FIGDIR = os.path.join(PAPERDIR, "figures", "")
DATADIR = os.path.join(HOME, "Dropbox", "nanopores", "fields")
f.set_dir_mega()
number = False
geop = nanopores.Params(pughpore.params)
hpore = geop.hpore
fieldsname = 'eventsnew_both_1_'
params = dict(avgbind1=23e6,
avgbind2=3e4,
P_bind1=0.035,
P_bind2=3e-1,
z0=hpore / 2. + 0.)
drop, th = f.get("events_pugh_experiment", "drop", "t")
th = [1e0 * time for time in th]
#cmap=matplotlib.cm.get_cmap('viridis')
data = f.get_fields(fieldsname, **params)
figname = fieldsname + '_%.1e_%.1e_%.1e_%.1e' % (
params["avgbind1"], params["avgbind2"], params["P_bind1"],
params["P_bind2"]) + str(params["z0"])
t = data["t"]
a = data["a"]
ood = data["ood"]
lendata = len(t)
fac = 1.
if max(t) < 1e-2:
fac = 1e3
t = [x * 1e3 for x in t]
# label="Simple Gamma fit")
plt.plot(tt, gamma.pdf_direct(tt), label="Compound Gamma fit")
#plt.plot(tt, gamma.pdf_bessel(tt), ".k", label="Compound Gamma fit")
#plt.plot(kk*dt, poisson.pmf(kk, k0), label="Poisson fit")
#plt.plot(tt)
if xlog:
plt.xscale("log")
#plt.ylim(ymin=1e-10)
#plt.yscale("log")
plt.xlabel("Attempt time [ns]")
plt.ylabel("Rel. frequency")
plt.legend()
if todo.fit_experiments:
# get data
drop, tsample = fields.get("events_pugh_experiment", "drop", "t")
tsample = tsample.load()
log = True
std = False
cutoff = 0.1 # [ms], detection limit cutoff
# plot data with indication of two clusters
sep = 2.
large = tsample >= sep
toosmall = tsample < cutoff
plt.figure("data_scatter", figsize=(4, 3))
plt.scatter(tsample[toosmall], drop[toosmall], color="r")
plt.scatter(tsample[~toosmall], drop[~toosmall])
#plt.scatter(tsample[~large & ~toosmall], drop[~large & ~toosmall])
#plt.scatter(tsample[large], drop[large], color="g")
plt.axvline(x=cutoff, color="r")
l2 = up.l2
l3 = up.l3
l4 = up.l4
hpore = up.hpore
hmem = up.hmem
h2 = up.h2
h1 = up.h1
h4 = up.h4
figsize1 = (2.2, 1.7)
figsize2 = (10, 2.21)
lw = .5
# eventspara_nobind_traj_0.00109600_0424_1.7e+07_3.0e+04_1.9e-01_3.0e-0123.0
# eventspara_nobind_traj_0.00236500_0316_1.7e+07_3.0e+04_1.9e-01_3.0e-0123.0
x, y, z, j, t, b1, b2 = fields.get("eventspara_nobind", "X", "Y", "Z", "J",
"T", "b1", "b2")
ind = [424, 316] # indices
loc = [8, 9]
colors = ["red", "green"]
for m in 0, 1:
i = ind[m]
X = x[i].load()
Y = y[i].load()
Z = z[i].load()
T = t[i].load()
J = j[i].load()
I0 = 7.523849e-10
bind1 = np.where(T > 1e6)[0]
# (c) 2017 Gregor Mitscha-Baude
import matplotlib.pyplot as plt
from matplotlib import rcParams, rc
rcParams.update({
"font.size" : 7,
"axes.titlesize" : 7,
"font.family" : "sans-serif",
"font.sans-serif" : ["CMU Sans Serif"],
"lines.linewidth" : 1,
"lines.markersize" : 5,
})
from nanopores.tools import fields, savefigs
fields.set_dir_mega()
t_exp, A_exp = fields.get("events_pugh_experiment", "t", "drop")
t_sim, A_sim = fields.get("eventsnew_both_1_", "t", "a")
plt.figure("pugh", figsize=(1.7, 1.6))
plt.scatter(t_sim, A_sim, s=3, alpha=0.5, linewidth=0, color="#00cc00", zorder=100, label="Simulation")
plt.scatter(t_exp, A_exp, s=3, alpha=0.5, linewidth=0, color="r", label="Experiment")
plt.xscale("log")
plt.ylim(ymax=51)
plt.xlim(.5e-5, 3e2)
ax = plt.gca()
ax.invert_yaxis()
ax.set_yticklabels([])
ax.set_xticklabels([])
ax.set_yticks([])
ax.set_xticks([])