#fid_out.write("# Time(ps)\tAverage lipid per area\n");
psf = '{0}{1}'.format(base_path, structure_file);
flg_top = 0; # check bi/mono layer
flg_btm = 0; # check bi/mono layer
timeStamp = []; # time stamp for trajectory
# data based on trajectory
STMP = [];
#creating BIN 0~90 degree
BIN = [];
DIST = [];
topDIST = [];
btmDIST = [];
for ibin in stanalyzer.frange(0, 90, 0.1):
BIN.append(ibin);
DIST.append(0.0);
topDIST.append(0.0);
btmDIST.append(0.0);
trj_cnt = 0;
for idx in range(len(trajectoryFile)):
print "[{0}/{1}] trajectory is processing...".format(idx+1, len(trajectoryFile));
cnt = 0;
# turning on periodic boundary conditions
MDAnalysis.core.flags['use_periodic_selections'] = True
MDAnalysis.core.flags['use_KDTree_routines'] = False
# reading trajectory
trj = '{0}{1}'.format(base_path, trajectoryFile[idx]);
elif cntAxs == 'y':
top_cut = sysY * 0.165;
btm_cut = -1.0 * top_cut;
top_selQry = "{} and (prop y > {})".format(selQry, top_cut);
btm_selQry = "{} and (prop y < {})".format(selQry, btm_cut);
else:
top_cut = sysZ * 0.165;
btm_cut = -1.0 * top_cut;
top_selQry = "{} and (prop z > {})".format(selQry, top_cut);
btm_selQry = "{} and (prop z < {})".format(selQry, btm_cut);
# augumented X axis
BIN_X = [];
min_x = math.floor(0.5 * -sysX) - 5.0;
max_x = math.ceil(0.5 * sysX) + 5.0;
for i in stanalyzer.frange(min_x, max_x, binsize):
BIN_X.append(i);
BIN_Y = [];
min_y = math.floor(0.5 * -sysY) - 5.0;
max_y = math.ceil(0.5 * sysY) + 5.0;
for i in stanalyzer.frange(min_y, max_y, binsize):
BIN_Y.append(i);
BIN_top = [];
BIN_btm = [];
for i in BIN_X:
for j in BIN_Y:
tmp = [i,j, 0.0];
BIN_top.append(tmp);
BIN_btm.append(tmp);
elif cntAxs == 'y':
top_cut = sysY * 0.165;
btm_cut = -1.0 * top_cut;
top_selQry = "{} and (prop y > {})".format(selQry, top_cut);
btm_selQry = "{} and (prop y < {})".format(selQry, btm_cut);
else:
top_cut = sysZ * 0.165;
btm_cut = -1.0 * top_cut;
top_selQry = "{} and (prop z > {})".format(selQry, top_cut);
btm_selQry = "{} and (prop z < {})".format(selQry, btm_cut);
# augumented X axis
BIN_X = [];
min_x = math.floor(0.5 * -sysX) - 5.0;
max_x = math.ceil(0.5 * sysX) + 5.0;
for i in stanalyzer.frange(min_x, max_x, binsize):
BIN_X.append(i);
BIN_Y = [];
min_y = math.floor(0.5 * -sysY) - 5.0;
max_y = math.ceil(0.5 * sysY) + 5.0;
for i in stanalyzer.frange(min_y, max_y, binsize):
BIN_Y.append(i);
BIN_top = [];
BIN_btm = [];
for i in BIN_X:
for j in BIN_Y:
tmp = [i,j, 0.0];
BIN_top.append(tmp);
BIN_btm.append(tmp);
flg_top = 0
# check bi/mono layer
flg_btm = 0
# check bi/mono layer
timeStamp = []
# time stamp for trajectory
# data based on trajectory
STMP = []
#creating BIN 0~90 degree
BIN = []
DIST = []
topDIST = []
btmDIST = []
for ibin in stanalyzer.frange(0, 90, 0.1):
BIN.append(ibin)
DIST.append(0.0)
topDIST.append(0.0)
btmDIST.append(0.0)
trj_cnt = 0
for idx in range(len(trajectoryFile)):
print "[{0}/{1}] trajectory is processing...".format(
idx + 1, len(trajectoryFile))
cnt = 0
# turning on periodic boundary conditions
MDAnalysis.core.flags['use_periodic_selections'] = True
MDAnalysis.core.flags['use_KDTree_routines'] = False
# reading trajectory
btm_selQry1 = "{} and (prop y < {})".format(selQry1, btm_cut);
btm_selQry2 = "{} and (prop y < {})".format(selQry2, btm_cut);
else:
top_cut = sysZ * 0.165;
btm_cut = -1.0 * top_cut;
top_selQry1 = "{} and (prop z > {})".format(selQry1, top_cut);
top_selQry2 = "{} and (prop z > {})".format(selQry2, top_cut);
btm_selQry1 = "{} and (prop z < {})".format(selQry1, btm_cut);
btm_selQry2 = "{} and (prop z < {})".format(selQry2, btm_cut);
#----- creating BIN for distance density
min_bin = 1.0;
max_bin = math.sqrt(augX * augX + augY * augY + augY * augY);
BIN = [];
for i in stanalyzer.frange(min_bin, max_bin, binsize):
BIN.append(i);
#----- calculating denominator for density distribution
DEN = []; topDNST = []; btmDNST = [];
pre_out = 0.0;
for i in range(len(BIN)):
if i == 0:
sp_out = 4.0/3.0 * math.pi * (BIN[i]**3);
sp_in = 0.0;
vol = sp_out - sp_in;
pre_out = sp_out;
else:
sp_out = 4.0/3.0 * math.pi * (BIN[i]**3);
sp_in = pre_out;
vol = sp_out - sp_in;
btm_selQry1 = "{} and (prop y < {})".format(selQry1, btm_cut)
btm_selQry2 = "{} and (prop y < {})".format(selQry2, btm_cut)
else:
top_cut = sysZ * 0.165
btm_cut = -1.0 * top_cut
top_selQry1 = "{} and (prop z > {})".format(selQry1, top_cut)
top_selQry2 = "{} and (prop z > {})".format(selQry2, top_cut)
btm_selQry1 = "{} and (prop z < {})".format(selQry1, btm_cut)
btm_selQry2 = "{} and (prop z < {})".format(selQry2, btm_cut)
#----- creating BIN for distance density
min_bin = 1.0
max_bin = math.sqrt(augX * augX + augY * augY + augY * augY)
BIN = []
for i in stanalyzer.frange(min_bin, max_bin, binsize):
BIN.append(i)
#----- calculating denominator for density distribution
DEN = []
topDNST = []
btmDNST = []
pre_out = 0.0
for i in range(len(BIN)):
if i == 0:
sp_out = 4.0 / 3.0 * math.pi * (BIN[i]**3)
sp_in = 0.0
vol = sp_out - sp_in
pre_out = sp_out
else:
sp_out = 4.0 / 3.0 * math.pi * (BIN[i]**3)
