Syntax error in PyRunner

Hello,

I am using Ubuntu 18.04, and Yade 2019-08-08.git-775ae74

I slightely changed https://.../script-session1.py and now get a syntax error in PyRunner line as follows:

ehsan@ehsan:~/Desktop/mycodes/3axtst$ /home/ehsan/yade/install/bin/yade-2019-08-08.git-775ae74 3axtst.py
Welcome to Yade 2019-08-08.git-775ae74
Using python version: 3.6.8 (default, Oct 7 2019, 12:59:55)
[GCC 8.3.0]
TCP python prompt on localhost:9000, auth cookie `sukesd'
XMLRPC info provider on http://localhost:21000
Running script 3axtst.py
Traceback (most recent call last):
  File "/home/ehsan/yade/install/bin/yade-2019-08-08.git-775ae74", line 336, in runScript
    execfile(script,globals())
  File "/usr/lib/python3/dist-packages/past/builtins/misc.py", line 81, in execfile
    code = compile(source, filename, "exec")
  File "3axtst.py", line 87
    PyRunner(iterPeriod=20,command='history()',label='recorder'),
           ^
SyntaxError: invalid syntax
[[ ^L clears screen, ^U kills line. F12 controller, F11 3D view (press "h" in 3D view for help), F10 both, F9 generator, F8 plot. ]]

In [1]:

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Reading wiki and he source code, I can't find the problem. Would you help me with that please?
Also, please let me know if the code has any other problem.

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My code:

############################################################################################################################
######### TRIAXIAL PROBLEM, Y IS THE VERTICAL AXIS, X IS THE RIGHT AXIS, Z IS THE FRONT AXIS #########
############################################################################################################################

import numpy as np
import math
from yade import pack, plot, qt, export, utils
from datetime import datetime
from yade.params import table

######################################################
######### DEFINING VARIABLES #########

nRead=readParamsFromTable(
 num_spheres=1500, # number of spheres
 compFricDegree = 30, # contact friction during the confining phase
 key='_triax_base_', # put you simulation's name here
 unknownOk=True
)

num_spheres=table.num_spheres # number of spheres
key=table.key
targetPorosity = 0.43 #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=15e6 # contact stiffness
poisson=0.4
mn,mx=Vector3(0,0,0),Vector3(10,10,10) # corners of the initial packing
sigmaIso=-50e3 # confining pressure

######################################################
######### DEFINING MATERIALS #########

O.materials.append(FrictMat(young=young,poisson=poisson,frictionAngle=radians(compFricDegree),density=2600,label='spheres')) # particles(spheres)
O.materials.append(FrictMat(young=young,poisson=poisson,frictionAngle=0,density=0,label='frictionlesswalls')) # walls(plates)

####################################################
######### DEFINING PACKING #########

walls=aabbWalls([mn,mx],thickness=0,material='frictionlesswalls') # create walls around the packing
wallIds=O.bodies.append(walls) # assigning walls to O.bodies
sp=pack.SpherePack() # generating a random loose particles packing, an empty cloud which contains only geometrical information
clumps=False # Rigid aggregate of bodies, turn this true for the same example with clumps
if clumps:
 volume = (mx[0]-mn[0])*(mx[1]-mn[1])*(mx[2]-mn[2]) # volume of the box given by minCorner and maxCorner (specimen)
 mean_rad = pow(0.09*volume/num_spheres,0.3333) # approximate mean radius of the future dense packing for latter use
 c1=pack.SpherePack([((-0.2*mean_rad,0,0),0.5*mean_rad),((0.2*mean_rad,0,0),0.5*mean_rad)]) # define a unique clump type (we could have many, see clumpCloud documentation)
 sp.makeClumpCloud(mn,mx,[c1],periodic=False) # generate positions, put spheres with defined radius inside box given by corners mn and mx
 sp.toSimulation(material='spheres') # input positions in the simulation, create particles and add them to the simulation
 O.bodies.updateClumpProperties() # get more accurate clump masses/volumes/inertia
else:
 sp.makeCloud(mn,mx,-1,0.3333,num_spheres,False, 0.95,seed=1) #"seed" make the "random" generation always the same
 O.bodies.append([sphere(center,rad,material='spheres') for center,rad in sp])
 #or alternatively (higher level function doing exactly the same):
 #sp.toSimulation(material='spheres')

##########################################################
######### DEFINING TRIAXIAL TEST #########

triax=TriaxialStressController( # TriaxialStressController will be used to control stress and strain. It controls particles size and plates positions.
 maxMultiplier=1.+2e4/young, # spheres growing factor (fast growth)
 finalMaxMultiplier=1.+2e3/young, # spheres growing factor (slow growth)
 thickness = 0,
 stressMask = 7,
 internalCompaction=False # If true the confining pressure is generated by growing particles
)

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

newton=NewtonIntegrator(damping=damp)
O.engines=[
 ForceResetter(),
 InsertionSortCollider([Bo1_Sphere_Aabb(),Bo1_Box_Aabb()]),
 InteractionLoop(
  [Ig2_Sphere_Sphere_ScGeom(),Ig2_Box_Sphere_ScGeom()],
  [Ip2_FrictMat_FrictMat_FrictPhys()],
  [Law2_ScGeom_FrictPhys_CundallStrack()]
 ),
 GlobalStiffnessTimeStepper(active=1,timeStepUpdateInterval=100,timestepSafetyCoefficient=0.8), # will use the global stiffness of each body to determine an optimal timestep
 triax,
 TriaxialStateRecorder(iterPeriod=100,file='WallStresses'+table.key),
 newton
 PyRunner(iterPeriod=20,command='history()',label='recorder'),
 PyRunner(command='checkUnbalanced()',realPeriod=2)
]
Gl1_Sphere.stripes=True # Display spheres with different colors for seeing rotations better
if nRead==0: yade.qt.Controller(), yade.qt.View()

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

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

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

# We will reach a prescribed value of porosity with the REFD algorithm
#import sys #this is only for the flush() below
#while triax.porosity>targetPorosity:
 #compFricDegree = 0.95*compFricDegree # decrease friction value
 #setContactFriction(radians(compFricDegree)) # apply compFricDegree to all the bodies and contacts
 #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 ###"

######################################################
######### DEVIATORIC LOADING #########

triax.internalCompaction=False # turn internal compaction off to keep particles sizes constant
#setContactFriction(radians(finalFricDegree)) # change contact friction (remember that decreasing it would generate instantaneous instabilities)
triax.stressMask = 5 # set stress control on x and z, we will impose strain rate on y, now goal2 is the target strain rate
triax.goal2=rate # now goal2 is the target strain rate
triax.goal1=sigmaIso # we defined the lateral stresses during the test, here the same sigmaIso as for the initial confinement
triax.goal3=sigmaIso # we defined the lateral stresses during the test, here the same sigmaIso as for the initial confinement

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

########################################################
######### RECORD AND PLOT DATA #########

qt.View()

def checkUnbalanced():
 if unbalancedForce()<.05:
  O.pause()
  plot.saveDataTxt('bbb.txt.bz2')

def history(): # a function to save variables
 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,unbalanced=unbalancedForce() #,**O.energy,Etot=O.energy.total()
)
O.run(5000,True)
plot.plots={'e22':('s11','s22','s33'),'e22':('ev')} # the traditional triaxial curves would be more like this
plot.labels={'s11':'$\sigma_{11}$' , 's22':'$\sigma_{22}$' , 's33':'$\sigma_{33}$' , 'e11':'$\epsilon_{11}$' , 'e22':'$\epsilon_{22}$' , 'e33':'$\epsilon_{33}$' , 'ev':'$\epsilon_{V}$'}
plot.plot() # display on the screen (doesn't work on VMware image it seems)
plot.saveDataTxt('results'+key) # save the data to a text file at the the end of the simulation
plot.saveGnuplot('plotScript'+key) # generate a script for gnuplot. Open another terminal and type "gnuplot plotScriptKEY.gnuplot

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Thank you for your help.