dataset = []
for filename, t in data:
data = genfromtxt(datapath + filename + ".ASC", unpack=True, delimiter=" ")
h = histogram(data[1, :], 4096)
dataset.append(h[0][1:] / t)
##
d = dataset[1] - dataset[0]
edges = (50, 250)
p = fits.gaussian_fit(array([
0, 0, 1000, edges[0], 50]),
d[slice(*edges)], arange(edges[1] - edges[0]))
d[slice(*edges)] = p[0][0] * arange(*edges) + p[0][1]
cs662 = sum(d[2500:3000]) / gamma_area / ((0.851 * cesium_activity) \
/ (4 * pi * gamma_R ** 2))
clf()
plot(arange(len(d)), d)
title("Cesium - topp vid 662 keV")
show()
en = arange(edges[1] - edges[0])
c = p[0][0] * en + p[0][1] + p[0][2] * \
exp(-0.5 * ((en - p[0][3]) / p[0][4]) ** 2)
xlabel("Kanalnummer")
ylabel("Frekvens")
thetitle = "hist_" + entry[0].split("/")[-1].split(".")[0] + ".eps"
savefig(imgpath + thetitle, format="eps")
close()
if do_fits:
print ("\n------\nFile is %s" % entry[0])
for limit in entry[2]:
setoff = limit[0]
h = histogram(data[entry[1], :], 4096)
p = fits.gaussian_fit(
array([0, 0, 10000, (limit[1] - setoff) / 2, 10]),
h[0][setoff : limit[1] + 1],
arange(h[0][setoff : limit[1] + 1].shape[0]),
)
energy = p[0][3] + setoff
stdenergy = p[0][4] / abs(p[0][4] * p[0][2] * sqrt(2 * pi))
print energy, stdenergy
print p[0]
# clf()
# plot(arange(h[0][setoff:limit[1] + 1].shape[0]),
# h[0][setoff:limit[1] + 1], 'ro')
# en = arange(h[0][setoff:limit[1] + 1].shape[0])
# c = p[0][0] * en + p[0][1] + p[0][2] * \
# exp(-0.5 * ((en - p[0][3]) / p[0][4]) ** 2)
# plot(en, c, 'g-')
angles = []
nset = []
nerrset = []
ncorrset = []
ncorrerrset = []
pset = []
for f, theta, t, ppeak, peak in fileset:
angles.append(theta)
data = genfromtxt(datapath + f + ".ASC", unpack=True, delimiter=" ")
# Total count rate n
h_p = histogram(data[1, :], 4096)
p = fits.gaussian_fit(
array([0, 0, 200, mean(peak), peak[1] - peak[0]]),
h_p[0][slice(*peak)],
arange(*peak))
# clf()
# plot(arange(len(h_p[0][1:])), h_p[0][1:])
# en = arange(*peak)
# c = p[0][0] * en + p[0][1] + p[0][2] * \
# exp(-0.5 * ((en - p[0][3]) / p[0][4]) ** 2)
# plot(en, c, 'r-')
# show()
n = abs(p[0][4] * p[0][2] * sqrt(2 * pi)) / t
nerr = sqrt(sum(h_p[0][slice(*peak)])) / t
# nerr = sqrt((sum(h_p[0][1:]) / t ** 2 * 30) ** 2 +
# (sqrt(sum(h_p[0][1:])) / t) ** 2)
# print "diff is ", n_alt / n
