From f2af9c0f7beba3ab59a442a21af1027816092ad7 Mon Sep 17 00:00:00 2001
From: Pete R Jemian <prjemian@gmail.com>
Date: Wed, 31 Jul 2024 15:54:23 -0500
Subject: [PATCH] MNT #1260 refactor per discussion

---
 ophyd/tests/test_utils.py |  6 +++---
 ophyd/utils/epics_pvs.py  | 24 +++++++++++++-----------
 2 files changed, 16 insertions(+), 14 deletions(-)

diff --git a/ophyd/tests/test_utils.py b/ophyd/tests/test_utils.py
index 3af8a7ace..b8377e746 100644
--- a/ophyd/tests/test_utils.py
+++ b/ophyd/tests/test_utils.py
@@ -150,13 +150,13 @@ def test_set_signal_to_None():
         # compare array shapes
         [[1, 2, 3], [1, 2, 3], [], None, None, True],  # identical
         [[1, 2, 3], [0, 0, 0], [], None, None, False],  # b has different values
-        [[1, 2, 3], [1, 2, 3, 0], [], None, None, True],  # only compares len(a) items
-        [[1, 2, 3, 0], [1, 2, 3], [], None, None, False],  # len(a) > len(b)
+        [[1, 2, 3], [1, 2, 3, 0], [], None, None, False],  # different shape
+        # [[1, 2, 3, 0], [1, 2, 3], [], None, None, False],  # len(a) > len(b)
         [5, [1, 2, 3], [], None, None, False],  # not the same type
         [[1, 2, 3], 5, [], None, None, False],  # not the same type
         # numpy arrays
         [[1, 2, 3], np.array([1, 2, 3]), [], None, None, True],  # identical
-        [[1, 2, 3], np.array([1, 2, 3, 0]), [], None, None, True],  # len(a)
+        # [[1, 2, 3], np.array([1, 2, 3, 0]), [], None, None, True],  # len(a)
         # tuple
         [(1, 2, 3), np.array([1, 2, 3]), [], None, None, True],  # identical
         # with tolerance
diff --git a/ophyd/utils/epics_pvs.py b/ophyd/utils/epics_pvs.py
index 3e8793721..a28a403aa 100644
--- a/ophyd/utils/epics_pvs.py
+++ b/ophyd/utils/epics_pvs.py
@@ -267,7 +267,9 @@ def _wait_for_value(signal, val, poll_time=0.01, timeout=10, rtol=None, atol=Non
     TimeoutError if timeout is exceeded
     """
     expiration_time = ttime.time() + timeout if timeout is not None else None
-    current_value = signal.get()
+    array_like = (list, np.ndarray, tuple)
+    item_count = None if not isinstance(val, array_like) else len(val)
+    current_value = signal.get(count=item_count)
 
     if atol is None and hasattr(signal, "tolerance"):
         atol = signal.tolerance
@@ -305,7 +307,7 @@ def _wait_for_value(signal, val, poll_time=0.01, timeout=10, rtol=None, atol=Non
         ttime.sleep(poll_time)
         if poll_time < 0.1:
             poll_time *= 2  # logarithmic back-off
-        current_value = signal.get()
+        current_value = signal.get(count=item_count)
         if expiration_time is not None and ttime.time() > expiration_time:
             raise TimeoutError(
                 "Attempted to set %r to value %r and timed "
@@ -335,15 +337,15 @@ def _compare_maybe_enum(a, b, enums, atol, rtol):
         # then compare the strings
         return a == b
 
-    array_like = (list, np.ndarray, tuple)
-    if isinstance(a, array_like) and isinstance(b, array_like):
-        a = np.array(a)  # target
-        b = np.array(b)  # reported by EPICS
-        if len(a.shape) == 1 and len(b.shape) == 1 and len(a) < len(b):
-            b = b[: len(a)]  # cut 1-D EPICS array down to requested size
-
-        if a.shape != b.shape:
-            return False
+    # array_like = (list, np.ndarray, tuple)
+    # if isinstance(a, array_like) and isinstance(b, array_like):
+    #     a = np.array(a)  # target
+    #     b = np.array(b)  # reported by EPICS
+    #     if len(a.shape) == 1 and len(b.shape) == 1 and len(a) < len(b):
+    #         b = b[: len(a)]  # cut 1-D EPICS array down to requested size
+
+    #     if a.shape != b.shape:
+    #         return False
 
     # if either relative/absolute tolerance is used, use numpy
     # to compare: