Coverage for python/lsst/sims/seeingModel/seeingData.py : 25%
Hot-keys on this page
r m x p toggle line displays
j k next/prev highlighted chunk
0 (zero) top of page
1 (one) first highlighted chunk
|
"""Read the seeing data from disk and return appropriate FWHM_500 value at a given time. This is for use in simulations only. Otherwise data would come from the EFD.
Parameters ---------- start_time : astropy.time.Time The time of the start of the simulation. The seeing database will be assumed to start on Jan 01 of the same year. seeing_db : str or None, opt The name of the seeing database. If None (default), this will use the Seeing.db file in the 'data' directory of this package. offset_year : float, opt Offset into the cloud database by 'offset_year' years. Default 0. """ self.seeing_db = seeing_db if self.seeing_db is None: self.seeing_db = os.path.join(getPackageDir('sims_seeingModel'), 'data', 'seeing.db')
# Seeing database starts in Jan 01 of the year of the start of the simulation year_start = start_time.datetime.year + offset_year self.start_time = Time('%d-01-01' % year_start, format='isot', scale='tai')
self.seeing_dates = None self.seeing_values = None self.read_data()
"""Get the FWHM_500 value for the specified time.
Parameters ---------- time : astropy.time.Time Time in the simulation for which to find the 'current' zenith seeing values. The difference between this time and the start_time, plus the offset, will be used to query the seeing database.
Returns ------- float The FWHM_500(") closest to the specified time. """ delta_time = (time - self.start_time).sec # Find the date to look for in the time range of the data. # Note that data dates should not necessarily start at zero. dbdate = delta_time % self.time_range + self.min_time idx = np.searchsorted(self.seeing_dates, dbdate) # searchsorted ensures that left < date < right # but we need to know if date is closer to left or to right left = self.seeing_dates[idx - 1] right = self.seeing_dates[idx] if dbdate - left < right - dbdate: idx -= 1 return self.seeing_values[idx]
"""Read the seeing information from disk.
The default behavior is to use the module stored database. However, an alternate database file can be provided. The alternate database file needs to have a table called *Seeing* with the following columns:
seeingId int : A unique index for each seeing entry. s_date int : The time (in seconds) from the start of the simulation, for the seeing observation. seeing float : The FWHM of the atmospheric PSF (in arcseconds) at zenith. """ with sqlite3.connect(self.seeing_db) as conn: cur = conn.cursor() query = "select s_date, seeing from Seeing order by s_date;" cur.execute(query) results = np.array(cur.fetchall()) self.seeing_dates = np.hsplit(results, 2)[0].flatten() self.seeing_values = np.hsplit(results, 2)[1].flatten() cur.close() # Make sure seeing dates are ordered appropriately (monotonically increasing). ordidx = self.seeing_dates.argsort() self.seeing_dates = self.seeing_dates[ordidx] self.seeing_values = self.seeing_values[ordidx] self.min_time = self.seeing_dates[0] self.max_time = self.seeing_dates[-1] self.time_range = self.max_time - self.min_time
"""Report information about configuration of this data.
Returns ------- OrderedDict """ config_info = {} config_info['Start time for db'] = self.start_time config_info['Seeing database'] = self.seeing_db return config_info |