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011b_compare_to_meas.py
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011b_compare_to_meas.py
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import os
import numpy as np
import matplotlib.pyplot as plt
from scipy.io import loadmat
#from scipy.constants import c
from scipy.optimize import curve_fit
from EmittanceTool.h5_storage import loadH5Recursive
#import data_loader
import uwf_model as uwf
import myplotstyle as ms
plt.close('all')
data_dir = '/afs/psi.ch/intranet/SF/Beamdynamics/Philipp/data/data_2020-02-03/'
bl_meas_file = data_dir + 'Bunch_length_meas_2020-02-03_21-54-24.h5'
mat1 = data_dir + 'Eloss_UNDbis.mat'
total_charge = 200e-12
trim = True
dd = loadmat(mat1)
for c_ctr in (0, 1, 2):
result_dict = loadH5Recursive(os.path.basename(mat1)+'_wake%i.h5' % c_ctr)
charge_profile = result_dict['charge_profile']
charge_xx = result_dict['charge_xx']
energy_eV = result_dict['energy_eV']
gap_list = result_dict['gap_list']
#result_dict = {str(i): result_list[i] for i, gap in enumerate(gap_list)}
result_list = [result_dict[str(i)] for i, gap in enumerate(gap_list)]
ms.figure('Undulator wakefield measurements')
plt.subplots_adjust(hspace=0.4)
subplot = ms.subplot_factory(3,3)
sp_ctr = 1
sp_charge = subplot(sp_ctr, title='Current_profile')
sp_ctr += 1
sp_charge.plot(charge_xx*1e6, charge_profile)
xlabel = 's [$\mu$m]'
ylabel = 'w [kV/(pC$\cdot$m)]'
ylabel2 = '$\Delta$ E [MeV]'
sp_wf_surface = subplot(sp_ctr, title='Surface wake', xlabel=xlabel, ylabel=ylabel)
sp_ctr += 1
sp_wf_res = subplot(sp_ctr, title='Resistive wake', xlabel=xlabel, ylabel=ylabel)
sp_ctr += 1
sp_wf_surface_W = subplot(sp_ctr, title='Surface wake convolved', xlabel=xlabel, ylabel=ylabel2)
sp_ctr += 1
sp_wf_res_W = subplot(sp_ctr, title='Resistive wake convolved', xlabel=xlabel, ylabel=ylabel2)
sp_ctr += 1
sp_chirp = subplot(sp_ctr, title='Combined effect', xlabel='s [$\mu$m]', ylabel=ylabel2)
sp_ctr += 1
sp_gap_effect = subplot(sp_ctr, title='Proj Energy loss', xlabel='Gap [mm]', ylabel='Energy loss [MeV]')
sp_ctr += 1
sp_espread = subplot(sp_ctr, title='Proj Espread increase [keV]', xlabel='Gap [mm]', ylabel='Espread change[MeV]')
sp_ctr += 1
eloss_surface = []
eloss_ac = []
espread_surface = []
espread_ac = []
W_combined = []
for gap, wf_dict in zip(gap_list, result_list):
loss_surface = wf_dict['proj_Eloss_surface']
loss_ac = wf_dict['proj_Eloss_ac']
eloss_surface.append(loss_surface)
eloss_ac.append(loss_ac)
espread_surface.append(wf_dict['proj_Espread_surface'])
espread_ac.append(wf_dict['proj_Espread_ac'])
label = '%.1f' % (gap*1e3)
plot_xx = charge_xx * 1e6
factor1 = 1e-3*1e-12
factor2 = 1e-6
sp_wf_surface.errorbar(plot_xx, wf_dict['w_surface']*factor1, label=label, yerr=wf_dict['w_surface_err']*factor1)
sp_wf_res.plot(plot_xx, wf_dict['w_ac']*factor1, label=label)
sp_wf_surface_W.plot(plot_xx, wf_dict['W_surface']*factor2, label=label)
sp_wf_res_W.plot(plot_xx, wf_dict['W_ac']*factor2, label=label)
comb = (wf_dict['W_ac']+wf_dict['W_surface'])
W_combined.append(comb)
sp_chirp.plot(plot_xx, comb*factor2, label=label)
eloss_surface = np.array(eloss_surface)
eloss_ac = np.array(eloss_ac)
espread_surface = np.array(espread_surface)
espread_ac = np.array(espread_ac)
W_combined = np.array(W_combined)
eloss_surface -= eloss_surface.max()
eloss_ac -= eloss_ac.max()
sp_gap_effect.plot(gap_list*1e3, eloss_surface/1e6, label='Surface')
sp_gap_effect.plot(gap_list*1e3, eloss_ac/1e6, label='Resistive')
sp_gap_effect.plot(gap_list*1e3, (eloss_ac+eloss_surface)/1e6, label='Combined')
delta_E_screen = yy0 = dd['delta'].squeeze() * energy_eV
yy = yy0.mean(axis=0)
yy_err = yy0.std(axis=0)
yy -= yy[0]
sp_gap_effect.errorbar(gap_list*1e3, yy/1e6, yerr=yy_err/1e6, label='Screen')
delta_E_bpm = yy0 = dd['delta1'].T.squeeze() * energy_eV
yy = yy0.mean(axis=0)
yy_err = yy0.std(axis=0)
yy -= yy[0]
sp_gap_effect.errorbar(gap_list*1e3, yy/1e6, yerr=yy_err/1e6, label='BPM')
espread_fwhm = yy0 = dd['fwhm_delta'] * energy_eV
yy = yy0.mean(axis=0)
yy_err = yy0.std(axis=0)
yy -= yy[0]
espread_fwhm_plot = yy
sp_espread.errorbar(gap_list*1e3, espread_fwhm_plot/1e6, yerr=yy_err/1e6, label='FWHM')
espread_ac_plot = espread_ac - espread_ac[0]
espread_surface_plot = espread_surface - espread_surface[0]
sp_espread.plot(gap_list*1e3, espread_ac_plot/1e6, label='Resistive')
sp_espread.plot(gap_list*1e3, espread_surface_plot/1e6, label='Surface')
sp_espread.plot(gap_list*1e3, (espread_surface_plot+espread_ac_plot)/1e6, label='Combined')
mean_x = np.mean(charge_xx)
ms.figure('Debug fit')
sp_ctr = 1
sp_initial_chirp = subplot(sp_ctr, title='Initial chirp')
sp_ctr += 1
#sp_final_chirp = subplot(sp_ctr, title='Final chirp', sciy=True)
#sp_ctr += 1
sp_espread_fit = subplot(sp_ctr, title='Energy spread')
sp_ctr += 1
def fit_initial_chirp(gap_list, dE_ds, plot=False):
init_chirp = dE_ds * (charge_xx - mean_x)
#init_Espread = np.sqrt(np.sum(init_chirp**2*charge_profile)/np.sum(charge_profile) - (np.sum(init_chirp*charge_profile)/np.sum(charge_profile))**2)
#init_Espread2 = uwf.calc_espread(init_chirp, charge_profile)
if plot:
label = '%.2e' % dE_ds
sp_initial_chirp.plot(charge_xx, init_chirp/1e6, label=label)
final_chirp_list = []
for i, gap in enumerate(gap_list):
final_chirp = init_chirp + W_combined[i]
final_espread = uwf.calc_espread(final_chirp, charge_profile)
final_chirp_list.append(final_espread)
if plot:
#sp_final_chirp.plot(charge_xx, final_chirp, label=label)
pass
#import pdb; pdb.set_trace()
final_chirp_list = np.array(final_chirp_list)
outp = final_chirp_list - final_chirp_list[0]
if plot:
sp_espread_fit.plot(gap_list*1e3, outp/1e6, label=label)
return outp
initial_guess = -1e8/charge_xx.max()
fit_chirp = curve_fit(fit_initial_chirp, gap_list, espread_fwhm_plot, p0=[initial_guess])
fit_chirp_yy0 = fit_initial_chirp(gap_list, fit_chirp[0])
for deds in np.array([0, 0.8, 1, 1.2])*initial_guess:
fit_chirp_yy = fit_initial_chirp(gap_list, deds, plot=True)
sp_espread_fit.errorbar(gap_list*1e3, espread_fwhm_plot/1e6, yerr=yy_err/1e6, label='FWHM')
sp_espread.plot(gap_list*1e3, fit_chirp_yy0/1e6, label='Fit')
for sp_ in sp_wf_res, sp_wf_surface, sp_wf_res_W, sp_wf_surface_W, sp_espread, sp_gap_effect, sp_chirp, sp_espread_fit, sp_initial_chirp:
sp_.legend()
#for gap, wf_dict in zip(gap_list, result_list):
# print(gap, loss_surface, loss_ac)
plt.show()