From fba20f5635b77a4ac28e9084a62213fa31bf8d1c Mon Sep 17 00:00:00 2001
From: Ben-Choat <liminal.engr@gmail.com>
Date: Tue, 2 Jan 2024 13:30:30 -0700
Subject: [PATCH] Update objectives.py so uses kge instead of 1-kge

I think as an artifact of previous times when all optimization was done via minimization, if a user wanted to optimize using 'kling_gupta', they would have to specify 'min' as target. This is completely counterintuitive since kge should be maxmized (-inf<kge<=1 and kge=1 is best possible score). By using kge direclty, the user can intuitively set the target as 'max'.
---
 python/ngen_cal/src/ngen/cal/objectives.py | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/python/ngen_cal/src/ngen/cal/objectives.py b/python/ngen_cal/src/ngen/cal/objectives.py
index 573df159..bf417e9f 100644
--- a/python/ngen_cal/src/ngen/cal/objectives.py
+++ b/python/ngen_cal/src/ngen/cal/objectives.py
@@ -24,7 +24,7 @@ def inverted_nnse(observed, simulated):
     return 1 - nnse
 
 def kge(observed, simulated):
-    return 1 - kling_gupta_efficiency(observed, simulated)
+    return kling_gupta_efficiency(observed, simulated)
 
 def peak_error_single(observed, simulated):
     max_sim = simulated.max()