Using the method described in the sim_asol_centroids notebook, this plots the mission trend of the upper limit on 1-axis aspect solution RMS error. This shows that nearly all observations are comfortably below the SE31 image reconstruction budget. However there
is a detectable trend upward that correlates with increase ACA CCD temperature, and
some outliers are approaching or have exceeded the limit.
Obsid 14462 was noted independently because of large yaw gyro biases. Obsid 14557 was highlighted in V&V for extremely large centroid residuals. The root cause was not fully understood, but perhaps this was the result of a very unlucky configuration of CCD hot pixels.
In [1]:
from mica.vv import get_rms_data
from astropy.table import Table
import matplotlib.pyplot as plt
from Ska.Matplotlib import plot_cxctime
from astropy.time import Time
%matplotlib inline
In [2]:
# Get the mica table of V&V data
dat = Table(get_rms_data())
In [3]:
# Filter table to select only useful and final data
datm = dat['obsid isdefault tstart used slot type dy_rms dz_rms'.split()]
ok = (dat['type'] == 'GUIDE') & (dat['used'] == 1) & (dat['isdefault'] == 1)
datm = datm[ok]
datm.sort('obsid')
datm
Out[3]:
In [4]:
# Group by obsid
datmg = datm['obsid tstart dy_rms dz_rms'.split()].group_by('obsid')
In [5]:
datmg.groups[1]
Out[5]:
In [6]:
# Select the minimum within each obsid
datmg_min = datmg.groups.aggregate(np.min)
In [15]:
# Make the plot
dyz_rms = np.maximum(datmg_min['dy_rms'], datmg_min['dz_rms'])
for sym, alpha in (('.b', 0.8), (',r', 0.5), (',y', 0.15)):
plot_cxctime(datmg_min['tstart'], dyz_rms, sym, alpha=alpha)
plt.grid()
x0, x1 = plt.xlim()
plt.hlines(0.177, x0, x1, linestyles='--', colors='r')
plt.text(x0, 0.177, ' SE31 image reconstruction budget', va='bottom', ha='left')
plt.text(Time('2013:240').plot_date, 0.21, 'Obsid 14557', ha='right')
plt.text(Time('2012:180').plot_date, 0.255, 'Obsid 14462', ha='right')
plt.ylabel('Error upper limit (arcsec)');
plt.title('Aspect solution 1-axis RMS error upper limit vs. time');
plt.savefig('asol_rms_err_upper_limit.png');
Figure 1 - Using the method described in the sim_asol_centroids notebook, this plot shows the mission trend of the upper limit on 1-axis aspect solution RMS error.
In [16]:
# Show outliers
ok = dyz_rms > 0.2
datmg_min[ok]
Out[16]:
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