From 0afedc4d2ae4c444b4795edf4b3e244e87fefba8 Mon Sep 17 00:00:00 2001
From: Thibault Hallouin <thibhlln@gmail.com>
Date: Wed, 10 Aug 2022 17:44:27 +0200
Subject: [PATCH] update to latest evalhyd version

which includes the explicit assignment of NaN in outputs where threshold
is not provided by user for given site (i.e. set to NaN)
---
 deps/evalhyd              |  2 +-
 tests/test_probabilist.py | 12 +++++++-----
 2 files changed, 8 insertions(+), 6 deletions(-)

diff --git a/deps/evalhyd b/deps/evalhyd
index 0cb58bb..a2957cb 160000
--- a/deps/evalhyd
+++ b/deps/evalhyd
@@ -1 +1 @@
-Subproject commit 0cb58bb553733c00eed1930b62b7636899819b54
+Subproject commit a2957cb3f6e674df6cf5e148870f74c9d53251b4
diff --git a/tests/test_probabilist.py b/tests/test_probabilist.py
index 89c2571..6dfc37f 100644
--- a/tests/test_probabilist.py
+++ b/tests/test_probabilist.py
@@ -16,17 +16,19 @@ class TestMetrics(unittest.TestCase):
 
     expected_thr = {
         'BS':
-            [[[[0.1081672, 0.073954980, 0.08681672]]]],
+            [[[[0.1081672, 0.073954980, 0.08681672, numpy.nan]]]],
         'BSS':
-            [[[[0.56240422, 0.66612211, 0.56288391]]]],
+            [[[[0.56240422, 0.66612211, 0.56288391, numpy.nan]]]],
         'BS_CRD':
             [[[[[0.01335634, 0.15237434, 0.24718520],
                 [0.00550861, 0.15305671, 0.22150309],
-                [0.00753750, 0.11933328, 0.19861250]]]]],
+                [0.00753750, 0.11933328, 0.19861250],
+                [numpy.nan, numpy.nan, numpy.nan]]]]],
         'BS_LBD':
             [[[[[0.01244569, 0.14933386, 0.24505537],
                 [0.00801337, 0.14745568, 0.21339730],
-                [0.01719462, 0.10479711, 0.17441921]]]]]
+                [0.01719462, 0.10479711, 0.17441921],
+                [numpy.nan, numpy.nan, numpy.nan]]]]]
     }
 
     expected_qtl = {
@@ -38,7 +40,7 @@ class TestMetrics(unittest.TestCase):
     }
 
     def test_threshold_metrics(self):
-        thr = numpy.array([[690, 534, 445]])
+        thr = numpy.array([[690, 534, 445, numpy.nan]])
         for metric in self.expected_thr.keys():
             with self.subTest(metric=metric):
                 numpy.testing.assert_almost_equal(
-- 
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