Calibration Smoothing¶
by Josh Dillon, last updated December 20, 2025
This notebook runs calibration smoothing to the gains coming out of file_calibration notebook. It removes any flags founds on by that notebook and replaces them with flags generated from full_day_rfi and full_day_antenna_flagging. It flags antennas with high relative difference between the original gains and smoothed gains. It also plots the results for a couple of antennas.
Here's a set of links to skip to particular figures and tables:
• Figure 1: Identifying and Blacklisting abscal Failures¶
• Figure 2: Antenna Phases with Identified Phase Flips¶
• Figure 3: Full-Day Gain Amplitudes Before and After smooth_cal¶
• Figure 4: Full-Day Gain Phases Before and After smooth_cal¶
• Figure 5: Full-Day $\chi^2$ / DoF Waterfall from Redundant-Baseline Calibration¶
• Figure 6: Average $\chi^2$ per Antenna¶
• Figure 7: Relative Difference Before and After Smoothing¶
In [1]:
import time
tstart = time.time()
In [2]:
import os
os.environ['HDF5_USE_FILE_LOCKING'] = 'FALSE'
import h5py
import hdf5plugin # REQUIRED to have the compression plugins available
import numpy as np
import glob
import copy
import warnings
import matplotlib
import matplotlib.pyplot as plt
from hera_cal import io, utils, smooth_cal
from hera_qm.time_series_metrics import true_stretches
%matplotlib inline
from IPython.display import display, HTML
Parse inputs¶
In [3]:
# get files
SUM_FILE = os.environ.get("SUM_FILE", None)
# SUM_FILE = "/lustre/aoc/projects/hera/h6c-analysis/IDR3/2459893/zen.2459893.25258.sum.uvh5"
SUM_SUFFIX = os.environ.get("SUM_SUFFIX", 'sum.uvh5')
CAL_SUFFIX = os.environ.get("CAL_SUFFIX", 'sum.omni.calfits')
SMOOTH_CAL_SUFFIX = os.environ.get("SMOOTH_CAL_SUFFIX", 'sum.smooth.calfits')
ANT_FLAG_SUFFIX = os.environ.get("ANT_FLAG_SUFFIX", 'sum.antenna_flags.h5')
RFI_FLAG_SUFFIX = os.environ.get("RFI_FLAG_SUFFIX", 'sum.flag_waterfall.h5')
FREQ_SMOOTHING_SCALE = float(os.environ.get("FREQ_SMOOTHING_SCALE", 30.0)) # MHz
TIME_SMOOTHING_SCALE = float(os.environ.get("TIME_SMOOTHING_SCALE", 1e4)) # seconds
EIGENVAL_CUTOFF = float(os.environ.get("EIGENVAL_CUTOFF", 1e-12))
PER_POL_REFANT = os.environ.get("PER_POL_REFANT", "False").upper() == "TRUE"
BLACKLIST_TIMESCALE_FACTOR = float(os.environ.get("BLACKLIST_TIMESCALE_FACTOR", 4.0))
BLACKLIST_RELATIVE_ERROR_THRESH = float(os.environ.get("BLACKLIST_RELATIVE_ERROR_THRESH", 1))
BLACKLIST_RELATIVE_WEIGHT = float(os.environ.get("BLACKLIST_RELATIVE_WEIGHT", 0.1))
FM_LOW_FREQ = float(os.environ.get("FM_LOW_FREQ", 87.5)) # in MHz
FM_HIGH_FREQ = float(os.environ.get("FM_HIGH_FREQ", 108.0)) # in MHz
SC_RELATIVE_DIFF_CUTOFF = float(os.environ.get("SC_RELATIVE_DIFF_CUTOFF", 0.2))
for setting in ['SUM_FILE', 'SUM_SUFFIX', 'CAL_SUFFIX', 'SMOOTH_CAL_SUFFIX', 'ANT_FLAG_SUFFIX',
'RFI_FLAG_SUFFIX', 'FREQ_SMOOTHING_SCALE', 'TIME_SMOOTHING_SCALE', 'EIGENVAL_CUTOFF',
'PER_POL_REFANT', 'BLACKLIST_TIMESCALE_FACTOR', 'BLACKLIST_RELATIVE_ERROR_THRESH',
'BLACKLIST_RELATIVE_WEIGHT', 'FM_LOW_FREQ', 'FM_HIGH_FREQ', 'SC_RELATIVE_DIFF_CUTOFF']:
if issubclass(type(eval(setting)), str):
print(f'{setting} = "{eval(setting)}"')
else:
print(f'{setting} = {eval(setting)}')
SUM_FILE = "/mnt/sn1/data2/2461114/zen.2461114.23164.sum.uvh5" SUM_SUFFIX = "sum.uvh5" CAL_SUFFIX = "sum.omni.calfits" SMOOTH_CAL_SUFFIX = "sum.smooth.calfits" ANT_FLAG_SUFFIX = "sum.antenna_flags.h5" RFI_FLAG_SUFFIX = "sum.flag_waterfall.h5" FREQ_SMOOTHING_SCALE = 10.0 TIME_SMOOTHING_SCALE = 600000.0 EIGENVAL_CUTOFF = 1e-12 PER_POL_REFANT = False BLACKLIST_TIMESCALE_FACTOR = 4.0 BLACKLIST_RELATIVE_ERROR_THRESH = 1.0 BLACKLIST_RELATIVE_WEIGHT = 0.1 FM_LOW_FREQ = 87.5 FM_HIGH_FREQ = 108.0 SC_RELATIVE_DIFF_CUTOFF = 0.2
Load files and select reference antenna(s)¶
In [4]:
hd = io.HERAData(SUM_FILE)
sum_glob = '.'.join(SUM_FILE.split('.')[:-3]) + '.*.' + SUM_SUFFIX
cal_files_glob = sum_glob.replace(SUM_SUFFIX, CAL_SUFFIX)
cal_files = sorted(glob.glob(cal_files_glob))
print(f'Found {len(cal_files)} *.{CAL_SUFFIX} files starting with {cal_files[0]}.')
Found 1851 *.sum.omni.calfits files starting with /mnt/sn1/data2/2461114/zen.2461114.23164.sum.omni.calfits.
In [5]:
rfi_flag_files_glob = sum_glob.replace(SUM_SUFFIX, RFI_FLAG_SUFFIX)
rfi_flag_files = sorted(glob.glob(rfi_flag_files_glob))
print(f'Found {len(rfi_flag_files)} *.{RFI_FLAG_SUFFIX} files starting with {rfi_flag_files[0]}.')
Found 1851 *.sum.flag_waterfall.h5 files starting with /mnt/sn1/data2/2461114/zen.2461114.23164.sum.flag_waterfall.h5.
In [6]:
ant_flag_files_glob = sum_glob.replace(SUM_SUFFIX, ANT_FLAG_SUFFIX)
ant_flag_files = sorted(glob.glob(ant_flag_files_glob))
print(f'Found {len(ant_flag_files)} *.{ANT_FLAG_SUFFIX} files starting with {ant_flag_files[0]}.')
Found 1851 *.sum.antenna_flags.h5 files starting with /mnt/sn1/data2/2461114/zen.2461114.23164.sum.antenna_flags.h5.
In [7]:
cs = smooth_cal.CalibrationSmoother(cal_files, flag_file_list=(ant_flag_files + rfi_flag_files),
ignore_calflags=True, pick_refant=False, load_chisq=True, load_cspa=True)
invalid value encountered in multiply
In [8]:
# Pick reference antenna(s) but don't let ants known to flip phases get picked as reference antennas
banned_refants = [(144, 'Jnn'), (121, 'Jee'), (71, 'Jnn')]
cs.refant = smooth_cal.pick_reference_antenna({ant: cs.gain_grids[ant] for ant in cs.gain_grids if ant not in banned_refants},
{ant: cs.flag_grids[ant] for ant in cs.gain_grids if ant not in banned_refants},
cs.freqs, per_pol=True, acceptable_candidate_frac=0.25, antpos=hd.antpos)
for pol in cs.refant:
print(f'Reference antenna {cs.refant[pol][0]} selected for smoothing {pol} gains.')
if not PER_POL_REFANT:
# in this case, rephase both pols separately before smoothing, but also smooth the relative polarization calibration phasor
overall_refant = smooth_cal.pick_reference_antenna({ant: cs.gain_grids[ant] for ant in cs.refant.values()},
{ant: cs.flag_grids[ant] for ant in cs.refant.values()},
cs.freqs, per_pol=False)
print(f'Overall reference antenna {overall_refant} selected.')
other_refant = [ant for ant in cs.refant.values() if ant != overall_refant][0]
relative_pol_phasor = cs.gain_grids[overall_refant] * cs.gain_grids[other_refant].conj() # TODO: is this conjugation right?
relative_pol_phasor /= np.abs(relative_pol_phasor)
abscal_refants = {cs.refant[pol]: cs.gain_grids[cs.refant[pol]] for pol in ['Jee', 'Jnn']}
Reference antenna 168 selected for smoothing Jnn gains. Reference antenna 43 selected for smoothing Jee gains.
Overall reference antenna (np.int64(43), 'Jee') selected.
In [9]:
cs.rephase_to_refant(propagate_refant_flags=True)
In [10]:
lst_grid = utils.JD2LST(cs.time_grid) * 12 / np.pi
lst_grid[lst_grid > lst_grid[-1]] -= 24
Find consistent outliers in relative error after a coarse smoothing¶
These are typically a sign of failures of abscal.
In [11]:
relative_error_samples = {pol: np.zeros_like(cs.gain_grids[cs.refant[pol]], dtype=float) for pol in ['Jee', 'Jnn']}
sum_relative_error = {pol: np.zeros_like(cs.gain_grids[cs.refant[pol]], dtype=float) for pol in ['Jee', 'Jnn']}
per_ant_avg_relative_error = {}
# perform a 2D DPSS filter with a BLACKLIST_TIMESCALE_FACTOR longer timescale, averaging the results per-pol
for ant in cs.gain_grids:
if np.all(cs.flag_grids[ant]):
continue
filtered, _ = smooth_cal.time_freq_2D_filter(gains=cs.gain_grids[ant],
wgts=(~cs.flag_grids[ant]).astype(float),
freqs=cs.freqs,
times=cs.time_grid,
freq_scale=FREQ_SMOOTHING_SCALE,
time_scale=TIME_SMOOTHING_SCALE * BLACKLIST_TIMESCALE_FACTOR,
eigenval_cutoff=EIGENVAL_CUTOFF,
method='DPSS',
fit_method='lu_solve',
fix_phase_flips=True,
phase_flip_time_scale = TIME_SMOOTHING_SCALE / 2,
flag_phase_flip_ints=True,
skip_flagged_edges=True,
freq_cuts=[(FM_LOW_FREQ + FM_HIGH_FREQ) * .5e6],
)
relative_error = np.where(cs.flag_grids[ant], 0, np.abs(cs.gain_grids[ant] - filtered) / np.abs(filtered))
per_ant_avg_relative_error[ant] = np.nanmean(np.where(cs.flag_grids[ant], np.nan, relative_error))
relative_error_samples[ant[1]] += (~cs.flag_grids[ant]).astype(float)
sum_relative_error[ant[1]] += relative_error
# figure out per-antpol cuts for where to set weights to 0 for the main smooth_cal (but not necessarily flags)
cs.blacklist_wgt = BLACKLIST_RELATIVE_WEIGHT
for pol in ['Jee', 'Jnn']:
avg_rel_error = sum_relative_error[pol] / relative_error_samples[pol]
to_blacklist = np.where(relative_error_samples[pol] > 0, avg_rel_error > BLACKLIST_RELATIVE_ERROR_THRESH, False)
for ant in cs.ants:
if ant[1] == pol:
cs.waterfall_blacklist[ant] = to_blacklist
invalid value encountered in divide
In [12]:
def plot_relative_error():
with warnings.catch_warnings():
warnings.simplefilter("ignore")
fig, axes = plt.subplots(1, 3, figsize=(14, 7))
extent = [cs.freqs[0] / 1e6, cs.freqs[-1] / 1e6, lst_grid[-1], lst_grid[0]]
cmap = plt.get_cmap('Greys', 256)
cmap.set_over('red')
for ax, pol in zip(axes[0:2], ['Jee', 'Jnn']):
to_plot = sum_relative_error[pol] / relative_error_samples[pol]
im = ax.imshow(np.where(np.isfinite(to_plot), to_plot, np.nan), aspect='auto', interpolation='none',
vmin=0, vmax=BLACKLIST_RELATIVE_ERROR_THRESH, extent=extent, cmap=cmap)
ax.set_title(pol)
ax.set_yticklabels(ax.get_yticks() % 24)
ax.set_ylabel('LST (hours)')
ax.set_xlabel('Frequency (MHz)')
plt.colorbar(im, ax=axes[0:2], location='top', extend='max', label='Average Relative Error on Initial Smoothing')
for pol in ['Jee', 'Jnn']:
axes[2].hist((sum_relative_error[pol] / relative_error_samples[pol]).ravel(), bins=np.arange(0,2,.01), alpha=.5, label=pol)
axes[2].set_yscale('log')
axes[2].set_ylabel('Number of Waterfall Pixels')
axes[2].set_xlabel('Relative Error')
axes[2].axvline(BLACKLIST_RELATIVE_ERROR_THRESH, ls='--', c='r', label='Blacklist Threshold')
axes[2].legend()
Figure 1: Identifying and Blacklisting abscal Failures¶
This plot highlights regions of the waterfall that are per-polarization blacklisted (i.e. given 0 weight in the main smooth_cal fit, but not necessarily flagged). This is usually a sign of problems with abscal and often occurs because
In [13]:
plot_relative_error()
In [14]:
# duplicate a small number of abscal gains for plotting
antnums = set([ant[0] for ant in cs.ants])
flags_per_antnum = [np.sum(cs.flag_grids[ant, 'Jnn']) + np.sum(cs.flag_grids[ant, 'Jee']) for ant in antnums]
larger_relative_error = np.array([np.max([per_ant_avg_relative_error.get((ant, pol), np.inf) for pol in ['Jee', 'Jnn']]) for ant in antnums])
refant_nums = [ant[0] for ant in cs.refant.values()]
# pick candidates that don't exhibit too many flags or non-smooth structure on first pass
candidate_ants = []
rel_error_factor = 1
while len(candidate_ants) < 6: # Select more candidates to ensure we have enough after potential flagging
candidate_ants = [ant for ant, nflags, rel_err in zip(antnums, flags_per_antnum, larger_relative_error)
if (ant not in refant_nums) and (nflags <= np.percentile(flags_per_antnum, 25))
and (rel_err <= SC_RELATIVE_DIFF_CUTOFF * rel_error_factor)
and not np.all(cs.flag_grids[ant, 'Jee']) and not np.all(cs.flag_grids[ant, 'Jnn'])]
rel_error_factor += .1
# choose antennas to plot: select up to 6 candidates, prioritizing diversity across antenna numbers
candidate_ants_sorted = sorted(candidate_ants)
step = max(1, len(candidate_ants_sorted) // 6) # spread them out
_candidates = sorted(candidate_ants_sorted[::step][:6])
ants_to_plot_candidates = [_candidates[i//2] if i % 2 == 0 else _candidates[-(i//2)-1] for i in range(len(_candidates))]
# Store abscal gains for all candidates
abscal_gains = {}
for pol in ['Jee', 'Jnn']:
for antnum in ants_to_plot_candidates:
if PER_POL_REFANT:
abscal_gains[antnum, pol] = cs.gain_grids[(antnum, pol)] * np.abs(abscal_refants[cs.refant[pol]]) / abscal_refants[cs.refant[pol]]
else:
abscal_gains[antnum, pol] = cs.gain_grids[(antnum, pol)] / np.abs(abscal_refants[cs.refant[pol]]) * abscal_refants[cs.refant[pol]]
abscal_gains[antnum, pol] *= np.abs(abscal_refants[overall_refant]) / abscal_refants[overall_refant]
Perform smoothing¶
In [15]:
if not PER_POL_REFANT:
# treat the relative_pol_phasor as if it were antenna -1
cs.gain_grids[(-1, other_refant[1])] = relative_pol_phasor
cs.flag_grids[(-1, other_refant[1])] = cs.flag_grids[overall_refant] | cs.flag_grids[other_refant]
cs.waterfall_blacklist[(-1, other_refant[1])] = cs.waterfall_blacklist[cs.ants[0][0], 'Jee'] | cs.waterfall_blacklist[cs.ants[0][0], 'Jnn']
In [16]:
meta = cs.time_freq_2D_filter(freq_scale=FREQ_SMOOTHING_SCALE,
time_scale=TIME_SMOOTHING_SCALE,
eigenval_cutoff=EIGENVAL_CUTOFF,
method='DPSS',
fit_method='lu_solve',
fix_phase_flips=True,
phase_flip_time_scale = TIME_SMOOTHING_SCALE / 2,
flag_phase_flip_ints=True,
skip_flagged_edges=True,
freq_cuts=[(FM_LOW_FREQ + FM_HIGH_FREQ) * .5e6],)
8 phase flips detected on antenna (np.int64(51), 'Jnn'). A total of 253 integrations were phase-flipped relative to the 0th integration between 2461114.2933767205 and 2461114.32189799.
22 phase flips detected on antenna (np.int64(66), 'Jnn'). A total of 502 integrations were phase-flipped relative to the 0th integration between 2461114.292929328 and 2461114.48575548.
8 phase flips detected on antenna (np.int64(250), 'Jnn'). A total of 218 integrations were phase-flipped relative to the 0th integration between 2461114.295725531 and 2461114.320779509.
8 phase flips detected on antenna (np.int64(98), 'Jee'). A total of 74 integrations were phase-flipped relative to the 0th integration between 2461114.3003113037 and 2461114.3192136353.
2 phase flips detected on antenna (np.int64(228), 'Jee'). A total of 1 integrations were phase-flipped relative to the 0th integration between 2461114.307134039 and 2461114.307134039.
2 phase flips detected on antenna (np.int64(210), 'Jee'). A total of 1 integrations were phase-flipped relative to the 0th integration between 2461114.307134039 and 2461114.307134039.
2 phase flips detected on antenna (np.int64(67), 'Jnn'). A total of 239 integrations were phase-flipped relative to the 0th integration between 2461114.2942715054 and 2461114.320891357.
2 phase flips detected on antenna (np.int64(114), 'Jee'). A total of 166 integrations were phase-flipped relative to the 0th integration between 2461114.297515101 and 2461114.31597004.
2 phase flips detected on antenna (np.int64(84), 'Jnn'). A total of 215 integrations were phase-flipped relative to the 0th integration between 2461114.2952781385 and 2461114.3192136353.
4 phase flips detected on antenna (np.int64(79), 'Jee'). A total of 8 integrations were phase-flipped relative to the 0th integration between 2461114.302548266 and 2461114.30467338.
2 phase flips detected on antenna (np.int64(245), 'Jee'). A total of 1 integrations were phase-flipped relative to the 0th integration between 2461114.307134039 and 2461114.307134039.
4 phase flips detected on antenna (np.int64(113), 'Jee'). A total of 56 integrations were phase-flipped relative to the 0th integration between 2461114.3009823924 and 2461114.307581431.
12 phase flips detected on antenna (np.int64(191), 'Jee'). A total of 21 integrations were phase-flipped relative to the 0th integration between 2461114.3021008736 and 2461114.307134039.
14 phase flips detected on antenna (np.int64(65), 'Jee'). A total of 14 integrations were phase-flipped relative to the 0th integration between 2461114.3003113037 and 2461114.3095946973.
6 phase flips detected on antenna (np.int64(179), 'Jnn'). A total of 219 integrations were phase-flipped relative to the 0th integration between 2461114.2951662904 and 2461114.32010842.
18 phase flips detected on antenna (np.int64(181), 'Jnn'). A total of 27 integrations were phase-flipped relative to the 0th integration between 2461114.299640215 and 2461114.306239254.
6 phase flips detected on antenna (np.int64(198), 'Jnn'). A total of 225 integrations were phase-flipped relative to the 0th integration between 2461114.2953899866 and 2461114.320891357.
4 phase flips detected on antenna (np.int64(52), 'Jnn'). A total of 221 integrations were phase-flipped relative to the 0th integration between 2461114.294830746 and 2461114.3195491796.
2 phase flips detected on antenna (np.int64(150), 'Jee'). A total of 1 integrations were phase-flipped relative to the 0th integration between 2461114.307134039 and 2461114.307134039.
4 phase flips detected on antenna (np.int64(254), 'Jnn'). A total of 763 integrations were phase-flipped relative to the 0th integration between 2461114.4062314695 and 2461114.493361152.
12 phase flips detected on antenna (np.int64(69), 'Jnn'). A total of 108 integrations were phase-flipped relative to the 0th integration between 2461114.298633582 and 2461114.3136212295.
6 phase flips detected on antenna (np.int64(53), 'Jnn'). A total of 186 integrations were phase-flipped relative to the 0th integration between 2461114.2963966196 and 2461114.3174240654.
2 phase flips detected on antenna (np.int64(100), 'Jnn'). A total of 251 integrations were phase-flipped relative to the 0th integration between 2461114.2942715054 and 2461114.3222335344.
2 phase flips detected on antenna (np.int64(115), 'Jee'). A total of 218 integrations were phase-flipped relative to the 0th integration between 2461114.294942594 and 2461114.3192136353.
6 phase flips detected on antenna (np.int64(131), 'Jee'). A total of 10 integrations were phase-flipped relative to the 0th integration between 2461114.302548266 and 2461114.30467338.
8 phase flips detected on antenna (np.int64(229), 'Jee'). A total of 82 integrations were phase-flipped relative to the 0th integration between 2461114.3000876075 and 2461114.3106013304.
6 phase flips detected on antenna (np.int64(96), 'Jee'). A total of 70 integrations were phase-flipped relative to the 0th integration between 2461114.299640215 and 2461114.3085880643.
14 phase flips detected on antenna (np.int64(200), 'Jnn'). A total of 115 integrations were phase-flipped relative to the 0th integration between 2461114.298633582 and 2461114.3144041663.
8 phase flips detected on antenna (np.int64(50), 'Jee'). A total of 12 integrations were phase-flipped relative to the 0th integration between 2461114.3003113037 and 2461114.305232621.
22 phase flips detected on antenna (np.int64(50), 'Jnn'). A total of 710 integrations were phase-flipped relative to the 0th integration between 2461114.2924819356 and 2461114.4893346196.
16 phase flips detected on antenna (np.int64(65), 'Jnn'). A total of 657 integrations were phase-flipped relative to the 0th integration between 2461114.292929328 and 2461114.488551683.
4 phase flips detected on antenna (np.int64(193), 'Jee'). A total of 195 integrations were phase-flipped relative to the 0th integration between 2461114.2952781385 and 2461114.317088521.
2 phase flips detected on antenna (np.int64(153), 'Jee'). A total of 218 integrations were phase-flipped relative to the 0th integration between 2461114.294942594 and 2461114.3192136353.
2 phase flips detected on antenna (np.int64(68), 'Jnn'). A total of 202 integrations were phase-flipped relative to the 0th integration between 2461114.295725531 and 2461114.3182070022.
4 phase flips detected on antenna (np.int64(136), 'Jee'). A total of 75 integrations were phase-flipped relative to the 0th integration between 2461114.3127264446 and 2461114.3212269014.
1 phase flips detected on antenna (np.int64(155), 'Jee'). A total of 2879 integrations were phase-flipped relative to the 0th integration between 2461114.32368756 and 2461114.6455864375.
10 phase flips detected on antenna (np.int64(211), 'Jee'). A total of 122 integrations were phase-flipped relative to the 0th integration between 2461114.29874543 and 2461114.3137330776.
20 phase flips detected on antenna (np.int64(177), 'Jnn'). A total of 300 integrations were phase-flipped relative to the 0th integration between 2461114.294830746 and 2461114.4266996747.
6 phase flips detected on antenna (np.int64(178), 'Jnn'). A total of 238 integrations were phase-flipped relative to the 0th integration between 2461114.2950544422 and 2461114.32189799.
2 phase flips detected on antenna (np.int64(195), 'Jee'). A total of 264 integrations were phase-flipped relative to the 0th integration between 2461114.29281748 and 2461114.3222335344.
20 phase flips detected on antenna (np.int64(196), 'Jnn'). A total of 356 integrations were phase-flipped relative to the 0th integration between 2461114.2943833536 and 2461114.426811523.
2 phase flips detected on antenna (np.int64(217), 'Jnn'). A total of 209 integrations were phase-flipped relative to the 0th integration between 2461114.2963966196 and 2461114.3196610278.
4 phase flips detected on antenna (np.int64(216), 'Jnn'). A total of 231 integrations were phase-flipped relative to the 0th integration between 2461114.2953899866 and 2461114.3212269014.
14 phase flips detected on antenna (np.int64(281), 'Jnn'). A total of 186 integrations were phase-flipped relative to the 0th integration between 2461114.296732164 and 2461114.3182070022.
4 phase flips detected on antenna (np.int64(152), 'Jee'). A total of 186 integrations were phase-flipped relative to the 0th integration between 2461114.296620316 and 2461114.3175359135.
1 phase flips detected on antenna (np.int64(233), 'Jee'). A total of 2911 integrations were phase-flipped relative to the 0th integration between 2461114.32010842 and 2461114.6455864375.
4 phase flips detected on antenna (np.int64(119), 'Jnn'). A total of 229 integrations were phase-flipped relative to the 0th integration between 2461114.2951662904 and 2461114.320891357.
2 phase flips detected on antenna (np.int64(154), 'Jee'). A total of 261 integrations were phase-flipped relative to the 0th integration between 2461114.293041176 and 2461114.3221216863.
2 phase flips detected on antenna (np.int64(133), 'Jee'). A total of 197 integrations were phase-flipped relative to the 0th integration between 2461114.295949227 and 2461114.317871458.
2 phase flips detected on antenna (np.int64(214), 'Jee'). A total of 254 integrations were phase-flipped relative to the 0th integration between 2461114.29281748 and 2461114.3211150533.
4 phase flips detected on antenna (np.int64(160), 'Jnn'). A total of 172 integrations were phase-flipped relative to the 0th integration between 2461114.296732164 and 2461114.316081888.
2 phase flips detected on antenna (np.int64(97), 'Jee'). A total of 181 integrations were phase-flipped relative to the 0th integration between 2461114.296732164 and 2461114.316864825.
4 phase flips detected on antenna (np.int64(174), 'Jee'). A total of 249 integrations were phase-flipped relative to the 0th integration between 2461114.293041176 and 2461114.320891357.
2 phase flips detected on antenna (np.int64(138), 'Jnn'). A total of 246 integrations were phase-flipped relative to the 0th integration between 2461114.294718898 and 2461114.3221216863.
5 phase flips detected on antenna (np.int64(215), 'Jee'). A total of 2906 integrations were phase-flipped relative to the 0th integration between 2461114.3204439646 and 2461114.6455864375.
2 phase flips detected on antenna (np.int64(116), 'Jee'). A total of 101 integrations were phase-flipped relative to the 0th integration between 2461114.311160571 and 2461114.3223453825.
4 phase flips detected on antenna (np.int64(140), 'Jnn'). A total of 193 integrations were phase-flipped relative to the 0th integration between 2461114.2961729234 and 2461114.31775961.
4 phase flips detected on antenna (np.int64(101), 'Jnn'). A total of 224 integrations were phase-flipped relative to the 0th integration between 2461114.294830746 and 2461114.32010842.
2 phase flips detected on antenna (np.int64(282), 'Jnn'). A total of 2 integrations were phase-flipped relative to the 0th integration between 2461114.312950141 and 2461114.313061989.
12 phase flips detected on antenna (np.int64(117), 'Jnn'). A total of 453 integrations were phase-flipped relative to the 0th integration between 2461114.294047809 and 2461114.483182973.
8 phase flips detected on antenna (np.int64(233), 'Jnn'). A total of 242 integrations were phase-flipped relative to the 0th integration between 2461114.2955018347 and 2461114.322904623.
2 phase flips detected on antenna (np.int64(234), 'Jnn'). A total of 221 integrations were phase-flipped relative to the 0th integration between 2461114.295613683 and 2461114.3202202683.
10 phase flips detected on antenna (np.int64(141), 'Jnn'). A total of 9 integrations were phase-flipped relative to the 0th integration between 2461114.3009823924 and 2461114.305456317.
2 phase flips detected on antenna (np.int64(134), 'Jee'). A total of 227 integrations were phase-flipped relative to the 0th integration between 2461114.2943833536 and 2461114.3196610278.
2 phase flips detected on antenna (np.int64(231), 'Jee'). A total of 225 integrations were phase-flipped relative to the 0th integration between 2461114.2941596573 and 2461114.3192136353.
6 phase flips detected on antenna (np.int64(176), 'Jnn'). A total of 499 integrations were phase-flipped relative to the 0th integration between 2461114.294047809 and 2461114.4320683843.
8 phase flips detected on antenna (np.int64(192), 'Jee'). A total of 151 integrations were phase-flipped relative to the 0th integration between 2461114.2981861895 and 2461114.3157463437.
4 phase flips detected on antenna (np.int64(36), 'Jee'). A total of 8 integrations were phase-flipped relative to the 0th integration between 2461114.3003113037 and 2461114.30467338.
2 phase flips detected on antenna (np.int64(177), 'Jee'). A total of 66 integrations were phase-flipped relative to the 0th integration between 2461114.312167204 and 2461114.3194373315.
24 phase flips detected on antenna (np.int64(80), 'Jee'). A total of 102 integrations were phase-flipped relative to the 0th integration between 2461114.298857278 and 2461114.3133975333.
10 phase flips detected on antenna (np.int64(121), 'Jnn'). A total of 160 integrations were phase-flipped relative to the 0th integration between 2461114.296732164 and 2461114.3157463437.
2 phase flips detected on antenna (np.int64(173), 'Jee'). A total of 202 integrations were phase-flipped relative to the 0th integration between 2461114.295725531 and 2461114.3182070022.
10 phase flips detected on antenna (np.int64(103), 'Jnn'). A total of 51 integrations were phase-flipped relative to the 0th integration between 2461114.299640215 and 2461114.307581431.
4 phase flips detected on antenna (np.int64(292), 'Jee'). A total of 10 integrations were phase-flipped relative to the 0th integration between 2461114.3027719622 and 2461114.30467338.
10 phase flips detected on antenna (np.int64(217), 'Jee'). A total of 404 integrations were phase-flipped relative to the 0th integration between 2461114.354445792 and 2461114.621762789.
4 phase flips detected on antenna (np.int64(118), 'Jnn'). A total of 255 integrations were phase-flipped relative to the 0th integration between 2461114.2943833536 and 2461114.322904623.
4 phase flips detected on antenna (np.int64(194), 'Jee'). A total of 226 integrations were phase-flipped relative to the 0th integration between 2461114.2943833536 and 2461114.3196610278.
14 phase flips detected on antenna (np.int64(155), 'Jnn'). A total of 511 integrations were phase-flipped relative to the 0th integration between 2461114.289126492 and 2461114.483182973.
16 phase flips detected on antenna (np.int64(116), 'Jnn'). A total of 437 integrations were phase-flipped relative to the 0th integration between 2461114.29460705 and 2461114.483182973.
2 phase flips detected on antenna (np.int64(38), 'Jnn'). A total of 214 integrations were phase-flipped relative to the 0th integration between 2461114.2953899866 and 2461114.3192136353.
2 phase flips detected on antenna (np.int64(175), 'Jee'). A total of 270 integrations were phase-flipped relative to the 0th integration between 2461114.29281748 and 2461114.322904623.
8 phase flips detected on antenna (np.int64(3), 'Jnn'). A total of 56 integrations were phase-flipped relative to the 0th integration between 2461114.3008705443 and 2461114.3088117605.
4 phase flips detected on antenna (np.int64(212), 'Jee'). A total of 166 integrations were phase-flipped relative to the 0th integration between 2461114.2972914046 and 2461114.315858192.
2 phase flips detected on antenna (np.int64(139), 'Jnn'). A total of 197 integrations were phase-flipped relative to the 0th integration between 2461114.296620316 and 2461114.3185425466.
4 phase flips detected on antenna (np.int64(159), 'Jnn'). A total of 184 integrations were phase-flipped relative to the 0th integration between 2461114.2971795565 and 2461114.317871458.
12 phase flips detected on antenna (np.int64(306), 'Jee'). A total of 97 integrations were phase-flipped relative to the 0th integration between 2461114.299752063 and 2461114.3136212295.
4 phase flips detected on antenna (np.int64(157), 'Jnn'). A total of 237 integrations were phase-flipped relative to the 0th integration between 2461114.295725531 and 2461114.3223453825.
6 phase flips detected on antenna (np.int64(319), 'Jee'). A total of 175 integrations were phase-flipped relative to the 0th integration between 2461114.296732164 and 2461114.3165292805.
13 phase flips detected on antenna (np.int64(135), 'Jnn'). A total of 2764 integrations were phase-flipped relative to the 0th integration between 2461114.2943833536 and 2461114.6455864375.
4 phase flips detected on antenna (np.int64(232), 'Jee'). A total of 252 integrations were phase-flipped relative to the 0th integration between 2461114.29281748 and 2461114.321003205.
24 phase flips detected on antenna (np.int64(137), 'Jnn'). A total of 337 integrations were phase-flipped relative to the 0th integration between 2461114.2943833536 and 2461114.426811523.
5 phase flips detected on antenna (np.int64(156), 'Jee'). A total of 2907 integrations were phase-flipped relative to the 0th integration between 2461114.3203321164 and 2461114.6455864375.
6 phase flips detected on antenna (np.int64(120), 'Jnn'). A total of 199 integrations were phase-flipped relative to the 0th integration between 2461114.295949227 and 2461114.3183188504.
1 phase flips detected on antenna (np.int64(82), 'Jnn'). A total of 2871 integrations were phase-flipped relative to the 0th integration between 2461114.324582345 and 2461114.6455864375.
6 phase flips detected on antenna (np.int64(85), 'Jnn'). A total of 168 integrations were phase-flipped relative to the 0th integration between 2461114.296732164 and 2461114.3157463437.
2 phase flips detected on antenna (np.int64(36), 'Jnn'). A total of 259 integrations were phase-flipped relative to the 0th integration between 2461114.2943833536 and 2461114.3232401675.
4 phase flips detected on antenna (np.int64(197), 'Jnn'). A total of 241 integrations were phase-flipped relative to the 0th integration between 2461114.295725531 and 2461114.322904623.
In [17]:
# calculate average chi^2 per antenna before additional flagging
avg_cspa_vs_time = {ant: np.nanmean(np.where(cs.flag_grids[ant], np.nan, cs.cspa_grids[ant]), axis=1) for ant in cs.ants}
avg_cspa_vs_freq = {ant: np.nanmean(np.where(cs.flag_grids[ant], np.nan, cs.cspa_grids[ant]), axis=0) for ant in cs.ants}
avg_cspa = {ant: np.nanmean(np.where(cs.flag_grids[ant], np.nan, cs.cspa_grids[ant])) for ant in cs.ants}
Mean of empty slice
Mean of empty slice
Mean of empty slice
In [18]:
# Pick out antennas with too high relative differences before and after smoothing and flag them.
avg_relative_diffs = {ant: np.nanmean(rel_diff) for ant, rel_diff in meta['freq_avg_rel_diff'].items()}
to_cut = sorted([ant for ant, diff in avg_relative_diffs.items() if ant[0] >= 0 and diff > SC_RELATIVE_DIFF_CUTOFF])
if len(to_cut) > 0:
for ant in to_cut:
print(f'Flagging antenna {ant[0]}{ant[1][-1]} with a relative difference before and after smoothing of {avg_relative_diffs[ant]:.2%} '
f'(compared to the {SC_RELATIVE_DIFF_CUTOFF:.2%} cutoff).')
cs.flag_grids[ant] |= True
else:
print(f'No antennas have a relative difference above the {SC_RELATIVE_DIFF_CUTOFF:.2%} cutoff.')
Flagging antenna 3n with a relative difference before and after smoothing of 36.92% (compared to the 20.00% cutoff). Flagging antenna 5n with a relative difference before and after smoothing of 26.64% (compared to the 20.00% cutoff). Flagging antenna 9n with a relative difference before and after smoothing of 20.44% (compared to the 20.00% cutoff). Flagging antenna 15n with a relative difference before and after smoothing of 28.96% (compared to the 20.00% cutoff). Flagging antenna 16n with a relative difference before and after smoothing of 26.71% (compared to the 20.00% cutoff). Flagging antenna 17n with a relative difference before and after smoothing of 23.11% (compared to the 20.00% cutoff). Flagging antenna 36e with a relative difference before and after smoothing of 28.92% (compared to the 20.00% cutoff). Flagging antenna 36n with a relative difference before and after smoothing of 76.21% (compared to the 20.00% cutoff). Flagging antenna 37e with a relative difference before and after smoothing of 21.27% (compared to the 20.00% cutoff). Flagging antenna 38n with a relative difference before and after smoothing of 50.43% (compared to the 20.00% cutoff). Flagging antenna 41n with a relative difference before and after smoothing of 24.53% (compared to the 20.00% cutoff). Flagging antenna 50e with a relative difference before and after smoothing of 29.00% (compared to the 20.00% cutoff). Flagging antenna 50n with a relative difference before and after smoothing of 121.69% (compared to the 20.00% cutoff). Flagging antenna 51e with a relative difference before and after smoothing of 24.14% (compared to the 20.00% cutoff). Flagging antenna 51n with a relative difference before and after smoothing of 59.96% (compared to the 20.00% cutoff). Flagging antenna 52e with a relative difference before and after smoothing of 20.46% (compared to the 20.00% cutoff). Flagging antenna 52n with a relative difference before and after smoothing of 53.14% (compared to the 20.00% cutoff). Flagging antenna 53n with a relative difference before and after smoothing of 47.73% (compared to the 20.00% cutoff). Flagging antenna 54n with a relative difference before and after smoothing of 31.64% (compared to the 20.00% cutoff). Flagging antenna 55n with a relative difference before and after smoothing of 25.87% (compared to the 20.00% cutoff). Flagging antenna 56n with a relative difference before and after smoothing of 22.68% (compared to the 20.00% cutoff). Flagging antenna 65e with a relative difference before and after smoothing of 30.23% (compared to the 20.00% cutoff). Flagging antenna 65n with a relative difference before and after smoothing of 114.03% (compared to the 20.00% cutoff). Flagging antenna 66e with a relative difference before and after smoothing of 27.48% (compared to the 20.00% cutoff). Flagging antenna 66n with a relative difference before and after smoothing of 86.12% (compared to the 20.00% cutoff). Flagging antenna 67e with a relative difference before and after smoothing of 21.94% (compared to the 20.00% cutoff). Flagging antenna 67n with a relative difference before and after smoothing of 54.31% (compared to the 20.00% cutoff). Flagging antenna 68n with a relative difference before and after smoothing of 47.63% (compared to the 20.00% cutoff). Flagging antenna 69n with a relative difference before and after smoothing of 36.91% (compared to the 20.00% cutoff). Flagging antenna 70n with a relative difference before and after smoothing of 27.43% (compared to the 20.00% cutoff). Flagging antenna 71n with a relative difference before and after smoothing of 23.27% (compared to the 20.00% cutoff). Flagging antenna 79e with a relative difference before and after smoothing of 23.00% (compared to the 20.00% cutoff). Flagging antenna 80e with a relative difference before and after smoothing of 31.75% (compared to the 20.00% cutoff). Flagging antenna 82e with a relative difference before and after smoothing of 29.42% (compared to the 20.00% cutoff). Flagging antenna 82n with a relative difference before and after smoothing of 53.94% (compared to the 20.00% cutoff). Flagging antenna 83e with a relative difference before and after smoothing of 24.52% (compared to the 20.00% cutoff). Flagging antenna 84e with a relative difference before and after smoothing of 22.06% (compared to the 20.00% cutoff). Flagging antenna 84n with a relative difference before and after smoothing of 50.30% (compared to the 20.00% cutoff). Flagging antenna 85n with a relative difference before and after smoothing of 48.52% (compared to the 20.00% cutoff). Flagging antenna 87n with a relative difference before and after smoothing of 24.11% (compared to the 20.00% cutoff). Flagging antenna 96e with a relative difference before and after smoothing of 27.16% (compared to the 20.00% cutoff). Flagging antenna 97e with a relative difference before and after smoothing of 39.66% (compared to the 20.00% cutoff). Flagging antenna 98e with a relative difference before and after smoothing of 39.69% (compared to the 20.00% cutoff). Flagging antenna 100e with a relative difference before and after smoothing of 28.45% (compared to the 20.00% cutoff). Flagging antenna 100n with a relative difference before and after smoothing of 58.76% (compared to the 20.00% cutoff). Flagging antenna 101e with a relative difference before and after smoothing of 23.28% (compared to the 20.00% cutoff). Flagging antenna 101n with a relative difference before and after smoothing of 52.30% (compared to the 20.00% cutoff). Flagging antenna 102e with a relative difference before and after smoothing of 20.54% (compared to the 20.00% cutoff). Flagging antenna 103n with a relative difference before and after smoothing of 31.99% (compared to the 20.00% cutoff). Flagging antenna 105n with a relative difference before and after smoothing of 21.17% (compared to the 20.00% cutoff). Flagging antenna 113e with a relative difference before and after smoothing of 25.53% (compared to the 20.00% cutoff). Flagging antenna 114e with a relative difference before and after smoothing of 37.38% (compared to the 20.00% cutoff). Flagging antenna 115e with a relative difference before and after smoothing of 46.17% (compared to the 20.00% cutoff). Flagging antenna 116e with a relative difference before and after smoothing of 48.04% (compared to the 20.00% cutoff).
Flagging antenna 116n with a relative difference before and after smoothing of 84.97% (compared to the 20.00% cutoff). Flagging antenna 117n with a relative difference before and after smoothing of 84.32% (compared to the 20.00% cutoff). Flagging antenna 118e with a relative difference before and after smoothing of 30.68% (compared to the 20.00% cutoff). Flagging antenna 118n with a relative difference before and after smoothing of 59.58% (compared to the 20.00% cutoff). Flagging antenna 119e with a relative difference before and after smoothing of 26.41% (compared to the 20.00% cutoff). Flagging antenna 119n with a relative difference before and after smoothing of 53.75% (compared to the 20.00% cutoff). Flagging antenna 120n with a relative difference before and after smoothing of 49.40% (compared to the 20.00% cutoff). Flagging antenna 121n with a relative difference before and after smoothing of 41.24% (compared to the 20.00% cutoff). Flagging antenna 122n with a relative difference before and after smoothing of 27.05% (compared to the 20.00% cutoff). Flagging antenna 123n with a relative difference before and after smoothing of 22.84% (compared to the 20.00% cutoff). Flagging antenna 131e with a relative difference before and after smoothing of 22.58% (compared to the 20.00% cutoff). Flagging antenna 133e with a relative difference before and after smoothing of 42.65% (compared to the 20.00% cutoff). Flagging antenna 133n with a relative difference before and after smoothing of 21.28% (compared to the 20.00% cutoff). Flagging antenna 134e with a relative difference before and after smoothing of 48.83% (compared to the 20.00% cutoff). Flagging antenna 135n with a relative difference before and after smoothing of 85.89% (compared to the 20.00% cutoff). Flagging antenna 136e with a relative difference before and after smoothing of 46.14% (compared to the 20.00% cutoff). Flagging antenna 137n with a relative difference before and after smoothing of 69.11% (compared to the 20.00% cutoff). Flagging antenna 138e with a relative difference before and after smoothing of 30.11% (compared to the 20.00% cutoff). Flagging antenna 138n with a relative difference before and after smoothing of 57.82% (compared to the 20.00% cutoff). Flagging antenna 139e with a relative difference before and after smoothing of 26.75% (compared to the 20.00% cutoff). Flagging antenna 139n with a relative difference before and after smoothing of 50.65% (compared to the 20.00% cutoff). Flagging antenna 140e with a relative difference before and after smoothing of 24.19% (compared to the 20.00% cutoff). Flagging antenna 140n with a relative difference before and after smoothing of 46.15% (compared to the 20.00% cutoff). Flagging antenna 141n with a relative difference before and after smoothing of 28.04% (compared to the 20.00% cutoff). Flagging antenna 143n with a relative difference before and after smoothing of 20.87% (compared to the 20.00% cutoff). Flagging antenna 150e with a relative difference before and after smoothing of 21.43% (compared to the 20.00% cutoff). Flagging antenna 152e with a relative difference before and after smoothing of 40.44% (compared to the 20.00% cutoff). Flagging antenna 153e with a relative difference before and after smoothing of 46.69% (compared to the 20.00% cutoff). Flagging antenna 153n with a relative difference before and after smoothing of 23.59% (compared to the 20.00% cutoff). Flagging antenna 154e with a relative difference before and after smoothing of 53.98% (compared to the 20.00% cutoff). Flagging antenna 155e with a relative difference before and after smoothing of 73.20% (compared to the 20.00% cutoff). Flagging antenna 155n with a relative difference before and after smoothing of 97.60% (compared to the 20.00% cutoff). Flagging antenna 156e with a relative difference before and after smoothing of 66.25% (compared to the 20.00% cutoff). Flagging antenna 157e with a relative difference before and after smoothing of 35.85% (compared to the 20.00% cutoff). Flagging antenna 157n with a relative difference before and after smoothing of 59.58% (compared to the 20.00% cutoff). Flagging antenna 158e with a relative difference before and after smoothing of 32.77% (compared to the 20.00% cutoff). Flagging antenna 159n with a relative difference before and after smoothing of 47.77% (compared to the 20.00% cutoff). Flagging antenna 160e with a relative difference before and after smoothing of 24.89% (compared to the 20.00% cutoff). Flagging antenna 160n with a relative difference before and after smoothing of 42.60% (compared to the 20.00% cutoff). Flagging antenna 161e with a relative difference before and after smoothing of 21.88% (compared to the 20.00% cutoff). Flagging antenna 162n with a relative difference before and after smoothing of 22.80% (compared to the 20.00% cutoff). Flagging antenna 173e with a relative difference before and after smoothing of 45.71% (compared to the 20.00% cutoff). Flagging antenna 173n with a relative difference before and after smoothing of 26.59% (compared to the 20.00% cutoff). Flagging antenna 174e with a relative difference before and after smoothing of 51.86% (compared to the 20.00% cutoff). Flagging antenna 175e with a relative difference before and after smoothing of 59.86% (compared to the 20.00% cutoff). Flagging antenna 176n with a relative difference before and after smoothing of 95.12% (compared to the 20.00% cutoff). Flagging antenna 177e with a relative difference before and after smoothing of 48.01% (compared to the 20.00% cutoff). Flagging antenna 177n with a relative difference before and after smoothing of 67.13% (compared to the 20.00% cutoff). Flagging antenna 178e with a relative difference before and after smoothing of 36.75% (compared to the 20.00% cutoff). Flagging antenna 178n with a relative difference before and after smoothing of 58.54% (compared to the 20.00% cutoff). Flagging antenna 179e with a relative difference before and after smoothing of 32.41% (compared to the 20.00% cutoff). Flagging antenna 179n with a relative difference before and after smoothing of 53.38% (compared to the 20.00% cutoff). Flagging antenna 180e with a relative difference before and after smoothing of 28.12% (compared to the 20.00% cutoff). Flagging antenna 181n with a relative difference before and after smoothing of 31.25% (compared to the 20.00% cutoff).
Flagging antenna 182e with a relative difference before and after smoothing of 22.41% (compared to the 20.00% cutoff). Flagging antenna 182n with a relative difference before and after smoothing of 27.04% (compared to the 20.00% cutoff). Flagging antenna 183e with a relative difference before and after smoothing of 20.13% (compared to the 20.00% cutoff). Flagging antenna 183n with a relative difference before and after smoothing of 23.82% (compared to the 20.00% cutoff). Flagging antenna 190e with a relative difference before and after smoothing of 20.24% (compared to the 20.00% cutoff). Flagging antenna 191e with a relative difference before and after smoothing of 22.15% (compared to the 20.00% cutoff). Flagging antenna 192e with a relative difference before and after smoothing of 34.76% (compared to the 20.00% cutoff). Flagging antenna 193e with a relative difference before and after smoothing of 43.21% (compared to the 20.00% cutoff). Flagging antenna 194e with a relative difference before and after smoothing of 49.80% (compared to the 20.00% cutoff). Flagging antenna 194n with a relative difference before and after smoothing of 23.88% (compared to the 20.00% cutoff). Flagging antenna 195e with a relative difference before and after smoothing of 58.03% (compared to the 20.00% cutoff). Flagging antenna 196n with a relative difference before and after smoothing of 74.36% (compared to the 20.00% cutoff). Flagging antenna 197e with a relative difference before and after smoothing of 39.04% (compared to the 20.00% cutoff). Flagging antenna 197n with a relative difference before and after smoothing of 79.03% (compared to the 20.00% cutoff). Flagging antenna 198e with a relative difference before and after smoothing of 34.17% (compared to the 20.00% cutoff). Flagging antenna 198n with a relative difference before and after smoothing of 54.50% (compared to the 20.00% cutoff). Flagging antenna 200n with a relative difference before and after smoothing of 37.78% (compared to the 20.00% cutoff). Flagging antenna 201n with a relative difference before and after smoothing of 28.44% (compared to the 20.00% cutoff). Flagging antenna 202e with a relative difference before and after smoothing of 21.98% (compared to the 20.00% cutoff). Flagging antenna 203n with a relative difference before and after smoothing of 20.36% (compared to the 20.00% cutoff). Flagging antenna 209e with a relative difference before and after smoothing of 20.91% (compared to the 20.00% cutoff). Flagging antenna 210e with a relative difference before and after smoothing of 22.79% (compared to the 20.00% cutoff). Flagging antenna 211e with a relative difference before and after smoothing of 31.97% (compared to the 20.00% cutoff). Flagging antenna 212e with a relative difference before and after smoothing of 42.45% (compared to the 20.00% cutoff). Flagging antenna 214e with a relative difference before and after smoothing of 57.10% (compared to the 20.00% cutoff). Flagging antenna 214n with a relative difference before and after smoothing of 25.32% (compared to the 20.00% cutoff). Flagging antenna 215e with a relative difference before and after smoothing of 74.38% (compared to the 20.00% cutoff). Flagging antenna 216e with a relative difference before and after smoothing of 40.71% (compared to the 20.00% cutoff). Flagging antenna 216n with a relative difference before and after smoothing of 57.32% (compared to the 20.00% cutoff). Flagging antenna 217e with a relative difference before and after smoothing of 35.68% (compared to the 20.00% cutoff). Flagging antenna 217n with a relative difference before and after smoothing of 53.19% (compared to the 20.00% cutoff). Flagging antenna 218e with a relative difference before and after smoothing of 31.21% (compared to the 20.00% cutoff). Flagging antenna 219e with a relative difference before and after smoothing of 27.42% (compared to the 20.00% cutoff). Flagging antenna 219n with a relative difference before and after smoothing of 30.58% (compared to the 20.00% cutoff). Flagging antenna 220e with a relative difference before and after smoothing of 23.92% (compared to the 20.00% cutoff). Flagging antenna 220n with a relative difference before and after smoothing of 26.64% (compared to the 20.00% cutoff). Flagging antenna 221e with a relative difference before and after smoothing of 22.05% (compared to the 20.00% cutoff). Flagging antenna 221n with a relative difference before and after smoothing of 23.14% (compared to the 20.00% cutoff). Flagging antenna 222e with a relative difference before and after smoothing of 20.28% (compared to the 20.00% cutoff). Flagging antenna 226e with a relative difference before and after smoothing of 20.18% (compared to the 20.00% cutoff). Flagging antenna 228e with a relative difference before and after smoothing of 23.58% (compared to the 20.00% cutoff). Flagging antenna 229e with a relative difference before and after smoothing of 29.26% (compared to the 20.00% cutoff). Flagging antenna 231e with a relative difference before and after smoothing of 57.19% (compared to the 20.00% cutoff). Flagging antenna 231n with a relative difference before and after smoothing of 21.30% (compared to the 20.00% cutoff). Flagging antenna 232e with a relative difference before and after smoothing of 61.92% (compared to the 20.00% cutoff). Flagging antenna 232n with a relative difference before and after smoothing of 25.91% (compared to the 20.00% cutoff). Flagging antenna 233e with a relative difference before and after smoothing of 74.34% (compared to the 20.00% cutoff). Flagging antenna 233n with a relative difference before and after smoothing of 61.26% (compared to the 20.00% cutoff). Flagging antenna 234e with a relative difference before and after smoothing of 40.52% (compared to the 20.00% cutoff). Flagging antenna 234n with a relative difference before and after smoothing of 55.57% (compared to the 20.00% cutoff). Flagging antenna 237e with a relative difference before and after smoothing of 27.61% (compared to the 20.00% cutoff). Flagging antenna 237n with a relative difference before and after smoothing of 28.98% (compared to the 20.00% cutoff). Flagging antenna 238e with a relative difference before and after smoothing of 25.51% (compared to the 20.00% cutoff). Flagging antenna 238n with a relative difference before and after smoothing of 25.07% (compared to the 20.00% cutoff).
Flagging antenna 239e with a relative difference before and after smoothing of 23.07% (compared to the 20.00% cutoff). Flagging antenna 239n with a relative difference before and after smoothing of 21.76% (compared to the 20.00% cutoff). Flagging antenna 240e with a relative difference before and after smoothing of 20.80% (compared to the 20.00% cutoff). Flagging antenna 242e with a relative difference before and after smoothing of 20.07% (compared to the 20.00% cutoff). Flagging antenna 243e with a relative difference before and after smoothing of 21.64% (compared to the 20.00% cutoff). Flagging antenna 244e with a relative difference before and after smoothing of 22.97% (compared to the 20.00% cutoff). Flagging antenna 245e with a relative difference before and after smoothing of 23.10% (compared to the 20.00% cutoff). Flagging antenna 250n with a relative difference before and after smoothing of 57.41% (compared to the 20.00% cutoff). Flagging antenna 253e with a relative difference before and after smoothing of 31.18% (compared to the 20.00% cutoff). Flagging antenna 254e with a relative difference before and after smoothing of 28.99% (compared to the 20.00% cutoff). Flagging antenna 254n with a relative difference before and after smoothing of 27.87% (compared to the 20.00% cutoff). Flagging antenna 255n with a relative difference before and after smoothing of 24.47% (compared to the 20.00% cutoff). Flagging antenna 256e with a relative difference before and after smoothing of 24.70% (compared to the 20.00% cutoff). Flagging antenna 256n with a relative difference before and after smoothing of 21.16% (compared to the 20.00% cutoff). Flagging antenna 257e with a relative difference before and after smoothing of 22.96% (compared to the 20.00% cutoff). Flagging antenna 269e with a relative difference before and after smoothing of 31.64% (compared to the 20.00% cutoff). Flagging antenna 269n with a relative difference before and after smoothing of 30.41% (compared to the 20.00% cutoff). Flagging antenna 270e with a relative difference before and after smoothing of 29.96% (compared to the 20.00% cutoff). Flagging antenna 270n with a relative difference before and after smoothing of 27.56% (compared to the 20.00% cutoff). Flagging antenna 272e with a relative difference before and after smoothing of 26.25% (compared to the 20.00% cutoff). Flagging antenna 272n with a relative difference before and after smoothing of 21.08% (compared to the 20.00% cutoff). Flagging antenna 278n with a relative difference before and after smoothing of 20.41% (compared to the 20.00% cutoff). Flagging antenna 281e with a relative difference before and after smoothing of 44.92% (compared to the 20.00% cutoff). Flagging antenna 281n with a relative difference before and after smoothing of 52.65% (compared to the 20.00% cutoff). Flagging antenna 282e with a relative difference before and after smoothing of 40.63% (compared to the 20.00% cutoff). Flagging antenna 282n with a relative difference before and after smoothing of 38.52% (compared to the 20.00% cutoff). Flagging antenna 283e with a relative difference before and after smoothing of 36.74% (compared to the 20.00% cutoff). Flagging antenna 283n with a relative difference before and after smoothing of 32.93% (compared to the 20.00% cutoff). Flagging antenna 287e with a relative difference before and after smoothing of 28.44% (compared to the 20.00% cutoff). Flagging antenna 292e with a relative difference before and after smoothing of 29.07% (compared to the 20.00% cutoff). Flagging antenna 293n with a relative difference before and after smoothing of 22.97% (compared to the 20.00% cutoff). Flagging antenna 294n with a relative difference before and after smoothing of 24.89% (compared to the 20.00% cutoff). Flagging antenna 299e with a relative difference before and after smoothing of 31.98% (compared to the 20.00% cutoff). Flagging antenna 299n with a relative difference before and after smoothing of 25.89% (compared to the 20.00% cutoff). Flagging antenna 301e with a relative difference before and after smoothing of 29.32% (compared to the 20.00% cutoff). Flagging antenna 301n with a relative difference before and after smoothing of 23.83% (compared to the 20.00% cutoff). Flagging antenna 302n with a relative difference before and after smoothing of 20.22% (compared to the 20.00% cutoff). Flagging antenna 306e with a relative difference before and after smoothing of 36.49% (compared to the 20.00% cutoff). Flagging antenna 307n with a relative difference before and after smoothing of 25.59% (compared to the 20.00% cutoff). Flagging antenna 311e with a relative difference before and after smoothing of 37.13% (compared to the 20.00% cutoff). Flagging antenna 313n with a relative difference before and after smoothing of 26.62% (compared to the 20.00% cutoff). Flagging antenna 314e with a relative difference before and after smoothing of 32.65% (compared to the 20.00% cutoff). Flagging antenna 315e with a relative difference before and after smoothing of 31.50% (compared to the 20.00% cutoff). Flagging antenna 315n with a relative difference before and after smoothing of 22.68% (compared to the 20.00% cutoff). Flagging antenna 316e with a relative difference before and after smoothing of 31.60% (compared to the 20.00% cutoff). Flagging antenna 316n with a relative difference before and after smoothing of 21.72% (compared to the 20.00% cutoff). Flagging antenna 317e with a relative difference before and after smoothing of 32.76% (compared to the 20.00% cutoff). Flagging antenna 317n with a relative difference before and after smoothing of 24.39% (compared to the 20.00% cutoff). Flagging antenna 319e with a relative difference before and after smoothing of 47.21% (compared to the 20.00% cutoff). Flagging antenna 319n with a relative difference before and after smoothing of 26.94% (compared to the 20.00% cutoff).
In [19]:
if not PER_POL_REFANT:
# put back in the smoothed phasor, ensuring the amplitude is 1 and that data are flagged anywhere either polarization's refant is flagged
smoothed_relative_pol_phasor = cs.gain_grids[(-1, other_refant[-1])] / np.abs(cs.gain_grids[(-1, other_refant[-1])])
for ant in cs.gain_grids:
if ant[0] >= 0 and ant[1] == other_refant[1]:
cs.gain_grids[ant] /= smoothed_relative_pol_phasor
cs.flag_grids[ant] |= (cs.flag_grids[(-1, other_refant[1])])
cs.refant = overall_refant
In [20]:
def phase_flip_diagnostic_plot():
'''Shows time-smoothed antenna avg phases after taking out a delay and filtering in time.'''
if not np.any([np.any(meta['phase_flipped'][ant]) for ant in meta['phase_flipped']]):
print("No antennas have phase flips identified. Nothing to plot.")
return
plt.figure(figsize=(14,4))
for ant in meta['phase_flipped']:
if np.any(meta['phase_flipped'][ant]):
to_plot = np.angle(np.exp(1.0j * (meta['phases'][ant] - meta['time_smoothed_phases'][ant])))
to_plot[to_plot < -np.pi / 2] += 2 * np.pi
plt.plot(cs.time_grid - int(cs.time_grid[0]), to_plot, label=f'{ant[0]}{ant[1][-1]}')
plt.legend(title='Antennas with Identified Phase Flips', ncol=4)
plt.xlabel(f'JD - {int(cs.time_grid[0])}')
plt.ylabel('Average Phase After Filtering (radians)')
plt.tight_layout()
Figure 2: Antenna Phases with Identified Phase Flips¶
In [21]:
phase_flip_diagnostic_plot()
Plot results¶
In [22]:
def amplitude_plot(ant_to_plot):
with warnings.catch_warnings():
warnings.simplefilter("ignore")
# Pick vmax to not saturate 90% of the abscal gains
vmax = np.max([np.percentile(np.abs(cs.gain_grids[ant_to_plot, pol][~cs.flag_grids[ant_to_plot, pol]]), 99) for pol in ['Jee', 'Jnn']])
display(HTML(f'<h2>Antenna {ant_to_plot} Amplitude Waterfalls</h2>'))
# Plot abscal gain amplitude waterfalls for a single antenna
fig, axes = plt.subplots(4, 2, figsize=(14,14), gridspec_kw={'height_ratios': [1, 1, .4, .4]})
for ax, pol in zip(axes[0], ['Jee', 'Jnn']):
ant = (ant_to_plot, pol)
extent=[cs.freqs[0]/1e6, cs.freqs[-1]/1e6, lst_grid[-1], lst_grid[0]]
im = ax.imshow(np.where(cs.flag_grids[ant], np.nan, np.abs(cs.gain_grids[ant])), aspect='auto', cmap='inferno',
interpolation='nearest', vmin=0, vmax=vmax, extent=extent)
ax.set_title(f'Smoothcal Gain Amplitude of Antenna {ant[0]}: {pol[-1]}-polarized' )
ax.set_xlabel('Frequency (MHz)')
ax.set_ylabel('LST (Hours)')
ax.set_xlim([cs.freqs[0]/1e6, cs.freqs[-1]/1e6])
ax.set_yticklabels(ax.get_yticks() % 24)
plt.colorbar(im, ax=ax, orientation='horizontal', pad=.15)
# Now flagged plot abscal waterfall
for ax, pol in zip(axes[1], ['Jee', 'Jnn']):
ant = (ant_to_plot, pol)
extent=[cs.freqs[0]/1e6, cs.freqs[-1]/1e6, lst_grid[-1], lst_grid[0]]
im = ax.imshow(np.where(cs.flag_grids[ant], np.nan, np.abs(abscal_gains[ant])), aspect='auto', cmap='inferno',
interpolation='nearest', vmin=0, vmax=vmax, extent=extent)
ax.set_title(f'Abscal Gain Amplitude of Antenna {ant[0]}: {pol[-1]}-polarized' )
ax.set_xlabel('Frequency (MHz)')
ax.set_ylabel('LST (Hours)')
ax.set_xlim([cs.freqs[0]/1e6, cs.freqs[-1]/1e6])
ax.set_yticklabels(ax.get_yticks() % 24)
plt.colorbar(im, ax=ax, orientation='horizontal', pad=.15)
# Now plot mean gain spectra
for ax, pol in zip(axes[2], ['Jee', 'Jnn']):
ant = (ant_to_plot, pol)
nflags_spectrum = np.sum(cs.flag_grids[ant], axis=0)
to_plot = nflags_spectrum <= np.percentile(nflags_spectrum, 75)
ax.plot(cs.freqs[to_plot] / 1e6, np.nanmean(np.where(cs.flag_grids[ant], np.nan, np.abs(abscal_gains[ant])), axis=0)[to_plot], 'r.', label='Abscal')
ax.plot(cs.freqs[to_plot] / 1e6, np.nanmean(np.where(cs.flag_grids[ant], np.nan, np.abs(cs.gain_grids[ant])), axis=0)[to_plot], 'k.', ms=2, label='Smoothed')
ax.set_ylim([0, vmax])
ax.set_xlim([cs.freqs[0]/1e6, cs.freqs[-1]/1e6])
ax.set_xlabel('Frequency (MHz)')
ax.set_ylabel('|g| (unitless)')
ax.set_title(f'Mean Infrequently-Flagged Gain Amplitude of Antenna {ant[0]}: {pol[-1]}-polarized')
ax.legend(loc='upper left')
# Now plot mean gain time series
for ax, pol in zip(axes[3], ['Jee', 'Jnn']):
ant = (ant_to_plot, pol)
nflags_series = np.sum(cs.flag_grids[ant], axis=1)
to_plot = nflags_series <= np.percentile(nflags_series, 75)
ax.plot(lst_grid[to_plot], np.nanmean(np.where(cs.flag_grids[ant], np.nan, np.abs(abscal_gains[ant])), axis=1)[to_plot], 'r.', label='Abscal')
ax.plot(lst_grid[to_plot], np.nanmean(np.where(cs.flag_grids[ant], np.nan, np.abs(cs.gain_grids[ant])), axis=1)[to_plot], 'k.', ms=2, label='Smoothed')
ax.set_ylim([0, vmax])
ax.set_xlabel('LST (hours)')
ax.set_ylabel('|g| (unitless)')
ax.set_title(f'Mean Infrequently-Flagged Gain Amplitude of Antenna {ant[0]}: {pol[-1]}-polarized')
ax.set_xticklabels(ax.get_xticks() % 24)
ax.legend(loc='upper left')
plt.tight_layout()
plt.show()
In [23]:
def phase_plot(ant_to_plot):
with warnings.catch_warnings():
warnings.simplefilter("ignore")
display(HTML(f'<h2>Antenna {ant_to_plot} Phase Waterfalls</h2>'))
fig, axes = plt.subplots(4, 2, figsize=(14,14), gridspec_kw={'height_ratios': [1, 1, .4, .4]})
# Plot phase waterfalls for a single antenna
for ax, pol in zip(axes[0], ['Jee', 'Jnn']):
ant = (ant_to_plot, pol)
extent=[cs.freqs[0]/1e6, cs.freqs[-1]/1e6, lst_grid[-1], lst_grid[0]]
im = ax.imshow(np.where(cs.flag_grids[ant], np.nan, np.angle(cs.gain_grids[ant])), aspect='auto', cmap='inferno',
interpolation='nearest', vmin=-np.pi, vmax=np.pi, extent=extent)
refant = (cs.refant[pol] if isinstance(cs.refant, dict) else cs.refant)
ax.set_title(f'Smoothcal Gain Phase of Ant {ant[0]}{pol[-1]} / Ant {refant[0]}{refant[1][-1]}')
ax.set_xlabel('Frequency (MHz)')
ax.set_ylabel('LST (Hours)')
ax.set_xlim([cs.freqs[0]/1e6, cs.freqs[-1]/1e6])
ax.set_yticklabels(ax.get_yticks() % 24)
plt.colorbar(im, ax=ax, orientation='horizontal', pad=.15)
# Now plot abscal phase waterfall
for ax, pol in zip(axes[1], ['Jee', 'Jnn']):
ant = (ant_to_plot, pol)
extent=[cs.freqs[0]/1e6, cs.freqs[-1]/1e6, lst_grid[-1], lst_grid[0]]
im = ax.imshow(np.where(cs.flag_grids[ant], np.nan, np.angle(abscal_gains[ant])), aspect='auto', cmap='inferno',
interpolation='nearest', vmin=-np.pi, vmax=np.pi, extent=extent)
refant = (cs.refant[pol] if isinstance(cs.refant, dict) else cs.refant)
ax.set_title(f'Abscal Gain Phase of Ant {ant[0]}{pol[-1]} / Ant {refant[0]}{refant[1][-1]}')
ax.set_xlabel('Frequency (MHz)')
ax.set_ylabel('LST (Hours)')
ax.set_xlim([cs.freqs[0]/1e6, cs.freqs[-1]/1e6])
ax.set_yticklabels(ax.get_yticks() % 24)
plt.colorbar(im, ax=ax, orientation='horizontal', pad=.15)
# Now plot median gain spectra
for ax, pol in zip(axes[2], ['Jee', 'Jnn']):
ant = (ant_to_plot, pol)
nflags_spectrum = np.sum(cs.flag_grids[ant], axis=0)
to_plot = nflags_spectrum <= np.percentile(nflags_spectrum, 75)
ax.plot(cs.freqs[to_plot] / 1e6, np.nanmedian(np.where(cs.flag_grids[ant], np.nan, np.angle(abscal_gains[ant])), axis=0)[to_plot], 'r.', label='Abscal')
ax.plot(cs.freqs[to_plot] / 1e6, np.nanmedian(np.where(cs.flag_grids[ant], np.nan, np.angle(cs.gain_grids[ant])), axis=0)[to_plot], 'k.', ms=2, label='Smoothed')
ax.set_ylim([-np.pi, np.pi])
ax.set_xlim([cs.freqs[0]/1e6, cs.freqs[-1]/1e6])
ax.set_xlabel('Frequency (MHz)')
refant = (cs.refant[pol] if isinstance(cs.refant, dict) else cs.refant)
ax.set_ylabel(f'Phase of g$_{{{ant[0]}{pol[-1]}}}$ / g$_{{{refant[0]}{refant[1][-1]}}}$')
ax.set_title(f'Median Infrequently-Flagged Gain Phase of Ant {ant[0]}{pol[-1]} / Ant {refant[0]}{refant[1][-1]}')
ax.legend(loc='upper left')
# # Now plot median gain time series
for ax, pol in zip(axes[3], ['Jee', 'Jnn']):
ant = (ant_to_plot, pol)
nflags_series = np.sum(cs.flag_grids[ant], axis=1)
to_plot = nflags_series <= np.percentile(nflags_series, 75)
ax.plot(lst_grid[to_plot], np.nanmean(np.where(cs.flag_grids[ant], np.nan, np.angle(abscal_gains[ant])), axis=1)[to_plot], 'r.', label='Abscal')
ax.plot(lst_grid[to_plot], np.nanmean(np.where(cs.flag_grids[ant], np.nan, np.angle(cs.gain_grids[ant])), axis=1)[to_plot], 'k.', ms=2, label='Smoothed')
ax.set_ylim([-np.pi, np.pi])
ax.set_xlabel('LST (hours)')
refant = (cs.refant[pol] if isinstance(cs.refant, dict) else cs.refant)
ax.set_ylabel(f'Phase of g$_{{{ant[0]}{pol[-1]}}}$ / g$_{{{refant[0]}{refant[1][-1]}}}$')
ax.set_title(f'Mean Infrequently-Flagged Gain Phase of Ant {ant[0]}{pol[-1]} / Ant {refant[0]}{refant[1][-1]}')
ax.set_xticklabels(ax.get_xticks() % 24)
ax.legend(loc='upper left')
plt.tight_layout()
plt.show()
In [24]:
# Select first 2 unflagged antennas from candidates for amplitude plotting
ants_to_plot = []
for ant_candidate in ants_to_plot_candidates:
if not (np.all(cs.flag_grids[ant_candidate, 'Jee']) and np.all(cs.flag_grids[ant_candidate, 'Jnn'])):
ants_to_plot.append(ant_candidate)
if len(ants_to_plot) >= 2:
break
Figure 3: Full-Day Gain Amplitudes Before and After smooth_cal¶
Here we plot abscal and smooth_cal gain amplitudes for both of the sample antennas. We also show means across time/frequency, excluding frequencies/times that are frequently flagged.
In [25]:
if len(ants_to_plot) == 0:
print("Warning: No unflagged antennas available for plotting.")
else:
for ant_to_plot in ants_to_plot:
amplitude_plot(ant_to_plot)
Antenna 45 Amplitude Waterfalls
Antenna 125 Amplitude Waterfalls
Figure 4: Full-Day Gain Phases Before and After smooth_cal¶
Here we plot abscal and smooth_cal phases relative to each polarization's reference antenna for both of the sample antennas. We also show medians across time/frequency, excluding frequencies/times that are frequently flagged.
In [26]:
# Use the same selected unflagged antennas for phase plotting
if len(ants_to_plot) == 0:
print("Warning: No unflagged antennas available for plotting.")
else:
for ant_to_plot in ants_to_plot:
phase_plot(ant_to_plot)
Antenna 45 Phase Waterfalls
Antenna 125 Phase Waterfalls
Examine $\chi^2$¶
In [27]:
def chisq_plot():
fig, axes = plt.subplots(1, 2, figsize=(14, 10), sharex=True, sharey=True)
extent = [cs.freqs[0]/1e6, cs.freqs[-1]/1e6, lst_grid[-1], lst_grid[0]]
for ax, pol in zip(axes, ['Jee', 'Jnn']):
refant = (cs.refant[pol] if isinstance(cs.refant, dict) else cs.refant)
im = ax.imshow(np.where(cs.flag_grids[refant], np.nan, cs.chisq_grids[pol]), vmin=1, vmax=5,
aspect='auto', cmap='turbo', interpolation='none', extent=extent)
ax.set_yticklabels(ax.get_yticks() % 24)
ax.set_title(f'{pol[1:]}-Polarized $\\chi^2$ / DoF')
ax.set_xlabel('Frequency (MHz)')
axes[0].set_ylabel('LST (hours)')
plt.tight_layout()
fig.colorbar(im, ax=axes, pad=.07, label='$\\chi^2$ / DoF', orientation='horizontal', extend='both', aspect=50)
Figure 5: Full-Day $\chi^2$ / DoF Waterfall from Redundant-Baseline Calibration¶
Here we plot $\chi^2$ per degree of freedom from redundant-baseline calibration for both polarizations separately. While this plot is a little out of place, as it was not produced by this notebook, it is a convenient place where all the necessary components are readily available. If the array were perfectly redundant and any non-redundancies in the calibrated visibilities were explicable by thermal noise alone, this waterfall should be all 1.
In [28]:
chisq_plot()
set_ticklabels() should only be used with a fixed number of ticks, i.e. after set_ticks() or using a FixedLocator. set_ticklabels() should only be used with a fixed number of ticks, i.e. after set_ticks() or using a FixedLocator.
In [29]:
def cspa_vs_time_plot():
fig, axes = plt.subplots(2, 1, figsize=(14, 6), sharex=True, sharey=True, gridspec_kw={'hspace': 0})
for ax, pol in zip(axes, ['Jee', 'Jnn']):
detail_cutoff = np.percentile([np.nanmean(m) for ant, m in avg_cspa_vs_time.items()
if ant[1] == pol and np.isfinite(np.nanmean(m))], 95)
for ant in avg_cspa_vs_time:
if ant[1] == pol and not np.all(cs.flag_grids[ant]):
if np.nanmean(avg_cspa_vs_time[ant]) > detail_cutoff:
ax.plot(lst_grid, avg_cspa_vs_time[ant], label=str((int(ant[0]), ant[1])), zorder=100)
else:
ax.plot(lst_grid, avg_cspa_vs_time[ant], c='grey', alpha=.2, lw=.5)
ax.legend(title=f'{pol[1:]}-Polarized', ncol=2)
ax.set_ylabel('Mean Unflagged $\\chi^2$ per Antenna')
ax.set_xlabel('LST (hours)')
ax.set_xticklabels(ax.get_xticks() % 24)
plt.ylim([1, 5.4])
plt.tight_layout()
In [30]:
def cspa_vs_freq_plot():
fig, axes = plt.subplots(2, 1, figsize=(14, 6), sharex=True, sharey=True, gridspec_kw={'hspace': 0})
for ax, pol in zip(axes, ['Jee', 'Jnn']):
detail_cutoff = np.percentile([np.nanmean(m) for ant, m in avg_cspa_vs_freq.items()
if ant[1] == pol and np.isfinite(np.nanmean(m))], 95)
for ant in avg_cspa_vs_freq:
if ant[1] == pol and not np.all(cs.flag_grids[ant]):
if np.nanmean(avg_cspa_vs_freq[ant]) > detail_cutoff:
ax.plot(cs.freqs / 1e6, avg_cspa_vs_freq[ant], label=str((int(ant[0]), ant[1])), zorder=100)
else:
ax.plot(cs.freqs / 1e6, avg_cspa_vs_freq[ant], c='grey', alpha=.2, lw=.5)
ax.legend(title=f'{pol[1:]}-Polarized', ncol=2)
ax.set_ylabel('Mean Unflagged $\\chi^2$ per Antenna')
ax.set_xlabel('Frequency (MHz)')
plt.ylim([1, 5.4])
plt.tight_layout()
In [31]:
def avg_cspa_array_plot():
hd = io.HERAData(SUM_FILE)
fig, axes = plt.subplots(1, 2, figsize=(14, 8), sharex=True, sharey=True, gridspec_kw={'wspace': 0})
for pol, ax in zip(['Jee', 'Jnn'], axes):
ants_here = [ant for ant in avg_cspa if np.isfinite(avg_cspa[ant]) and ant[1] == pol if ant[0] in hd.antpos]
avg_chisqs = [avg_cspa[ant] for ant in ants_here]
xs = [hd.antpos[ant[0]][0] for ant in ants_here]
ys = [hd.antpos[ant[0]][1] for ant in ants_here]
names = [ant[0] for ant in ants_here]
im = ax.scatter(x=xs, y=ys, c=avg_chisqs, s=200, vmin=1, vmax=3, cmap='turbo')
ax.set_aspect('equal')
for x,y,n in zip(xs, ys, names):
ax.text(x, y, str(n), va='center', ha='center', fontsize=8)
ax.set_title(pol)
ax.set_xlabel('East-West Antenna Position (m)')
axes[0].set_ylabel('North-South Antenna Position (m)')
plt.tight_layout()
plt.colorbar(im, ax=axes, location='top', aspect=60, pad=.04, label='Mean Unflagged $\\chi^2$ per Antenna', extend='both')
Figure 6: Average $\chi^2$ per Antenna¶
Here we plot $\chi^2$ per antenna from redundant-baseline calibration, separating polarizations and averaging the unflagged pixels in the waterfalls over frequency or time. The worst 5% of antennas are shown in color and highlighted in the legends, the rest are shown in grey. We also show time- and frequency-averaged $\chi^2$ for each antennas as a scatter plot with array position.
In [32]:
cspa_vs_freq_plot()
cspa_vs_time_plot()
avg_cspa_array_plot()
Mean of empty slice
No artists with labels found to put in legend. Note that artists whose label start with an underscore are ignored when legend() is called with no argument.
set_ticklabels() should only be used with a fixed number of ticks, i.e. after set_ticks() or using a FixedLocator. Mean of empty slice No artists with labels found to put in legend. Note that artists whose label start with an underscore are ignored when legend() is called with no argument. set_ticklabels() should only be used with a fixed number of ticks, i.e. after set_ticks() or using a FixedLocator.
Examine relative differences before and after smoothing¶
In [33]:
def time_avg_diff_plot():
fig, axes = plt.subplots(2, 1, figsize=(14, 6), sharex=True, sharey=True, gridspec_kw={'hspace': 0})
for ax, pol in zip(axes, ['Jee', 'Jnn']):
detail_cutoff = np.percentile([np.nanmean(diff) for ant, diff in meta['time_avg_rel_diff'].items()
if ant[1] == pol and np.isfinite(np.nanmean(diff))], 95)
for ant, rel_diff in meta['time_avg_rel_diff'].items():
if ant[0] >= 0 and ant[1] == pol and np.any(np.isfinite(rel_diff)):
if np.nanmean(rel_diff) > detail_cutoff:
if np.all(cs.flag_grids[ant]):
ax.plot(cs.freqs / 1e6, rel_diff, label=str((int(ant[0]), ant[1])), zorder=99, ls='--', c='r', lw=.5)
else:
ax.plot(cs.freqs / 1e6, rel_diff, label=str((int(ant[0]), ant[1])), zorder=100)
else:
ax.plot(cs.freqs / 1e6, rel_diff, c='grey', alpha=.2, lw=.5)
med_rel_diff = np.nanmedian([diff for ant, diff in meta['time_avg_rel_diff'].items() if ant[1] == pol], axis=0)
ax.plot(cs.freqs / 1e6, med_rel_diff, 'k--', label='Median')
ax.set_ylim([0, 1.05])
ax.legend(title=f'{pol[1:]}-Polarized', ncol=2)
ax.set_ylabel('Time-Averaged Relative Difference\nBefore and After Smoothing')
ax.set_xlabel('Frequency (MHz)')
plt.tight_layout()
In [34]:
def freq_avg_diff_plot():
fig, axes = plt.subplots(2, 1, figsize=(14, 6), sharex=True, sharey=True, gridspec_kw={'hspace': 0})
for ax, pol in zip(axes, ['Jee', 'Jnn']):
detail_cutoff = np.percentile([np.nanmean(m) for ant, m in meta['freq_avg_rel_diff'].items()
if ant[1] == pol and np.isfinite(np.nanmean(m))], 95)
for ant, rel_diff in meta['freq_avg_rel_diff'].items():
if ant[0] >= 0 and ant[1] == pol and np.any(np.isfinite(rel_diff)):
if np.nanmean(rel_diff) > detail_cutoff:
if np.all(cs.flag_grids[ant]):
ax.plot(lst_grid, rel_diff, label=str((int(ant[0]), ant[1])), zorder=99, ls='--', c='r', lw=.5)
else:
ax.plot(lst_grid, rel_diff, label=str((int(ant[0]), ant[1])), zorder=100)
else:
ax.plot(lst_grid, rel_diff, c='grey', alpha=.2, lw=.5)
med_rel_diff = np.nanmedian([diff for ant, diff in meta['freq_avg_rel_diff'].items() if ant[1] == pol], axis=0)
ax.plot(lst_grid, med_rel_diff, 'k--', label='Median', zorder=101)
ax.set_ylim([0, 1.05])
ax.legend(title=f'{pol[1:]}-Polarized', ncol=2)
ax.set_ylabel('Frequency-Averaged Relative Difference\nBefore and After Smoothing')
ax.set_xlabel('LST (hours)')
ax.set_xticklabels(ax.get_xticks() % 24)
plt.tight_layout()
In [35]:
def avg_difference_array_plot():
hd = io.HERAData(SUM_FILE)
fig, axes = plt.subplots(1, 2, figsize=(14, 8), sharex=True, sharey=True, gridspec_kw={'wspace': 0})
for pol, ax in zip(['Jee', 'Jnn'], axes):
avg_diffs = [np.nanmean(meta['time_avg_rel_diff'][ant]) for ant in meta['time_avg_rel_diff'] if ant[1] == pol if ant[0] in hd.antpos]
xs = [hd.antpos[ant[0]][0] for ant in meta['time_avg_rel_diff'] if ant[1] == pol if ant[0] in hd.antpos]
ys = [hd.antpos[ant[0]][1] for ant in meta['time_avg_rel_diff'] if ant[1] == pol if ant[0] in hd.antpos]
names = [ant[0] for ant in meta['time_avg_rel_diff'] if ant[1] == pol if ant[0] in hd.antpos]
im = ax.scatter(x=xs, y=ys, c=avg_diffs, s=200, vmin=0, vmax=.25, cmap='turbo')
ax.set_aspect('equal')
for x,y,n in zip(xs, ys, names):
color = ('w' if np.all(cs.flag_grids[n, pol]) else 'k')
ax.text(x, y, str(n), va='center', ha='center', fontsize=8, c=color)
ax.set_title(pol)
ax.set_xlabel('East-West Antenna Position (m)')
axes[0].set_ylabel('North-South Antenna Position (m)')
plt.tight_layout()
plt.colorbar(im, ax=axes, location='top', aspect=60, pad=.04, label='Average Relative Difference Before and After Smoothing', extend='max')
Figure 7: Relative Difference Before and After Smoothing¶
Similar to the above plots, here we show the relative difference before and after smoothing, compared to the magnitude of the smoothed calibration solution. Totally flagged antennas (because they are above the SC_RELATIVE_DIFF_CUTOFF) are red in the first two plots, and their numbers are white in the last plot.
In [36]:
time_avg_diff_plot()
freq_avg_diff_plot()
avg_difference_array_plot()
All-NaN slice encountered
All-NaN slice encountered set_ticklabels() should only be used with a fixed number of ticks, i.e. after set_ticks() or using a FixedLocator. All-NaN slice encountered set_ticklabels() should only be used with a fixed number of ticks, i.e. after set_ticks() or using a FixedLocator.
Save Results¶
In [37]:
add_to_history = 'Produced by calibration_smoothing notebook with the following environment:\n' + '=' * 65 + '\n' + os.popen('conda env export').read() + '=' * 65
In [38]:
cs.write_smoothed_cal(output_replace=(CAL_SUFFIX, SMOOTH_CAL_SUFFIX), add_to_history=add_to_history, clobber=True)
Mean of empty slice
invalid value encountered in multiply invalid value encountered in divide
Metadata¶
In [39]:
for repo in ['hera_cal', 'hera_qm', 'hera_filters', 'hera_notebook_templates', 'pyuvdata']:
exec(f'from {repo} import __version__')
print(f'{repo}: {__version__}')
hera_cal: 3.7.7.dev97+gc2668d3f7 hera_qm: 2.2.1.dev4+gf6d02113b hera_filters: 0.1.7
hera_notebook_templates: 0.0.1.dev1313+g92178a09c pyuvdata: 3.2.5.dev1+g5a985ae31
In [40]:
print(f'Finished execution in {(time.time() - tstart) / 60:.2f} minutes.')
Finished execution in 56.27 minutes.