returns the interpolated from from the spline x can either be a scalar or a listable item, in which case a Numeric Float array will be returned and the multiple interpolations will be done somewhat more efficiently. If derivs is not False, return y, y', y'' instead of just y. Definition at line 95 of file spline.py. 00095 : 00096 """returns the interpolated from from the spline 00097 x can either be a scalar or a listable item, in which case a Numeric Float array will be 00098 returned and the multiple interpolations will be done somewhat more efficiently. 00099 If derivs is not False, return y, y', y'' instead of just y.""" 00100 if type(x) is types.IntType or type(x) is types.FloatType: 00101 if (x<xa[0] or x>xa[-1]): 00102 raise RangeError, "%f not in range (%f, %f) in splint()" % (x, xa[0], xa[-1]) 00103 00104 khi=max(searchsorted(xa,x),1) 00105 klo=khi-1 00106 h=float(xa[khi]-xa[klo]) 00107 a=(xa[khi]-x)/h; b=1.0-a 00108 ylo=ya[klo]; yhi=ya[khi]; y2lo=y2a[klo]; y2hi=y2a[khi] 00109 else: 00110 #if we got here, we are processing a list, and should do so more efficiently 00111 if (min(x)<xa[0] or max(x)>xa[-1]): 00112 raise RangeError, "(%f, %f) not in range (%f, %f) in splint()" % (min(x), max(x), xa[0], xa[-1]) 00113 00114 npoints=len(x) 00115 khi=clip(searchsorted(xa,x),1,len(xa)) 00116 00117 klo=khi-1 00118 xhi=take(xa, khi) 00119 xlo=take(xa, klo) 00120 yhi=take(ya, khi) 00121 ylo=take(ya, klo) 00122 y2hi=take(y2a, khi) 00123 y2lo=take(y2a, klo) 00124 00125 h=(xhi-xlo).astype(Float) 00126 a=(xhi-x)/h 00127 b=1.0-a 00128 00129 y=a*ylo+b*yhi+((a*a*a-a)*y2lo+(b*b*b-b)*y2hi)*(h*h)/6.0 00130 if derivs: 00131 return y, (yhi-ylo)/h+((3*b*b-1)*y2hi-(3*a*a-1)*y2lo)*h/6.0, b*y2hi+a*y2lo 00132 else: 00133 return y 00134 00135 def cubeinterpolate(xlist, ylist, x3):
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1.5.4