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scripting
Example of python scripts which setup simulation, run it, and plot results are can be seen in test2.py and testServer2.py files.
Here we provide overview of various operations done in this example scripts with a bit more detailed explanation than just inline-comments within the script code. The topics and are discussed in order in which are done in the example the script test2.py. The order of operations is sometimes important ( e.g. you cannot allocate grid until you set it's size, you cannot do scan until you sample forcefiled etc. )
import os
import numpy as np
import matplotlib.pyplot as plt
import elements
import basUtils
C++ part of ProbeParticle library ( ProbeParticle.cpp ) is compiled into ProbeParticle_lib.so binary dynamic library. If we do any change in C++ code, we have to recompile the library. This is done automatically during call of import ProbeParticle if the file ProbeParticle_lib.so is not pressent in the directory. So, If we want force recompilation of the C++ dynamic library, we just delelete the library. This can be done e.g. like this:
def makeclean( ):
import os
[ os.remove(f) for f in os.listdir(".") if f.endswith(".so") ]
[ os.remove(f) for f in os.listdir(".") if f.endswith(".o") ]
[ os.remove(f) for f in os.listdir(".") if f.endswith(".pyc") ]
makeclean( ) # force to recompile
import ProbeParticle as PP
One way to change simulation parameters is to change the default dictionary PP.params. Which is by default e.g. defined like this:
params={
'PBC': False,
'gridN': np.array( [ 150, 150, 50 ] ).astype(np.int32),
'gridA': np.array( [ 12.798, -7.3889, 0.00000 ] ),
'gridB': np.array( [ 12.798, 7.3889, 0.00000 ] ),
'gridC': np.array( [ 0, 0, 5.0 ] ),
'moleculeShift': np.array( [ 0.0, 0.0, -2.0 ] ),
'probeType': 8,
'charge': 0.00,
'r0Probe' : np.array( [ 0.00, 0.00, 4.00] ),
'stiffness': np.array( [ 0.5, 0.5, 20.00] ),
'scanStep': np.array( [ 0.10, 0.10, 0.10] ),
'scanMin': np.array( [ 0.0, 0.0, 5.0 ] ),
'scanMax': np.array( [ 20.0, 20.0, 8.0 ] ),
'kCantilever' : 1800.0,
'f0Cantilever' : 30300.0,
'Amplitude' : 1.0,
'plotSliceFrom': 16,
'plotSliceTo' : 22,
'plotSliceBy' : 1,
'imageInterpolation': 'nearest',
'colorscale' : 'gray',
}
An alternative way is to load the parameters from a file using PP.loadParams. This should be done before all other operations ( like definition and allocation of sampling and scanning grid )
PP.loadParams( 'params.ini' ) # load parametes from ini file
Then we should define system geometry ( positions of atoms and it types )
atoms = basUtils.loadAtoms('input.xyz', elements.ELEMENT_DICT )
Rs = np.array([atoms[1],atoms[2],atoms[3]]);
iZs = np.array( atoms[0])
The size and shape of sampling and scanning grid is normally set by parameters PP.params['gridA'],'gridB','gridC','scanMin','scanMax'. However, in case of non-periodic samples ( such as single molecule ) it is more conveninent let program build proper sampling and scanning box around the molecule, instead of defining the super-lattice verctors. This can be done by calling PP.autoGeom( fitCell=True ) function like this:
Before the simulation the geometry of molecule should be shifted to proper position with respect to sampling grid. The shift of the molecule can be set either manually in PP.params['moleculeShift' ], or let program set this parameter automatically using PP.autoGeom( shiftXY=True ).
if not PP.params['PBC' ]:
PP.autoGeom( Rs, shiftXY=True, fitCell=True, border=3.0 )
Rs[0] += PP.params['moleculeShift' ][0] # shift molecule so that we sample reasonable part of potential
Rs[1] += PP.params['moleculeShift' ][1]
Rs[2] += PP.params['moleculeShift' ][2]
Rs = np.transpose( Rs, (1,0) ).copy()
If we used periodic boundary condition, it is necessary to multiply geometry of sample to neighboring unit cells. There is automatic procedure PP.PBCAtoms() to do that.
if PP.params['PBC' ]:
iZs,Rs,Qs = PP.PBCAtoms( iZs, Rs, Qs, avec=PP.params['gridA'], bvec=PP.params['gridB'] )
Beside the geometry (position of atoms) the sample properties are defined also by parameters of this atoms,such as Lenard-Jones parameters and charge. In principle it is possible to set parameters (C6,C12 and Q ) of each atom independently by hand (it is just array of numbers). However, more convenient way is to read it from file of L-J parameters by PP.loadSpecies() for each atom type and set the the parameters for each atom instance by PP.getAtomsLJ(). Charges for pairwise pointcharge Coulomb interaction are read from 5-th column of geometry file.
NOTE: it is important to do this step after the multiplication of periodic images to neighboring cells.
Qs = np.array( atoms[4] )
FFparams = PP.loadSpecies ( 'atomtypes.ini' )
C6,C12 = PP.getAtomsLJ( PP.params['probeType'], iZs, FFparams )
do this before simulation, in case it will crash
dz = PP.params['scanStep'][2]
zTips = np.arange( PP.params['scanMin'][2], PP.params['scanMax'][2]+0.00001, dz )[::-1];
ntips = len(zTips);
print " zTips : ",zTips
rTips = np.zeros((ntips,3))
rs = np.zeros((ntips,3))
fs = np.zeros((ntips,3))
rTips[:,0] = 1.0
rTips[:,1] = 1.0
rTips[:,2] = zTips
PP.setTip()
xTips = np.arange( PP.params['scanMin'][0], PP.params['scanMax'][0]+0.00001, 0.1 )
yTips = np.arange( PP.params['scanMin'][1], PP.params['scanMax'][1]+0.00001, 0.1 )
extent=( xTips[0], xTips[-1], yTips[0], yTips[-1] )
fzs = np.zeros(( len(zTips), len(yTips ), len(xTips ) ));
nslice = 10;
FFparams = PP.loadSpecies ( 'atomtypes.ini' )
C6,C12 = PP.getAtomsLJ( PP.params['probeType'], iZs, FFparams )
print " # ============ define Grid "
cell =np.array([
PP.params['gridA'],
PP.params['gridB'],
PP.params['gridC'],
]).copy()
gridN = PP.params['gridN']
FF = np.zeros( (gridN[2],gridN[1],gridN[0],3) )
PP.setFF( FF, cell )
PP.setFF_Pointer( FF )
PP.getLenardJonesFF( Rs, C6, C12 )
plt.figure(figsize=( 5*nslice,5 )); plt.title( ' FF LJ ' )
for i in range(nslice):
plt.subplot( 1, nslice, i+1 )
plt.imshow( FF[i,:,:,2], origin='image', interpolation='nearest' )
withElectrostatics = ( abs( PP.params['charge'] )>0.001 )
if withElectrostatics:
print " # =========== Sample Coulomb "
FFel = np.zeros( np.shape( FF ) )
CoulombConst = -14.3996448915; # [ e^2 eV/A ]
Qs *= CoulombConst
#print Qs
PP.setFF_Pointer( FFel )
PP.getCoulombFF ( Rs, Qs )
plt.figure(figsize=( 5*nslice,5 )); plt.title( ' FFel ' )
for i in range(nslice):
plt.subplot( 1, nslice, i+1 )
plt.imshow( FFel[i,:,:,2], origin='image', interpolation='nearest' )
FF += FFel*PP.params['charge']
PP.setFF_Pointer( FF )
del FFel
plt.figure(figsize=( 5*nslice,5 )); plt.title( ' FF total ' )
for i in range(nslice):
plt.subplot( 1, nslice, i+1 )
plt.imshow( FF[i,:,:,2], origin='image', interpolation='nearest' )
for ix,x in enumerate( xTips ):
print "relax ix:", ix
rTips[:,0] = x
for iy,y in enumerate( yTips ):
rTips[:,1] = y
itrav = PP.relaxTipStroke( rTips, rs, fs ) / float( len(zTips) )
fzs[:,iy,ix] = fs[:,2].copy()
dfs = PP.Fz2df( fzs, dz = dz, k0 = PP.params['kCantilever'], f0=PP.params['f0Cantilever'], n=int(PP.params['Amplitude']/dz) )
print " # ============ Plot Relaxed Scan 3D "
#slices = range( PP.params['plotSliceFrom'], PP.params['plotSliceTo'], PP.params['plotSliceBy'] )
#print "plotSliceFrom, plotSliceTo, plotSliceBy : ", PP.params['plotSliceFrom'], PP.params['plotSliceTo'], PP.params['plotSliceBy']
#print slices
#nslice = len( slices )
slices = range( 0, len(dfs) )
for ii,i in enumerate(slices):
print " plotting ", i
plt.figure( figsize=( 10,10 ) )
plt.imshow( dfs[i], origin='image', interpolation=PP.params['imageInterpolation'], cmap=PP.params['colorscale'], extent=extent )
z = zTips[i] - PP.params['moleculeShift' ][2]
plt.colorbar();
plt.xlabel(r' Tip_x $\AA$')
plt.ylabel(r' Tip_y $\AA$')
plt.title( r"df Tip_z = %2.2f $\AA$" %z )
plt.savefig( 'df_%3i.png' %i, bbox_inches='tight' )