def SavGol(t,y,s,k):
c1 = SG.derivatives(s,k,0)
c2 = SG.derivatives(s,k,1)
ys = []
ydiff = []
xs =[]
m = (s-1)/2
for j in range(m,len(t)-m):
sum1 = 0.0
dev1 =0.0
for l in range(0,s):
sum1 = sum1 + c1[l]*y[j-m+l]
dev1 = dev1 + c2[l]*y[j-m+l]/(t[1]-t[0])
ys.append(sum1)
ydiff.append(dev1)
xs.append(t[j])
return (xs,ys,ydiff)
def Savitzky(x,y,s,k):
m = (s-1)/2
coeffs = SG.derivatives(s,k,0)
coeffs_1st = SG.derivatives(s,k,1)
xt = []
yt = []
y_diff =[]
for i in range(m,len(x)-m):
sum1 = 0.0
dev1 = 0.0
for j in range(0,s):
sum1 = sum1 + coeffs[j]*y[i-m+j]
dev1 = dev1 + coeffs_1st[j]*y[i-m+j]
yt.append(sum1)
y_diff.append(dev1)
xt.append(x[i])
return (yt,y_diff,xt)
y = np.zeros(len(x))
for i in range(len(x)):
y[i] = np.sin(x[i]*10.0*pi/x[-1])+random.random()/10.0
Q=0.1
R = 0.7
#xks,ydiffs = deriv(x,y)
ks = kalman.kalman(x,y,Q,R)
ys = []
ydiff = []
xs =[]
s =11
k = 5
c1 = SG.derivatives(s,k,0)
c2 = SG.derivatives(s,k,1)
m = (s-1)/2
for j in range(m,len(y)-m):
sum1 = 0.0
dev1 =0.0
for l in range(0,s):
sum1 = sum1 + c1[l]*y[j-m+l]
dev1 = dev1 + c2[l]*y[j-m+l]/(x[1]-x[0])
ys.append(sum1)
ydiff.append(dev1)
xs.append(x[j])
plt.subplot(211)
plt.plot(x,y,label='real')
