From df57f297e732bd6972ad7bda2241a2386c014cca Mon Sep 17 00:00:00 2001
From: Daniel Weindl <dweindl@users.noreply.github.com>
Date: Tue, 15 Oct 2024 07:51:46 +0200
Subject: [PATCH] Prevent `Mean of empty slice` warning in
 `fiddy.success.Consistency.method` (#55)

Fixes #52.
---
 fiddy/success.py | 43 ++++++++++++++++++++++---------------------
 1 file changed, 22 insertions(+), 21 deletions(-)

diff --git a/fiddy/success.py b/fiddy/success.py
index 257e72a..4cadd28 100644
--- a/fiddy/success.py
+++ b/fiddy/success.py
@@ -1,6 +1,6 @@
 import abc
 from collections.abc import Callable
-from typing import Any, Union
+from typing import Any
 
 import numpy as np
 
@@ -97,25 +97,26 @@ def method(
                 equal_nan=self.equal_nan,
             ).all()
 
-        consistent_results = [
-            np.nanmean(list(results_by_size[size].values()), axis=0)
-            for size, success in success_by_size.items()
-            if success
-        ]
-
-        success = False
-        value = np.nanmean(np.array(consistent_results), axis=0)
-        if consistent_results:
-            success = (
-                np.isclose(
-                    consistent_results,
-                    value,
-                    rtol=self.rtol,
-                    atol=self.atol,
-                    equal_nan=self.equal_nan,
-                ).all()
-                and not np.isnan(consistent_results).all()
-            )
-        value = np.average(np.array(consistent_results), axis=0)
+        consistent_results = np.array(
+            [
+                np.nanmean(list(results_by_size[size].values()), axis=0)
+                for size, success in success_by_size.items()
+                if success
+            ]
+        )
+
+        if len(consistent_results) == 0:
+            return False, np.nan
 
+        value = np.nanmean(consistent_results, axis=0)
+        success = (
+            np.isclose(
+                consistent_results,
+                value,
+                rtol=self.rtol,
+                atol=self.atol,
+                equal_nan=self.equal_nan,
+            ).all()
+            and not np.isnan(consistent_results).all()
+        )
         return success, value