diff --git a/app/cocal_methods.py b/app/cocal_methods.py
index c0fe4834273283be15c9aad085c80ebc2a499713..755c671b50702199cd404fc0b1532245f15fbed2 100644
--- a/app/cocal_methods.py
+++ b/app/cocal_methods.py
@@ -757,28 +757,29 @@ class CocalMethods:
         mask_ri = np.r_[mask, mask]
 
         # function to draw samples for Monte Carlo
-        draw_samples = lambda size: real_imag_2_complex(
-            np.random.normal(
-                self.ref_spectrum_ri[mask_ri],
-                self.ref_spectrum_unc_ri[mask_ri],
-                size=(size, self.ref_spectrum_ri[mask_ri].size),
+        def draw_samples(size):
+            return real_imag_2_complex(
+                np.random.normal(
+                    self.ref_spectrum_ri[mask_ri],
+                    self.ref_spectrum_unc_ri[mask_ri],
+                    size=(size, self.ref_spectrum_ri[mask_ri].size),
+                )
             )
-        )
 
         # function to evaluate samples in Monte Carlo
         w_empirical_exp = (
-            np.exp(
-                -1j * 2 * np.pi * self.ref_frequency[mask] / frame_rate
-            ),
-        )
-        evaluate = lambda sample: self.fit_filter(
-            sample,
-            H_dut=self.dut_spectrum[mask],
-            theta0=theta0,
-            Nb=Nb,
-            w_empirical_exp=w_empirical_exp,
+            np.exp(-1j * 2 * np.pi * self.ref_frequency[mask] / frame_rate),
         )
 
+        def evaluate(sample):
+            return self.fit_filter(
+                sample,
+                H_dut=self.dut_spectrum[mask],
+                theta0=theta0,
+                Nb=Nb,
+                w_empirical_exp=w_empirical_exp,
+            )
+
         umc_kwargs = {
             "draw_samples": draw_samples,
             "evaluate": evaluate,