外推很容易产生垃圾；试试这个。当然，许多不同的外推是可能的。一些产生明显的垃圾，一些不明显的垃圾，许多是不明确的。
""" extrapolate y,m,d data with scipy UnivariateSpline """
import numpy as np
from scipy.interpolate import UnivariateSpline
# pydoc scipy.interpolate.UnivariateSpline -- fitpack, unclear
from datetime import date
from pylab import * # ipython -pylab
__version__ = "denis 23oct"
def daynumber( y,m,d ):
""" 2005,1,1 -> 0 2006,1,1 -> 365 ... """
return date( y,m,d ).toordinal() - date( 2005,1,1 ).toordinal()
days, values = np.array([
(daynumber(2005,1,1), 1.2 ),
(daynumber(2005,4,1), 1.8 ),
(daynumber(2005,9,1), 5.3 ),
(daynumber(2005,10,1), 5.3 )
]).T
dayswanted = np.array([ daynumber( year, month, 1 )
for year in range( 2005, 2006+1 )
for month in range( 1, 12+1 )])
np.set_printoptions( 1 ) # .1f
print "days:", days
print "values:", values
print "dayswanted:", dayswanted
title( "extrapolation with scipy.interpolate.UnivariateSpline" )
plot( days, values, "o" )
for k in (1,2,3): # line parabola cubicspline
extrapolator = UnivariateSpline( days, values, k=k )
y = extrapolator( dayswanted )
label = "k=%d" % k
print label, y
plot( dayswanted, y, label=label ) # pylab
legend( loc="lower left" )
grid(True)
savefig( "extrapolate-UnivariateSpline.png", dpi=50 )
show()
补充：一张Scipy 票说，“scipy.interpolate 中 FITPACK 类的行为比文档让人相信的要复杂得多”——恕我直言，其他软件文档也是如此。