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removed RadialDistributionPure for properties_abandon and edited Radi… #17

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removed RadialDistributionPure for properties_abandon and edited Radi… #17

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127 changes: 39 additions & 88 deletions rubicon/analysis/lammps/properties_abandon.py
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Original file line number Diff line number Diff line change
Expand Up @@ -692,11 +692,10 @@ def runradial(self, datfilename, mol1, mol2, comx, comy, comz, Lx, Ly, Lz,
firststep)
(nummol1, nummol2, mol1, mol2) = self.getnummol(moltypel, nummoltype,
mol1, mol2)
while count < len(comx):
(count) = self.radialdistribution(g, mol1, mol2, len(comx[1]),
moltype, comx, comy, comz, Lx,
Ly, Lz, binsize, numbins, maxr,
count)

(count) = self.radialdistribution(g, len(comx[1]), moltype, comx, comy,
comz, Lx, Ly, Lz, binsize, numbins,
maxr, count)
(radiuslist) = self.radialnormalization(numbins, binsize, Lx, Ly, Lz,
nummol1, nummol2, count, g,
firststep)
Expand All @@ -721,23 +720,49 @@ def getnummol(self, moltypel, nummoltype, mol1, mol2):
mol2 = int(moltypel.index(mol2))
return nummol1, nummol2, mol1, mol2

def radialdistribution(self, g, mol1, mol2, nummol, moltype, comx, comy,
def radialdistribution(self, g, nummol, moltype, comx, comy,
comz, Lx, Ly, Lz, binsize, numbins, maxr, count):
# uses FORTRAN code to calculate the number of molecules within each
# shell
g1 = comradial.comradial(mol1, mol2, nummol, moltype, comx[count],
comy[count], comz[count], Lx, Ly, Lz, binsize,
numbins, maxr)
g += g1
count += 1
# calculates the number of molecules within each shell

comxt = np.array(comx[count:]).transpose()
comyt = np.array(comy[count:]).transpose()
comzt = np.array(comz[count:]).transpose()
indexlist = []

for i in range(0,len(g)):
indexlist.append(np.array(moltype) == i)


for molecule in range(0, nummol - 1):
dx = comxt[molecule+1:] - np.tile(comxt[molecule],
(len(comxt)-molecule-1,1))
dy = comyt[molecule+1:] - np.tile(comyt[molecule],
(len(comyt)-molecule-1,1))
dz = comzt[molecule+1:] - np.tile(comzt[molecule],
(len(comzt)-molecule-1,1))

dx -= Lx * np.around(dx / Lx)
dy -= Ly * np.around(dy / Ly)
dz -= Lz * np.around(dz / Lz)

r2 = dx ** 2 + dy ** 2 + dz ** 2
r = np.sqrt(r2)
for i in range(0,len(indexlist)):
gt,dist = np.histogram(r[indexlist[i][molecule+1:]].ravel(),
bins=numbins,
range=(0.5*binsize,binsize*(numbins+0.5)))
g[moltype[molecule]][i]+= gt
g[i][moltype[molecule]]+= gt

count = len(comx)
return count

def radialnormalization(self, numbins, binsize, Lx, Ly, Lz, nummol1,
nummol2, count, g, firststep):
# normalizes g to box density
radiuslist = (np.arange(numbins) + 1) * binsize
g *= Lx * Ly * Lz / nummol1 / nummol2 / 4 / np.pi / (
radiuslist) ** 2 / binsize / (
radiuslist) ** 2 / binsize / (
count - firststep)
return radiuslist

Expand Down Expand Up @@ -975,77 +1000,3 @@ def writetofile(self, numbins, radiuslist, g):
str(radiuslist[radius]) + " " + str(g[radius]) + "\n")
gfile.close()


class RadialDistributionPure:
def runradial(self, datfilename, comx, comy, comz, Lx, Ly, Lz, Lx2, Ly2,
Lz2, output, nummoltype, moltypel, moltype, firststep=1):
(maxr, binsize, numbins, count, g) = self.setgparam(Lx2, Ly2, Lz2,
firststep,
moltypel)
while count < len(comx):
(count) = self.radialdistribution(g, len(comx[1]), moltype, comx,
comy, comz, Lx, Ly, Lz, binsize,
numbins, maxr, count)
(radiuslist) = self.radialnormalization(numbins, binsize, Lx, Ly, Lz,
nummoltype, count, g,
firststep)
self.append_dict(radiuslist, g, output, moltypel)
return output

def setgparam(self, Lx2, Ly2, Lz2, firststep, moltypel):
# uses side lengths to set the maximum radius for box and number of bins
# also sets the first line using data on firststep and number of atoms
maxr = min(Lx2, Ly2, Lz2)
binsize = 0.1
numbins = int(np.ceil(maxr / binsize))
count = firststep
g = np.zeros((len(moltypel), len(moltypel), numbins))
return maxr, binsize, numbins, count, g

def radialdistribution(self, g, nummol, moltype, comx, comy, comz, Lx, Ly,
Lz, binsize, numbins, maxr, count):
# implements a FORTRAN code to calculate the number of molecules within each shell

for molecule1 in range(0, nummol - 1):
for molecule2 in range(molecule1 + 1, nummol):
dx = comx[count][molecule1] - comx[count][molecule2]
dy = comy[count][molecule1] - comy[count][molecule2]
dz = comz[count][molecule1] - comz[count][molecule2]

dx -= Lx * round(dx / Lx)
dy -= Ly * round(dy / Ly)
dz -= Lz * round(dz / Lz)

r2 = dx ** 2 + dy ** 2 + dz ** 2
r = np.sqrt(r2)

if r <= maxr:
g[moltype[molecule1]][moltype[molecule2]][
int(round(r / binsize) - 1)] += 1
g[moltype[molecule2]][moltype[molecule1]][
int(round(r / binsize) - 1)] += 1

count += 1
return count

def radialnormalization(self, numbins, binsize, Lx, Ly, Lz, nummol, count,
g, firststep):
# normalizes g to box density
radiuslist = (np.arange(numbins) + 1) * binsize
for i in range(0, len(g)):
for j in range(0, len(g)):
g[i][j] *= Lx * Ly * Lz / nummol[i] / nummol[j] / 4 / np.pi / (
radiuslist) ** 2 / binsize / (
count - firststep)
return radiuslist

def append_dict(self, radiuslist, g, output, moltypel):
for i in range(0, len(moltypel)):
for j in range(i, len(moltypel)):
if not all([v == 0 for v in g[i][j]]):
output['RDF']['{0}-{1}'.format(moltypel[i],
moltypel[
j])] = copy.deepcopy(
g[i][j].tolist())
if 'distance' not in list(output['RDF'].keys()):
output['RDF']['distance'] = copy.deepcopy(radiuslist.tolist())