data_folder_fill +
'/fill_bunchbybunch_data_csvs/bunchbybunch_data_fill_%d.csv' %
filln,
verbose=False))
if use_recalculated:
fill_dict.update(qf.get_fill_dict(filln))
else:
fill_dict.update(
tm.parse_timber_file(
data_folder_fill +
'/fill_heatload_data_csvs/heatloads_fill_%d.csv' % filln,
verbose=False))
elif os.path.isdir(data_folder_fill + '/fill_basic_data_h5s'):
fill_dict.update(
tm.CalsVariables_from_h5(
data_folder_fill +
'/fill_basic_data_h5s/basic_data_fill_%d.h5' % filln, ))
fill_dict.update(
tm.CalsVariables_from_h5(
data_folder_fill +
'/fill_bunchbybunch_data_h5s/bunchbybunch_data_fill_%d.h5' %
filln, ))
if use_recalculated:
fill_dict.update(qf.get_fill_dict(filln))
else:
fill_dict.update(
tm.CalsVariables_from_h5(
data_folder_fill +
'/fill_heatload_data_h5s/heatloads_fill_%d.h5' % filln, ))
for csv in added_csvs:
for filln in sorted(dict_fill_bmodes.keys())[::-1]:
print('Fill %i' % filln)
h5filename = h5folder + '/imp_and_SR_fill_%d.h5' % filln
if dict_fill_bmodes[filln]['flag_complete'] is False:
print("Fill incomplete --> no h5 convesion")
continue
if os.path.isfile(h5filename):
print("Already complete and in h5")
continue
try:
fill_dict = {}
fill_dict.update(
tm.CalsVariables_from_h5(
'fill_basic_data_h5s/basic_data_fill_%d.h5' % filln))
fill_dict.update(
tm.CalsVariables_from_h5(
'fill_bunchbybunch_data_h5s/bunchbybunch_data_fill_%d.h5' %
filln))
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)
hl_imped_fill = fc.HeatLoad_calculated_fill(fill_dict,
hli_calculator,
filln = snapshots[i_snapshot]['filln']
t_sample_h = snapshots[i_snapshot]['t_h']
t_offset_h = snapshots[i_snapshot]['t_offs_h']
# get location of current data
data_folder_fill = dict_fill_bmodes[filln]['data_folder']
t_fill_st = dict_fill_bmodes[filln]['t_startfill']
t_fill_end = dict_fill_bmodes[filln]['t_endfill']
t_ref = t_fill_st
tref_string = time.strftime("%a, %d %b %Y %H:%M:%S", time.localtime(t_ref))
tref_string_short = time.strftime("%d %b %Y %H:%M", time.localtime(t_ref))
if from_published:
fill_file = f"{data_folder_fill}/fill_cell_by_cell_heatload_data_h5s/cell_by_cell_heatloads_fill_{filln}.h5"
hid = tm.CalsVariables_from_h5(fill_file)
else:
hid = qf.get_fill_dict(filln, h5_storage=H5_storage(recalc_h5_folder))
# extract standard fill data
fill_dict = {}
if os.path.isdir(data_folder_fill + '/fill_basic_data_csvs'):
# 2016 structure
fill_dict.update(
tm.parse_timber_file(
data_folder_fill +
'/fill_basic_data_csvs/basic_data_fill_%d.csv' % filln,
verbose=args.v))
fill_dict.update(
tm.parse_timber_file(
data_folder_fill +
if ':' in zero_at:
t_zero_unix = time.mktime(time.strptime(zero_at, '%d-%m-%Y,%H:%M'))
else:
t_zero_unix = t_ref_unix + float(zero_at)*3600.
filln_offset = fill_info.filln_at_time(t_zero_unix)
data_folder_fill = dict_fill_bmodes[filln_offset]['data_folder']
try:
fill_dict = tm.timber_variables_from_h5(data_folder_fill+'/heatloads_fill_h5s/heatloads_all_fill_%d.h5'%filln_offset)
print('From h5!')
except IOError:
print("h5 file not found, using h5s :-P")
fill_dict = {}
fill_dict.update(tm.CalsVariables_from_h5(
data_folder_fill + ('/fill_basic_data_h5s/'
'basic_data_fill_%d.h5'%filln_offset)))
fill_dict.update(tm.CalsVariables_from_h5(
data_folder_fill + ('/fill_heatload_data_h5s/'
'heatloads_fill_%d.h5'%filln_offset)))
if args.use_recalc:
fill_dict.update(qf.get_fill_dict(filln_offset,
h5_storage=H5_storage(recalc_h5_folder),
use_dP=True))
dict_offsets={}
for kk in hl_varlist:
dict_offsets[kk] = np.interp(t_zero_unix, np.float_(np.array(fill_dict[kk].t_stamps)), fill_dict[kk].float_values())
import sys, os
BIN = os.path.expanduser("../")
sys.path.append(BIN)
# Load fills
import LHCMeasurementTools.TimberManager as tm
filln = 6740
fill_dict = {}
fill_dict.update(
tm.CalsVariables_from_h5(
('../../LHC_followup_download_scripts/fill_basic_data_h5s'
'/basic_data_fill_%d.h5' % filln)))
fill_dict.update(
tm.CalsVariables_from_h5(
('../../LHC_followup_download_scripts/fill_bunchbybunch_data_h5s/'
'bunchbybunch_data_fill_%d.h5' % filln)))
# Build heat load calculators
import impedance_heatload as ihl
import synchrotron_radiation_heatload as srhl
hli_calculator = ihl.HeatLoadCalculatorImpedanceLHCArc()
hlsr_calculator = srhl.HeatLoadCalculatorSynchrotronRadiationLHCArc()
# Use fill calculator
import FillCalculator as fc
hl_imped_fill = fc.HeatLoad_calculated_fill(fill_dict, hli_calculator)
hl_sr_fill = fc.HeatLoad_calculated_fill(fill_dict, hlsr_calculator)
t_ref = dict_fill_bmodes[filln]['t_startfill']
tref_string = time.strftime("%a, %d %b %Y %H:%M:%S", time.localtime(t_ref))
fill_dict = {}
if os.path.isdir(data_folder_fill + '/fill_basic_data_csvs'):
fill_dict.update(
tm.parse_timber_file(
data_folder_fill +
'/fill_bunchbybunch_data_csvs/bunchbybunch_data_fill_%d.csv' %
filln,
verbose=False))
elif os.path.isdir(data_folder_fill + '/fill_basic_data_h5s'):
fill_dict.update(
tm.CalsVariables_from_h5(
data_folder_fill +
'/fill_bunchbybunch_data_h5s/bunchbybunch_data_fill_%d.h5' %
filln, ))
else:
raise ValueError('What?!')
i_fig = 0
plt.close('all')
# Loop over beams
beam_col = ['b', 'r']
for beam in [1, 2]:
print('\nPreparing plot beam %d...' % beam)
fbct = FBCT.FBCT(fill_dict, beam=beam)
dt = np.diff(fbct.t_stamps)[0]
fbct_t_all, fbct_v_all = fbct.uniform_time(t_inter=dt)
nslots = fbct_v_all.shape[1]
xlim = None, None
if '--notrace' in sys.argv:
list_scan_times = []
fill_dict = {}
if os.path.isdir(data_folder_fill + '/fill_basic_data_csvs'):
fill_dict.update(
tm.parse_timber_file(
data_folder_fill +
'/fill_basic_data_csvs/basic_data_fill_%d.csv' % filln,
verbose=True))
elif os.path.isdir(data_folder_fill + '/fill_basic_data_h5s'):
fill_dict.update(
tm.CalsVariables_from_h5(
data_folder_fill +
'/fill_basic_data_h5s/basic_data_fill_%d.h5' % filln, ))
pl.close('all')
sp_ploss = None
# START PLOT
fig_h = pl.figure(1, figsize=(8 * 1.6, 6 * 1.3))
fig_h.patch.set_facecolor('w')
ms.mystyle_arial(fontsz=16, dist_tick_lab=5)
fig_h.suptitle('Fill %d: started on %s' % (filln, tref_string), fontsize=18)
sp_int = pl.subplot2grid((2, 3), (0, 0), rowspan=1)
sp_energy = sp_int.twinx()
sp_totploss = pl.subplot2grid((2, 3), (1, 0), rowspan=1, sharex=sp_int)
plotaveonly = True
fill_dict = {}
if os.path.isdir(data_folder_fill+'/fill_basic_data_csvs'):
# 2016+ structure
fill_dict.update(tm.parse_timber_file(
data_folder_fill+'/fill_basic_data_csvs/basic_data_fill_%d.csv'%filln,
verbose=True))
fill_dict.update(tm.parse_timber_file(
(data_folder_fill +
'/fill_bunchbybunch_data_csvs/bunchbybunch_data_fill_%d.csv'%filln),
verbose=True))
elif os.path.isdir(data_folder_fill+'/fill_basic_data_h5s'):
# 2016+ structure
fill_dict.update(tm.CalsVariables_from_h5(
data_folder_fill+'/fill_basic_data_h5s/basic_data_fill_%d.h5'%filln))
fill_dict.update(tm.CalsVariables_from_h5(
(data_folder_fill +
'/fill_bunchbybunch_data_h5s/bunchbybunch_data_fill_%d.h5'%filln)))
else:
# 2015 structure
fill_dict.update(tm.parse_timber_file(data_folder_fill+'/fill_csvs/fill_%d.csv'%filln, verbose=True))
beam_col = ['k', 'b','r']
sp_sigma_h = None
sp_t = None
pl.close('all')
ms.mystyle_arial(fontsz=16, dist_tick_lab=5)
spemit = None