color=color)
sp.set_ylim(-10, None)
ms.comb_legend(sp, sp2, bbox_to_anchor=(1.3, 1), fontsize=myfontsz)
if args.contributions:
fig = ms.figure('Heat load contributions', figs)
fig.subplots_adjust(right=0.75, wspace=0.45, hspace=0.4)
sp = None
fill_dict.update(
tm.parse_timber_file(
'./fill_bunchbybunch_data_csvs/bunchbybunch_data_fill_%d.csv' %
filln,
verbose=False))
hli_calculator = ihl.HeatLoadCalculatorImpedanceLHCArc()
hlsr_calculator = srhl.HeatLoadCalculatorSynchrotronRadiationLHCArc()
hl_imped_fill = fc.HeatLoad_calculated_fill(fill_dict, hli_calculator)
hl_sr_fill = fc.HeatLoad_calculated_fill(fill_dict, hlsr_calculator)
model_time = (hl_sr_fill.t_stamps - t_ref) / 3600
t_start_injphys = (dict_fill_bmodes[filln]['t_start_INJPHYS'] -
t_ref) / 3600.
def compute_offset(tt, yy):
mask_offset = np.logical_and(tt < t_start_injphys,
tt > t_start_injphys - 600)
offset = np.mean(yy[mask_offset])
return offset
def extract_and_compute_extra_fill_data(fill_dict,
t_ref,
t_sample_h,
thresh_bint=3e10):
from LHCMeasurementTools.LHC_FBCT import FBCT
from LHCMeasurementTools.LHC_BCT import BCT
from LHCMeasurementTools.LHC_BQM import blength
from LHCMeasurementTools.LHC_Energy import energy
import HeatLoadCalculators.impedance_heatload as ihl
import HeatLoadCalculators.synchrotron_radiation_heatload as srhl
import HeatLoadCalculators.FillCalculator as fc
fbct_bx = {}
bct_bx = {}
blength_bx = {}
for beam_n in [1, 2]:
fbct_bx[beam_n] = FBCT(fill_dict, beam=beam_n)
bct_bx[beam_n] = BCT(fill_dict, beam=beam_n)
blength_bx[beam_n] = blength(fill_dict, beam=beam_n)
hli_calculator = ihl.HeatLoadCalculatorImpedanceLHCArc()
hlsr_calculator = srhl.HeatLoadCalculatorSynchrotronRadiationLHCArc()
hl_imped_fill = fc.HeatLoad_calculated_fill(fill_dict,
hli_calculator,
bct_dict=bct_bx,
fbct_dict=fbct_bx,
blength_dict=blength_bx)
hl_sr_fill = fc.HeatLoad_calculated_fill(fill_dict,
hlsr_calculator,
bct_dict=bct_bx,
fbct_dict=fbct_bx,
blength_dict=blength_bx)
hl_imped_sample = hl.magnet_length['AVG_ARC'][0] * np.interp(
t_sample_h, (hl_imped_fill.t_stamps - t_ref) / 3600,
hl_imped_fill.heat_load_calculated_total)
hl_sr_sample = hl.magnet_length['AVG_ARC'][0] * np.interp(
t_sample_h, (hl_imped_fill.t_stamps - t_ref) / 3600,
hl_sr_fill.heat_load_calculated_total)
intensity_b1 = np.interp(t_sample_h, (bct_bx[1].t_stamps - t_ref) / 3600,
bct_bx[1].values)
intensity_b2 = np.interp(t_sample_h, (bct_bx[2].t_stamps - t_ref) / 3600,
bct_bx[2].values)
bl_ave_b1 = np.interp(t_sample_h, (blength_bx[1].t_stamps - t_ref) / 3600,
blength_bx[1].avblen)
bl_ave_b2 = np.interp(t_sample_h, (blength_bx[2].t_stamps - t_ref) / 3600,
blength_bx[2].avblen)
n_bunches_b1 = np.sum(fbct_bx[1].nearest_older_sample(t_sample_h * 3600 +
t_ref) > thresh_bint)
n_bunches_b2 = np.sum(fbct_bx[2].nearest_older_sample(t_sample_h * 3600 +
t_ref) > thresh_bint)
energy_GeV = energy(fill_dict,
beam=1).nearest_older_sample(t_sample_h * 3600 + t_ref)
return intensity_b1, intensity_b2, bl_ave_b1, bl_ave_b2, n_bunches_b1, n_bunches_b2, energy_GeV, hl_imped_sample, hl_sr_sample
