diff --git a/cal_tools/cal_tools/agipdutils.py b/cal_tools/cal_tools/agipdutils.py
index 347198785c517a8c4e6621466fa374de351ec3b6..85bc81bb3d8e60e1104da6b9e792fd0aea464b3c 100644
--- a/cal_tools/cal_tools/agipdutils.py
+++ b/cal_tools/cal_tools/agipdutils.py
@@ -1,8 +1,9 @@
 import copy
+from typing import Tuple
 
 import numpy as np
 from cal_tools.enums import BadPixels, SnowResolution
-from scipy.signal import cwt, find_peaks_cwt, ricker
+from scipy.signal import cwt, ricker
 from sklearn.mixture import GaussianMixture
 from sklearn.preprocessing import StandardScaler
 
@@ -249,8 +250,10 @@ def correct_baseline_via_hist(d, pcm, g):
             return d, 0
         it += 1
 
-    def min_hist_distance(pc, bins=100, ran=(-10000, 10000), dec=20,
-                          minbin=10):
+    def min_hist_distance(pc: int,
+                          bins: int = 100,
+                          ran: Tuple[int, int] = (-10000, 10000),
+                          minbin: int = 10) -> float:
         hh, e = np.histogram(dd[g == 0] - pc, bins=bins, range=ran)
         hm, e = np.histogram((dd[g == 1] - pc) * pcm[g == 1], bins=bins,
                              range=ran)