @@ def flagSoilMoistureByConstantsDetection(
     plateau_window_min="12h",
     plateau_var_limit=0.0005,
     rainfall_window_range="12h",
-    filter_window_size="3h",
+    filter_window_size=None,
     var_total_nans=np.inf,
     var_consec_nans=np.inf,
     derivative_maximum_lb=0.0025,
     derivative_minimum_ub=0,
     data_max_tolerance=0.95,
+    smooth_poly_order=2,
     **kwargs
 ):
 
-    """Function is not ready to use yet: we are waiting for response from the author of [Paper] in order of getting
-    able to exclude some sources of confusion.
+    """
 
     Note, function has to be harmonized to equidistant freq_grid
 
@@ -322,13 +322,27 @@ def flagSoilMoistureByConstantsDetection(
     # 2. extend forwards:
     if period_diff > 0:
         cond1_sets = cond1_sets.replace(1, method='ffill', limit=period_diff)
+
     # get first derivative
+    if filter_window_size is None:
+        filter_window_size = 3 * pd.Timedelta(moist_rate)
+    else:
+        filter_window_size = pd.Timedelta(filter_window_size)
     first_derivative = dataseries.diff()
-    # cumsum trick to seperate continous plateau groups from each other
+    filter_window_seconds = filter_window_size.seconds
+    smoothing_periods = int(np.ceil((filter_window_seconds / moist_rate.n)))
+    first_derivate = savgol_filter(
+        dataseries,
+        window_length=smoothing_periods,
+        polyorder=smooth_poly_order,
+        deriv=1,
+    )
+    first_derivate = pd.Series(data=first_derivate, index=dataseries.index, name=dataseries.name)
+    # cumsumming to seperate continous plateau groups from each other:
     group_counter = cond1_sets.cumsum()
     group_counter = group_counter[group_counter.diff() == 0]
     group_counter.name = 'group_counter'
-    group_frame = pd.merge(group_counter, first_derivative, left_index=True, right_index=True, how='inner')
+    group_frame = pd.merge(group_counter, first_derivate, left_index=True, right_index=True, how='inner')
     group_frame = group_frame.groupby('group_counter')
     condition_passed = group_frame.filter(
         lambda x: (x[field].max() >= derivative_maximum_lb) & (x[field].min() <= derivative_minimum_ub))

test/funcs/test_soil_moisture_tests.py

@@ -8,9 +8,10 @@ import pandas as pd
 from saqc.funcs.soil_moisture_tests import (
     flagSoilMoistureBySoilFrost,
     flagSoilMoistureByPrecipitationEvents,
+    flagSoilMoistureByConstantsDetection
 )
 
-from test.common import TESTFLAGGER
+from test.common import TESTFLAGGER, initData
 
 
 @pytest.mark.parametrize("flagger", TESTFLAGGER)
@@ -58,6 +59,22 @@ def test_flagSoilMoisturePrecipitationEvents(flagger):
     test_sum = (flag_result[flag_assertion] == flagger.BAD).sum()
     assert test_sum == len(flag_assertion)
 
+@pytest.mark.parametrize("flagger", TESTFLAGGER)
+def test_flagSoilMoistureByConstantsDetection(flagger):
+
+    data = initData(
+        1, start_date="2011-01-01 00:00:00", end_date="2011-01-02 00:00:00", freq="5min"
+    )
+    data.iloc[5:25] = 0
+    data.iloc[100:120] = data.max()[0]
+    field = data.columns[0]
+    flagger = flagger.initFlags(data)
+    data, flagger = flagSoilMoistureByConstantsDetection(data, field, flagger, plateau_window_min='1h',
+                                                         rainfall_window_range='1h')
+
+    assert ~(flagger.isFlagged()[5:25]).all()[0]
+    assert (flagger.isFlagged()[100:120]).all()[0]
+
 if __name__ == "__main__":
     flagger = TESTFLAGGER[2]
-    test_flagSoilMoistureBySoilFrost(flagger)
+    test_flagSoilMoistureByConstantsDetection(flagger)