def integrand2(theta, E, forward, x_min, x_max, sad):
p1 = at.klein_nishina(E, theta) * 10e30
p2 = rd.continue_line(theta, sad, x_min, x_max)
p3 = at.energy_limit_factor(E, theta, forward)
p4 = at.energy_distribution(E)
p5 = rd.continue_log(E / 1000, af.E, af.prob_NE213)
return p1 * p2 * p3 * p4 * (1 - p5)
def integrand(E, theta_S, sad, forward, x_min, x_max):
p1 = rd.continue_line(theta_S, sad, x_min, x_max)
p2 = at.klein_nishina(E, theta_S)
p3 = at.energy_limit_factor(E, theta_S, forward) * 1e35
p4 = at.energy_distribution(E)
#print(p1*p2*p3*p4,p1,p2,p3,p4,E,theta_S)
return p1 * p2 * p3 * p4
def plot_E_all():
scale1 = 1.7
x_min = 0
x_max = 6000
d = rd.read_h5py_file()
d = rd.cut_selection(d, 9, 0, True)
E = rd.extract_parameter(d, 1) # + rd.extract_parameter(d, 3)
n, bins, patches = plt.hist(E, 500)
x = np.linspace(x_min, x_max, 200)
y = np.array([at.energy_distribution(i) for i in x])
y = y * np.amax(n) / np.amax(y) * scale1
#plt.plot(x,y,label="A")
plt.xlim(x_min, x_max)
plt.xlabel("Detected Energy [keV]")
plt.ylabel("Frequency [Counts/Bin]")
def plot_E_dist(
forward,
num_bins=300,
):
x_min = 0000
x_max = 5000
y_min = 0
#y_max=140000
scale1 = 1.8
scale2 = 1
d = rd.read_h5py_file()
d = rd.cut_selection(d, 9, 0, forward)
E = rd.extract_parameter(d, 1) + rd.extract_parameter(d, 3)
n, bins, patches = plt.hist(E, num_bins)
x = np.linspace(x_min, x_max, 100)
y = np.array([at.energy_distribution(i) for i in x])
y = y * np.amax(n) / np.amax(y) * scale1
plt.plot(x, y, label="A")
if forward:
t_min, t_max, sad = at.fsad_min, at.fsad_max, at.fsad
else:
t_min, t_max, sad = at.bsad_min, at.bsad_max, at.bsad
y2 = np.array([
quad(integrand1, t_min, t_max, (i, forward, t_min, t_max, sad), 0,
10e-5, 10e-5)[0] for i in x
])
y2 = y2 * np.amax(n) / np.amax(y2) * scale2
plt.plot(x, y2, label="B")
plt.xlabel("Total Detected Energy [keV]")
plt.ylabel("Frequency [Counts/Bin]")
plt.legend()
plt.xlim(x_min, x_max)
plt.ylim(0, 50000)
def integrand2(Energy):
return at.energy_distribution(Energy * 1000)
def integrand1(Energy):
return at.energy_distribution(Energy * 1000) * rd.continue_linear_set(
Energy, E, average_distance)
def integrand1(theta, E, forward, x_min, x_max, sad):
p1 = at.klein_nishina(E, theta) * 10e30
p2 = rd.continue_line(theta, sad, x_min, x_max)
p3 = at.energy_limit_factor(E, theta, forward)
p4 = at.energy_distribution(E)
return p1 * p2 * p3 * p4