def recalc(self):
xvalues = self.rib1.profile_2d.XValues
#Map Ballooning
if len(self.miniribs) == 0: # In case there is no midrib, The Cell represents itself!
self._cells = [self] # The cell itself is its cell, clear?
self._phi = [self.rib1.ballooning(x)+self.rib2.ballooning(x) for x in xvalues]
self._yvalues = [0, 1]
else:
ballooning = [self.rib1.ballooning[x]+self.rib2.ballooning[x] for x in xvalues]
self._cells = []
miniribs = sorted(self.miniribs, key=lambda rib: rib.xvalue) # sort for cell-wide (x) argument.
self._yvalues = [0] + [i.xvalue for i in miniribs] + [1]
prof1 = self.rib1.profile_3d
for minirib in miniribs:
big = self._midrib(minirib.xvalue, True).data # SUPER!!!?
small = self._midrib(minirib.xvalue, False).data
for i in range(len(big)): # Calculate Rib
fakt = minirib.function(xvalues[i]) # factor ballooned/unb. (0-1)
point = small[i]+fakt*(big[i]-small[i])
minirib.data.append(point)
prof2 = minirib
self._cells.append(BasicCell(prof1, prof2, [])) # leave ballooning empty
prof1 = prof2
#Last Sub-Cell
self._cells.append(BasicCell(prof1, self.rib2.profile_3d, []))
# Calculate ballooning for each x-value
# Hamilton Principle:
# http://en.wikipedia.org/wiki/Hamilton%27s_principle
# http://en.wikipedia.org/wiki/Hamilton%E2%80%93Jacobi_equation
# b' = b
# f' = f*(l/l') [f=b/l]
for i in range(len(prof1.data)):
bl = ballooning[i]+1 # B/L old
l = norm(self.prof2.data[i]-self.prof1.data[i]) # L
lnew = sum([norm(c.prof1.data[i]-c.prof2.data[i]) for c in self._cells]) # L-NEW
for c in self._cells:
c._phi.append(arsinc(1/(bl*l/lnew))) # B/L NEW
def _calcballooning(self):
xvalues = self.rib1.profile_2d.XValues
balloon = [self.rib1.ballooning[i] + self.rib2.ballooning[i] for i in xvalues]
self._phi = [arsinc(1/(1+i)) for i in balloon]
BasicCell._calcballooning(self)
