Replace np.NaN with np.nan

moeyensj · Oct 29, 2024 · c3a40a5 · c3a40a5
1 parent f8c26ac
commit c3a40a5
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Showing 5 changed files with 21 additions and 21 deletions.
diff --git a/src/difi/difi.py b/src/difi/difi.py
@@ -238,7 +238,7 @@ def analyzeLinkages(
                 "object_id": objects.index.values,
                 # "class" : ["None" for i in range(len(objects))],
                 "num_obs": np.zeros(len(objects), dtype=int),
-                "findable": [np.NaN for i in range(len(objects))],
+                "findable": [np.nan for i in range(len(objects))],
             }
         )
         all_objects["object_id"] = all_objects["object_id"].astype(str)
@@ -262,7 +262,7 @@ def analyzeLinkages(
                 "No findable column found in all_objects. Completeness\n" "statistics can not be calculated."
             )
             warnings.warn(warn, UserWarning)
-            all_objects.loc[:, "findable"] = np.NaN
+            all_objects.loc[:, "findable"] = np.nan
             findable_present = False
         _checkColumnTypesEqual(all_objects, observations, ["object_id"])
 
@@ -614,7 +614,7 @@ def analyzeLinkages(
 
             # Calculate completeness
             if findable == 0:
-                completeness = np.NaN
+                completeness = np.nan
             else:
                 completeness = 100.0 * findable_found / findable
             summary["completeness"].append(completeness)
@@ -638,12 +638,12 @@ def analyzeLinkages(
             summary["not_findable_missed"].append(not_findable_missed)
 
         else:
-            summary["completeness"].append(np.NaN)
-            summary["findable"].append(np.NaN)
-            summary["findable_found"].append(np.NaN)
-            summary["findable_missed"].append(np.NaN)
-            summary["not_findable_found"].append(np.NaN)
-            summary["not_findable_missed"].append(np.NaN)
+            summary["completeness"].append(np.nan)
+            summary["findable"].append(np.nan)
+            summary["findable_found"].append(np.nan)
+            summary["findable_missed"].append(np.nan)
+            summary["not_findable_found"].append(np.nan)
+            summary["not_findable_missed"].append(np.nan)
 
         # Calculate number of linkage types that contain observations of this class
         for linkage_type in [
@@ -702,8 +702,8 @@ def analyzeLinkages(
             ].nunique()
         )
 
-    all_linkages.loc[all_linkages["mixed"] == 1, "object_id"] = np.NaN
-    all_linkages.loc[all_linkages["mixed"] == 1, "contamination_percentage_in_linkages"] = np.NaN
+    all_linkages.loc[all_linkages["mixed"] == 1, "object_id"] = np.nan
+    all_linkages.loc[all_linkages["mixed"] == 1, "contamination_percentage_in_linkages"] = np.nan
     all_linkages["object_id"] = all_linkages["object_id"].astype(str)
 
     # Drop all duplicate linkage_id entries which has the effect of

diff --git a/src/difi/metrics.py b/src/difi/metrics.py
@@ -680,11 +680,11 @@ def _run_object_worker(
                 }
             else:
                 findable = {
-                    "window_id": np.NaN,
-                    "object_id": np.NaN,
-                    "findable": np.NaN,
-                    "discovery_opportunities": np.NaN,
-                    "obs_ids": np.NaN,
+                    "window_id": np.nan,
+                    "object_id": np.nan,
+                    "findable": np.nan,
+                    "discovery_opportunities": np.nan,
+                    "obs_ids": np.nan,
                 }
 
             findable_dicts.append(findable)

diff --git a/src/difi/tests/conftest.py b/src/difi/tests/conftest.py
@@ -287,7 +287,7 @@ def test_linkages(test_observations):
         all_linkages_expected["pure_complete"].append(False)
         all_linkages_expected["partial"].append(False)
         all_linkages_expected["mixed"].append(True)
-        all_linkages_expected["contamination_percentage"].append(np.NaN)
+        all_linkages_expected["contamination_percentage"].append(np.nan)
         all_linkages_expected["found_pure"].append(False)
         all_linkages_expected["found_partial"].append(False)
         all_linkages_expected["found"].append(False)

diff --git a/src/difi/tests/test_utils.py b/src/difi/tests/test_utils.py
@@ -79,7 +79,7 @@ def test__checkColumnTypesEqual():
 
 
 def test__percentHandler():
-    # If the denominator is 0, then _percentHandler should return np.NaN
+    # If the denominator is 0, then _percentHandler should return np.nan
     number = np.random.choice(np.arange(0, 10000))
     total_number = 0
     assert np.isnan(_percentHandler(number, total_number))
@@ -228,7 +228,7 @@ def test__classHandler_warnings():
     # Remove the orange class from classes dict
     classes_dict_ = copy.deepcopy(classes_dict)
     classes_dict_.pop("orange")
-    observations.loc[observations["class"].isin(["orange"]), "class"] = np.NaN
+    observations.loc[observations["class"].isin(["orange"]), "class"] = np.nan
 
     # Test for UserWarning when not all truths have an assigned class
     with pytest.warns(UserWarning):

diff --git a/src/difi/utils.py b/src/difi/utils.py
@@ -192,7 +192,7 @@ def _classHandler(
 def _percentHandler(number: float, number_total: float) -> float:
     """
     Returns a percentage value of number / number_total. Returns
-    np.NaN is number total is zero.
+    np.nan is number total is zero.
 
     Parameters
     ----------
@@ -206,7 +206,7 @@ def _percentHandler(number: float, number_total: float) -> float:
     percent : float
     """
     if number_total == 0:
-        percent_total = np.NaN
+        percent_total = np.nan
     else:
         percent_total = 100.0 * number / number_total