def find_json(name, model_spec):
if model_spec is None:
name = short_name[name]
model_spec = get_xija_model_file(name)
elif not os.path.exists(model_spec):
raise IOError("The JSON file %s does not exist!" % model_spec)
return model_spec
def calc_ccd_model(start, stop):
start = DateTime(start)
stop = DateTime(stop)
model_spec = chandra_models.get_xija_model_file('aca')
# Initially propagate model for three days prior to estimate aca0 value
model = xija.XijaModel('aca', model_spec=model_spec, start=start - 3, stop=stop)
dat = fetch.Msid('aacccdpt', start - 3, start - 2, stat='5min')
model.comp['aca0'].set_data(float(dat.vals[0]))
model.make()
model.calc()
return model
def aca_ccd_model(tstart, tstop, init_temp):
cmd_states = get_cmd_states.fetch_states(tstart,
tstop,
vals=['obsid',
'pitch',
'q1', 'q2', 'q3', 'q4'])
model_spec = chandra_models.get_xija_model_file('aca')
model = xija.ThermalModel('aca', start=tstart, stop=tstop, model_spec=model_spec)
times = np.array([cmd_states['tstart'], cmd_states['tstop']])
model.comp['pitch'].set_data(cmd_states['pitch'], times)
model.comp['aca0'].set_data(init_temp, tstart)
model.comp['aacccdpt'].set_data(init_temp, tstart)
model.make()
model.calc()
return model
