def __init__(self, pfile, n, atom1, atom2, data, box, pdr, step, No_Windows=False):
# This class aim is to calculate the Deconvolution of the RDF
# the parameters are :
# - pfile is the output file (ascii/netcdf)
# - n = is the neibhor number
# - atom1/2 give the number of the atom in typat
# - box : give the number of box wide for the calculculation of g(r)
# - pdr : give the radial precision of the calculation
# - pstep : give the self.increment for the step loop
file = pfile
pos = file.getXCart() # position of atom (cartesian)
nei = n
inc = step #incrementation
acell = file.getAcell() #acell
a_max = max(acell[:,0])
b_max = max(acell[:,1])
c_max = max(acell[:,2])
if box >= 0:
f = (1/2.+ box) # factor of maximum radius
else: # box < 0
f = 3**0.5/2.
rmax = f*min(a_max,b_max,c_max)
deltaR = pdr # delta r (Bohr)
maxbin = int((rmax/deltaR)) # number of iteration
typat = file.getTypat() # Type of particule
if atom1 == 0:
indexAtom1 = array([i for i,x in enumerate(typat) if x == 1 and 2],dtype=int) + 1
else:
indexAtom1 = array([i for i,x in enumerate(typat) if x == atom1],dtype=int) + 1 #get list of the index of typat1 (+1 for fortran)
if atom2 == 0:
indexAtom2 = array([i for i,x in enumerate(typat) if x == 1 and 2 ],dtype=int) + 1
else:
indexAtom2 = array([i for i,x in enumerate(typat) if x == atom2],dtype=int) + 1 #get list of the index of typat2 (+1 for fortran)
nbtime = len(pos) # final step
self.r = arange(maxbin)*deltaR
self.n = topo.n_distribution(nei,nbtime,data,inc,deltaR,indexAtom1,indexAtom2,0,self.r)
def __init__(self, nei, pfile, atom1, atom2, pdr, pstep, No_Windows=False):
# This class aim is to calculate the Neighbor Distrubution Function
# the parameters are :
# - nei gives the neith neibours we consider.
# - pfile is the output file (ascii/netcdf)
# - atom1 give the number of the atom in typat
# - pdt : give the dtheta for the calculation
# - pstep : give the self.increment for the step loop
file = pfile
pos = file.getXCart() # position of atom (cartesian)
inc = pstep #incrementation
acell = file.getAcell() #acell
a = acell[:, 0]
b = acell[:, 1]
c = acell[:, 2]
rprim = zeros((3, 3)) # primitives vectors of the cell
rprim[0] = file.getRPrim()[0, 0]
rprim[1] = file.getRPrim()[0, 1]
rprim[2] = file.getRPrim()[0, 2]
deltaR = pdr
typat = file.getTypat() # Type of particule
if atom1 == 0:
indexAtom1 = array(
[i
for i, x in enumerate(typat) if x == 1 and 2], dtype=int) + 1
else:
indexAtom1 = array(
[i for i, x in enumerate(typat) if x == atom1], dtype=int
) + 1 #get list of the index of typat1 (+1 for fortran)
if atom2 == 0:
indexAtom2 = array(
[i
for i, x in enumerate(typat) if x == 1 and 2], dtype=int) + 1
else:
indexAtom2 = array(
[i for i, x in enumerate(typat) if x == atom2], dtype=int
) + 1 #get list of the index of typat2 (+1 for fortran)
nbtime = len(pos) # final step
nba = len(pos[0]) # number of atom
it = (int(nbtime / inc) + 1) * nba * (nba - 1)
self.m = topo.m_distribution(nei, nbtime, pos, rprim, inc, it, a, b, c,
indexAtom1, indexAtom2)
maxi = self.m[0]
mini = self.m[1]
data = self.m[2]
self.r = []
for i in range(int(mini * 1000), int(maxi * 1000 + 1),
int(deltaR * 1000)):
i = i / 1000.
self.r.append(i)
self.n = topo.n_distribution(nei, nbtime, data, inc, deltaR,
indexAtom1, indexAtom2, mini, self.r)