def profile_from_blmeas(file_, tt_halfrange, charge, energy_eV, subtract_min=False, zero_crossing=1):
bl_meas = data_loader.load_blmeas(file_)
time_meas0 = bl_meas['time_profile%i' % zero_crossing]
current_meas0 = bl_meas['current%i' % zero_crossing]
if subtract_min:
current_meas0 = current_meas0 - current_meas0.min()
if tt_halfrange is None:
tt, cc = time_meas0, current_meas0
else:
current_meas0 *= charge/current_meas0.sum()
gf_blmeas = GaussFit(time_meas0, current_meas0)
time_meas0 -= gf_blmeas.mean
time_meas1 = np.arange(-tt_halfrange, time_meas0.min(), np.diff(time_meas0).mean())
time_meas2 = np.arange(time_meas0.max(), tt_halfrange, np.diff(time_meas0).mean())
time_meas = np.concatenate([time_meas1, time_meas0, time_meas2])
current_meas = np.concatenate([np.zeros_like(time_meas1), current_meas0, np.zeros_like(time_meas2)])
tt, cc = time_meas, current_meas
return BeamProfile(tt, cc, energy_eV, charge)
import matplotlib.pyplot as plt
import numpy as np
from scipy.constants import c
import data_loader
import uwf_model as uwf
import myplotstyle as ms
plt.close('all')
semigap = 4e-3 / 2.
data_dir = '/afs/psi.ch/intranet/SF/Beamdynamics/Philipp/data/data_2020-02-03/'
meas1 = 'Bunch_length_meas_2020-02-03_21-54-24.h5'
lims = [25, 70]
bl_meas = data_loader.load_blmeas(data_dir + meas1)
charge = 200e-12
charge_xx = bl_meas['time_profile1'] * c
charge_xx -= charge_xx.min()
current_profile = bl_meas['current1']
charge_profile = current_profile * charge / np.sum(current_profile)
energy_eV = bl_meas['energy_eV']
mask_charge = np.logical_and(charge_xx > lims[0] * 1e-6,
charge_xx < lims[1] * 1e-6)
assert np.any(mask_charge)
charge_xx = charge_xx[mask_charge]
charge_xx -= charge_xx.min()
charge_profile = charge_profile[mask_charge]
import numpy as np
np
from scipy.constants import c
import matplotlib.pyplot as plt
from scipy.io import loadmat
import myplotstyle as ms
import wf_model
import data_loader
data_dir = '/storage/data_2020-02-03/'
data_dir = '/afs/psi.ch/intranet/SF/Beamdynamics/Philipp/data/data_2020-02-03/'
data_dir = '/sf/data/measurements//2020/02/03/'
bl_meas_file = data_dir + 'Bunch_length_meas_2020-02-03_15-59-13.h5'
bl_meas = data_loader.load_blmeas(bl_meas_file)
total_charge = 200e-12
current_profile = bl_meas['current1']
charge_profile = current_profile * total_charge / np.sum(current_profile)
charge_xx = bl_meas['time_profile1'] * c
charge_xx -= charge_xx.min()
energy_eV = bl_meas['energy_eV']
plt.close('all')
files = [
data_dir + '/Eloss_DEH1.fig.mat', data_dir + '/Eloss_DEH2.fig.mat',
data_dir + '/Eloss_DEH1-2.fig.mat'
]
lengths = [1, 1, 2]
titles = ['Structure 1', 'Structure 2', 'Structures 1+2']
subplot = ms.subplot_factory(3,3)
sp_current = subplot(sp_ctr, title='Current')
sp_ctr += 1
full_gap = 10e-3
offset0 = (-4.22e-3) - 0.52e-3
del_offset_arr = np.array([0,])*2*1e-6
n_particles = int(20e3)
energy_eV = 5.95e9
bin_number = 200
timestamp = elegant_matrix.get_timestamp(2020, 10, 3, 15, 43, 29)
timestamp = 1601681166
dl = data_loader.load_blmeas('/sf/data/measurements/2020/10/03/Bunch_length_meas_2020-10-03_15-43-29.h5')
energy_eV = dl["energy_eV"]
arr0 = np.zeros([len(del_offset_arr), bin_number], float)
output = {
'energy_eV': energy_eV,
'full_gap_s2': full_gap,
'delta_offset': del_offset_arr,
'proj_no_streak': arr0.copy(),
'axis_no_streak': arr0.copy(),
'proj_streak': arr0.copy(),
'axis_streak': arr0.copy(),
}
curr = dl['current1'][::-1]
xx = dl['time_profile1']
ms.figure('All blmeas of 03.02.2020')
sp_ctr = 1
subplot = ms.subplot_factory(2,2)
sp_current = subplot(sp_ctr, title='Current 1', xlabel='z [$\mu$m]', ylabel='I [kA]')
sp_ctr += 1
sp_current2 = subplot(sp_ctr, title='Current 2')
sp_ctr += 1
for ctr, (blmeas, charge) in enumerate(meas_charge):
label = ctr
meas = data_loader.load_blmeas(data_dir + blmeas)
xx = meas['time_profile1']*c
yy = meas['current1']
sp_current.plot(xx*1e6, yy/1e3, label=label)
print(ctr, '%.1e' % np.trapz(yy, xx))
if meas['time_profile2'] is not None:
xx = meas['time_profile2']*c
yy = meas['current2']
sp_current2.plot(xx*1e6, yy/1e3, label=label)
xlim = sp_current.get_xlim()
meas2 = 'Bunch_length_meas_2020-02-03_22-08-38.h5'
meas3 = 'Bunch_length_meas_2020-02-03_23-55-33.h5'
charge_lims1 = [25, 70]
charge_lims2 = [40, 125]
charge_lims3 = [40, 100]
mat_files_current_charge_lims = [
('Eloss_UNDbis.mat', meas1, 200e-12, charge_lims1),
('Eloss_UND2ndStreak.mat', meas1, 200e-12, charge_lims1),
('Eloss_UND-COMP2.mat', meas2, 100e-12, charge_lims2),
('Eloss_UND-COMP3.mat', meas3, 100e-12, charge_lims3),
]
for mat_file, current_file, charge, lims in mat_files_current_charge_lims:
bl_meas = data_loader.load_blmeas(data_dir + current_file)
charge_xx = bl_meas['time_profile1'] * c
charge_xx -= charge_xx.min()
current_profile = bl_meas['current1']
charge_profile = current_profile * charge / np.sum(current_profile)
energy_eV = bl_meas['energy_eV']
mask_charge = np.logical_and(charge_xx > lims[0] * 1e-6,
charge_xx < lims[1] * 1e-6)
assert np.any(mask_charge)
charge_xx = charge_xx[mask_charge]
charge_xx -= charge_xx.min()
charge_profile = charge_profile[mask_charge]
wf_meas = loadmat(data_dir + mat_file)