__init__

def __init__ (   self,   x,   y,   lowerSlope = None,   upperSlope = None,   XConversions = None,   YConversions = None,   cubic_spline = True   ) create the InterpolatingFunction Parameters: x  the array of abscissas y  the array of ordinates lowerSlope  if not None, the slope at the lower end of the spline. If None, use 'natural' spline with zero second derivative upperSlope  if not None, the slope at the lower end of the spline. If None, use 'natural' spline with zero second derivative XConversions  a list of functions used for transforming the abscissa YConversions  a list of functions used for tranforming the ordinate cubic_spline  is true for a normal cubic spline, false for piecewise linear interpolation Definition at line 1129 of file C2Functions.py. 01129 : 01130 C2Function.__init__(self) #just on general principle, right now this does nothing 01131 self.SetDomain(min(x), max(x)) 01132 self.Xraw=_numeric.array(x) #keep a private copy 01133 self.xInverted=False 01134 01135 if YConversions is not None: self.YConversions=YConversions #inherit from class if not passed 01136 if self.YConversions is None: 01137 self.fYin, self.fYinP, self.fYinPP, self.fYout = self.YConversions = _identity, _one, _zero, _identity 01138 self.yNonLin=False 01139 F=self.F=_numeric.array(y) 01140 else: 01141 self.fYin, self.fYinP, self.fYinPP, self.fYout = self.YConversions 01142 self.yNonLin=True 01143 self.F=_numeric.array([self.fYin(q) for q in y]) 01144 if lowerSlope is not None: lowerSlope *= self.fYinP(y[0]) 01145 if upperSlope is not None: upperSlope *= self.fYinP(y[-1]) 01146 01147 if XConversions is not None: self.XConversions=XConversions #inherit from class if not passed 01148 if self.XConversions is None: 01149 self.fXin, self.fXinP, self.fXinPP, self.fXout = self.XConversions = _identity, _one, _zero, _identity 01150 self.xNonLin=False 01151 self.X=_numeric.array(x) 01152 else: 01153 self.fXin, self.fXinP, self.fXinPP, self.fXout = self.XConversions 01154 self.xNonLin=True 01155 self.X=_numeric.array([self.fXin(q) for q in x]) 01156 if lowerSlope is not None: lowerSlope /= self.fXinP(x[0]) 01157 if upperSlope is not None: upperSlope /= self.fXinP(x[-1]) 01158 01159 if self.X[0] > self.X[-1]: #make sure our transformed X array is increasing 01160 self.Xraw=self.Xraw[::-1] 01161 self.X=self.X[::-1] 01162 self.F=self.F[::-1] 01163 self.xInverted=True 01164 lowerSlope, upperSlope=upperSlope, lowerSlope 01165 01166 dx=self.X[1:]-self.X[:-1] 01167 if min(dx) < 0 or min(self.X) < self.X[0] or max(self.X) > self.X[-1]: 01168 raise C2Exception("monotonicity error in X values for interpolating function: " + 01169 _numeric.array_str(self.X)) 01170 if cubic_spline: 01171 self.y2=_spline(self.X, self.F, yp1=lowerSlope, ypn=upperSlope) 01172 else: 01173 #use a dummy y2 table if we are not really cubic splining 01174 self.y2=_numeric.zeros(len(self.X), _numeric_float) ##

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