def test_channel_merge(self):
dummyData = np.r_[1:6] /10 +1
dummyData2ch = np.vstack((dummyData, dummyData+1))
s_1ch = pyspt.Signal(dummyData, 1, comment="one ch")
s_2ch = pyspt.Signal(dummyData2ch, 1, comment="two channels")
tmp = s_2ch | s_2ch
self.assertEqual(tmp.nChannels, 4)
tmp =s_1ch | s_1ch
self.assertEqual(tmp.nChannels, 2)
tmp =s_1ch | s_2ch
self.assertEqual(tmp.nChannels, 3)
def test_time_shift_for_individual_channels(self):
sig = pyspt.Signal(range(101),1)
sig |= sig
sig2 = pyspt.dsp.time_shift(sig, [-10, 10] ) # list
sig2 = pyspt.dsp.time_shift(sig, np.array([-10, 10])) # array of int
sig2 = pyspt.dsp.time_shift(sig, np.array([-1.10, 10.1]) ) # array of float
def test_time_shift(self):
plt.figure()
sig = pyspt.Signal(range(101),1)
sig |= sig
plot = False
if plot:
#% matplotlib
sig.plot_time(ax=plt.subplot(511))
plt.title('original')
sig2 = pyspt.dsp.sample_shift(sig, 20, cyclic=True)
if plot:
sig2.plot_time(ax=plt.subplot(523))
plt.title('cyclic shift +20 samples')
sig2 = pyspt.dsp.sample_shift(sig, 20, cyclic=False)
if plot:
sig2.plot_time(ax=plt.subplot(524))
plt.title('shift +20 samples')
sig2 = pyspt.dsp.sample_shift(sig, -20, cyclic=True)
if plot:
sig2.plot_time(ax=plt.subplot(525))
plt.title('cyclic shift -20 samples')
sig2 = pyspt.dsp.sample_shift(sig, -20, cyclic=False)
if plot:
sig2.plot_time(ax=plt.subplot(526))
plt.title('shift -20 samples')
sig2 = pyspt.dsp.time_shift(sig, 40, cyclic=True)
if plot:
sig2.plot_time(ax=plt.subplot(527))
plt.title('cyclic shift 40 sec')
sig2 = pyspt.dsp.time_shift(sig, 40, cyclic=False)
if plot:
sig2.plot_time(ax=plt.subplot(528))
plt.title('shift 40 sec')
sig2 = pyspt.dsp.time_shift(sig, -40, cyclic=True)
if plot:
sig2.plot_time(ax=plt.subplot(529))
plt.title('cyclic shift -40 sec')
sig2 = pyspt.dsp.time_shift(sig, -40, cyclic=False)
if plot:
sig2.plot_time(ax=plt.subplot(5,2,10))
plt.title('shift -40 sec')
sweep = pyspt.generate_sweep(signal_length=3,
f_stop=20000,
bandwidth=1 / 24,
zero_padding=0.5)
#sweep = pyspt.dsp.normalize(sweep)
inv_sweep = pyspt.dsp.invert_spk(sweep, [20, 20000])
# inv_sweep.plot_freq()
# tmp = sweep * inv_sweep
# tmp.plot_freq()
# do meausrements
rec_dat = sd.playrec(sweep.timeData.T * 0.5, sweep.samplingRate, channels=1)
time.sleep(sweep.length)
rec = pyspt.Signal(rec_dat.T, sweep.samplingRate, domain='time')
# measurement post processing
ir = rec * inv_sweep
ir.signalType = 'energy'
ir.comment = "Impulse response"
ir.plot_freq()
ir.plot_time()
cmp = pyspt.other_functions.merge([sweep, rec])
cmp.plot_freq()
def get_delay(ir):
idx_max = np.argmax(np.abs(ir.timeData))
delay_time = ir.timeVector[idx_max]
import sys import matplotlib.pyplot as plt import importlib %matplotlib # %% # reload file del sys.modules['pyspt'] import pyspt help(pyspt) # %% testSig = np.array(range(80)).reshape((8,10)) t = pyspt.Signal(testSig, 1) plt.plot(testSig.T) # %% del sys.modules['pyspt'] import pyspt defaultColorCycle = ['r', 'g', 'b', 'y'] lineStyles = ['-', '--']
arrayconfig = configparser.ConfigParser()
arrayconfig.read('array_config.ini')
x_spacing = float(arrayconfig['array_info']['x_spacing'])
nBeams = float(arrayconfig['array_info']['nbeams'])
beamSep = float(arrayconfig['array_info']['beam_sep'])
# %% read file
with open(fileName, 'rb') as fh:
tx_rf_outdata = pickle.load(fh)
nAntennas, nSamplesRF = tx_rf_outdata.shape
tx_sig = pyspt.Signal(tx_rf_outdata, tx_rf_samplingRate, iqInterleaved=True)
tx_sig.length /= nPulses # take only first pulse
# %% up-mixing
tmp = pyspt.dsp.resample(tx_sig, tx_sig.samplingRate + usrp_mixing_freq * 2)
tx_sig = pyspt.dsp.frequency_mixer(tmp, usrp_mixing_freq)
# %% check phase in time signals
tData = tx_sig.timeData
iSample = 2000
print("angles in deg in time data: {}".format(
np.angle(tData[1:, iSample] / tData[0, iSample]) / np.pi * 180))
# %%
# array on x-axis, y axis in facing direction of array
def test_channel_sum(self):
dummyData = np.r_[1:6] /10 +1
dummyData2ch = np.vstack((dummyData, dummyData+1))
s_2ch = pyspt.Signal(dummyData2ch, 1, comment="two channels")
s_2ch.sum()
def test_signal_class_init(self):
sr = 10000
phi = [ 2*np.pi*30*t / sr for t in range(3002) ]
vec = np.sin(phi)
r = pyspt.Signal(vec, sr, comment='sine test signal')
self.assertIsInstance(r, pyspt.Signal)