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-rwxr-xr-x_signal_processing/krakenSDR_signal_processor.py11
1 files changed, 5 insertions, 6 deletions
diff --git a/_signal_processing/krakenSDR_signal_processor.py b/_signal_processing/krakenSDR_signal_processor.py
index b0f87e2..d60ad66 100755
--- a/_signal_processing/krakenSDR_signal_processor.py
+++ b/_signal_processing/krakenSDR_signal_processor.py
@@ -228,7 +228,6 @@ class SignalProcessor(threading.Thread):
spectrum_samples = self.module_receiver.iq_samples #spectrum_signal #self.processed_signal #self.module_receiver.iq_samples #self.processed_signal
-
N = self.spectrum_window_size
N_perseg = 0
@@ -287,7 +286,7 @@ class SignalProcessor(threading.Thread):
RD_matrix = cc_detector_ons(ref_ch, surv_ch, self.module_receiver.iq_header.sampling_freq, max_Doppler, max_range)
end = time.time()
- print("Time: " + str((end-start) * 1000))
+ #print("Time: " + str((end-start) * 1000))
que_data_packet.append(['RD_matrix', RD_matrix])
@@ -421,8 +420,8 @@ def pruned_correlation(ref_ch, surv_ch, clen, N):
ypp = np.vstack([xp[1:, :], np.zeros(cols, dtype=c_dtype)]) #vstack appears to be faster than pad
yp = np.concatenate([xp, ypp], axis=1)
- print("pruned corr xp shape: " + str(xp.shape))
- print("pruned corr yp shape: " + str(yp.shape))
+ #print("pruned corr xp shape: " + str(xp.shape))
+ #print("pruned corr yp shape: " + str(yp.shape))
# execute FFT on the matrices
xpw = fft.fft(xp, n = 2*cols, axis=1, workers=4, overwrite_x=True)
@@ -526,8 +525,8 @@ def cc_detector_ons(ref_ch, surv_ch, fs, fD_max, r_max):
ref_ch_align, surv_ch_align = resize_and_align(no_sub_tasks, ref_ch, surv_ch, fs, fD_max, r_max)
- print("ref_ch_align shape: " + str(ref_ch_align.shape))
- print("surv_ch_align shape: " + str(surv_ch_align.shape))
+ #print("ref_ch_align shape: " + str(ref_ch_align.shape))
+ #print("surv_ch_align shape: " + str(surv_ch_align.shape))
# row wise fft on both channels