def running_harmonic(self,omega,windowlength=3*86400.0,overlap=12*3600.0, plot=True):
"""
Running harmonic fit of the time series at frequency, omega.
windowlength - length of each time window [seconds]
overlap - overlap between windows [seconds]
"""
# Make sure that omega is a list
try:
len(omega)
except:
omega=[omega]
pt1,pt2 = window_index_time(self.t,windowlength,overlap)
npt = len(pt1)
tmid = []
amp = np.zeros((npt,))
phs = np.zeros((npt,))
ymean = np.zeros((npt,))
ii=-1
for t1,t2 in zip(pt1,pt2):
ii+=1
# Perform the harmonic fit on the segment
U = uspectra(self.t[t1:t2],self.y[t1:t2],frq=omega,method='lsqfast')
# Reference the phase to the start of the time series
amp[ii],phs[ii] = U.phsamp(phsbase = self.t[0])
# Return the mid time point
ind = np.floor(t1 + (t2-t1)/2)
tmid.append(self.t[ind])
# Return the fitted time series
ymean[ii] = self.y[t1:t2].mean()
#yout[t1:t2] += ymean + U.invfft()
tmid = np.asarray(tmid)
if plot:
plt.subplot(211)
self.plot()
plt.plot(tmid,ymean,'r')
plt.fill_between(tmid,ymean-amp,y2=ymean+amp,color=[0.5,0.5,0.5],alpha=0.5)
plt.legend(('Original Signal','Harmonic reconstruction'))
ax=plt.subplot(212)
plt.fill_between(tmid,amp,alpha=0.5)
plt.xticks(rotation=17)
plt.ylabel('Amplitude')
ax.set_xlim([self.t[0],self.t[-1]])
return tmid, amp, phs
def tidefit(self,frqnames=None,basetime=None,axis=-1):
"""
Perform a tidal harmonic fit to the data
Returns the amp, phase, frequencies and fitted time series
"""
# Get the tidal fruequencies
if frqnames == None:
# This returns the default frequencies from the uspectra class
frq,frqnames = getTideFreq(Fin=None)
else:
frq,frqnames = getTideFreq(Fin=frqnames)
# Call the uspectra method
U = uspectra(self.tsec,self.y,frq=frq,method='lsqfast')
amp,phs = U.phsamp(phsbase=basetime)
return amp, phs, frq, frqnames, U.invfft()
def tidefit(self, frqnames=None, basetime=None, axis=-1):
"""
Perform a tidal harmonic fit to the data
Returns the amp, phase, frequencies and fitted time series
"""
# Get the tidal fruequencies
if frqnames == None:
# This returns the default frequencies from the uspectra class
frq, frqnames = getTideFreq(Fin=None)
else:
frq, frqnames = getTideFreq(Fin=frqnames)
# Call the uspectra method
U = uspectra(self.tsec, self.y, frq=frq, method='lsqfast')
amp, phs = U.phsamp(phsbase=basetime)
return amp, phs, frq, frqnames, U.invfft()
def running_harmonic(self,
omega,
windowlength=3 * 86400.0,
overlap=12 * 3600.0,
plot=True):
"""
Running harmonic fit of the time series at frequency, omega.
windowlength - length of each time window [seconds]
overlap - overlap between windows [seconds]
"""
# Make sure that omega is a list
try:
len(omega)
except:
omega = [omega]
pt1, pt2 = window_index_time(self.t, windowlength, overlap)
npt = len(pt1)
tmid = []
amp = np.zeros((npt, ))
phs = np.zeros((npt, ))
ymean = np.zeros((npt, ))
ii = -1
for t1, t2 in zip(pt1, pt2):
ii += 1
# Perform the harmonic fit on the segment
U = uspectra(self.t[t1:t2],
self.y[t1:t2],
frq=omega,
method='lsqfast')
# Reference the phase to the start of the time series
amp[ii], phs[ii] = U.phsamp(phsbase=self.t[0])
# Return the mid time point
ind = np.floor(t1 + (t2 - t1) / 2)
tmid.append(self.t[ind])
# Return the fitted time series
ymean[ii] = self.y[t1:t2].mean()
#yout[t1:t2] += ymean + U.invfft()
tmid = np.asarray(tmid)
if plot:
plt.subplot(211)
self.plot()
plt.plot(tmid, ymean, 'r')
plt.fill_between(tmid,
ymean - amp,
y2=ymean + amp,
color=[0.5, 0.5, 0.5],
alpha=0.5)
plt.legend(('Original Signal', 'Harmonic reconstruction'))
ax = plt.subplot(212)
plt.fill_between(tmid, amp, alpha=0.5)
plt.xticks(rotation=17)
plt.ylabel('Amplitude')
ax.set_xlim([self.t[0], self.t[-1]])
return tmid, amp, phs
