more unit tests

src/adler/utilities/science_utilities.py

@@ -18,7 +18,7 @@ def outlier_diff(new_res, diff_cut=1.0):
     """
 
     if not isinstance(new_res, np.ndarray):
-        new_res = np.array(new_res)
+        new_res = np.array(new_res, ndmin=1)
 
     outlier_flag = np.array([False] * len(new_res))
     outlier_flag[np.abs(new_res) >= diff_cut] = True
@@ -47,7 +47,7 @@ def outlier_std(new_res, data_res, std_cut=3.0):
     data_std = np.std(data_res)
 
     if not isinstance(new_res, np.ndarray):
-        new_res = np.array(new_res)
+        new_res = np.array(new_res, ndmin=1)
 
     outlier_flag = np.array([False] * len(new_res))
     outlier_flag[np.abs(new_res) >= (data_std * std_cut)] = True

tests/adler/utilities/test_science_utilities.py

@@ -184,6 +184,30 @@ def test_outlier_diff():
     assert_array_equal(outliers, outliers_y)
 
 
+# check that a single value gets processed as a np.array
+def test_outlier_diff_single_val():
+    outliers = sci_utils.outlier_diff(y_res[0], diff_cut=1.0)
+    assert_array_equal(outliers, outliers_y[:1])
+
+
+# check that a list gets processed as a np.array
+def test_outlier_diff_single_val():
+    outliers = sci_utils.outlier_diff(list(y_res[:3]), diff_cut=1.0)
+    assert_array_equal(outliers, outliers_y[:3])
+
+
+# test if a single data point is outlying the std residuals of the previous data points
+def test_outlier_std():
+    outliers = sci_utils.outlier_std(y_res[-8], y_res[:-8])
+    assert_array_equal(outliers, outliers_y[-8])
+
+
+# test the std residual of a list of data points
+def test_outlier_std():
+    outliers = sci_utils.outlier_std(y_res[-8:-5], y_res[:-8])
+    assert_array_equal(outliers, outliers_y[-8:-5])
+
+
 def test_zero_func():
     assert sci_utils.zero_func(y_res) == 0