totalDeltaDensity = targetDensity - startDensity
density = startDensity
deltaDensity = totalDeltaDensity
decayFactor = 2.5
deltaDensity = 0.01
print "start approaching target density", targetDensity
while density < targetDensity:
#deltaDensity /= decayFactor
density += deltaDensity
print "current density", density
solver.setVolumeDensity(density)
solver.solve()
g = solver.getRDF()
solver.setStartValue(g)
#Direct calculation
print "Directly calculating RDF for target density", targetDensity
solver.setStartValue(np.zeros(solver.getNumberOfRadialSamplingPoints()) )
solver.setVolumeDensity(targetDensity)
solver.solve()
g_direct = solver.getRDF()
#Plot results
r = np.arange(solver.getNumberOfRadialSamplingPoints() ).astype('float') + 1.0
r *= solver.getDelta_r()/solver.getHardSphereRadius()
pl.plot(r, g, label = 'RDF obtained by iterating over densities' );
#plot
import matplotlib.pyplot as plt
import pylab as pl
if __name__ == '__main__':
closureRDFdictionary = {}
solver = ScipyAndersonOZsolver(port=0)
solver.setPotentialByName('HardSphere')
solver.setVolumeDensity(0.4)
#Default is PY
print "PY closure.."
solver.solve()
closureRDFdictionary['PY'] = solver.getRDF()
print "HNC closure.."
solver.doHNCclosure()
solver.solve()
closureRDFdictionary['HNC'] = solver.getRDF()
print "RY closure, alpha -> 0.."
solver.doRYclosure(alpha=0.0001) #Not exactly zero...
solver.solve()
closureRDFdictionary['RY alpha -> 0'] = solver.getRDF()
print "RY closure, alpha -> inf.."
solver.doRYclosure(alpha=100000.0)
solver.solve()
closureRDFdictionary['RY alpha -> inf'] = solver.getRDF()
#Define the density range to scan
densityRange = np.arange(0.3, 0.4, 0.1)
#densityRange = np.asarray([0.3])
#densityRange = np.asarray([0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5])
densityRDFdictionary = {}
#Start loop over densities and measure wall clock time
t_start = time.time()
for d in densityRange:
s.setVolumeDensity(float(d))
s.solve()
g = s.getRDF()
densityRDFdictionary[d] = g
t_stop = time.time()
#Print out benchmark
print "time used for", densityRange.size, "density parameters:", t_stop - t_start, " sec"
print "time used for one OZ run:", (t_stop - t_start)/float(densityRange.size), "seconds"
#Plot results
r = np.arange(s.getNumberOfRadialSamplingPoints() ).astype('float') + 1.0
r *= s.getDelta_r()/s.getHardSphereRadius()
for densityKey in densityRDFdictionary:
pl.plot(r, densityRDFdictionary[densityKey], label = 'RDF for d=' + str(densityKey));
pl.xlabel('r/sigma'); pl.ylabel('g(r)')
#plot
import matplotlib.pyplot as plt
import pylab as pl
if __name__ == '__main__':
closureRDFdictionary = {}
solver = ScipyAndersonOZsolver(port = 0)
solver.setPotentialByName('HardSphere')
solver.setVolumeDensity(0.4)
#Default is PY
print "PY closure.."
solver.solve()
closureRDFdictionary['PY'] = solver.getRDF()
print "HNC closure.."
solver.doHNCclosure()
solver.solve()
closureRDFdictionary['HNC'] = solver.getRDF()
print "RY closure, alpha -> 0.."
solver.doRYclosure(alpha=0.0001) #Not exactly zero...
solver.solve()
closureRDFdictionary['RY alpha -> 0'] = solver.getRDF()
print "RY closure, alpha -> inf.."
solver.doRYclosure(alpha=100000.0)
solver.solve()
closureRDFdictionary['RY alpha -> inf'] = solver.getRDF()
