add split-explicit method by Knoth et al.

examples/boussinesq_2d_imex/plotgmrescounter.py

@@ -14,7 +14,9 @@
   udirk = np.load('dirk.npy')
   uimex = np.load('rkimex.npy')
   uref  = np.load('uref.npy')
+  usplit = np.load('split.npy')
 
+  print("Estimated discretisation error split explicit:  %5.3e" % ( np.linalg.norm(usplit.flatten() - uref.flatten(), np.inf)/np.linalg.norm(uref.flatten(),np.inf) ))
   print("Estimated discretisation error of DIRK: %5.3e" % ( np.linalg.norm(udirk.flatten() - uref.flatten(), np.inf)/np.linalg.norm(uref.flatten(),np.inf) ))
   print("Estimated discretisation error of RK-IMEX:  %5.3e" % ( np.linalg.norm(uimex.flatten() - uref.flatten(), np.inf)/np.linalg.norm(uref.flatten(),np.inf) ))
   print("Estimated discretisation error of SDC:  %5.3e" % ( np.linalg.norm(uend.flatten() - uref.flatten(), np.inf)/np.linalg.norm(uref.flatten(),np.inf) ))

examples/boussinesq_2d_imex/rungmrescounter.py

@@ -21,7 +21,7 @@
 
 from unflatten import unflatten
 
-from standard_integrators import dirk, bdf2, trapezoidal, rk_imex
+from standard_integrators import dirk, bdf2, trapezoidal, rk_imex, SplitExplicit
 
 if __name__ == "__main__":
 
@@ -46,8 +46,8 @@
 
     # setup parameters "in time"
     t0     = 0
-    Tend   = 3000   
-    Nsteps =  500
+    Tend   = 3000 
+    Nsteps = 500
     dt = Tend/float(Nsteps)
 
     # This comes as read-in for the problem class
@@ -96,19 +96,33 @@
     print("CFL number of acoustics (horizontal): %4.2f" % cfl_acoustic_hor)
     print("CFL number of acoustics (vertical):   %4.2f" % cfl_acoustic_ver)
 
-    dirkp = dirk(P, np.min([4,dirk_order]))
+    method_split = 'MIS4_4'
+#   method_split = 'RK3'
+    splitp = SplitExplicit(P, method_split, pparams) 
     u0 = uinit.values.flatten()
+    usplit = np.copy(u0)
+#   for i in range(0,Nsteps):
+    print(np.linalg.norm(usplit))  
+    for i in range(0,2*Nsteps):
+      usplit = splitp.timestep(usplit, dt/2)  
+    print(np.linalg.norm(usplit))
+
+    dirkp = dirk(P, np.min([4,dirk_order]))
     udirk = np.copy(u0)
     print("Running DIRK ....")
+    print(np.linalg.norm(udirk))  
     for i in range(0,Nsteps):
       udirk = dirkp.timestep(udirk, dt)  
+    print np.linalg.norm(udirk)
 
     rkimex = rk_imex(P, dirk_order)
     uimex  = np.copy(u0)
     dt_imex = dt
     print("Running RK-IMEX ....")
     for i in range(0,Nsteps):
+#     print("Running RK-IMEWX Step:  %4.2f" % dt_imex)
       uimex = rkimex.timestep(uimex, dt_imex)
+    print(np.linalg.norm(uimex))  
 
     # call main function to get things done...
     print("Running SDC...")
@@ -123,6 +137,7 @@
     for i in range(0,10*Nsteps):
       uref = rkimexref.timestep(uref, dt_ref)
 
+    usplit = unflatten(usplit, 4, P.N[0], P.N[1])
     udirk = unflatten(udirk, 4, P.N[0], P.N[1])
     uimex = unflatten(uimex, 4, P.N[0], P.N[1])
     uref  = unflatten(uref,  4, P.N[0], P.N[1])
@@ -131,8 +146,17 @@
     np.save('sdc', uend.values)
     np.save('dirk', udirk)
     np.save('rkimex', uimex)
+    np.save('split', usplit)
     np.save('uref', uref)
+
+    print "diff split  ",np.linalg.norm(uref-usplit)
+    print "diff dirk   ",np.linalg.norm(uref-udirk)
+    print "diff rkimex ",np.linalg.norm(uref-uimex)
+    print "diff sdc    ",np.linalg.norm(uref-uend.values)
 
+    print(" #### Logging report for Split    #### " )
+    print("Total number of matrix multiplcations: %5i" % splitp.logger.nsmall)
+
     print(" #### Logging report for DIRK-%1i #### " % dirkp.order)
     print("Number of calls to implicit solver: %5i" % dirkp.logger.solver_calls)
     print("Total number of GMRES iterations: %5i" % dirkp.logger.iterations)

examples/boussinesq_2d_imex/standard_integrators.py

@@ -270,8 +270,149 @@ def f_solve(self, b, alpha, u0):
     return sol
 
 #
-# A diagonally implicit Runge-Kutta method of order 2, 3 or 4
+#  Split-Explicit method
 #
+
+class SplitExplicit:
+
+  def __init__(self, problem, method, pparams):
+
+    assert isinstance(problem, boussinesq_2d_imex), "problem is wrong type of object"
+    self.Ndof = np.shape(problem.M)[0]
+    self.method = method
+    self.logger = logging()
+    self.problem = problem
+    self.pparams = pparams
+    self.NdofTher = 2*problem.N[0]*problem.N[1]
+    self.NdofMom = 2*problem.N[0]*problem.N[1]
+
+    print "dx  ",problem.h[0]
+    print "dz  ",problem.h[1]
+
+    assert self.method in ["MIS4_4","RK3"], 'Method must be MIS4_4'
+
+    if (self.method=='RK3'):
+      self.nstages=3
+      self.aRunge=np.zeros((4,4))
+      self.aRunge[0,0]= 1./3.
+      self.aRunge[1,1]= 1./2.
+      self.aRunge[2,2]= 1.
+      self.dRunge=np.zeros((4,4))
+      self.gRunge=np.zeros((4,4))
+    if (self.method=='MIS4_4'):
+      self.nstages=4
+      self.aRunge=np.zeros((4,4))
+      self.aRunge[0,0]=  0.38758444641450318
+      self.aRunge[1,0]=  -2.5318448354142823e-002
+      self.aRunge[1,1]=  0.38668943087310403
+      self.aRunge[2,0]=  0.20899983523553325
+      self.aRunge[2,1]= -0.45856648476371231
+      self.aRunge[2,2]=  0.43423187573425748
+      self.aRunge[3,0]= -0.10048822195663100
+      self.aRunge[3,1]= -0.46186171956333327
+      self.aRunge[3,2]=  0.83045062122462809
+      self.aRunge[3,3]=  0.27014914900250392
+      self.dRunge=np.zeros((4,4))
+      self.dRunge[1,1]=  0.52349249922385610
+      self.dRunge[2,1]=   1.1683374366893629
+      self.dRunge[2,2]= -0.75762080241712637
+      self.dRunge[3,1]=  -3.6477233846797109e-002
+      self.dRunge[3,2]=  0.56936148730740477
+      self.dRunge[3,3]=  0.47746263002599681
+      self.gRunge=np.zeros((4,4))
+      self.gRunge[1,1]=  0.13145089796226542
+      self.gRunge[2,1]= -0.36855857648747881
+      self.gRunge[2,2]=  0.33159232636600550
+      self.gRunge[3,1]=  -6.5767130537473045E-002
+      self.gRunge[3,2]=   4.0591093109036858E-002
+      self.gRunge[3,3]=   6.4902111640806712E-002
+    self.dtRunge=np.zeros(self.nstages);
+    for i in range(0,self.nstages):
+      self.dtRunge[i]=0  
+      temp=1.
+      for j in range(0,i+1):
+        self.dtRunge[i]=self.dtRunge[i]+self.aRunge[i,j]
+        temp=temp-self.dRunge[i,j]
+      self.dRunge[i,0]=temp
+      for j in range(0,i+1):
+        self.aRunge[i,j]=self.aRunge[i,j]/self.dtRunge[i]
+        self.gRunge[i,j]=self.gRunge[i,j]/self.dtRunge[i]
+
+    self.U  = np.zeros((self.Ndof,self.nstages+1))
+    self.F  = np.zeros((self.Ndof,self.nstages))
+    self.FSlow  = np.zeros((self.Ndof))
+    self.nsMin = 8
+    self.logger.nsmall = 0
+
+  def NumSmallTimeSteps(self , dx, dz, dt):   
+
+    cs = self.pparams['c_s']
+    ns = dt / (.9 / np.sqrt(1/(dx*dx)+1/(dz*dz)) / cs)
+    ns = max(np.int(np.ceil(ns)),self.nsMin)
+#   print " dx " , dx
+#   print " dz " , dz
+#   print " cs " , cs
+#   print 1/np.sqrt(1/(dx*dx)+1/(dz*dz))/cs
+#   print " dt ",dt," ns ",ns
+
+    return ns
+
+
+  def timestep(self, u0, dt):
+
+    self.U[:,0] = u0
+
+    self.ns = self.NumSmallTimeSteps(self.problem.h[0], self.problem.h[1], dt)
+
+    for i in range(0,self.nstages):
+      self.F[:,i] = self.f_slow(self.U[:,i])    
+      self.FSlow[:] = 0.
+      for j in range(0,i+1):
+        self.FSlow += (self.aRunge[i,j]*self.F[:,j] + self.gRunge[i,j]/dt*(self.U[:,j] - u0))    
+      self.U[:,i+1] = 0
+      for j in range(0,i+1):
+        self.U[:,i+1] += self.dRunge[i,j]*self.U[:,j]
+      nsLoc = np.int(np.ceil(self.ns*self.dtRunge[i]))
+      self.logger.nsmall += nsLoc
+      dtLoc = dt*self.dtRunge[i]
+      dTau = dtLoc/nsLoc
+      self.U[:,i+1] = self.VerletLin(self.U[:,i+1], self.FSlow, nsLoc, dTau)
+    u0 = self.U[:,self.nstages]
+    return  u0
+
+
+  def VerletLin(self, u0, FSlow, ns, dTau):
+    for i in range(0,ns): 
+      u0[0:self.NdofMom] += dTau * (self.f_fastMom(u0) + FSlow[0:self.NdofMom])
+      u0[self.NdofMom:self.Ndof] += dTau * (self.f_fastTher(u0) + FSlow[self.NdofMom:self.Ndof])
+
+    return u0    
+
+  def RK3Lin(self, u0, FSlow, ns, dTau):
+
+    u = u0
+    for i in range(0,ns): 
+      u = u0 + dTau/3.*(self.f_fast(u) + FSlow)
+      u = u0 + dTau/2.*(self.f_fast(u) + FSlow)
+      u = u0 + dTau*(self.f_fast(u) + FSlow)
+      u0 = u
+
+    return u0    
+
+  def f_slow(self, u):
+    return self.problem.D_upwind.dot(u)
+
+  def f_fast(self, u):
+    return self.problem.M.dot(u)
+
+  def f_fastMom(self, u):
+    return self.problem.M[0:self.NdofMom,self.NdofMom:self.Ndof]\
+                              .dot(u[self.NdofMom:self.Ndof])
+
+  def f_fastTher(self, u):
+    return self.problem.M[self.NdofMom:self.Ndof,0:self.NdofMom]\
+                              .dot(u[0:self.NdofMom])
+
 class dirk:
 
   def __init__(self, problem, order):
@@ -283,7 +424,7 @@ def __init__(self, problem, order):
     self.problem = problem
 
     assert self.order in [2,22,3,4], 'Order must be 2,22,3,4'
-    
+
     if (self.order==2):
       self.nstages = 1
       self.A       = np.zeros((1,1))