diff --git a/higgs_dna/systematics/event_weight_systematics.py b/higgs_dna/systematics/event_weight_systematics.py
index 4b98ba3bc2c805a4b095f8a48ddd94e64d6cb7f4..b734539222a38db039b9a755871cc8570e3ef880 100644
--- a/higgs_dna/systematics/event_weight_systematics.py
+++ b/higgs_dna/systematics/event_weight_systematics.py
@@ -1,7 +1,6 @@
 import numpy as np
 import json
 import os
-from scipy.interpolate import interp1d
 import correctionlib
 import awkward as ak
 from higgs_dna.utils.misc_utils import choose_jet
@@ -609,41 +608,46 @@ def NNLOPS(
     json_file = os.path.join(os.path.dirname(__file__), "JSONs/NNLOPS_reweight.json")
 
     if is_correction:
-        if 'ggh' not in dataset_name.lower() and 'glugluh' not in dataset_name.lower():
-            logger.info(f"\n WARNING: You specified NNLOPS reweighting for dataset with {dataset_name} but this does not appear like a ggF sample. Consider checking your runner JSON Proceed with caution.")
-        # Extract NNLOPS weights from json file
-        with open(json_file, "r") as jf:
-            nnlops_reweight = json.load(jf)
-
-        # Load reweight factors for specific generator
-        nnlops_reweight = nnlops_reweight[generator]
-
-        # Build linear splines for different njet bins
-        spline_0jet = interp1d(
-            nnlops_reweight["0jet"]["pt"], nnlops_reweight["0jet"]["weight"]
-        )
-        spline_1jet = interp1d(
-            nnlops_reweight["1jet"]["pt"], nnlops_reweight["1jet"]["weight"]
-        )
-        spline_2jet = interp1d(
-            nnlops_reweight["2jet"]["pt"], nnlops_reweight["2jet"]["weight"]
-        )
-        spline_ge3jet = interp1d(
-            nnlops_reweight["3jet"]["pt"], nnlops_reweight["3jet"]["weight"]
-        )
+        if (
+            all(s not in dataset_name.lower() for s in ('glugluhh', 'gghh'))
+            and any(s in dataset_name.lower() for s in ("ggh", "glugluh"))
+        ):
+            # Extract NNLOPS weights from json file
+            with open(json_file, "r") as jf:
+                nnlops_reweight = json.load(jf)
 
-        # Load truth Higgs pt and njets (pt>30) from events
-        higgs_pt = events.HTXS.Higgs_pt
-        njets30 = events.HTXS.njets30
-
-        # Extract scale factors from splines and mask for different jet bins
-        # Define maximum pt values as interpolated splines only go up so far
-        sf = (
-            (njets30 == 0) * spline_0jet(np.minimum(np.array(higgs_pt), 125.0))
-            + (njets30 == 1) * spline_1jet(np.minimum(np.array(higgs_pt), 625.0))
-            + (njets30 == 2) * spline_2jet(np.minimum(np.array(higgs_pt), 800.0))
-            + (njets30 >= 3) * spline_ge3jet(np.minimum(np.array(higgs_pt), 925.0))
-        )
+            # Load reweight factors for specific generator
+            nnlops_reweight = nnlops_reweight[generator]
+
+            # Build linear splines for different njet bins
+            spline_0jet = np.interp(
+                nnlops_reweight["0jet"]["pt"], nnlops_reweight["0jet"]["weight"]
+            )
+            spline_1jet = np.interp(
+                nnlops_reweight["1jet"]["pt"], nnlops_reweight["1jet"]["weight"]
+            )
+            spline_2jet = np.interp(
+                nnlops_reweight["2jet"]["pt"], nnlops_reweight["2jet"]["weight"]
+            )
+            spline_ge3jet = np.interp(
+                nnlops_reweight["3jet"]["pt"], nnlops_reweight["3jet"]["weight"]
+            )
+
+            # Load truth Higgs pt and njets (pt>30) from events
+            higgs_pt = events.HTXS.Higgs_pt
+            njets30 = events.HTXS.njets30
+
+            # Extract scale factors from splines and mask for different jet bins
+            # Define maximum pt values as interpolated splines only go up so far
+            sf = (
+                (njets30 == 0) * spline_0jet(np.minimum(np.array(higgs_pt), 125.0))
+                + (njets30 == 1) * spline_1jet(np.minimum(np.array(higgs_pt), 625.0))
+                + (njets30 == 2) * spline_2jet(np.minimum(np.array(higgs_pt), 800.0))
+                + (njets30 >= 3) * spline_ge3jet(np.minimum(np.array(higgs_pt), 925.0))
+            )
+
+        else:
+            logger.info(f"\n WARNING: You specified NNLOPS reweighting for dataset with {dataset_name} but this does not appear like a ggF to single Higgs sample. The reweighting in not applied.")
 
     else:
         raise RuntimeError(