def TS_probabilities(Tdirs,coordfile,contact_args):
""" Calculate the TS contact probabilities along some reaction coordinate
Parameters
----------
Tdirs : list
List of directory names to collect reaction coordinate file from
coordfile : str
Name of file containing reaction coordinate.
contact_args : object
Object containing the
"""
T = Tdirs[0].split("_")[0]
coordname = coordfile.split(".")[0]
if not os.path.exists("%s_profile/state_bounds.txt" % coordname):
# Determine state bounds from 1D profile
print "calculating state bounds"
coordvst = np.concatenate([np.loadtxt("%s/%s" % (x,coordfile)) for x in Tdirs ])
if not os.path.exists("%s_profile" % coordname):
os.mkdir("%s_profile" % coordname)
os.chdir("%s_profile" % coordname)
mid_bin, Fdata = pmfutil.pmf1D(coordvst,bins=40)
xinterp, F = pmfutil.interpolate_profile(mid_bin,Fdata)
minidx, maxidx = pmfutil.extrema_from_profile(xinterp,F)
min_bounds, max_bounds = pmfutil.state_bounds_from_profile(xinterp,F)
min_labels, max_labels = pmfutil.assign_state_labels(min_bounds,max_bounds)
pmfutil.save_state_bounds(T,min_bounds,max_bounds,min_labels,max_labels)
os.chdir("..")
with open("%s_profile/%s_state_bounds.txt" % (coordname,T),"r") as fin:
state_bins = np.array([ [float(x.split()[1]),float(x.split()[2])]
for x in fin.readlines() if x.split()[0].startswith("TS")])
else:
# Load state bounds
with open("%s_profile/state_bounds.txt" % coordname,"r") as fin:
state_bins = np.array([ [float(x.split()[1]),float(x.split()[2])]
for x in fin.readlines() if x.split()[0].startswith("TS")])
# Calculate the contact probability in TS
print "calculating TS"
contact_args.bins = state_bins
bin_edges, qi_vs_Q = simulation.calc.binned_contacts.calculate_binned_contacts_vs_q(contact_args)
TS = qi_vs_Q[0,:]
return TS
# get directories
tempdirs = glob.glob("T_*_1") + glob.glob("T_*_2") + glob.glob("T_*_3")
organized_temps = util.get_organized_temps(temperature_dirs=tempdirs)
T = organized_temps.keys()
T.sort()
# determine which temperature is closest to the folding temperature
os.chdir(coordname + "_profile")
if not (os.path.exists("T_used") and os.path.exists("minima.dat")):
dF_min_idx = np.argmin([(float(open("T_{}_stab.dat".format(x)).read())) ** 2 for x in T])
T_used = T[dF_min_idx]
mid_bin = np.loadtxt("T_{}_mid_bin.dat".format(T_used))
Fdata = np.loadtxt("T_{}_F.dat".format(T_used))
xinterp, F = pmfutil.interpolate_profile(mid_bin, Fdata)
minidx, maxidx = pmfutil.extrema_from_profile(xinterp, F)
np.savetxt("minima.dat", xinterp[minidx])
with open("T_used.dat", "w") as fout:
fout.write(str(T_used))
U = xinterp[minidx].min()
N = xinterp[minidx].max()
else:
with open("T_used", "r") as fin:
T_used = float(fin.read())
minima = np.loadtxt("minima.dat")
U = minima.min()
N = minima.max()
os.chdir("..")
dirs = organized_temps[T_used]
