Commands API¶

Commands¶

kadi.commands.commands_v2.clear_caches()[source]¶

Clear all commands caches.

This is useful for testing and in case upstream products like the Command Events sheet have changed during a session.

kadi.commands.commands_v2.get_cmds(start=None, stop=None, *, inclusive_stop=False, scenario=None, **kwargs) → CommandTable[source]¶

Get commands using loads table, relying entirely on RLTT.

Parameters:

startCxoTime-like: Start time for cmds
stopCxoTime-like: Stop time for cmds
scenariostr, None: Scenario name
inclusive_stopbool: Include commands at exactly stop if True.
loads_stopCxoTime-like, None: Stop time for loads table (default is all available loads, but useful for development/testing work)
**kwargsdict: key=val keyword argument pairs for filtering

Returns:

CommandTable

Observations¶

kadi.commands.observations.get_observations(start=None, stop=None, *, obsid=None, scenario=None, cmds=None, starcat_date=None)[source]¶

Get observations corresponding to input parameters.

The start, stop, starcat_date and obsid parameters serve as matching filters on the list of observations that is returned.

Over the mission there are thousands of instances of multiple observations with the same obsid, so this function always returns a list of observation parameters even when obsid is specified. This most frequently occurs after any unexpected stoppage of the observng loads (SCS-107) which therefore cancels subsequent obsid commanding. In many cases you can just use the first element.

Examples:

>>> from kadi.commands import get_observations
>>> obs = get_observations(obsid=8008)[0]
>>> obs
{'obsid': 8008,
'simpos': 92904,
'obs_stop': '2007:002:18:04:28.965',
'manvr_start': '2007:002:04:31:48.216',
'targ_att': (0.149614271, 0.490896707, 0.831470649, 0.21282047),
'npnt_enab': True,
'obs_start': '2007:002:04:46:58.056',
'prev_att': (0.319214732, 0.535685207, 0.766039803, 0.155969017),
'starcat_date': '2007:002:04:31:43.965',
'starcat_idx': 147908,
'source': 'DEC2506C'}

>>> obs_all = get_observations()  # All observations in commands archive

# Might be convenient to handle this as a Table >>> from astropy.table
import Table >>> obs_all = Table(obs_all)

>>> from kadi.commands import get_observations
>>> get_observations(starcat_date='2022:001:17:00:58.521')
[{'obsid': 23800,
'simpos': 75624,
'obs_stop': '2022:002:01:24:53.004',
'manvr_start': '2022:001:17:01:02.772',
'targ_att': (0.177875061, 0.452625075, 0.827436517, 0.280784286),
'npnt_enab': True,
'obs_start': '2022:001:17:33:53.255',
'prev_att': (0.116555575, -0.407948573, -0.759717367, 0.492770009),
'starcat_date': '2022:001:17:00:58.521',
'starcat_idx': 171677,
'source': 'DEC3021A'}]

Parameters:

startCxoTime-like, None: Start time (default=beginning of commands)
stopCxoTime-like, None: Stop time (default=end of commands)
obsidint, None: ObsID
scenariostr, None: Scenario
cmdsCommandTable, None: Use this command table instead of querying the archive
starcat_dateCxoTime-like, None: Date of the observation’s star catalog

Returns:

list of dict: Observation parameters for matching observations.

kadi.commands.observations.get_starcats(start=None, stop=None, *, obsid=None, scenario=None, cmds=None, as_dict=False, starcat_date=None, show_progress=False)[source]¶

Get a list of star catalogs corresponding to input parameters.

The start, stop and obsid parameters serve as matching filters on the list of star catalogs that is returned.

By default the result is a list of ACATable objects similar to the output of proseco.get_aca_catalog.

If as_dict is True then the the result is a list of dictionaries with the same keys as the table columns plus a special “meta” key. The “meta” value is a dict with relevant metadata including the obsid, att, date, duration, sim_offset, and detctor. This method is substantially faster than the default.

There are numerous instances of multiple observations with the same obsid, so this function always returns a list of star catalogs even when obsid is specified. In most cases you can just use the first element.

The mag column corresponds to the AGASC magnitude without the AGASC supplement.

Star ID’s are determined by finding the brightest AGASC star within a search box centered at the catalog location. The search box is 1.5 arcsec halfwidth in size, but it can be changed by setting the star_id_match_halfwidth configuration parameter. Fid ID’s are determined similarly by computing fid locations given the commanded SIM-Z position. The default box size is 40 arcsec halfwidth, but it can be changed by setting the fid_id_match_halfwidth configuration parameter.

The first time each particular star catalog is fetched, the star and fid ID’s are computed which is relatively slow. The resulting star catalog is (by default) cached in the ~/.kadi/starcats.db file. Subsequent calls are significantly faster.

Example:

>>> from kadi.commands import get_starcats
>>> cat = get_starcats(obsid=8008)[0]
>>> cat
[<ACATable length=11>
slot  idx     id    type  sz    mag    maxmag   yang     zang    dim   res
int64 int64  int64   str3 str3 float64 float64 float64  float64  int64 int64
----- ----- -------- ---- ---- ------- ------- -------- -------- ----- -----
    0     1        1  FID  8x8    7.00    8.00   937.71  -829.17     1     1
    1     2        5  FID  8x8    7.00    8.00 -1810.42  1068.87     1     1
    2     3        6  FID  8x8    7.00    8.00   403.68  1712.93     1     1
    3     4 31075128  BOT  6x6    9.35   10.86  -318.22  1202.41    20     1
    4     5 31076560  BOT  6x6    9.70   11.20  -932.79  -354.55    20     1
    5     6 31463496  BOT  6x6    9.46   10.97  2026.85  1399.61    20     1
    6     7 31983336  BOT  6x6    8.64   10.14   890.71 -1600.39    20     1
    7     8 32374896  BOT  6x6    9.17   10.66  2023.08 -2021.72    13     1
    0     9 31075368  ACQ  6x6    9.13   10.64    54.04   754.79    20     1
    1    10 31982136  ACQ  6x6   10.19   11.70   562.06  -186.39    20     1
    2    11 32375384  ACQ  6x6    9.79   11.30  1612.28  -428.24    20     1]

Parameters:

startCxoTime-like, None: Start time (default=beginning of commands)
stopCxoTime-like, None: Stop time (default=end of commands)
obsidint, None: ObsID
scenariostr, None: Scenario
cmdsCommandTable, None: Use this command table instead of querying the archive.
as_dictbool, False: Return a list of dict instead of a list of ACATable objects.
starcat_dateCxoTime-like, None: Date of the observation’s star catalog
show_progressbool: Show progress bar for long queries (default=False)

Returns:

list: List of star catalogs (ACATable or dict) for matching observations.

kadi.commands.observations.get_starcats_as_table(start=None, stop=None, *, obsid=None, unique=False, scenario=None, cmds=None, starcat_date=None)[source]¶

Get a single table of star catalog entries corresponding to input parameters.

This function calls get_starcats with the same parameters and then concatenates the results into a single table for convenience. In addition to the usual star catalog columns, the obsid and starcat_date are included.

The unique parameter can be set to True to only return unique star catalog entries. There are numerous instances of a single commanded star catalogs that is associated with two ObsIDs, for instance ACIS undercover observations. To get only the first one, set unique=True.

In the following example we get every unique commanded guide star in 2020 and then join that with the corresponding observation information:

>>> from kadi.commands import get_starcats_as_table, get_observations
>>> from astropy import table
>>> start='2020:001'
>>> stop='2021:001'
>>> aces = get_starcats_as_table(start, stop, unique=True)
>>> ok = np.isin(aces['type'], ['GUI', 'BOT'])
>>> guides = aces[ok]
>>> obss = table.Table(get_observations(start, stop))
>>> obss = obss[~obss['starcat_date'].mask]  # keep only obs with starcat
>>> guides = table.join(guides, obss, keys=['starcat_date', 'obsid'])

Parameters:

startCxoTime-like, None: Start time (default=beginning of commands)
stopCxoTime-like, None: Stop time (default=end of commands)
obsidint, None: ObsID
uniquebool: If True return remove duplicate entries
scenariostr, None: Scenario
cmdsCommandTable, None: Use this command table instead of querying the archive.
starcat_dateCxoTime-like, None: Date of the observation’s star catalog

Returns:

Table: Star catalog entries for matching observations.

Utils¶

class kadi.commands.utils.TimeSeriesChunk(first: kadi.commands.utils.TimeSeriesPoint = None, min: kadi.commands.utils.TimeSeriesPoint = None, max: kadi.commands.utils.TimeSeriesPoint = None, last: kadi.commands.utils.TimeSeriesPoint = None)[source]¶

class kadi.commands.utils.TimeSeriesPoint(time: float, val: float)[source]¶

Add regions to a figure with a date-based x-axis

figure_start and figure_stop are the start and stop times for the figure. region_starts and region_stops are lists of start/stop times for regions.

kadi.commands.utils.fill_gaps_with_nan(times: list, vals: list, max_gap: float, dt: float = 0.001)[source]¶

Fill gaps in vals with NaNs where gaps in times is more than max_gap.

Do something like:

times = [1, 2, 20, 21, 22]  => [1, 2, 2.001, 19.999, 20, 21, 22]
vals = [1, 2, 3, 4, 5] => [1.0, 2.0, NaN, NaN, 3.0, 4.0, 5.0]

Parameters:

times: times
vals: values
max_gap: maximum gap in seconds
dt: time delta to use for filling gaps

Returns:

times, vals with gaps filled with NaNs

Commands API¶

Commands¶

Observations¶

Utils¶

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