triaxial test with CohFrictMat

Hello everybody when I run this triaxial test code In the case where setCohesionNow=True
I get this error terminate called after throwing an instance of 'std::runtime_error'
  what(): Undefined or ambiguous IPhys dispatch for types FrictMat and CohFrictMat.(core dump)
Please guide me.

from yade import pack
############################################
### DEFINING VARIABLES AND MATERIALS ###
############################################

# The following 5 lines will be used later for batch execution
nRead=readParamsFromTable(
 num_spheres=1000,# number of spheres
 compFricDegree = 30, # contact friction during the confining phase
 key='_triax_base_', # put you simulation's name here
 unknownOk=True
)
from yade.params import table

num_spheres=table.num_spheres# number of spheres
key=table.key
targetPorosity = 0.34#the porosity we want for the packing
compFricDegree = table.compFricDegree # initial contact friction during the confining phase (will be decreased during the REFD compaction process)
finalFricDegree = 30 # contact friction during the deviatoric loading
rate=-0.02 # loading rate (strain rate)
damp=0.2 # damping coefficient
stabilityThreshold=0.01 # we test unbalancedForce against this value in different loops (see below)
young=5e6 # contact stiffness
mn,mx=Vector3(0,0,0),Vector3(.8,.8,.8) # corners of the initial packing

## create materials for spheres and trash
O.materials.append(FrictMat(young=young,poisson=0.5,frictionAngle=radians(compFricDegree),density=2600,label='spheres'))
O.materials.append(CohFrictMat(young=1e6,poisson=0.1,density=1400,label='trash',frictionAngle=radians(compFricDegree),
    isCohesive=True,
    normalCohesion=50000000,
    shearCohesion=50000000,
))
O.materials.append(FrictMat(young=young,poisson=0.5,frictionAngle=0,density=0,label='walls'))

## create walls around the packing
walls=aabbWalls([mn,mx],thickness=0,material='walls')
wallIds=O.bodies.append(walls)

## use a SpherePack object to generate a random loose particles packing
sp=pack.SpherePack()
spSmall = pack.SpherePack()
spBig = pack.SpherePack()

sp.makeCloud((0,0,0),(.8,.8,.8),psdSizes=[.01,.0105,.011,.078,.08,.081],psdCumm=[0,.97,.9868,.987,.99,1],distributeMass=False,seed=1)

for ss in sp: #split SpherePack into two other packs based on the particle size
  r = ss[1]
  if r > .05/2:# please note that you feed diameters nor radii in psdSizes, that is why I divide it by 2
    spBig.add(ss[0],ss[1])

  else:
    spSmall.add(ss[0],ss[1])
# add only the spheres that you want to replace and replace them with clump1
spSmall.toSimulation(material='spheres')
ct1 = clumpTemplate([1,1],[[0,0,0],[0,0,1]])

O.bodies.replaceByClumps( [ct1] , [1], discretization = 20 )
for b in O.bodies:
        if b.isClumpMember: b.shape.color=(1,1,1)
####product trash#####
a=[0,.005,.01,.015,.02,.025,.03,.035]
b=[0,.005,.01,.015,.02,.025,.03,.035,.04,.045,.05,.055,.06,.065,.07,.075]
c=[.005]
d=[]
e=[.005]
g=e*128
for i in a:
 for j in b:
  for k in c:
   d.append((i,j,k))
#add the remaining spheres stored in the other sphere pack
spBig.toSimulation(material='trash')
ct2 = clumpTemplate(g,d)
aa=O.bodies.replaceByClumps( [ct2] , [1], discretization = 20 )
for ii in aa:
  xx=ii[1]
  for jj in xx:
    O.bodies[jj].shape.color=(1,1,0)

#O.dt = 0
#O.step()
#for i in O.interactions:
    #i.phys.unp = i.geom.penetrationDepth

#############################
### DEFINING ENGINES ###
############################

triax=TriaxialStressController(
 ## TriaxialStressController will be used to control stress and strain. It controls particles size and plates positions.
 ## this control of boundary conditions was used for instance in http://dx.doi.org/10.1016/j.ijengsci.2008.07.002
 maxMultiplier=1.+2e4/young, # spheres growing factor (fast growth)
 finalMaxMultiplier=1.+2e3/young, # spheres growing factor (slow growth)
 thickness = 0,
 ## switch stress/strain control using a bitmask. What is a bitmask, huh?!
 ## Say x=1 if stess is controlled on x, else x=0. Same for for y and z, which are 1 or 0.
 ## Then an integer uniquely defining the combination of all these tests is: mask = x*1 + y*2 + z*4
 ## to put it differently, the mask is the integer whose binary representation is xyz, i.e.
 ## "100" (1) means "x", "110" (3) means "x and y", "111" (7) means "x and y and z", etc.
 stressMask = 7,
 internalCompaction=False, # If true the confining pressure is generated by growing particles
)

newton=NewtonIntegrator(damping=damp)

O.engines=[
 ForceResetter(),
 InsertionSortCollider([Bo1_Sphere_Aabb(),Bo1_Box_Aabb()]),
 InteractionLoop(
  [Ig2_Sphere_Sphere_ScGeom(),Ig2_Box_Sphere_ScGeom()],
  [Ip2_CohFrictMat_CohFrictMat_CohFrictPhys(
            setCohesionNow=True,
            setCohesionOnNewContacts=False,
            )],
        [Law2_ScGeom6D_CohFrictPhys_CohesionMoment(),Law2_ScGeom_FrictPhys_CundallStrack()]
 ),
 ## We will use the global stiffness of each body to determine an optimal timestep (see https://yade-dem.org/w/images/1/1b/Chareyre&Villard2005_licensed.pdf)
 GlobalStiffnessTimeStepper(active=1,timeStepUpdateInterval=100,timestepSafetyCoefficient=0.8),
 triax,
 TriaxialStateRecorder(iterPeriod=100,file='WallStresses'+table.key),
 newton
]

#Display spheres with 2 colors for seeing rotations better
Gl1_Sphere.stripes=0
if nRead==0: yade.qt.Controller(), yade.qt.View()

#######################################
### APPLYING CONFINING PRESSURE ###
#######################################

#the value of (isotropic) confining stress defines the target stress to be applied in all three directions
triax.goal1=triax.goal2=triax.goal3=-10000

while 1:
 print(O.iter)
 O.run(1000, True)
  ##the global unbalanced force on dynamic bodies, thus excluding boundaries, which are not at equilibrium
 unb=unbalancedForce()
 print ('unbalanced force:',unb,' mean stress: ',triax.meanStress)
 if unb<stabilityThreshold and abs(-10000-triax.meanStress)/10000<0.001:
  break

O.save('confinedState'+key+'.yade.gz')
#print ("### Isotropic state saved ###")

###################################################
### REACHING A SPECIFIED POROSITY PRECISELY ###
###################################################

### We will reach a prescribed value of porosity with the REFD algorithm
### (see http://dx.doi.org/10.2516/ogst/2012032 and
### http://www.geosyntheticssociety.org/Resources/Archive/GI/src/V9I2/GI-V9-N2-Paper1.pdf)

import sys #this is only for the flush() below
while triax.porosity>targetPorosity:
 ## we decrease friction value and apply it to all the bodies and contacts
 compFricDegree = 0.95*compFricDegree
 setContactFriction(radians(compFricDegree))
 print ("\r Friction: ",compFricDegree," porosity:",triax.porosity)
 sys.stdout.flush()
 ## while we run steps, triax will tend to grow particles as the packing
 ## keeps shrinking as a consequence of decreasing friction. Consequently
 ## porosity will decrease
 O.run(500,1)

O.save('compactedState'+key+'.yade.gz')
#print "### Compacted state saved ###"
O.pause()
print('print')
##############################
### DEVIATORIC LOADING ###
##############################

##We move to deviatoric loading, let us turn internal compaction off to keep particles sizes constant
triax.internalCompaction=False

## Change contact friction (remember that decreasing it would generate instantaneous instabilities)
setContactFriction(radians(finalFricDegree))

##set stress control on x and z, we will impose strain rate on y
triax.stressMask = 5
##now goal2 is the target strain rate
triax.goal2=rate
## we define the lateral stresses during the test, here the same 10kPa as for the initial confinement.
triax.goal1=-10000
triax.goal3=-10000

##we can change damping here. What is the effect in your opinion?
newton.damping=0.1

##Save temporary state in live memory. This state will be reloaded from the interface with the "reload" button.
O.saveTmp()

#####################################################
### Example of how to record and plot data ###
#####################################################

from yade import plot

### a function saving variables
def history():
 plot.addData(e11=-triax.strain[0], e22=-triax.strain[1], e33=-triax.strain[2],
        ev=-triax.strain[0]-triax.strain[1]-triax.strain[2],
      s11=-triax.stress(triax.wall_right_id)[0],
      s22=-triax.stress(triax.wall_top_id)[1],
      s33=-triax.stress(triax.wall_front_id)[2],
      i=O.iter)

if 1:
  ## include a periodic engine calling that function in the simulation loop
 O.engines=O.engines[0:5]+[PyRunner(iterPeriod=20,command='history()',label='recorder')]+O.engines[5:7]
  ##O.engines.insert(4,PyRunner(iterPeriod=20,command='history()',label='recorder'))
else:
  ## With the line above, we are recording some variables twice. We could in fact replace the previous
  ## TriaxialRecorder
  ## by our periodic engine. Uncomment the following line:
 O.engines[4]=PyRunner(iterPeriod=20,command='history()',label='recorder')

O.run(100000,True)
### declare what is to plot. "None" is for separating y and y2 axis
plot.plots={'i':('e11','e22','e33',None,'s11','s22','s33')}
### the traditional triaxial curves would be more like this:
##plot.plots={'e22':('s11','s22','s33',None,'ev')}

## display on the screen (doesn't work on VMware image it seems)
plot.plot()

##### PLAY THE SIMULATION HERE WITH "PLAY" BUTTON OR WITH THE COMMAND O.run(N) #####

## In that case we can still save the data to a text file at the the end of the simulation, with:
plot.saveDataTxt('results'+key)
##or even generate a script for gnuplot. Open another terminal and type "gnuplot plotScriptKEY.gnuplot:
plot.saveGnuplot('plotScript'+key)