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Adding loco beta beating and coupling correction iterations
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@elafmusa
elafmusa authored Nov 13, 2024
1 parent 36ca4b7 commit 2532b80
Showing 1 changed file with 52 additions and 34 deletions.
86 changes: 52 additions & 34 deletions pySC/example.py
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Original file line number Diff line number Diff line change
Expand Up @@ -185,44 +185,44 @@ def _marker(name):
nTurns=200)
# LOCO

cor_ords = sc_tools.ords_from_regex(SC.RING, 'CXY')
used_correctors1 = loco.select_equally_spaced_elements(SC.ORD.CM[0], 20)
used_correctors2 = loco.select_equally_spaced_elements(SC.ORD.CM[1], 20)
used_cor_ords = [used_correctors1, used_correctors2]
used_bpms_ords = loco.select_equally_spaced_elements(SC.ORD.BPM, len(SC.ORD.BPM))
cav_ords = sc_tools.ords_from_regex(SC.RING, 'RFC')
quads_ords = [sc_tools.ords_from_regex(SC.RING, 'QF'), sc_tools.ords_from_regex(SC.RING, 'QD')]
sext_ords = [sc_tools.ords_from_regex(SC.RING, 'SF'), sc_tools.ords_from_regex(SC.RING, 'SD')]

CMstep = np.array([1.e-4]) # correctors change [rad]
dk = 1.e-4 # quads change
RFstep = 1e3



orbit_response_matrix_model = SCgetModelRM(SC, used_bpms_ords, used_cor_ords, trackMode='ORB', useIdealRing=True, dkick=CMstep)
_, _, twiss = at.get_optics(SC.IDEALRING, SC.ORD.BPM)
dx = twiss.dispersion[:, 0]
dy = twiss.dispersion[:, 2]
dispersion_meas = np.column_stack((dx, dy))
orbit_response_matrix_model2 = np.hstack(
(orbit_response_matrix_model, ((dispersion_meas) / CMstep).reshape(-1, 1)))

print('Optics parameters before LOCO')
loco.analyze_ring(SC, twiss, SC.ORD.BPM, useIdealRing=False, makeplot=False)

Jn = loco.calculate_jacobian(SC, orbit_response_matrix_model, CMstep, used_cor_ords, used_bpms_ords, np.concatenate(quads_ords), dk,
trackMode='ORB', useIdealRing=False, skewness=False, order=1, method='add',
includeDispersion=False, rf_step=RFstep, cav_ords=cav_ords)
includeDispersion=False, rf_step=RFstep, cav_ords=cav_ords, full_jacobian=True)

Jn2 = loco.calculate_jacobian(SC, orbit_response_matrix_model, CMstep, used_cor_ords, used_bpms_ords, np.concatenate(quads_ords), dk,
Jn2 = loco.calculate_jacobian(SC, orbit_response_matrix_model2, CMstep, used_cor_ords, used_bpms_ords, np.concatenate(quads_ords), dk,
trackMode='ORB', useIdealRing=False, skewness=False, order=1, method='add',
includeDispersion=True, rf_step=RFstep, cav_ords=cav_ords, full_jacobian=False)

Js = loco.calculate_jacobian(SC, orbit_response_matrix_model, CMstep, used_cor_ords, used_bpms_ords, np.concatenate(sext_ords), 1.e-3,
Js = loco.calculate_jacobian(SC, orbit_response_matrix_model2, CMstep, used_cor_ords, used_bpms_ords, np.concatenate(sext_ords), 1.e-3,
trackMode='ORB', useIdealRing=False, skewness=True, order=1, method='add',
includeDispersion=True, rf_step=RFstep, cav_ords=cav_ords, full_jacobian=False)
includeDispersion=True, rf_step=RFstep, cav_ords=cav_ords, full_jacobian=True)

Jc = np.concatenate((Jn2, Js), axis=0)

# Beta correction iterations


#Jn = np.transpose(Jn, (0, 2, 1))
#weights = 1
Expand All @@ -231,14 +231,13 @@ def _marker(name):
A = tmp @ weights @ tmp.T
u, s, v = np.linalg.svd(A, full_matrices=True)
import matplotlib.pyplot as plt

plt.plot(np.log(s), 'd--')
plt.title('singular value')
plt.xlabel('singular values')
plt.ylabel('$\log(\sigma_i)$')
plt.show()

n_singular_values = 40
n_singular_values = 80

#Jt = loco_test.get_inverse(Jn, n_singular_values, weights)

Expand All @@ -247,13 +246,14 @@ def _marker(name):
info_tab = 14 * " "
LOGGER.info("RMS Beta-beating before LOCO:\n"
f"{info_tab}{bx_rms_err * 100:04.2f}% horizontal\n{info_tab}{by_rms_err * 100:04.2f}% vertical ")
n_iter = 3

n_iter = 2
# beta beating iterations
for x in range(n_iter): # optics correction using QF and QD
LOGGER.info(f'LOCO iteration {x}')
orbit_response_matrix_measured = loco.measure_closed_orbit_response_matrix(SC, used_bpms_ords, used_cor_ords, CMstep)
orbit_response_matrix_measured = loco.measure_closed_orbit_response_matrix(SC, used_bpms_ords, used_cor_ords, CMstep, includeDispersion=False)
n_quads, n_corrs, n_bpms = len(np.concatenate(quads_ords)), len(np.concatenate(used_cor_ords)), len(used_bpms_ords) * 2
bx_rms_err, by_rms_err = loco.model_beta_beat(SC.RING, twiss, SC.ORD.BPM, plot=False)
dx_rms_err, dy_rms_err = loco.getDispersionErr(SC.RING, twiss, SC.ORD.BPM)
total_length = n_bpms + n_corrs + n_quads
lengths = [n_quads, n_corrs, n_bpms]
including_fit_parameters = ['quads', 'cor', 'bpm']
Expand All @@ -263,11 +263,11 @@ def _marker(name):
initial_guess[lengths[0]:lengths[0] + lengths[1]] = 1e-6
initial_guess[lengths[0] + lengths[1]:] = 1e-6


# method lm (least squares)
#fit_parameters = loco.loco_correction_lm(initial_guess, (orbit_response_matrix_model),
# (orbit_response_matrix_measured), Jn, lengths,
# (orbit_response_matrix_measured), np.array(Jn), lengths,
# including_fit_parameters, bounds=(-0.03, 0.03), weights=weights, verbose=2)

# method ng
fit_parameters = loco.loco_correction_ng(initial_guess, orbit_response_matrix_model,
orbit_response_matrix_measured, np.array(Jn), lengths,
Expand All @@ -276,36 +276,48 @@ def _marker(name):
dg = fit_parameters[:lengths[0]] if len(fit_parameters) > n_quads else fit_parameters
SC = loco.set_correction(SC, dg, np.concatenate(quads_ords))
bx_rms_cor, by_rms_cor = loco.model_beta_beat(SC.RING, twiss, SC.ORD.BPM, plot=False)
dx_rms_cor, dy_rms_cor = loco.getDispersionErr(SC.RING, twiss, SC.ORD.BPM)
LOGGER.info(f"RMS Beta-beating after {x + 1} LOCO iterations:\n"
f"{info_tab}{bx_rms_cor * 100:04.2f}% horizontal\n{info_tab}{by_rms_cor * 100:04.2f}% vertical ")
LOGGER.info(f"Correction reduction: \n"
f" beta_x: {(1 - bx_rms_cor / bx_rms_err) * 100:.2f}%\n"
f" beta_y: {(1 - by_rms_cor / by_rms_err) * 100:.2f}%\n")
LOGGER.info(f"RMS dispersion after {x + 1} LOCO iterations:\n"
f"{info_tab}{dx_rms_cor * 100:04.2f}% horizontal\n{info_tab}{dy_rms_cor * 100:04.2f}% vertical ")
LOGGER.info(f"Correction reduction: \n"
f" dispersion_x: {(1 - dx_rms_cor / dx_rms_err) * 100:.2f}%\n"
f" dispersion_y: {(1 - dy_rms_cor / dy_rms_err) * 100:.2f}%\n")
print('Optics parameters after LOCO')
loco.analyze_ring(SC, twiss, SC.ORD.BPM, useIdealRing=False, makeplot=False)

# Coupling correction iterations
# dispersion correction iterations
weights = np.eye(len(used_bpms_ords) * 2)
tmp = np.sum(Jc, axis=2)
A = tmp @ weights @ tmp.T
u, s, v = np.linalg.svd(A, full_matrices=True)
u, s, v = np.linalg.svd(A, full_matrices=True)
import matplotlib.pyplot as plt

plt.plot(np.log(s), 'd--')
plt.title('singular value')
plt.xlabel('singular values')
plt.ylabel('$\log(\sigma_i)$')
plt.show()

n_singular_values = 60
n_iter = 2
n_singular_values = 75

n_iter = 1

for x in range(n_iter): # optics correction using QF and QD
LOGGER.info(f'LOCO iteration {x}')
print('Optics parameters after LOCO')
loco.analyze_ring(SC, twiss, SC.ORD.BPM, useIdealRing=False, makeplot=False)

orbit_response_matrix_measured = loco.measure_closed_orbit_response_matrix(SC, used_bpms_ords, used_cor_ords, CMstep, includeDispersion=True)
_, _, twiss_ = at.get_optics(SC.RING, used_bpms_ords)
dx = twiss_.dispersion[:, 0]
dy = twiss_.dispersion[:, 2]
dispersion_meas = np.column_stack((dx, dy))
orbit_response_matrix_measured = loco.measure_closed_orbit_response_matrix(SC, used_bpms_ords, used_cor_ords, CMstep)
n_quads, n_corrs, n_bpms = len(np.concatenate(quads_ords)), len(np.concatenate(used_cor_ords)), len(used_bpms_ords) * 2

n_quads, n_corrs, n_bpms = len(np.concatenate(quads_ords)) + len(np.concatenate(sext_ords)), len(np.concatenate(used_cor_ords)), len(used_bpms_ords) * 2
bx_rms_err, by_rms_err = loco.model_beta_beat(SC.RING, twiss, SC.ORD.BPM, plot=False)
dx_rms_err, dy_rms_err = loco.getDispersionErr(SC.RING, twiss, SC.ORD.BPM)

total_length = n_bpms + n_corrs + n_quads
lengths = [n_quads, n_corrs, n_bpms]
including_fit_parameters = ['quads', 'cor', 'bpm']
Expand All @@ -316,26 +328,32 @@ def _marker(name):
initial_guess[lengths[0] + lengths[1]:] = 1e-6

# method lm (least squares)
#fit_parameters = loco.loco_correction_lm(initial_guess, (orbit_response_matrix_model),
# (orbit_response_matrix_measured), Jn, lengths,
#fit_parameters = loco.loco_correction_lm(initial_guess, (orbit_response_matrix_model2),
# (orbit_response_matrix_measured), Jc, lengths,
# including_fit_parameters, bounds=(-0.03, 0.03), weights=weights, verbose=2)

# method ng
fit_parameters = loco.loco_correction_ng(initial_guess, orbit_response_matrix_model2,
orbit_response_matrix_measured, Jc, lengths,
including_fit_parameters, n_singular_values, weights=weights)
orbit_response_matrix_measured, Jc, lengths,
including_fit_parameters, n_singular_values, weights=weights)

dgn = fit_parameters[:len(np.concatenate(quads_ords))] #if len(fit_parameters) > n_quads else fit_parameters
dgs = fit_parameters[len(np.concatenate(quads_ords))::] #if len(fit_parameters) > n_quads else fit_parameters
dgs = fit_parameters[len(np.concatenate(quads_ords)):len(np.concatenate(sext_ords))+len(np.concatenate(quads_ords))] #if len(fit_parameters) > n_quads else fit_parameters

SC = loco.set_correction(SC, dgn, np.concatenate(quads_ords))
SC = loco.set_correction(SC, dgs, np.concatenate(sext_ords), skewness=True)

bx_rms_cor, by_rms_cor = loco.model_beta_beat(SC.RING, twiss, SC.ORD.BPM, plot=False)
dx_rms_cor, dy_rms_cor = loco.getDispersionErr(SC.RING, twiss, SC.ORD.BPM)
LOGGER.info(f"RMS Beta-beating after {x + 1} LOCO iterations:\n"
f"{info_tab}{bx_rms_cor * 100:04.2f}% horizontal\n{info_tab}{by_rms_cor * 100:04.2f}% vertical ")
LOGGER.info(f"Correction reduction: \n"
f" beta_x: {(1 - bx_rms_cor / bx_rms_err) * 100:.2f}%\n"
f" beta_y: {(1 - by_rms_cor / by_rms_err) * 100:.2f}%\n")

loco.analyze_ring(SC, twiss, SC.ORD.BPM, useIdealRing=False, makeplot=False)
LOGGER.info(f"RMS dispersion after {x + 1} LOCO iterations:\n"
f"{info_tab}{dx_rms_cor * 100:04.2f}% horizontal\n{info_tab}{dy_rms_cor * 100:04.2f}% vertical ")
LOGGER.info(f"Correction reduction: \n"
f" dispersion_x: {(1 - dx_rms_cor / dx_rms_err) * 100:.2f}%\n"
f" dispersion_y: {(1 - dy_rms_cor / dy_rms_err) * 100:.2f}%\n")
print('Optics parameters after LOCO')
loco.analyze_ring(SC, twiss, SC.ORD.BPM, useIdealRing=False, makeplot=False)

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