iss #298 added test for momm

brightwind-dev · Mar 21, 2023 · c05504b · c05504b
1 parent 78eb90c
commit c05504b
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Showing 2 changed files with 23 additions and 4 deletions.
diff --git a/brightwind/analyse/analyse.py b/brightwind/analyse/analyse.py
@@ -380,9 +380,9 @@ def _mean_of_monthly_means_seasonal_adjusted(var_series, coverage_threshold=0.8)
 
         results.update({month: var_series_month.mean()})
 
-    average_result = (pd.Series(results) * pd.Series(number_days_month) / sum(
+    result = (pd.Series(results) * pd.Series(number_days_month) / sum(
         number_days_month.values())).sum(skipna=True)
-    return average_result
+    return result
 
 
 def momm(data, date_from: str = '', date_to: str = '', seasonal_adjustment=False, coverage_threshold=0.8):

diff --git a/tests/test_analyse.py b/tests/test_analyse.py
@@ -30,6 +30,25 @@ def test_monthly_means():
                                      "For example, hourly data should not be averaged to 10 minute data."
 
 
+def test_momm():
+    # Derive mean of monthly mean with standard method
+    momm_standard = bw.momm(DATA[['Spd40mN', 'Spd40mS']])
+    assert round(momm_standard.T['Spd40mN'].values[0], 6) == 6.802488
+
+    # Derive mean of monthly mean with standard method only using a certain period
+    momm_standard = bw.momm(DATA[['Spd40mN', 'Spd40mS']], date_from='2016-06-01', date_to='2017-05-31')
+    assert round(momm_standard.T['Spd40mS'].values[0], 6) == 6.684251
+
+    # Derive mean of monthly mean seasonal adjusted and imposing coverage_threshold
+    momm_seas_adj = bw.momm(DATA[['Spd40mN', 'Spd40mS']], seasonal_adjustment=True, coverage_threshold=0.7)
+    assert round(momm_seas_adj.T['Spd40mN'].values[0], 6) == 6.749667
+
+    # Derive mean of monthly mean seasonal adjusted with months of zero coverage
+    data_test = DATA.drop(DATA.loc[str(DATA.index[0].year) + '-' + str(DATA.index.month.unique()[3])].index)
+    momm_seas_adj = bw.momm(data_test[['Spd40mN', 'Spd40mS']], seasonal_adjustment=True, coverage_threshold=0.7)
+    assert round(momm_seas_adj.T['Spd40mS'].values[0], 6) == 6.864868
+
+
 def test_sector_ratio():
     bw.sector_ratio(DATA['Spd80mN'], DATA['Spd80mS'], DATA['Dir78mS'], sectors=72, boom_dir_1=0,
                     boom_dir_2=180, return_data=True)
@@ -44,8 +63,8 @@ def test_sector_ratio():
                     DATA[['Dir78mS', 'Dir58mS', 'Dir38mS']], boom_dir_1=0, boom_dir_2=180,
                     figure_size=(25,25))
     bw.sector_ratio(DATA[['Spd80mN', 'Spd60mN', 'Spd40mN']], DATA[['Spd80mS', 'Spd60mS', 'Spd40mS']],
-                 DATA[['Dir78mS', 'Dir58mS', 'Dir38mS']], boom_dir_1=0, boom_dir_2=180, figure_size=(25, 25),
-                 return_data=True)
+                    DATA[['Dir78mS', 'Dir58mS', 'Dir38mS']], boom_dir_1=0, boom_dir_2=180, figure_size=(25, 25),
+                    return_data=True)
     bw.sector_ratio(DATA['Spd80mN'], DATA['Spd80mS'], DATA['Dir78mS'], boom_dir_1=0, boom_dir_2=180, return_data=True)
     bw.sector_ratio(DATA[['Spd80mN', 'Spd60mN']], DATA[['Spd80mS', 'Spd60mS']],
                     DATA[['Dir78mS', 'Dir58mS']], boom_dir_1=[0, 350], boom_dir_2=[180, 170], figure_size=(25, 25))