diff --git a/xfer_tracer/flattop.py b/xfer_tracer/flattop.py
deleted file mode 100755
index ef06607..0000000
--- a/xfer_tracer/flattop.py
+++ /dev/null
@@ -1,24 +0,0 @@
-#!/usr/bin/env python3
-
-import numpy as np
-from scipy import signal
-from scipy.fft import fft, fftshift
-import matplotlib.pyplot as plt
-
-window = signal.windows.flattop(2500)
-plt.plot(window)
-plt.title("Flat top window")
-plt.ylabel("Amplitude")
-plt.xlabel("Sample")
-
-plt.figure()
-A = fft(window,65536) / (len(window)/2.0)
-freq = np.linspace(-0.5*2500, 0.5*2500, len(A))
-response = 20 * np.log10(np.abs(fftshift(A / abs(A).max())))
-plt.plot(freq, response)
-#plt.axis([-0.5, 0.5, -120, 0])
-plt.title("Frequency response of the flat top window")
-plt.ylabel("Normalized magnitude [dB]")
-plt.xlabel("Normalized frequency [cycles per window]")
-
-plt.show()
diff --git a/xfer_tracer/script.py b/xfer_tracer/script.py
index 72fb8a2..56a2588 100755
--- a/xfer_tracer/script.py
+++ b/xfer_tracer/script.py
@@ -6,7 +6,7 @@ import time
 import pyaudio as pa
 import numpy as np
 import scipy as sc
-
+import matplotlib.pyplot as plt
 
 current_phase = 0.0
 normalized_f  = 0.0 # in cycles per sample : f = normalized_f * f_sampling
@@ -71,11 +71,13 @@ paudio = pa.PyAudio()
 
 audio_strm = paudio.open(format=pa.paFloat32,
 	channels=1,
-	rate=48000,
+	rate=44100,
 	output=True,
 	input=False,
 	stream_callback=audio_callback,
 	start=True)
+print(paudio.get_default_output_device_info())
+print(audio_strm.is_active())
 
 def acquire_samples(sc_frequency, oscillo):
 	global new_f
@@ -89,16 +91,15 @@ def acquire_samples(sc_frequency, oscillo):
 
 	oscillo.write("acquire:state run")
 	oscillo.write("data:source CH1")
-	input_ch = oscillo.query_binary("curve?", container=np.array)
+	input_ch = oscillo.query_binary_values("curve?",datatype="b",container=np.array).astype(np.float64)
 	oscillo.write("data:source CH2")
-	output_ch = oscillo.query_binary("curve?", container=np.array)
+	output_ch = oscillo.query_binary_values("curve?",datatype="b",container=np.array).astype(np.float64)
 
 	return input_ch, output_ch
-	#return (input_ch, output_ch)
 
 def manage_measures(f_list, oscillo): # These are NOT normalized frequencies
-	hscales = [25e-3, 10e-3, 5e-3, 2.5e-3, 1e-3,
-	           500e-6, 250e-6, 100e-6, 50e-6, 25e-6, 10e-6]
+	hscales = [0.25, 100e-3, 50e-3, 25e-3, 10e-3, 5e-3, 2.5e-3, 1e-3, 500e-6, 250e-6, 100e-6, 50e-6, 25e-6, 10e-6]
+	hscales_str = ["2.5e-1", "1.0e-1", "5.0e-2", "2.5e-2", "1.0e-2", "5.0e-3", "2.5e-3", "1.0e-3", "5.0e-4", "2.5e-4", "1.0e-4", "5.0e-5", "2.5e-5", "1.0e-5"]
 
 	hscale_index = 0
 	current_hscale = hscales[hscale_index]
@@ -112,13 +113,14 @@ def manage_measures(f_list, oscillo): # These are NOT normalized frequencies
 	W = sc.signal.windows.flattop(2500)
 
 	for f in f_list:
-		sc_frequency = np.round(2**20/48000 * f)/2**20
+		sc_frequency = np.round(2**20/44100 * f)/2**20
 		num_periods = f * 10 * current_hscale
 		while(num_periods >= 5 * 2.5):
 			hscale_index += 1
 			current_hscale = hscales[hscale_index]
 			num_periods = f * 10 * current_hscale
-			oscillo.write("horizontal:main:scale " + str(hscales))
+			print("horizontal:main:scale " + hscales_str[hscale_index])
+			oscillo.write("horizontal:main:scale " + hscales_str[hscale_index])
 			cal_done = False
 
 		print(f, " : ", current_hscale,"s/div, ", num_periods, " periods")
@@ -126,14 +128,15 @@ def manage_measures(f_list, oscillo): # These are NOT normalized frequencies
 		if not cal_done:
 			cal_A, cal_B = acquire_samples(0., oscillo)
 			cal_done = True
-
+		print(A)
+		print(B)
 		A, B = (A - cal_A)*W, (B - cal_B)*W
 		f_acq = 250./current_hscale
 		rel_f = f / f_acq
 
 		# Obtain the Fourier transforms of A, B @ rel_f, with flattop windowing 
 		V = np.exp(-2.0j * np.pi * np.arange(2500) * rel_f)
-		h = np.sum(B*V)/np.sum(A.V)
+		h = np.sum(B*V)/np.sum(A*V)
 		print("H(", f, ") = ", h)
 		H.append(h)
 	return H
@@ -147,18 +150,20 @@ def find_oscillo():
 #		exit(1)
 	return rm.open_resource(R[0])
 
+
 osci = find_oscillo()
+osci.timeout = 10000
 print(osci.query("*IDN?"))
 
 osci.write("*RST")
-time.sleep(5)
+time.sleep(10)
 
-osci.write("ch1:scale 1.0e-1")
+osci.write("ch1:scale 2.5e-1")
 osci.write("ch1:bandwidth ON")
 osci.write("ch1:coupling AC")
 osci.write("select:ch1 1")
 
-osci.write("ch2:scale 5.0e-2")
+osci.write("ch2:scale 2.5e-1")
 osci.write("ch2:bandwidth ON")
 osci.write("ch2:coupling AC")
 osci.write("select:ch2 1")
@@ -170,6 +175,16 @@ osci.write("trigger:main:type EDGE")
 
 osci.write("acquire:mode sample")
 osci.write("acquire:stopafter sequence")
-osci.write("data:encdg ascii")
-manage_measures([330., 470., 680., 820., 1000.])
+osci.write("data:encdg RIBinary")
+decade = [1.0, 1.2, 1.5, 1.8, 2.2, 2.7, 3.3, 3.9, 4.7, 5.6, 6.8, 8.2]
 
+X = [68., 82] + list(np.array(decade)*([100.]*len(decade))) + list(np.array(decade) * ([1000.]*len(decade))) + [1e4, 1.2e4, 1.5e4, 1.8e4]
+H = manage_measures(X, osci)
+Y = 20 * np.log10(np.abs(H))
+
+fig, axes = plt.subplots(nrows = 2, ncols=1, sharex = True)
+axes[0].semilogx(X,Y)
+axes[0].grid()
+axes[1].semilogx(X, np.angle(H, deg=True))
+axes[1].grid()
+plt.show()