plt.xticks(fontsize=sz - 5)
plt.yticks(fontsize=sz - 5)
plt.subplots_adjust(bottom=.11)
sp_r = fig_r.add_subplot(1, 1, 1)
plt.figure(fig1.number)
plt.subplots_adjust(right=0.99, left=.07)
test_obj = sey_mod
energy = np.linspace(0., E_ts, num=int(1e3))
energy_e = np.linspace(0., E_e, num=int(2e2))
energy_r = np.linspace(0., E_r, num=int(1e3))
for i_ct, ct in enumerate(cos_theta_test):
thiscol = ms.colorprog(i_ct, len(cos_theta_test))
label = 'costheta=%.2f' % ct
sp1.plot(E_impact_eV_test,
del_true_mat[i_ct, :],
color=thiscol,
label=label,
linewidth=linewid)
sp_ts.plot(E_impact_eV_test,
del_true_mat[i_ct, :],
color=thiscol,
label=label,
linewidth=linewid)
sp2.plot(E_impact_eV_test,
del_elast_mat[i_ct, :],
color=thiscol,
label=label,
sp1 = plt.subplot(3,1,2, sharex=sp0)
# plot simulation data
for coast_ctr, coast_str in enumerate(coast_strs):
for sey_ctr, sey in enumerate(sey_vect):
#print beam_snapshot, device_name, sey
try:
dip_contribution_per_meter, ob, t_bun = get_simulation_ob('ArcDipReal', sey, coast_str)
sim_loss_per_hc = dip_contribution_per_meter * l_dip + quad_contribution_per_meter * l_quad + drift_contribution_per_meter * l_drift
if sey_ctr == 0:
label = coast_str + ' e9 coasting'
else:
label = None
color_curr = ms.colorprog(sey_ctr, N_sims)
sp1.semilogy(ob.t/25e-9, ob.Nel_timep, color=color_curr, label=label, ls=coast_linestyle_dict[coast_str])
if coast_ctr == 0:
label = sey
else:
label = None
sp2 = plt.subplot(3,1,3, sharex=sp1)
ms.sciy()
sp2.plot(t_bun[:-1]/25e-9, sim_loss_per_hc, '.-', color=color_curr, label=label, ls=coast_linestyle_dict[coast_str])
except IOError as err:
print('Got:', err)
ene_hilleret = hilleret_energy(energy)
popt, pcov = curve_fit(average_true_sec_energy_PDF,
energy,
ene_hilleret,
bounds=(1., 30.))
print('Fitted parameters for average true energy PDF:')
print('p_n:')
print((popt[0:10]))
print('eps_n:')
print((1.634185 / (popt[0:10] - 1)))
plt.figure(2, figsize=(20, 15), facecolor='white')
E_0s = np.array([10., 20., 35., 50., 75., 100., 300., 500.])
for i_E, E_0_curr in enumerate(E_0s):
thiscol = ms.colorprog(i_E, len(E_0s))
energy = np.linspace(0.00001, E_0_curr, num=int(1e3))
sey_mod_FP, impact_management_object, _ = make_it_easier(*popt)
delta_e, _, delta_ts = sey_mod_FP.yield_fun_furman_pivi(E=E_0_curr,
costheta=1.)
delta_ts_prime = delta_ts / (1 - delta_e)
pdf = average_true_sec_energy_PDF(energy, *popt)
plt.plot(energy,
pdf,
color=thiscol,
linestyle='--',
linewidth=linewid,
label='FP, $E_0 =$ %.0f' % E_0_curr)
by / len_,
len_,
pivot='middle')
bar = plt.colorbar(outp)
bar.set_ticks([])
lim = 1.2 * np.max(xx_raw)
sp.set_xlim(-lim, lim)
sp.set_ylim(-lim, lim)
mask = np.abs(y_mpB) < 1e-12
mask2 = np.abs(x_mpB) < 1e-12
if angle_ctr == 0:
color = ms.colorprog(order, 4)
xx_plot = np.linspace(-1, 1, 1e3)
sp2.plot(x_mpB[mask], by[mask], '.', label=title, color=color)
sp2.plot(xx_plot, xx_plot**order, color=color)
sp3.plot(y_mpB[mask2], bx[mask2], '.', label=title, color=color)
if order % 2 == 0:
sp3.plot(xx_plot, np.zeros_like(xx_plot), color=color)
else:
sp3.plot(xx_plot, (xx_plot)**order * (-1)**((order - 1) / 2),
color=color)
sp2.set_ylim(-1.1, 1.1)
sp3.set_ylim(-1.1, 1.1)
#sp3.legend(loc='upper left', bbox_to_anchor=(1,1))
sp3.legend(loc='upper right', framealpha=0.5)
alpha = 0.9
extract_ene_hist = impact_management_object.extract_energy_distributions(n_rep, E_impact_eV_test, cos_theta_test, mass=me, Nbin_extract_ene=500, factor_ene_dist_max=1.0)
plt.close('all')
ms.mystyle_arial()
fig1 = plt.figure(1, figsize=(3 * 8, 2 * 8))
fig1.set_facecolor('w')
sp1 = fig1.add_subplot(2, 2, 1)
sp2 = fig1.add_subplot(2, 2, 2)
sp3 = fig1.add_subplot(2, 2, 3)
sp4 = fig1.add_subplot(2, 2, 4)
for i_ct, ct in enumerate(cos_theta_test):
thiscol = ms.colorprog(i_ct, len(cos_theta_test))
label = 'costheta=%.2f' % ct
areats = scipy.integrate.simps(extract_ene_hist['true'][:, i_ct], extract_ene_hist['emit_ene_g_hist'])
areae = scipy.integrate.simps(extract_ene_hist['elast'][:, i_ct], extract_ene_hist['emit_ene_g_hist'])
arear = scipy.integrate.simps(extract_ene_hist['rediff'][:, i_ct], extract_ene_hist['emit_ene_g_hist'])
areaab = scipy.integrate.simps(extract_ene_hist['absorb'][:, i_ct], extract_ene_hist['emit_ene_g_hist'])
sp1.plot(extract_ene_hist['emit_ene_g_hist'], extract_ene_hist['true'][:, i_ct] / areats, color=thiscol, label=label, alpha=alpha, linewidth=linewid, marker='o')
sp2.plot(extract_ene_hist['emit_ene_g_hist'], extract_ene_hist['elast'][:, i_ct] / areae, color=thiscol, label=label, alpha=alpha, linewidth=linewid, marker='o')
sp3.plot(extract_ene_hist['emit_ene_g_hist'], extract_ene_hist['rediff'][:, i_ct] / arear, color=thiscol, label=label, alpha=alpha, linewidth=linewid, marker='o')
sp4.plot(extract_ene_hist['emit_ene_g_hist'], extract_ene_hist['absorb'][:, i_ct] / areaab, color=thiscol, label=label, alpha=alpha, linewidth=linewid, marker='o')
linewid = 3
sp2.plot(0, 0, 'k', label='FP-model PDF', linewidth=linewid)
# sp2.plot(0, 0, 'k', label='ECLOUD-model PDF', linewidth=linewid, linestyle='--')