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Add option for high resolution clock file (100+ bigger) #18

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c68c32e
New solution with 24000334 ref divisor
matteobachetti Sep 29, 2020
f7be474
Add fixed control points machinery; use new solution based on average…
matteobachetti Sep 29, 2020
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63 changes: 54 additions & 9 deletions nuclockutils/nustarclock.py
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Original file line number Diff line number Diff line change
Expand Up @@ -315,7 +315,6 @@ def eliminate_trends_in_residuals(temp_table, clock_offset_table,
table_new['temp_corr'][:] = clock_off_fun(table_new['met'])

log.info("Final detrending...")

table_new = spline_detrending(
clock_offset_table, temp_table,
outlier_cuts=[-0.002, -0.001],
Expand Down Expand Up @@ -843,6 +842,7 @@ def __init__(self, temperature_file, mjdstart=None, mjdstop=None,
self.clock_jump_times = \
np.array([78708320, 79657575, 81043985, 82055671, 293346772])
self.fixed_control_points = np.arange(291e6, 295e6, 86400)

# Sum 30 seconds to avoid to exclude these points
# from previous interval
self.gtis = find_good_time_intervals(
Expand Down Expand Up @@ -971,7 +971,8 @@ def write_clock_file(self, filename=None, save_nodetrend=False,
idx0, idx1 = np.searchsorted(
allmets, [jumptime - twodays, jumptime + twodays])
# print(idx0, idx1)
good_for_clockfile[idx0:idx1:10] = True

good_for_clockfile[idx0:idx1] = True
new_clock_table_subsample = new_clock_table[good_for_clockfile]
else:
new_clock_table_subsample = new_clock_table
Expand Down Expand Up @@ -1392,14 +1393,56 @@ def clock_ppm_model(nustar_met, temperature, craig_fit=False):
parameters of the ppm-time relation (long-term clock decay)

"""

# Parameters([('b0',
# <Parameter 'b0', value=0.00881627228 (fixed), bounds=[0:inf]>),
# ('b1', <Parameter 'b1', value=95.9392102 (fixed), bounds=[0:inf]>),
# ('b2',
# <Parameter 'b2', value=-0.224413446 (fixed), bounds=[-inf:0]>),
# ('b3',
# <Parameter 'b3', value=0.0382542123 (fixed), bounds=[0:inf]>),
# ('e',
# <Parameter 'e', value=-0.01877278059005673 +/- 5.17e-05, bounds=[-inf:inf]>),
# ('__lnsigma',
# <Parameter '__lnsigma', value=-5.4061409197641535 +/- 0.0081, bounds=[-9.210340371976182:-4.605170185988

# a0 -0.07408473 4.8844e-05 (0.07%) -0.07395161774247343 -0.08000000 -0.06000000 True
# a1 0.00157866 2.6408e-05 (1.67%) 0.001701982761160454 -inf inf True
# c 0.00108028 5.9741e-05 (5.53%) 0.0009251728994994087 -inf inf True

# __lnsigma
# [[Variables]]
# b0: 0.008816272(fixed)
# b1: 95.93921(fixed)
# b2: -0.2244134(fixed)
# b3: 0.03825421(fixed)
# e: -0.01875000(init=0.01)

T0 = 13.440
# offset = 13.9158325193 - 0.027918 - 4.608765729063114e-4 -7.463444052344004e-9
# offset = 13.8874536353 - 4.095179312091239e-4
offset = 13.91877 -0.02020554 # sum the "e" parameter from long term

# # offset = 13.9158325193 - 0.027918 - 4.608765729063114e-4 -7.463444052344004e-9
# # offset = 13.8874536353 - 4.095179312091239e-4
# Solution with ref_f0 = 24000000
# offset = 13.91877 -0.02020554 # sum the "e" parameter from long term
# ppm_vs_T_pars = [-0.07408473, 0.00157866]
#
# ppm_vs_time_pars = [0.00874492067, 100.255995, -0.251789345,
# 0.0334934847]
# Solution with ref_f0 = 24000334
offset = 0.00108028 -0.01877278059005673 # sum the "e" parameter from long term

ppm_vs_T_pars = [-0.07413, 0.00158]

ppm_vs_time_pars = [0.00874492067, 100.255995, -0.251789345,
0.0334934847]
ppm_vs_time_pars = [0.00881627228, 95.9392102, -0.224413446,
0.0382542123]
# # Solution with ref_f0 = divisor
# offset = -0.24891560 -0.01877306331788237 # sum the "e" parameter from long term
# T0 = 13.4345218
# ppm_vs_T_pars = [-0.07408470, 0.00157877]
#
# ppm_vs_time_pars = [0.00881627228, 95.9392102, -0.224413446,
# 0.0382542123]

if craig_fit:
offset = 1.3847529679329989e+01
ppm_vs_T_pars = [-7.3964896025586133e-02, 1.5055740907563737e-03]
Expand Down Expand Up @@ -1440,8 +1483,10 @@ def temperature_delay(temptable, divisor,
print(table_times.min(), table_times.max())
raise

clock_rate_corr = (1 + ppm_mod / 1000000) * 24000000 / divisor - 1

# clock_rate_corr = (1 + ppm_mod / 1000000) * 24000000 / divisor - 1
clock_rate_corr = (1 + ppm_mod / 1000000) * 24000334 / divisor - 1
# clock_rate_corr = (1 + ppm_mod / 1000000) - 1
# print(clock_rate_corr)
delay_sim = simpcumquad(times_fine, clock_rate_corr)
return interp1d(times_fine, delay_sim, fill_value='extrapolate',
bounds_error=False)
Expand Down