def func_tranf(self):
chebyshev.raizes_unit(self)
poli_polos = np.poly(self.Sk)
polos = poli_polos.real
poli_zeros = list()
zeros = list()
for i in range(1, self.Nv+1):
Wz = 1 / np.cos((2*i - 1) * np.pi / (2*self.N))
poli_zeros.append(complex(0, -Wz))
poli_zeros.append(complex(0, Wz))
poli_zeros = np.poly(poli_zeros)
zeros = poli_zeros.real
aux = polos[-1]
for i in range(0, len(polos)):
polos[i] = polos[i] * zeros[-1]
for i in range(0, len(zeros)):
zeros[i] = zeros[i] * aux
if self.tipo == "PB":
num, den = signal.lp2lp(zeros, polos, self.Ws)
elif self.tipo == "PA":
num, den = signal.lp2hp(zeros, polos, self.Ws)
elif self.tipo == "PF":
num, den = signal.lp2bp(zeros, polos, self.Wo, self.Bs)
elif self.tipo == "RF":
num, den = signal.lp2bs(zeros, polos, self.Wo, self.Bs)
H = signal.TransferFunction(num, den)
self.H = H
return H
def transfunc(self, polos, **kwargs):
wc = kwargs.get('wc', 0)
w0 = kwargs.get('w0', 0)
Bw = kwargs.get('bw', self.Bp)
ordem = kwargs.get('ord', self.ordem)
resp = kwargs.get('response', self.tipo)
G_db = kwargs.get('G', self.G_bp)
fcn = 0
if resp == 'lp':
self.den_norm = np.real(np.poly(polos))
denm = np.zeros(len(self.den_norm))
for i in range(0, len(polos) + 1):
denm[i] = self.den_norm[i] * np.power(wc, i)
num = denm[-1]
fcn = signal.TransferFunction((pow(10, -G_db / 20.0)) * num, denm)
if resp == 'hp':
self.den_norm = np.real(np.poly(polos))
denm = np.zeros(len(polos) + 1)
for i in range(0, len(polos) + 1):
denm[i] = self.den_norm[len(polos) - i] * np.power(wc, i)
num = np.zeros(len(polos) + 1)
num[0] = denm[0]
fcn = signal.TransferFunction((pow(10, -G_db / 20.0)) * num, denm)
if (resp == 'bp'):
self.den_norm = np.real(np.poly(polos))
[num, den] = signal.lp2bp(self.den_norm[-1], self.den_norm, w0, Bw)
print('EMBAIXO')
print(self.den_norm)
fcn = signal.TransferFunction((pow(10, -G_db / 20.0)) * num, den)
if (resp == 'bs'):
self.den_norm = np.real(np.poly(polos))
[num, den] = signal.lp2bs(self.den_norm[-1], self.den_norm, w0, Bw)
fcn = signal.TransferFunction((pow(10, -G_db / 20.0)) * num, den)
self.fcn = fcn
return fcn
def transfunc(self, polos, **kwargs):
wc = kwargs.get('wc', 0)
w0 = kwargs.get('w0', 0)
Bw = kwargs.get('bw', self.Bp)
ordem = kwargs.get('ord', self.ordem)
fcn = 0
if self.tipo == 'lp':
self.den_norm = np.real(np.poly(polos))
denm = np.zeros(len(self.den_norm))
for i in range(0, len(polos) + 1):
denm[i] = self.den_norm[i] * np.power(wc, i)
num = denm[-1]
fcn = signal.TransferFunction(num, denm)
if self.tipo == 'hp':
self.den_norm = np.real(np.poly(polos))
denm = np.zeros(len(polos) + 1)
for i in range(0, len(polos) + 1):
denm[i] = self.den_norm[len(polos) - i] * np.power(wc, i)
num = np.zeros(len(polos) + 1)
num[0] = denm[0]
fcn = signal.TransferFunction(num, denm)
if (self.tipo == 'bp'):
self.den_norm = np.real(np.poly(polos))
[num, den] = signal.lp2bp(self.den_norm[-1], self.den_norm, w0, Bw)
fcn = signal.TransferFunction(num, den)
if (self.tipo == 'bs'):
self.den_norm = np.real(np.poly(polos))
[num, den] = signal.lp2bs(self.den_norm[-1], self.den_norm, w0, Bw)
fcn = signal.TransferFunction(num, den)
return fcn
def TransfFreq(self, zeros, polos, Kp):
if self.tipo == "PB":
num, den = signal.lp2lp(zeros, polos, Kp)
elif self.tipo == "PA":
num, den = signal.lp2hp(zeros, polos, Kp)
elif self.tipo == "PF":
num, den = signal.lp2bp(zeros, polos, Kp, self.Bp)
elif self.tipo == "RF":
num, den = signal.lp2bs(zeros, polos, Kp, self.Bp)
H = signal.TransferFunction(num, den)
return H
def func_tranf(self):
chebyshev.raizes_unit(self)
poli = np.poly(self.Sk)
coef = poli.real
D = list()
aux = 0
for i in range(-self.N, 1):
D.append(coef[aux] * pow(self.Wp, i))
aux = aux + 1
if self.N % 2 != 0:
if self.tipo == "PB":
num, den = signal.lp2lp(coef[-1], coef, self.Wp)
H = signal.TransferFunction(num[-1], den)
elif self.tipo == "PA":
num, den = signal.lp2hp(coef[-1], coef, self.Wp)
H = signal.TransferFunction(num, den)
elif self.tipo == "PF":
num, den = signal.lp2bp(coef[-1], coef, self.Wo, self.Bp)
H = signal.TransferFunction(num, den)
elif self.tipo == "RF":
num, den = signal.lp2bs(coef[-1], coef, self.Wo, self.Bp)
H = signal.TransferFunction(num, den)
else:
aux = 1 / np.sqrt(1 + self.e**2)
if self.tipo == "PB":
num, den = signal.lp2lp(coef[-1], coef, self.Wp)
H = signal.TransferFunction(num * aux, den)
elif self.tipo == "PA":
num, den = signal.lp2hp(coef[-1], coef, self.Wp)
H = signal.TransferFunction(num * aux, den)
elif self.tipo == "PF":
num, den = signal.lp2bp(coef[-1], coef, self.Wo, self.Bp)
H = signal.TransferFunction(num * aux, den)
elif self.tipo == "RF":
num, den = signal.lp2bs(coef[-1], coef, self.Wo, self.Bp)
H = signal.TransferFunction(num * aux, den)
self.H = H
return H
def transfunc(self, polos, **kwargs):
wp = kwargs.get('wp', 0)
w0 = kwargs.get('w0', 0)
Bw = kwargs.get('bw', self.Bp)
ordem = kwargs.get('ord', self.ordem())
resp = kwargs.get('response', self.tipo)
G_db = kwargs.get('G', self.G_bp)
fcn = 0
if resp == 'lp':
self.den_norm = np.real(np.poly(polos))
denm = np.zeros(len(self.den_norm))
for i in range(0, len(polos) + 1):
denm[i] = self.den_norm[i] * np.power(wp, i)
if (ordem % 2 == 0):
num = denm[-1] * (1 / np.sqrt(1 + np.power(self.eps, 2)))
else:
num = denm[-1]
fcn = signal.TransferFunction(pow(10, -G_db / 20.0) * num, denm)
if resp == 'hp':
self.den_norm = np.real(np.poly(polos))
denm = np.zeros(len(polos) + 1)
for i in range(0, len(polos) + 1):
denm[i] = self.den_norm[len(polos) - i] * np.power(wp, i)
num = np.zeros(len(polos) + 1)
if (self.ordem() % 2 == 0):
num[0] = denm[0] * (1 / np.sqrt(1 + np.power(self.eps, 2)))
else:
num[0] = denm[0]
fcn = signal.TransferFunction(pow(10, -G_db / 20.0) * num, denm)
if (resp == 'bp'):
self.den_norm = np.real(np.poly(polos))
[num, den] = signal.lp2bp(self.den_norm[-1], self.den_norm, w0, Bw)
if (self.ordem() % 2 == 0):
num[0] = num[0] * (1 / np.sqrt(1 + np.power(self.eps, 2)))
else:
num[0] = num[0]
fcn = signal.TransferFunction(num, den)
if (resp == 'bs'):
self.den_norm = np.real(np.poly(polos))
[num, den] = signal.lp2bs(self.den_norm[-1], self.den_norm, w0, Bw)
if (self.ordem() % 2 == 0):
num = num[::] * (1 / np.sqrt(1 + np.power(self.eps, 2)))
else:
num[-1] = num[-1]
fcn = signal.TransferFunction(num, den)
self.fcn = fcn
return fcn
def transf(self, ordem, tipo, **kwargs):
kf = kwargs.get('kf', 0)
w0 = kwargs.get('w0', 0)
Bw = kwargs.get('bw', 0)
G = kwargs.get('G', 1)
Glin = pow(10.0, G / 20.0)
if (tipo == 'lp'):
den = np.zeros(ordem + 1, dtype=float)
for i in range(0, ordem + 1):
den[i] = self.coeficientes[i] * pow(kf, i)
num = den[-1]
if (tipo == 'hp'):
num, den = signal.lp2hp(1, self.coeficientes, kf)
if (tipo == 'bp'):
num, den = signal.lp2bp(self.tf.den[-1], self.tf.den, w0, Bw)
self.tf = signal.TransferFunction(Glin * num, den)
return self.tf
def transfunc(self, zeros, polos, **kwargs):
ws = kwargs.get('ws', 0)
w0 = kwargs.get('w0', 0)
Bw = kwargs.get('bw', self.Bs)
G_db = kwargs.get('G', self.G_bp)
ordem = kwargs.get('ord', self.ordem())
fcn = 0
if self.tipo == 'lp':
if(len(zeros) == 1):
self.num_norm = np.array([1])
else:
self.num_norm = np.real(np.poly(zeros))
self.den_norm = np.real(np.poly(polos))
numm = self.num_norm
denm = self.den_norm
for i in range(0, len(polos) + 1):
denm[i] = denm[i]*pow(ws, i)
for i in range(0, len(zeros)+1):
numm[i] = numm[i]*pow(ws, i)
if(self.ativo == True and len(polos) == 2):
k = 1
else:
k = denm[-1]/numm[-1]
fcn = signal.TransferFunction((pow(10, -G_db/20.0))*k*numm, denm)
if(self.tipo == 'hp'):
self.den_norm = np.real(np.poly(polos))
self.num_norm = np.real(np.poly(zeros))
numm = self.num_norm[::-1]
denm = self.den_norm[::-1]
for i in range(0, len(polos) + 1):
denm[i] = denm[i]*pow(ws, i)
for i in range(0, len(zeros)+1):
numm[i] = numm[i]*pow(ws, i)
if(ordem%2 != 0):
numm = np.append(numm, 0)
k = denm[0]/numm[0]
fcn = signal.TransferFunction((pow(10, -G_db/20.0))*k*numm, denm)
if(self.tipo == 'bp'):
self.den_norm = np.real(np.poly(polos))
self.num_norm = np.real(np.poly(zeros))
k = self.den_norm[-1]/self.num_norm[-1]
numm, denm = signal.lp2bp(k*self.num_norm, self.den_norm, w0, Bw)
fcn = signal.TransferFunction((pow(10, -G_db/20.0))*numm, denm)
self.fcn = fcn
return fcn
def get_max_emg(context, filename, order,f_bp1, f_bp2, f_lp, muscle):
with open(filename) as f:
reader = csv.reader(f, delimiter=",")
header = reader.next()
dataMax = np.array([[float(col) for col in row] for row in reader])
with open(filename) as f:
reader = csv.reader(f, delimiter=",")
header = reader.next()
dataMin = np.array([[float(col) for col in row] for row in reader])
fs = len(data)/(data[-1,0]-data[0,0])
fny = fs/2
try:
idx = header.index(muscle)
except ValueError:
return 0
data = data[:,idx]
## HIGH PASS FILTER
bp_low = f_bp1
bp_high = f_bp2
centerfreq = (bp_high+bp_low)/2
bandwidthfreq = (bp_high -bp_low)
(b,a) = butter(2,0.5)
# Transform to band pass
(b,a) = lp2bp(b,a,centerfreq/fny, bandwidthfreq/fny)
data = filtfilt(b,a,data)
data = np.abs(data )
## Low pass filter envelope
lp_low = f_lp
(b,a) = butter(2,lp_low/fny)
data = filtfilt(b,a,data)
## Get max values
dmax = np.max( data )
return (dmax)
def func_tranf(self):
butterworth.raizes_unit(self)
poli = list()
poli = np.poly(self.Sk)
coefReal = poli.real
if self.tipo == "PB":
num, den = signal.lp2lp(coefReal[-1], coefReal, self.Wc)
H = signal.TransferFunction(num, den)
elif self.tipo == "PA":
num, den = signal.lp2hp(coefReal[-1], coefReal, self.Wc)
H = signal.TransferFunction(num, den)
elif self.tipo == "PF":
num, den = signal.lp2bp(coefReal[-1], coefReal, self.Wo, self.Bw)
H = signal.TransferFunction(num, den)
elif self.tipo == "RF":
num, den = signal.lp2bs(coefReal[-1], coefReal, self.Wo, self.Bw)
H = signal.TransferFunction(num, den)
self.H = H
return H
def fun_trans(self):
k = self.raizes()
wc = self.freq_corte()
Bw = (wc[2] - wc[1])
self.nden = np.real(np.poly(k)) #denominador normalizado
den = np.zeros(
len(k)) #criando o array para o denominador transformado
if self.tipo == 'Passa-baixa':
[num, den] = sig.lp2lp(self.nden[-1], self.nden, wc[0])
FT = sig.TransferFunction(num,
den) #gerando a FT para a freq. de corte
if self.tipo == 'Passa-alta':
[num, den] = sig.lp2hp(self.nden[-1], self.nden, wc[0])
FT = sig.TransferFunction(num, den)
if self.tipo == 'Passa-faixa':
[num, den] = sig.lp2bp(self.nden[-1], self.nden, wc[0], Bw)
FT = sig.TransferFunction(num, den)
if self.tipo == 'Rejeita-faixa':
[num, den] = sig.lp2bs(self.nden[-1], self.nden, wc[0], Bw)
FT = sig.TransferFunction(num, den)
return FT
def fun_trans(self):
raizes = self.raizes()
wc = self.freq_corte()
n = self.ordem()
eps = self.epso()
nden = np.real(np.poly(raizes))
if (n % 2 == 0):
nnum = nden[-1] * (1 / np.sqrt(1 + np.power(eps, 2)))
else:
nnum = nden[-1]
if self.tipo == 'Passa-baixa':
[num, den] = sig.lp2lp(nnum, nden, wc)
if self.tipo == 'Passa-alta':
[num, den] = sig.lp2hp(nnum, nden, wc)
if self.tipo == 'Passa-faixa':
Bw = self.Wp2 - self.Wp1
[num, den] = sig.lp2bp(nnum, nden, wc, Bw)
if self.tipo == 'Rejeita-faixa':
Bw = self.Wp2 - self.Wp1
[num, den] = sig.lp2bs(nnum, nden, wc, Bw)
FT = sig.TransferFunction(num, den)
return FT
from scipy import signal
import matplotlib.pyplot as plt
lp = signal.lti([1.0], [1.0, 1.0])
bp = signal.lti(*signal.lp2bp(lp.num, lp.den))
w, mag_lp, p_lp = lp.bode()
w, mag_bp, p_bp = bp.bode(w)
plt.plot(w, mag_lp, label='Lowpass')
plt.plot(w, mag_bp, label='Bandpass')
plt.semilogx()
plt.grid()
plt.xlabel('Frequency [rad/s]')
plt.ylabel('Magnitude [dB]')
plt.legend()
ripple = 1 # dB
eps = np.sqrt(10**(ripple / 10) - 1)
# Diseño un Butter.
# z,p,k = sig.buttap(nn)
z, p, k = sig.besselap(nn, norm='delay')
num_lp, den_lp = sig.zpk2tf(z, p, k)
# paso de un Butter. a maxima planicidad si eps != 1
# num_lp_shift, den_lp_shift = sig.lp2lp(num_lp,den_lp, eps**(-1/nn) )
num_lp_shift, den_lp_shift = (num_lp, den_lp)
# obtengo la transferencia normalizada del pasabanda
num_bp_n, den_bp_n = sig.lp2bp(num_lp_shift, den_lp_shift, wo=1, bw=1 / .253)
# obtengo la transferencia desnormalizada del pasabanda
num_bp, den_bp = sig.lp2bp(num_lp_shift, den_lp_shift, wo=8.367, bw=33)
# Averiguo los polos y ceros
z_bp_n, p_bp_n, k_bp_n = sig.tf2zpk(num_bp_n, den_bp_n)
str_aux = 'Pasabanda normalizado'
print(str_aux)
print('-' * len(str_aux))
this_lti = sig.TransferFunction(num_bp_n, den_bp_n)
pretty_print_lti(this_lti)
print('\n\n')
from splane import analyze_sys, pzmap, grpDelay, bodePlot, pretty_print_lti
nn = 2 # orden
ripple = 1 # dB
eps = np.sqrt(10**(ripple / 10) - 1)
# Diseño un Butter.
z, p, k = sig.buttap(nn)
num_lp, den_lp = sig.zpk2tf(z, p, k)
# paso de un Butter. a maxima planicidad si eps != 1
num_lp_butter, den_lp_butter = sig.lp2lp(num_lp, den_lp, eps**(-1 / nn))
# obtengo la transferencia normalizada del pasabanda
num_bp_n, den_bp_n = sig.lp2bp(num_lp_butter, den_lp_butter, wo=1, bw=1 / .253)
# obtengo la transferencia desnormalizada del pasabanda
num_bp, den_bp = sig.lp2bp(num_lp_butter, den_lp_butter, wo=8.367, bw=33)
# Averiguo los polos y ceros
z_bp_n, p_bp_n, k_bp_n = sig.tf2zpk(num_bp_n, den_bp_n)
str_aux = 'Pasabanda normalizado'
print(str_aux)
print('-' * len(str_aux))
this_lti = sig.TransferFunction(num_bp_n, den_bp_n)
pretty_print_lti(this_lti)
print('\n\n')
# Freq. transformation
#######################
if aprox_type != 'LP':
print_console_alert('Frequency transformation LP -> ' + aprox_type)
if aprox_type == 'HP':
num, den = sig.lp2hp(lowpass_proto_lti.num, lowpass_proto_lti.den)
if aprox_type == 'BP':
num, den = sig.lp2bp(lowpass_proto_lti.num,
lowpass_proto_lti.den,
wo=1,
bw=BWbp)
xp_tf = sig.TransferFunction(num, den)
print_console_subtitle('Transformed transfer function')
pretty_print_lti(xp_tf)
print_console_subtitle('Cascade of second order systems (SOS' 's)')
xp_sos = tf2sos_analog(num, den)
pretty_print_SOS(xp_sos)
pretty_print_SOS(xp_sos, mode='omegayq')
print_console_subtitle('Respuesta en frecuencia')
analyze_sys(xp_sos, str_designed_filter, same_figs=False)