Faster trivial equality checks for coordinates and arrays

docs/src/whatsnew/latest.rst

@@ -111,6 +111,8 @@ This document explains the changes made to Iris for this release
    :func:`~iris.analysis.stats.pearsonr` so it preserves lazy data in all cases
    and also runs a little faster.  (:pull:`5638`)
 
+#. `@bouweandela`_ made comparing coordinates and arrays to themselves faster. (:pull:`5691`)
+
 
 🔥 Deprecations
 ===============

lib/iris/coords.py

@@ -575,6 +575,9 @@ def __repr__(self):
         return self.summary(shorten=True)
 
     def __eq__(self, other):
+        if other is self:
+            return True
+
         # Note: this method includes bounds handling code, but it only runs
         #  within Coord type instances, as only these allow bounds to be set.
 

lib/iris/tests/unit/util/test_array_equal.py

@@ -101,12 +101,15 @@ def test_string_arrays_0d_and_scalar(self):
         self.assertFalse(array_equal(array_a, "foobar."))
 
     def test_nan_equality_nan_ne_nan(self):
-        array = np.array([1.0, np.nan, 2.0, np.nan, 3.0])
-        self.assertFalse(array_equal(array, array))
+        array_a = np.array([1.0, np.nan, 2.0, np.nan, 3.0])
+        array_b = array_a.copy()
+        self.assertFalse(array_equal(array_a, array_a))
+        self.assertFalse(array_equal(array_a, array_b))
 
     def test_nan_equality_nan_naneq_nan(self):
         array_a = np.array([1.0, np.nan, 2.0, np.nan, 3.0])
         array_b = np.array([1.0, np.nan, 2.0, np.nan, 3.0])
+        self.assertTrue(array_equal(array_a, array_a, withnans=True))
         self.assertTrue(array_equal(array_a, array_b, withnans=True))
 
     def test_nan_equality_nan_nanne_a(self):

lib/iris/util.py

@@ -373,6 +373,8 @@ def array_equal(array1, array2, withnans=False):
     This function maintains laziness when called; it does not realise data.
     See more at :doc:`/userguide/real_and_lazy_data`.
     """
+    if withnans and (array1 is array2):
+        return True
 
     def normalise_array(array):
         if not is_lazy_data(array):