diff --git a/fourier/06_direct_fourier.py b/fourier/06_direct_fourier.py
index 8d3d441..e160b1e 100644
--- a/fourier/06_direct_fourier.py
+++ b/fourier/06_direct_fourier.py
@@ -1,4 +1,12 @@
 #!/usr/bin/env python3
+# vim: fdm=indent ts=4
+
+__doc__ = \
+"""
+Show how the fourier transform can be calculated
+in a continuous fashion
+"""
+
 if __name__ == "__main__":
     import numpy as np
     import matplotlib.pyplot as plt
@@ -83,12 +91,14 @@ if __name__ == "__main__":
             from numpy.polynomial import Polynomial as P
         
             freq_out = np.zeros(len(phi_in))
-            amp_cut = 0.8
+            amp_cut = 0.5
 
             fig, ax = plt.subplots()
             ax.set_title("Frequency estimation by parabola fitting.\nStars are used for the parabola fit, vertical line is where $\\partial_f = 0 $")
             ax.set_xlabel("Frequency")
             ax.set_ylabel("Amplitude")
+
+            ax.axvline(f_beacon, lw=5, ls=(0,(5,5)))
         
             for j, amp in enumerate(amp_out):
 
@@ -98,9 +108,20 @@ if __name__ == "__main__":
                 max_amp_idx = np.argmax(amp)
                 max_amp = amp[max_amp_idx]
                 # filter amplitudes below amp_cut*max_amp
-                valid_idx = amp >= amp_cut*max_amp
-        
-                p_fit = P.fit(test_freqs[valid_idx], amp[valid_idx], 2)
+                valid_mask = amp >= amp_cut*max_amp
+
+                if True:
+                    # make sure not to use other peaks
+                    lower_mask = valid_mask[0:max_amp_idx]
+                    upper_mask = valid_mask[max_amp_idx:]
+
+                    lower_end = np.argmin(lower_mask[::-1])
+                    upper_end = np.argmin(upper_mask)
+
+                    valid_mask[0:(max_amp_idx - lower_end)] = False
+                    valid_mask[(max_amp_idx + upper_end):] = False
+
+                p_fit = P.fit(test_freqs[valid_mask], amp[valid_mask], 2)
                 func  = p_fit.convert()
 
                 # Find frequency of derivative == 0
@@ -110,7 +131,7 @@ if __name__ == "__main__":
 
 
                 l = ax.plot(test_freqs, amp, marker='.')
-                ax.plot(test_freqs[valid_idx], amp[valid_idx], marker='*', color=l[0].get_color())
+                ax.plot(test_freqs[valid_mask], amp[valid_mask], marker='*', color=l[0].get_color())
                 ax.axvline(freq_out[j], color=l[0].get_color())
 
                 if True: # plot the fit
@@ -126,7 +147,7 @@ if __name__ == "__main__":
         # Amplitudes figure
         if not True:
             fig, ax = plt.subplots()
-            ax.set_ylabels("Amplitude")
+            ax.set_ylabel("Amplitude")
             ax.set_xlabel("Frequency")
             if True:
                 for j, amp in enumerate(amp_out.T):