def plot_single_matrix(args):
cwd = os.getcwd()
subdir = args.subdir
os.chdir(subdir)
FRETfile = args.trace
FRETr = np.loadtxt(FRETfile)
# Calculate transition matrix
tmatrix = tmcalc.get_T_matrix(FRETr,
spacing=args.spacing,
framestep=args.fstep)
# Unflatten matrix if necessary
if tmcalc.check_matrix(tmatrix):
tmatrix = tmcalc.unflatten_matrix(tmatrix)
# Plot matrix
if "color" in args.plot_type:
diff = False
ptm.plot_matrix(tmatrix, "Transition Matrix", 0, 0.5, diff)
if "spy" in args.plot_type:
ptm.spy_matrix(tmatrix, "Non-Zero Transitions")
def calc_all(args):
cwd = os.getcwd()
if args.FRETdir != None:
os.chdir(args.FRETdir)
FRETfile = args.FRETfile
FRET_trace = np.loadtxt(FRETfile)
os.chdir(cwd)
if not os.path.isdir(args.savedir):
os.mkdir(args.savedir)
os.chdir(args.savedir)
fstep = args.fstep
fstep = range(fstep[0], fstep[1] + fstep[2], fstep[2])
if args.db:
db = True
else:
db = False
for i in range(len(fstep)):
T_matrix = tmcalc.get_T_matrix(FRET_trace,
spacing=args.spacing,
framestep=fstep[i],
flatten=False,
db=db)
np.savetxt("T_matrix_fstep_%s.dat" % fstep[i], T_matrix)
lagtime = float(fstep[i]) * 0.5
print "Calculating eigenvalues for frame step %d, lag time %1.1f ps" % (
fstep[i], lagtime)
eigs = compute_eigs(T_matrix)
np.savetxt("Eigenvalues_fstep_%s.dat" % fstep[i],
eigs,
header="eigenvalues for lag time %1.1f ps" % lagtime)
if args.ts:
timescale = compute_time_scale(eigs, lagtime)
np.savetxt("Calc_time_scales_fstep_%s.dat" % fstep[i], timescale)
if args.tplot:
plot_time_scale(fstep)
def plot_compare(args):
cwd = os.getcwd()
subdir = args.subdir
os.chdir(subdir)
FRETfile = args.trace
FRETr = np.loadtxt(FRETfile)
# Load full experimental transition matrix
TMfile = args.TMfile
T_matrix = np.loadtxt(TMfile)
# Calculate and unflatten transition matrix
tmatrix = tmcalc.get_T_matrix(FRETr,
spacing=args.spacing,
framestep=args.fstep)
if tmcalc.check_matrix(tmatrix):
tmatrix = tmcalc.unflatten_matrix(tmatrix)
# Calculate experimental matrix
bin_size = np.size(tmatrix)**0.5
spacing = 0.1
lower_ran = spacing * (np.floor(10 * np.min(FRETr)))
upper_ran = spacing * (np.ceil(10 * np.max(FRETr)))
ran_size = (lower_ran, upper_ran)
tmatrix_exp = xtm.tmatrix_exp_calc(T_matrix, bin_size, ran_size, spacing)
if tmcalc.check_matrix(tmatrix_exp):
tmatrix_exp = tmcalc.unflatten_matrix(tmatrix_exp)
# Difference matrix
diff_matrix = tmatrix - tmatrix_exp
diff_squared = np.mean(np.abs(diff_matrix))
print "Average absolute difference is: "
print diff_squared
# Generate plots
if "color" in args.plot_type:
ptm.plot_matrix(tmatrix, "Simulated Transition Matrix", 0, 0.5)
ptm.plot_matrix(tmatrix_exp, "Experimental Transition Matrix", 0, 0.5)
ptm.plot_matrix(diff_matrix,
"Transition Probability Differences",
-0.5,
0.5,
diff=True)
if "spy" in args.plot_type:
ptm.spy_matrix(tmatrix, "Non-zero entries, simulated")
ptm.spy_matrix(tmatrix_exp, "Non-zero entries, experimental")
ptm.spy_matrix(diff_matrix, "Non-zero entries, difference")
def plot_compare(args):
cwd = os.getcwd()
subdir = args.subdir
os.chdir(subdir)
FRETfile = args.trace
FRETr = np.loadtxt(FRETfile)
# Load full experimental transition matrix
TMfile = args.TMfile
T_matrix = np.loadtxt(TMfile)
# Calculate and unflatten transition matrix
tmatrix = tmcalc.get_T_matrix(FRETr, spacing=args.spacing, framestep=args.fstep)
if tmcalc.check_matrix(tmatrix):
tmatrix = tmcalc.unflatten_matrix(tmatrix)
# Calculate experimental matrix
bin_size = np.size(tmatrix)**0.5
spacing=0.1
lower_ran = spacing*(np.floor(10*np.min(FRETr)))
upper_ran = spacing*(np.ceil(10*np.max(FRETr)))
ran_size = (lower_ran, upper_ran)
tmatrix_exp = xtm.tmatrix_exp_calc(T_matrix, bin_size, ran_size, spacing)
if tmcalc.check_matrix(tmatrix_exp):
tmatrix_exp = tmcalc.unflatten_matrix(tmatrix_exp)
# Difference matrix
diff_matrix = tmatrix - tmatrix_exp
diff_squared = np.mean(np.abs(diff_matrix))
print "Average absolute difference is: "
print diff_squared
# Generate plots
if "color" in args.plot_type:
ptm.plot_matrix(tmatrix, "Simulated Transition Matrix", 0, 0.5)
ptm.plot_matrix(tmatrix_exp, "Experimental Transition Matrix", 0, 0.5)
ptm.plot_matrix(diff_matrix, "Transition Probability Differences", -0.5, 0.5, diff=True)
if "spy" in args.plot_type:
ptm.spy_matrix(tmatrix, "Non-zero entries, simulated")
ptm.spy_matrix(tmatrix_exp, "Non-zero entries, experimental")
ptm.spy_matrix(diff_matrix, "Non-zero entries, difference")
def plot_single_matrix(args):
cwd = os.getcwd()
subdir = args.subdir
os.chdir(subdir)
FRETfile = args.trace
FRETr = np.loadtxt(FRETfile)
# Calculate transition matrix
tmatrix = tmcalc.get_T_matrix(FRETr, spacing=args.spacing, framestep=args.fstep)
# Unflatten matrix if necessary
if tmcalc.check_matrix(tmatrix):
tmatrix = tmcalc.unflatten_matrix(tmatrix)
# Plot matrix
if "color" in args.plot_type:
diff = False
ptm.plot_matrix(tmatrix, "Transition Matrix", 0, 0.5, diff)
if "spy" in args.plot_type:
ptm.spy_matrix(tmatrix, "Non-Zero Transitions")