def subniquistMediciones():
entrada = SignalsReadWrite.readSignalCsv(
"ExpressInput/Mediciones basicas/med_22.csv", "1")
signal = SignalsReadWrite.readSignalCsv(
"ExpressInput/Mediciones basicas/med_22.csv", "2")
f_entrada = FourierTransform.fourierTransform(entrada)
f_signal = FourierTransform.fourierTransform(signal)
fs = 1070
ExpressPlot.CombinedPlot()\
.setTitle("Mediciones espectro $f_s=1.07k$")\
.setXTitle("Frecuencia (Hz)")\
.setYTitle("Amplitud (% del total)") \
.extraPlot(
plotFunction,
{"fs": fs}) \
.addSignalPlot(
signal=f_entrada,
color="green",
name="Entrada"
)\
.addSignalPlot(
signal=f_signal,
color="orange",
name="Medicion llave analógica")\
.plotAndSave(
filename="ExpressOutput/espectro_subniquist1.png"
)
plt.show()
entrada = SignalsReadWrite.readSignalCsv(
"ExpressInput/Mediciones basicas/med_23.csv", "1")
signal = SignalsReadWrite.readSignalCsv(
"ExpressInput/Mediciones basicas/med_23.csv", "2")
f_entrada = FourierTransform.fourierTransform(entrada)
f_signal = FourierTransform.fourierTransform(signal)
fs = 1070
ExpressPlot.CombinedPlot() \
.setTitle("Mediciones espectro $f_s=1.07k$") \
.setXTitle("Frecuencia (Hz)") \
.setYTitle("Amplitud (% del total)") \
.extraPlot(
plotFunction,
{"fs": fs}) \
.addSignalPlot(
signal=f_entrada,
color="green",
name="Entrada"
) \
.addSignalPlot(
signal=f_signal,
color="orange",
name="Medicion sample and hold") \
.plotAndSave(
filename="ExpressOutput/espectro_subniquist2.png"
)
plt.show()
def SubniquistSpectrum(input, fs, filename):
config.GetConfigData().setFs(fs)
config.GetConfigData().setSampleCycle(5)
inputSpectrum = FourierTransform.fourierTransform(input)
output = SampleAndHold.getSampleAndHold().processInput(input, None, 1)
outputSpectrum = FourierTransform.fourierTransform(output)
ExpressPlot.CombinedPlot()\
.setTitle("Simulación espectro $f_s="+str(fs/1000)+"k$")\
.setXTitle("Frecuencia (hz)")\
.setYTitle("Potencia (% del total)") \
.extraPlot(
plotFunction,
{"fs": fs}) \
.addSignalPlot(
signal=inputSpectrum,
color="green",
name="Entrada"
)\
.addSignalPlot(
signal=outputSpectrum,
color="orange",
name="Salida sample and hold"
).plotAndSave(
filename="ExpressOutput/"+filename
)
def joaco_spectrum():
fs = 1000
#config.GetConfigData().setFs(fs)
#config.GetConfigData().setSampleCycle(5)
input = SignalsReadWrite.readSignal()
inputSpectrum = FourierTransform.fourierTransform(input)
ExpressPlot.CombinedPlot() \
.setTitle("Simulación espectro $f_s=" + str(fs / 1000) + "k$") \
.setXTitle("Frecuencia (hz)") \
.setYTitle("Potencia (% del total)") \
.extraPlot(
plotFunction,
{"fs": fs}) \
.addSignalPlot(
signal=inputSpectrum,
color="green",
name="Salida llave analógica"
).plotAndSave(
filename="ExpressOutput/espectro_09"
)
plt.show()
def modeSelected(self):
mode = self.buttonSelector.var.get()
inputSignal = PlotSignals.getSignalsData().signals[mode]
self.plotContainerTabs.tab1.plot(inputSignal)
self.plotContainerTabs.tab2.plot(FourierTransform.fourierTransform(inputSignal))
self.plotContainerTabs.autoscale()
self.currentSignal = inputSignal
def joaco_spectrum2():
fmuestra = 30000
dmuestra = 1 / fmuestra
xvar = arange(0, 2, dmuestra)
print(xvar)
# print(len(xvar))
periodSegundos = 0.2
period = periodSegundos / dmuestra
fc = 1000
fm = 200
yvar = np.zeros(len(xvar))
for i in range(len(yvar)):
if i % period <= period * 0.25:
yvar[i] = 1 #*np.sin(2*np.pi*fc)*np.sin(2*np.pi*fm)
else:
yvar[i] = 0
s1 = Senial.Senial(xvar, yvar)
s1f = FourierTransform.fourierTransform(s1)
xaux = s1f.xvar
tau = period * 0.25
print(1 / periodSegundos)
yaux = [abs(np.sinc(it * 0.25)) for it in xaux]
lxvar = len(s1f.xvar) / 2
lxvar2 = len(xaux) / 2
ExpressPlot.CombinedPlot()\
.setTitle("Espectro")\
.setXTitle("Frecuencia (Hz)")\
.setYTitle("Ampltiud (%)")\
.addSignalPlot(
signal=Senial.Senial(s1f.xvar, s1f.values), color="blue",name="espectro1")\
.addSignalPlot(
signal=Senial.Senial(xaux, yaux),
color="orange",
name="sinc"
)\
.plotAndSave("testjoaco.png")
# plt.plot(xaux,yaux,color="orange")
plt.show()
def spectra_plot(medcsv, simxml, out, fmax=None):
fmed = []
pmed = []
with open(medcsv, 'rt') as csvfile:
reader = list(csv.reader(csvfile))
# hola = csv.reader(csvfile)
reader.pop(0) # saco el header, me quedo solo con las mediciones
if fmax is None:
fmax = float(reader[-1][0])
for row in reader:
f = float(row[0])
if f > fmax:
break
fmed.append(f)
pmed.append((10**(float(row[1]) / 20))**2)
#plt.plot(fmed, pmed)
#plt.show()
s1 = Senial.Senial(fmed, pmed)
s_xml = SignalsReadWrite.readSignal(simxml)
s2 = FourierTransform.fourierTransform(s_xml)
fsim = []
psim = []
for f in s2.xvar:
if f < 0:
continue
if f > fmax:
break
fsim.append(f)
psim.append(s2.values[s2.xvar.index(f)])
s2.xvar = fsim
s2.values = psim
psum = sum(s2.values)
s2.values = [v / psum * 100 for v in s2.values]
psum = sum(pmed)
s1.values = [v / psum * 100 for v in s1.values]
ExpressPlot.CombinedPlot()\
.setTitle(" ")\
.setXTitle("Frecuencia (Hz)")\
.setYTitle("Potencia (% de total)")\
.addSignalPlot(
signal=s1,
color="orange",
name="Medido"
)\
.addSignalPlot(
signal=s2,
color="blue",
name="Simulado"
)\
.plotAndSave(
filename=out
)
plt.show()