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# $Id$ |
# $Id$ |
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from escript.escript import * |
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from escript.modelframe import Model |
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from math import log |
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class Sequencer(Model): |
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"""@brief runs through time until t_end is reached. |
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from esys.modelframe import Model |
@param t_end (in) - model is terminate when t_end is passed (default Model.UNDEF_DT) |
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from esys.escript import * |
@param dt_max (in) - maximum time step size (default Model.UNDEF_DT) |
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from math import log |
@param t (out) - current time |
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""" |
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def __init__(self,debug=False): |
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Model.__init__(self,debug=debug) |
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self.declareParameter(t=0., \ |
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t_end=Model.UNDEF_DT, \ |
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dt_max=Model.UNDEF_DT) |
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def doInitialization(self): |
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self.__t_old=self.t |
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def doStepPreprocessing(self,dt): |
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self.t=self.__t_old+dt |
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def doStepPostprocessing(self,dt): |
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self.__t_old=self.t |
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def finalize(self): |
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"""true when t has reached t_end""" |
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return self.t>=self.t_end |
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def getSafeTimeStepSize(self,dt): |
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"""returns dt_max""" |
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return self.dt_max |
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class GausseanProfile(Model): |
class GausseanProfile(Model): |
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"""@brief generates a gaussean profile at center x_c, width width and height A over a domain |
"""@brief generates a gaussean profile at center x_c, width width and height A over a domain |
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@param A (in) - height of the profile. A maybe a vector. (default 1.) |
@param A (in) - height of the profile. A maybe a vector. (default 1.) |
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@param width (in) - width of the profile (default 0.1) |
@param width (in) - width of the profile (default 0.1) |
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@param r (in) - radius of the circle (default = 0) |
@param r (in) - radius of the circle (default = 0) |
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@param out (out) - profile |
@param out (callable) - profile |
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In the case that the spatial dimension is two, The third component of x_c is dropped |
In the case that the spatial dimension is two, The third component of x_c is dropped |
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""" |
""" |
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def __init__(self,debug=False): |
def __init__(self,debug=False): |
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Model.__init__(self,debug=debug) |
Model.__init__(self,debug=debug) |
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self.declareParameter(domain=None, x_c=numarray.zeros([3]),A=1.,width=0.1,r=0) |
self.declareParameter(domain=None, |
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x_c=numarray.zeros([3]), |
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A=1., |
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width=0.1, |
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r=0) |
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def out(self): |
def out(self): |
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x=self.domain.getX() |
x=self.domain.getX() |
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m=(l-self.r).whereNegative() |
m=(l-self.r).whereNegative() |
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return (m+(1.-m)*exp(-log(2.)*(l/self.width)**2))*self.A |
return (m+(1.-m)*exp(-log(2.)*(l/self.width)**2))*self.A |
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class InterpolateOverBox(Model): |
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""" |
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@brief returns values at each time. The values are defined through given values at time node. |
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@param domain (in) - domain |
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@param left_bottom_front (in) - coordinates of left,bottom,front corner of the box |
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@param right_top_back (in) - coordinates of the right, top, back corner of the box |
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@param value_left_bottom_front (in) - value at left,bottom,front corner |
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@param value_right_bottom_front (in) - value at right, bottom, front corner |
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@param value_left_top_front (in) - value at left,top,front corner |
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@param value_right_top_front (in) - value at right,top,front corner |
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@param value_left_bottom_back (in) - value at left,bottom,back corner |
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@param value_right_bottom_back (in) - value at right,bottom,back corner |
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@param value_left_top_back (in) - value at left,top,back corner |
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@param value_right_top_back (in) - value at right,top,back corner |
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@param out (callable) - values at doamin locations by bilinear interpolation. for two dimensional domains back values are ignored. |
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""" |
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def __init__(self,debug=False): |
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Model.__init__(self,debug=debug) |
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self.declareParameter(domain=None, |
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left_bottom_front=[0.,0.,0.], |
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right_top_back=[1.,1.,1.], |
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value_left_bottom_front=0., |
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value_right_bottom_front=0., |
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value_left_top_front=0., |
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value_right_top_front=0., |
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value_left_bottom_back=0., |
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value_right_bottom_back=0., |
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value_left_top_back=0., |
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value_right_top_back=0.) |
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def out(self): |
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x=self.domain.getX() |
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if self.domain.getDim()==2: |
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f_right=(x[0]-self.left_bottom_front[0])/(self.right_top_back[0]-self.left_bottom_front[0]) |
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f_left=1.-f_right |
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f_top=(x[1]-self.left_bottom_front[1])/(self.right_top_back[1]-self.left_bottom_front[1]) |
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f_bottom=1.-f_top |
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out=self.value_left_bottom_front * f_left * f_bottom \ |
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+self.value_right_bottom_front* f_right * f_bottom \ |
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+self.value_left_top_front * f_left * f_top \ |
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+self.value_right_top_front * f_right * f_top |
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else: |
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f_right=(x[0]-self.left_bottom_front[0])/(self.right_top_back[0]-self.left_bottom_front[0]) |
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f_left=1.-f_right |
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f_top=(x[1]-self.left_bottom_front[1])/(self.right_top_back[1]-self.left_bottom_front[1]) |
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f_bottom=1.-f_top |
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f_back=(x[2]-self.left_bottom_front[1])/(self.right_top_back[2]-self.left_bottom_front[2]) |
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f_front=1.-f_back |
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out=self.value_left_bottom_front * f_left * f_bottom * f_front \ |
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+self.value_right_bottom_front* f_right * f_bottom * f_front \ |
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+self.value_left_top_front * f_left * f_top * f_front \ |
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+self.value_right_top_front * f_right * f_top * f_front \ |
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+self.value_left_bottom_back * f_left * f_bottom * f_back \ |
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+self.value_right_bottom_back * f_right * f_bottom * f_back \ |
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+self.value_left_top_back * f_left * f_top * f_back \ |
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+self.value_right_top_back * f_right * f_top * f_back |
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return out |
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class InterpolatedTimeProfile(Model): |
class InterpolatedTimeProfile(Model): |
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""" """ |
"""@brief returns values at each time. The values are defined through given values at time node. |
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value[i] defines the value at time nodes[i]. Between nodes linear interpolation is used. |
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for time t<nodes[0] value[0] is used and for t>nodes[l] values[l] is used where l=len(nodes)-1. |
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@param t (in) - current time |
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@param node (in) - list of time nodes |
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@param values (in) - list of values at time nodes |
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@param out (callable) - current value |
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""" |
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def __init__(self,debug=False): |
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Model.__init__(self,debug=debug) |
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self.declareParameter(t=0., \ |
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nodes=[0.,1.],\ |
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values=[1.,1.]) |
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def out(self): |
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l=len(self.nodes)-1 |
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t=self.t |
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if t<=self.nodes[0]: |
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return self.values[0] |
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else: |
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for i in range(1,l): |
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if t<self.nodes[i]: |
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m=(self.values[i-1]-self.values[i])/(self.nodes[i-1]-self.nodes[i]) |
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return m*(t-self.nodes[i-1])+self.values[i-1] |
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return self.values[l] |
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class LinearCombination(Model): |
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"""@brief returns a linear combination of the f0*v0+f1*v1+f2*v2+f3*v3+f4*v4 |
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@param f0 (in) numerical object or None (default: None) |
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@param v0 (in) numerical object or None (default: None) |
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@param f1 (in) numerical object or None (default: None) |
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@param v1 (in) numerical object or None (default: None) |
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@param f2 (in) numerical object or None (default: None) |
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@param v2 (in) numerical object or None (default: None) |
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@param f3 (in) numerical object or None (default: None) |
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@param v3 (in) numerical object or None (default: None) |
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@param f4 (in) numerical object or None (default: None) |
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@param v4 (in) numerical object or None (default: None) |
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@param out (callable) - current value |
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""" |
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def __init__(self,debug=False): |
def __init__(self,debug=False): |
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Model.__init__(self,debug=debug) |
Model.__init__(self,debug=debug) |
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self.declareParameter(t=[0.,1.],\ |
self.declareParameter(f0=None, \ |
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values=[1.,1.],\ |
v0=None, \ |
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out=0.) |
f1=None, \ |
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def doInitialization(self,t): |
v1=None, \ |
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self.__tn=t |
f2=None, \ |
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v2=None, \ |
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def doStep(self,dt): |
f3=None, \ |
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t=self.__tn+dt |
v3=None, \ |
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if t<=self.t[0]: |
f4=None, \ |
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self.out=self.values[0] |
v4=None) |
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else: |
def out(self): |
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for i in range(1,len(self.t)): |
if not self.f0==None and not self.v0==None: |
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if t<self.t[i]: |
fv0=self.f0*self.v0 |
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m=(self.values[i-1]-self.values[i])/(self.t[i-1]-self.t[i]) |
else: |
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self.out=m*(t-self.t[i-1])+self.values[i-1] |
fv0=None |
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self.out=self.t[len(self.t)-1] |
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self.__tn+=dt |
if not self.f1==None and not self.v1==None: |
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fv1=self.f1*self.v1 |
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else: |
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fv1=None |
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if not self.f2==None and not self.v2==None: |
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fv2=f2*v2 |
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else: |
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fv2=None |
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if not self.f3==None and not self.v3==None: |
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fv3=self.f3*self.v3 |
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else: |
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fv3=None |
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if not self.f4==None and not self.v4==None: |
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fv4=self.f4*self.v4 |
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else: |
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fv4=None |
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if fv0==None: |
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out=0. |
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else: |
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out=fv0 |
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if not fv1==None: out+=fv1 |
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if not fv2==None: out+=fv2 |
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if not fv3==None: out+=fv3 |
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return out |
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