diff --git a/src/pygama/pargen/lq_cal.py b/src/pygama/pargen/lq_cal.py
index 1dfe1d865..2593a557f 100644
--- a/src/pygama/pargen/lq_cal.py
+++ b/src/pygama/pargen/lq_cal.py
@@ -739,43 +739,46 @@ def plot_lq_cut_fit(lq_class, data, figsize=(12, 8), fontsize=12) -> plt.figure:
     plt.rcParams["figure.figsize"] = figsize
     plt.rcParams["font.size"] = fontsize
     fig, (ax1, ax2) = plt.subplots(2, 1)
-
-    hist, bins = lq_class.fit_hist
-    fit_pars = lq_class.cut_fit_pars
-
-    x_low = bins[0]
-    x_high = bins[-1]
-
-    ax1.stairs(hist, bins, label="data")
-    xs = np.linspace(round(bins[0], 3), round(bins[-1], 3), len(bins) - 1)
-    ls = np.sum(hist)
-    dx = np.diff(bins)
-    ax1.plot(
-        xs,
-        gaussian.pdf_norm(xs, x_low, x_high, fit_pars[0], fit_pars[1]) * dx * ls,
-        label="Gaussian Fit",
-    )
-
-    # ax1.set_xlabel('LQ')
-    ax1.set_title("Fit of LQ events in DEP")
-    ax1.legend()
-
-    bin_centers = (bins[:-1] + bins[1:]) / 2
-    reses = (
-        hist
-        - (
+    try:
+        hist, bins = lq_class.fit_hist
+        fit_pars = lq_class.cut_fit_pars
+    
+        x_low = bins[0]
+        x_high = bins[-1]
+    
+        ax1.stairs(hist, bins, label="data")
+        xs = np.linspace(round(bins[0], 3), round(bins[-1], 3), len(bins) - 1)
+        ls = np.sum(hist)
+        dx = np.diff(bins)
+        ax1.plot(
+            xs,
+            gaussian.pdf_norm(xs, x_low, x_high, fit_pars[0], fit_pars[1]) * dx * ls,
+            label="Gaussian Fit",
+        )
+    
+        # ax1.set_xlabel('LQ')
+        ax1.set_title("Fit of LQ events in DEP")
+        ax1.legend()
+    
+        bin_centers = (bins[:-1] + bins[1:]) / 2
+        reses = (
+            hist
+            - (
+                gaussian.pdf_norm(bin_centers, x_low, x_high, fit_pars[0], fit_pars[1])
+                * dx
+                * ls
+            )
+        ) / (
             gaussian.pdf_norm(bin_centers, x_low, x_high, fit_pars[0], fit_pars[1])
             * dx
             * ls
         )
-    ) / (
-        gaussian.pdf_norm(bin_centers, x_low, x_high, fit_pars[0], fit_pars[1])
-        * dx
-        * ls
-    )
-    ax2.plot(bin_centers, reses, marker="s", linestyle="")
-    ax2.set_xlabel("LQ")
-    ax2.set_ylabel("residuals")
+        ax2.plot(bin_centers, reses, marker="s", linestyle="")
+        ax2.set_xlabel("LQ")
+        ax2.set_ylabel("residuals")
+
+    except Exception:
+        pass
 
     plt.tight_layout()
     plt.close()