def _reset_nest(self, data, nest=None):
n = data[10]
if nest is None:
k,m = data[5],len(data[0])
nest = m+k+1 # this is the maximum bound for nest
else:
if not n <= nest:
raise ValueError("`nest` can only be increased")
t, c, fpint, nrdata = [np.resize(data[n], nest) for n in [8,9,11,12]]
args = data[:8] + (t,c,n,fpint,nrdata,data[13])
data = dfitpack.fpcurf1(*args)
return data
def _reset_nest(self, data, nest=None):
n = data[10]
if nest is None:
k,m = data[5],len(data[0])
nest = m+k+1 # this is the maximum bound for nest
else:
if not n <= nest:
raise ValueError("`nest` can only be increased")
t, c, fpint, nrdata = [np.resize(data[n], nest) for n in [8,9,11,12]]
args = data[:8] + (t,c,n,fpint,nrdata,data[13])
data = dfitpack.fpcurf1(*args)
return data
def _reset_nest(self, data, nest=None):
n = data[10]
if nest is None:
k, m = data[5], len(data[0])
nest = m + k + 1 # this is the maximum bound for nest
else:
assert n <= nest, "nest can only be increased"
t, c, fpint, nrdata = data[8].copy(), data[9].copy(), data[11].copy(), data[12].copy()
t.resize(nest)
c.resize(nest)
fpint.resize(nest)
nrdata.resize(nest)
args = data[:8] + (t, c, n, fpint, nrdata, data[13])
data = dfitpack.fpcurf1(*args)
return data
def _reset_nest(self, data, nest=None):
n = data[10]
if nest is None:
k,m = data[5],len(data[0])
nest = m+k+1 # this is the maximum bound for nest
else:
assert n<=nest,"nest can only be increased"
t,c,fpint,nrdata = data[8].copy(),data[9].copy(),\
data[11].copy(),data[12].copy()
t.resize(nest)
c.resize(nest)
fpint.resize(nest)
nrdata.resize(nest)
args = data[:8] + (t,c,n,fpint,nrdata,data[13])
data = dfitpack.fpcurf1(*args)
return data
def set_smoothing_factor(self, s):
""" Continue spline computation with the given smoothing
factor s and with the knots found at the last call.
"""
data = self._data
if data[6] == -1:
warnings.warn("smoothing factor unchanged for" "LSQ spline with fixed knots")
return
args = data[:6] + (s,) + data[7:]
data = dfitpack.fpcurf1(*args)
if data[-1] == 1:
# nest too small, setting to maximum bound
data = self._reset_nest(data)
self._data = data
self._reset_class()
def set_smoothing_factor(self, s):
""" Continue spline computation with the given smoothing
factor s and with the knots found at the last call.
"""
data = self._data
if data[6] == -1:
warnings.warn('smoothing factor unchanged for'
'LSQ spline with fixed knots')
return
args = data[:6] + (s, ) + data[7:]
data = dfitpack.fpcurf1(*args)
if data[-1] == 1:
# nest too small, setting to maximum bound
data = self._reset_nest(data)
self._data = data
self._reset_class()
