def subset(self,time1,time2):
"""
Returns a subset of the array between time1 and time2
"""
t0 = othertime.findNearest(time1,self.t)
t1 = othertime.findNearest(time2,self.t)
return self.t[t0:t1],self.y[...,t0:t1]
def subset(self, time1, time2):
"""
Returns a subset of the array between time1 and time2
"""
t0 = othertime.findNearest(time1, self.t)
t1 = othertime.findNearest(time2, self.t)
return self.t[t0:t1], self.y[..., t0:t1]
def window_index_time_slow(t,windowsize,overlap):
"""
Determines the indices for window start and end points of a time vector
The window does not need to be evenly spaced
Inputs:
t - list or array of datetime objects
windowsize - length of the window [seconds]
overlap - number of overlap points [seconds]
Returns: pt1,pt2 the start and end indices of each window
"""
try:
t=t.tolist()
except:
t=t
t1=t[0]
t2=t1 + timedelta(seconds=windowsize)
pt1=[0]
pt2=[othertime.findNearest(t2,t)]
while t2 < t[-1]:
t1 = t2 - timedelta(seconds=overlap)
t2 = t1 + timedelta(seconds=windowsize)
pt1.append(othertime.findNearest(t1,t))
pt2.append(othertime.findNearest(t2,t))
return pt1, pt2
def window_index_time_slow(t, windowsize, overlap):
"""
Determines the indices for window start and end points of a time vector
The window does not need to be evenly spaced
Inputs:
t - list or array of datetime objects
windowsize - length of the window [seconds]
overlap - number of overlap points [seconds]
Returns: pt1,pt2 the start and end indices of each window
"""
try:
t = t.tolist()
except:
t = t
t1 = t[0]
t2 = t1 + timedelta(seconds=windowsize)
pt1 = [0]
pt2 = [othertime.findNearest(t2, t)]
while t2 < t[-1]:
t1 = t2 - timedelta(seconds=overlap)
t2 = t1 + timedelta(seconds=windowsize)
pt1.append(othertime.findNearest(t1, t))
pt2.append(othertime.findNearest(t2, t))
return pt1, pt2
def subset(self,time1,time2):
"""
Returns a subset of the array between time1 and time2
"""
try:
t0 = othertime.findNearest(time1,self.t)
t1 = othertime.findNearest(time2,self.t)
except:
t0 = np.searchsorted(self.t, np.datetime64(time1))
t1 = np.searchsorted(self.t, np.datetime64(time2))
return self.t[t0:t1],self.y[...,t0:t1]
def __init__(self,tmod,ymod,tobs,yobs,**kwargs):
"""
Inputs:
tmod,tobs - vector of datetime object
ymod,yobs - vector of values
Keywords:
long_name: string containing variable's name (used for plotting)
units: string containing variable's units (used for plotting)
Note that tmod and tobs don't need to be the same length. yobs is
linearly interpolated onto tmod.
"""
self.__dict__.update(kwargs)
# Set the range inclusive of both observation and model result
time0 = max(tmod[0],tobs[0])
time1 = min(tmod[-1],tobs[-1])
if time1 < time0:
print 'Error - the two datasets have no overlapping period.'
return None
# Clip both the model and observation to this daterange
t0 = othertime.findNearest(time0,tmod)
t1 = othertime.findNearest(time1,tmod)
TSmod = timeseries(tmod[t0:t1],ymod[...,t0:t1])
t0 = othertime.findNearest(time0,tobs)
t1 = othertime.findNearest(time1,tobs)
self.TSobs = timeseries(tobs[t0:t1],yobs[...,t0:t1])
# Interpolate the observed value onto the model step
#tobs_i, yobs_i = TSobs.interp(tmod[t0:t1],axis=0)
#self.TSobs = timeseries(tobs_i, yobs_i)
# Interpolate the modeled value onto the observation time step
tmod_i, ymod_i = TSmod.interp(tobs[t0:t1],axis=-1)
self.TSmod = timeseries(tmod_i,ymod_i)
self.N = self.TSmod.t.shape[0]
if self.N==0:
print 'Error - zero model points detected'
return None
self.calcStats()
# Calculate the data limits
self.calc_data_lims()
def __init__(self, tmod, ymod, tobs, yobs, **kwargs):
"""
Inputs:
tmod,tobs - vector of datetime object
ymod,yobs - vector of values
Keywords:
long_name: string containing variable's name (used for plotting)
units: string containing variable's units (used for plotting)
Note that tmod and tobs don't need to be the same length. yobs is
linearly interpolated onto tmod.
"""
self.__dict__.update(kwargs)
# Set the range inclusive of both observation and model result
time0 = max(tmod[0], tobs[0])
time1 = min(tmod[-1], tobs[-1])
if time1 < time0:
print 'Error - the two datasets have no overlapping period.'
return None
# Clip both the model and observation to this daterange
t0 = othertime.findNearest(time0, tmod)
t1 = othertime.findNearest(time1, tmod)
TSmod = timeseries(tmod[t0:t1], ymod[..., t0:t1])
t0 = othertime.findNearest(time0, tobs)
t1 = othertime.findNearest(time1, tobs)
self.TSobs = timeseries(tobs[t0:t1], yobs[..., t0:t1])
# Interpolate the observed value onto the model step
#tobs_i, yobs_i = TSobs.interp(tmod[t0:t1],axis=0)
#self.TSobs = timeseries(tobs_i, yobs_i)
# Interpolate the modeled value onto the observation time step
tmod_i, ymod_i = TSmod.interp(tobs[t0:t1], axis=-1)
self.TSmod = timeseries(tmod_i, ymod_i)
self.N = self.TSmod.t.shape[0]
if self.N == 0:
print 'Error - zero model points detected'
return None
self.calcStats()
def get_tslice(self,time1,time2):
"""
Returns the time indices bounded by time1 and time2
"""
try:
t0 = othertime.findNearest(time1,self.t)
t1 = othertime.findNearest(time2,self.t)
except:
t0 = np.searchsorted(self.t, np.datetime64(time1))
t1 = np.searchsorted(self.t, np.datetime64(time2))
#t1 = min( self.Nt, t1+1)
t1+=1
if t1 > self.Nt:
t1=self.Nt
#t0-=1
#if t0<0:
# t0 = 0
return t0, t1
def get_time_indices(self, trange):
"""
Find the time indices
"""
if not self.multifile:
self.time = gettime(self._nc, self.timecoord)
else:
self._MF = MFncdap(self._ncfiles, timevar=self.timecoord)
self.time = self._MF.time
# Time
if trange == None:
self.t1 = 0
self.t2 = self.time.shape[0]
else:
self.t1 = othertime.findNearest(trange[0], self.time)
self.t2 = othertime.findNearest(trange[1], self.time)
if self.t1 == self.t2:
self.t2 += 1
self.nt = self.t2 - self.t1
def get_time_indices(self,trange):
"""
Find the time indices
"""
if not self.multifile:
self.time = gettime(self._nc,self.timecoord)
else:
self._MF = MFncdap(self._ncfiles,timevar=self.timecoord)
self.time = self._MF.time
# Time
if trange==None:
self.t1=0
self.t2 = self.time.shape[0]
else:
self.t1 = othertime.findNearest(trange[0],self.time)
self.t2 = othertime.findNearest(trange[1],self.time)
if self.t1==self.t2:
self.t2+=1
self.nt = self.t2 - self.t1
