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xfer_tracer working

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hackens-bot 2024-12-17 21:49:00 +01:00
parent 8d3f1564f4
commit 4ebd626409
2 changed files with 31 additions and 40 deletions
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24
xfer_tracer/flattop.py
View file

@ -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()

47
xfer_tracer/script.py
View file

@ -6,7 +6,7 @@ import time
import pyaudio as pa import pyaudio as pa
import numpy as np import numpy as np
import scipy as sc import scipy as sc
import matplotlib.pyplot as plt
current_phase = 0.0 current_phase = 0.0
normalized_f = 0.0 # in cycles per sample : f = normalized_f * f_sampling 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, audio_strm = paudio.open(format=pa.paFloat32,
channels=1, channels=1,
rate=48000, rate=44100,
output=True, output=True,
input=False, input=False,
stream_callback=audio_callback, stream_callback=audio_callback,
start=True) start=True)
print(paudio.get_default_output_device_info())
print(audio_strm.is_active())
def acquire_samples(sc_frequency, oscillo): def acquire_samples(sc_frequency, oscillo):
global new_f global new_f
@ -89,16 +91,15 @@ def acquire_samples(sc_frequency, oscillo):
oscillo.write("acquire:state run") oscillo.write("acquire:state run")
oscillo.write("data:source CH1") 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") 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
#return (input_ch, output_ch)
def manage_measures(f_list, oscillo): # These are NOT normalized frequencies def manage_measures(f_list, oscillo): # These are NOT normalized frequencies
hscales = [25e-3, 10e-3, 5e-3, 2.5e-3, 1e-3, 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]
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 hscale_index = 0
current_hscale = hscales[hscale_index] 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) W = sc.signal.windows.flattop(2500)
for f in f_list: 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 num_periods = f * 10 * current_hscale
while(num_periods >= 5 * 2.5): while(num_periods >= 5 * 2.5):
hscale_index += 1 hscale_index += 1
current_hscale = hscales[hscale_index] current_hscale = hscales[hscale_index]
num_periods = f * 10 * current_hscale 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 cal_done = False
print(f, " : ", current_hscale,"s/div, ", num_periods, " periods") 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: if not cal_done:
cal_A, cal_B = acquire_samples(0., oscillo) cal_A, cal_B = acquire_samples(0., oscillo)
cal_done = True cal_done = True
print(A)
print(B)
A, B = (A - cal_A)*W, (B - cal_B)*W A, B = (A - cal_A)*W, (B - cal_B)*W
f_acq = 250./current_hscale f_acq = 250./current_hscale
rel_f = f / f_acq rel_f = f / f_acq
# Obtain the Fourier transforms of A, B @ rel_f, with flattop windowing # Obtain the Fourier transforms of A, B @ rel_f, with flattop windowing
V = np.exp(-2.0j * np.pi * np.arange(2500) * rel_f) 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) print("H(", f, ") = ", h)
H.append(h) H.append(h)
return H return H
@ -147,18 +150,20 @@ def find_oscillo():
# exit(1) # exit(1)
return rm.open_resource(R[0]) return rm.open_resource(R[0])
osci = find_oscillo() osci = find_oscillo()
osci.timeout = 10000
print(osci.query("*IDN?")) print(osci.query("*IDN?"))
osci.write("*RST") 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:bandwidth ON")
osci.write("ch1:coupling AC") osci.write("ch1:coupling AC")
osci.write("select:ch1 1") 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:bandwidth ON")
osci.write("ch2:coupling AC") osci.write("ch2:coupling AC")
osci.write("select:ch2 1") osci.write("select:ch2 1")
@ -170,6 +175,16 @@ osci.write("trigger:main:type EDGE")
osci.write("acquire:mode sample") osci.write("acquire:mode sample")
osci.write("acquire:stopafter sequence") osci.write("acquire:stopafter sequence")
osci.write("data:encdg ascii") osci.write("data:encdg RIBinary")
manage_measures([330., 470., 680., 820., 1000.]) 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()