def fit_msd(comp_key, conn, make_plot=False):
(fin,) = conn.execute("select fout from msd where comp_key = ?", (comp_key,)).fetchone()
Fin = h5py.File(fin, "r")
g_name = _fd("mean_squared_disp", comp_key)
msd = Fin[g_name]["msd"][:]
dt = Fin[g_name].attrs["dtime"]
temp = Fin[g_name].attrs["temperature"]
Fin.close()
del Fin
t = (np.arange(len(msd)) + 1) * dt
(x, r, rn, s) = np.linalg.lstsq(np.transpose(np.array([t, np.ones(len(msd))])), msd)
if make_plot:
fig = plots.tac_figure("t [ms]", "msd [px^2]", "msd and fit")
fig.draw_line(t, msd, "x", label="msd")
print x[1]
fig.draw_line(t, t * x[0] + x[1], label="fit")
scale = 6.45 / 60 # u[m]/[pix]
# lamda_x = sqrt(2Dt) (Einstein 1905)
# msd = 2*lambda_x^2 = 4 D t (Einstein 1905)
# the extra 2 is because I am looking at total displacement in 2D
D = (x[0] / 4) * (scale ** 2) * 1000 # u[m]^2/sec
r = _dilute_D_to_rad(D, temp) # u[m]
return (x[0], temp, r)
def display_fit(x,y,p,func,fig=None):
"""Displays the raw data and the fit. fig is an plots.tac_figure
object"""
if fig is None:
fig = plots.tac_figure('x','y','fitting')
fig.plot(x,np.log(y),label='data')
fig.plot(x,np.log(func(p,x)),'--x',label=func.__name__ + '('+
','.join(['%.1e'%k for k in p])+ ')')
return fig
def plot_msd_series(comp_key_lst, conn, sname=None):
""" Takes in a list of msd computations and makes a nice plot"""
tltstr = "mean squared displacement"
if not sname is None:
tltstr = tltstr + " " + sname
fig = plots.tac_figure(
"t[ms]", r"$\langle \Delta \rangle ^2$", tltstr, count=len(comp_key_lst), func=matplotlib.axes.Axes.plot
)
for c in comp_key_lst:
plot_msd(c[0], conn, fig)
def plot_msd_old(comp_key, conn, fig=None):
if fig is None:
fig = plots.tac_figure("t[s]", "msd", "msd")
pass
(fin, dset) = conn.execute("select fout,dset_key from comps where comp_key = ?", (comp_key,)).fetchone()
(temp,) = conn.execute("select temp from dsets where key = ?", (dset,)).fetchone()
Fin = h5py.File(fin, "r")
g_name = _fd("mean_squared_disp", comp_key)
msd = Fin[g_name]
msd = Fin[g_name]["data"][:]
dt = Fin[g_name].attrs["dtime"]
print
print "the delta is ", dt, "for comp ", comp_key
t = (np.arange(len(msd)) + 1) * dt
cm = plots.color_mapper(27, 33)
fig.plot(t, msd, label=str(temp), color=cm.get_color(temp))
Fin.close()
del Fin
return fig
def plot_msd(comp_key, conn, fig=None):
if fig is None:
fig = plots.tac_figure("t[s]", "msd", "msd")
pass
(fin,) = conn.execute("select fout from msd where comp_key = ?", (comp_key,)).fetchone()
Fin = h5py.File(fin, "r")
g_name = _fd("mean_squared_disp", comp_key)
msd = Fin[g_name]["msd"][:]
dt = Fin[g_name].attrs["dtime"]
temp = Fin[g_name].attrs["temperature"]
mtl = Fin[g_name].attrs["min_track_length"]
print
print "the delta is ", dt, "for comp ", comp_key
t = (np.arange(len(msd)) + 1) * dt
cm = plots.color_mapper(27, 33)
fig.plot(t, msd, label="%(#).2fC, %(!)d" % {"!": mtl, "#": temp}, color=cm.get_color(temp))
Fin.close()
del Fin
return fig
