plot_recent_acq.py

from Chandra.Time import DateTime
from Ska.DBI import DBI
from astropy.table import Table, join
import numpy as np
from Ska.Matplotlib import plot_cxctime
import matplotlib.pyplot as plt

if 'acqs' not in globals():
    start = DateTime() - 365 * .3
    db = DBI(server='sybase', user='aca_read', dbi='sybase')
    acqs = db.fetchall('SELECT obsid,tstart,obc_id FROM acq_stats_data '
                       'WHERE tstart>{}'
                       .format(start.secs))
    db.conn.close()

acqs = Table(acqs)
acqs_id = acqs[acqs['obc_id'] == 'ID']
gacqs = acqs_id.group_by('obsid')
n_acqs = gacqs.groups.aggregate(np.size)
del n_acqs['tstart']
t_acqs = gacqs.groups.aggregate(np.mean)
out = join(n_acqs, t_acqs, keys='obsid')

# In [6]: print out
# obsid obc_id     tstart   
# ----- ------ -------------
# 14204      7 519692466.208
# 14223      8 514467026.682
# 14233      7  519941788.76
# ...
# 14479      8 521789058.212
# 14481      8 516250320.755
# 14487      8 517774710.577

plot_cxctime(out['tstart'], out['obc_id'], '.')
plt.grid()
plt.margins(0.05)
plt.ylabel('Identified acq stars')