Station Device

This module implements the MCCS station device.

class MccsStation(*args: Any, **kwargs: Any)

An implementation of a station Tango device for MCCS.

AcquireDataForCalibration(first_channel: int, last_channel: int, daq_mode: str = 'TCC') → ska_tango_base.type_hints.DevVarLongStringArrayType

Instruct the SpsStation to start acquiring calibration data from the tiles.

Parameters:

• first_channel – The first channel to acquire data for

• last_channel – The last channel to acquire data for

• daq_mode – Which correlator to start, default TCC.

Returns:

A tuple containing a return code and a string message indicating status. The message is for information purpose only.

ApplyCalibration(load_time: str) → ska_tango_base.type_hints.TaskFunctionType

Load the calibration coefficients at the specified time delay.

Parameters:

load_time – load time, in ISO formatted time. If not set, defaults to calibrationLoadDelay seconds in the future.

Returns:

A tuple containing a return code and a string message indicating status. The message is for information purpose only.

Example:

>>> dp = tango.DeviceProxy("low-mccs/station/ci-1")
>>> dp.command_inout("ApplyCalibration", "")

ApplyConfiguration(**kwargs: Any) → ska_tango_base.type_hints.DevVarLongStringArrayType

Apply the aggregated channel table to this Station’s SpsStation.

Parameters:

kwargs – containing optional transaction_id, calibration_id, subarray_id.

Returns:

A tuple containing a return code and a string message indicating status. The message is for information purpose only.

Example:

>>> dp = tango.DeviceProxy("low-mccs/station/ci-1")
>>> dp.command_inout("ApplyConfiguration")

ApplyPointingDelays(load_time: str) → ska_tango_base.type_hints.TaskFunctionType

Set the pointing delay parameters of this Station’s Tiles.

Parameters:

load_time – switch time, in ISO formatted time. Default: now

Returns:

A tuple containing a return code and a string message indicating status. The message is for information purpose only.

Example:

>>> dp = tango.DeviceProxy("low-mccs/station/ci-1")
>>> time_string = switch time as ISO formatted time
>>> dp.command_inout("ApplyPointingDelays", time_string)

BeamformerRunningForSubarray(subarray_id: int) → bool

Get Beamformer Running status for a specific subarray.

Parameters:

subarray_id – subarray_id, in the range 1 to 16

Returns:

True if the beamformer is running

ConfigureChannels(argin: list[int]) → ska_tango_base.type_hints.DevVarLongStringArrayType

Set the beamformer table entries for a station beam.

Entries are defined as a flattened 2D array, for a maximum of 48 entries Each entry is 7 channels long and corresponds to 8 consecutive frequency channels.

Note

A call to this method will delete any previous channels allocated to this beam before reconfiguration.

Parameters:

argin –

list of channel block description.

Elements are:

• channel block index: value in range 0:47 for the channel block to set

• start_channel - (int) region starting channel, even in range 0 to 510

• beam_index - (int) beam used for this region with range 0 to 47

• subarray_id - (int) Subarray: 0 is reserved for unallocated entry

• subarray_logical_channel - (int) logical channel # in the subarray

• subarray_beam_id - (int) ID of the subarray beam

• substation_id - (int) Substation

• aperture_id: ID of the aperture (station*100+substation?)

Returns:

A tuple containing a return code and a string message indicating status. The message is for information purpose only.

Example:

>>> dp = tango.DeviceProxy("low-mccs/station/ci-1")
>>> dp.command_inout("ConfigureChannels", block_table)

ConfigureSemiStatic(antenna_config: dict[str, Any], station_config: dict[str, Any] | None = None, field_station_config: dict[str, Any] | None = None) → ska_tango_base.type_hints.TaskFunctionType

Configure semi static information like position of antennas.

Parameters:

• station_config – Configuration specification for the station device.

• field_station_config – Configuration specification for the field station device.

• antenna_config – Configuration specification for the antenna deviced.

Returns:

The task to be submitted as an LRC.

Example:

>>> dp = tango.DeviceProxy("low-mccs/station/ci-1")
>>> config = json.dumps({
    "station": {
        "StationId": 1,
        "ref_latitude": 1.0,
        "ref_longitude": 1.0,
        "ref_height": 1.0,
    }
})
>>> dp.command_inout("ConfigureSemiStatic", config)

ConfigureStationForCalibration(argin: str) → ska_tango_base.type_hints.TaskFunctionType

Configure the station for calibration.

Parameters:

argin – JSON-ified argument containing DAQ configuration overrides.

Returns:

A tuple containing a return code and a string message indicating status. The message is for information purpose only.

DeallocateSubarray(subarray_id: int) → ska_tango_base.type_hints.DevVarLongStringArrayType

Deallocates entries relative to a subarray in aggregate tables.

Parameters:

subarray_id – the ID of the subarray to deallocate

Returns:

A tuple containing a return code and a string message indicating status. The message is for information purpose only.

EndScan(subarray_id: int) → ska_tango_base.type_hints.DevVarLongStringArrayType

Stop the current scan associated with the station_beam.

Parameters:

subarray_id – the subarray for which the command applies

Returns:

A tuple containing a return code and a string message indicating status. The message is for information purpose only.

GetPointingDelays(pointing_type: str, values: dict | str, **kwargs: Any) → ndarray

Get pointing coefficients.

Parameters:

• pointing_type – The type of pointing requested.

• values – The pointing values, either in alt_az or ra_dec.

• kwargs – Optional arguments, including:

• interface: The schema version this is running against.

• reference_time: Time in which coordinates are equal,

  in ISO8601 formatted astropy.Time.

• time_step: Duration between each time step in seconds.

Returns:

The pointing delays as pairs of (delay, delay rate) in EEP order.

Initialise() → ska_tango_base.type_hints.TaskFunctionType

Initialise this station’s tiles.

Returns:

The task to be submitted as an LRC.

LoadBeamWeights(subarray_beam_id: int, antenna_weights: list[float]) → None

Load beam weights for a specific subarray beam.

Parameters:

• subarray_beam_id – The ID of the subarray beam for which to load weights.

• antenna_weights – A list of weights for each antenna in the subarray beam.

LoadCalibrationCoefficients(calibration_id: str | None) → ska_tango_base.type_hints.TaskFunctionType

Load Calibration solutions to the station, but does not apply them.

NOTE for each 384 channels this will select and load a solution specified by the selection rules https://developer.skao.int/projects/ska-low-mccs /en/0.22.0/api/calibration_store/selection_policy/index.html

TODO This method will load calibration solution for each antenna in the station. This will loop round all antenna and load a inverse jones for each 384 channels. A unity calibration is loaded is no solution is found, this sounds dangerous.

Parameters:

calibration_id – Unique identifier for calibration.

Returns:

A tuple containing a return code and a string message indicating status. The message is for information purpose only.

Example:

>>> dp = tango.DeviceProxy("low-mccs/station/ci-1")
>>> dp.command_inout("LoadCalibrationCoefficients")

LoadPointingDelays(delays: ndarray) → ska_tango_base.type_hints.TaskFunctionType

Set the pointing delay parameters of this Station’s Tiles.

Parameters:

delays – an array containing a beam index followed by antenna delays in antenna EEP order. 1 + 256*2 = 513 elements.

Returns:

A tuple containing a return code and a string message indicating status. The message is for information purpose only.

Example:

>>> dp = tango.DeviceProxy("low-mccs/station/ci-1")
>>> dp.command_inout("LoadPointingDelays", delay_list)

ResetCspIngest() → ska_tango_base.type_hints.DevVarLongStringArrayType

Reset link for beam data packets to CSP to defaults.

Returns:

result code name of ResetCspIngest

Scan(subarray_id: int, scan_id: int, start_time: str | None = None, duration: float = 0.0, **kwargs: Any) → ska_tango_base.type_hints.TaskFunctionType

Start the scan associated with the station_beam.

Parameters:

• subarray_id – The subarray for which the command applies

• scan_id – The ID for this scan

• start_time – UTC time for begin of scan, None for immediate start

• duration – Scan duration in seconds. 0.0 or omitted means forever

• kwargs – kwargs

Returns:

The task to be submitted as an LRC.

SetCspIngest(argin: str) → tuple[ska_control_model.ResultCode, str]

Configure link for beam data packets to CSP.

Parameters:

argin –

json dictionary with optional keywords:

• destination_ip - (string) Destination IP

• source_port - (int) Source port for integrated data streams

• destination_port - (int) Destination port for integrated data streams

Returns:

result code name of SetCspIngest

StartAcquisition(**kwargs: Any) → ska_tango_base.type_hints.TaskFunctionType

Start data acquisition.

Parameters:

kwargs – optional keywords:

• start_time - (ISO UTC time) start time

• delay - (int) delay start if StartTime is not specified, default 2s

Returns:

The task to be submitted as a LRC.

StopTracking(station_beam_id: int) → ska_tango_base.type_hints.TaskFunctionType

Stop the current tracking thread.

Parameters:

station_beam_id – the beam id whose tracking you wish to stop.

Returns:

A tuple containing a return code and a string message indicating status. The message is for information purpose only.

StopTrackingAll() → ska_tango_base.type_hints.TaskFunctionType

Stop all tracking threads.

Returns:

The task to be submitted as a LRC.

TrackObject(pointing_type: str, values: dict | str, reference_time: str, **kwargs: Any) → ska_tango_base.type_hints.DevVarLongStringArrayType

Track an object through the sky.

Parameters:

• pointing_type – the type of pointing requested

• values – Coordinates for object to be tracked

• reference_time – time in which coordinates are equal, in ISO8601 formatted astropy.Time time

• kwargs – optional kwargs inclusing scan_time, station_beam_number, time_step

Returns:

A tuple containing a return code and a string message. ResultCode.OK if tracking was successfully queued in the pointing manager, ResultCode.REJECTED otherwise.

TriggerAdcEqualisation(target_adc: float, **kwargs: Any) → ska_tango_base.type_hints.DevVarLongStringArrayType

Get the equalised ADC values.

Getting the equalised values takes up to 20 seconds (to get an average to avoid spikes). So we trigger the collection and publish to dbmPowers

Parameters:

• target_adc – the expected average power received by antennas in ADU units. Has an input minimum of 0, but in code its limited to 4.2e-7 (corresponds to the maxiumum output of 31.75 dB). There is no maximum value, however, 40 ADUs will result in 0 dB with no bias and 1600 ADUs will result in 0 dB with the maxiumum bias allowed of 32dB.

• kwargs – optional parameters include bias. user specifed bias in dB added to the antenna preadu levels. Bias input value rounded as part of value sanitation and as a result it increases in steps of 0.25. Ranges from -32 to 32 with default 0.

Returns:

A tuple containing a return code and a string message indicating status. The message is for information purpose only.

Example:

>>> dp = tango.DeviceProxy("mccs/station/001")
>>> json_arg = json.dumps({"target_adc" : "18", bias: "1"})
>>> dp.command_inout("TriggerAdcEqualisation", json_arg)

__init__(*args: Any, **kwargs: Any) → None

Initialise this device object.

Parameters:

• args – positional args to the init

• kwargs – keyword args to the init

activeBankCalibrationId() → str

Return the calibration id in the active bank.

Returns:

Return the calibration id in use

activeBeamInfo() → str

Return the configuration information of currently active PointingRequests.

List information about each active beam. Info includes pointing type,

values, reference time, scan time, time step, next update time, and whether the scan is complete.

Returns:

A json encoded dictionary with beam IDs as keys and their information as values.

additionalDebug(argin: bool) → None

Set whether additional debug information is enabled.

Parameters:

argin – True to enable additional debug information, False to disable.

antennaMasks(masks: list[bool]) → None

Set the antennaMasks.

This must be executed in EngineeringMode. Value is persisted in the database.

Parameters:

masks – masks to apply

appliedWeightingBlock() → ndarray

Return the last applied weighting block.

Magic number -1 represents that this has not been updated.

Returns:

The last know weightingBlock applied.

beamTrls() → list[str]

Return the TRLs of station beams associated with this station.

Returns:

the TRLs of station beams associated with this station

beamformerTable() → list[list[int]]

Return the ids of the channels configured for this beam.

Returns:

channel table

calibrationCoefficients() → list[float]

Return the calibration coefficients for the station.

Todo:

How big should this array be? 4 complex values (Jones matrix) per channel. This station can have up to 16 tiles of up to 16 antennas, so that is 8 x 16 x 16 = 2048 coefficients per channel. But how many channels? 384 channels, 786432 elements per station (402M for SKA Low)

Returns:

the calibration coefficients

calibrationJobId() → int

Return the calibration job id.

Returns:

the calibration job id

calibrationLoadDelay(value: float) → None

Set the load time for calls to ApplyCalibration.

Parameters:

value – Number of seconds in the future for the calibration to be applied.

configuredWeightingBlock() → ndarray

Return the configured weighting block.

This will return the Weighting Block configured. Note that this may or may not have been written to the hardware. Please view appliedWeightingBlock for the block applied.

Magic number -1 represents that this has not been updated.

Returns:

The current configured weightingBlock.

create_component_manager() → StationComponentManager

Create and return a component manager for this device.

Returns:

a component manager for this device.

cspIngestConfig() → str

Report the CspIngest configuration in use for this station.

Returns:

json string with CspIngest configuration.

daqJobId() → int

Return the DAQ job id.

Returns:

the DAQ job id

daqPath() → str

Report the DAQ path in use for this station.

Returns:

DAQ path.

dataDirectory() → str

Return the data directory.

(the parent directory for all files generated by this station)

Returns:

the data directory

dataReceivedResult() → tuple[str, str] | None

Read the result of the receiving of data.

Returns:

A tuple containing the data mode of transmission and a json string with any additional data about the data such as the file name.

delayCentre(value: list[float]) → None

Set the delay centre of the station.

Parameters:

value – WGS84 position

engineering_to_write(req_type: tango.AttReqType) → bool

Return a flag representing whether we are in Engineering mode.

Parameters:

req_type – the request type

Returns:

True if Tile is in Engineering Mode.

execute_AcquireDataForCalibration(first_channel: int, last_channel: int, daq_mode: str) → ska_tango_base.type_hints.TaskFunctionType

Execute the AcquireDataForCalibration command as a long-running task.

Parameters:

• first_channel – The first channel to acquire data for

• last_channel – The last channel to acquire data for

• daq_mode – Which correlator to start, default TCC.

Returns:

The task to be submitted as a LRC.

execute_ApplyConfiguration(**kwargs: Any) → ska_tango_base.type_hints.TaskFunctionType

Apply the aggregated channel table to this Station’s SpsStation.

Parameters:

kwargs – containing optional transaction_id, calibration_id, subarray_id.

Returns:

A tuple containing a return code and a string message indicating status. The message is for information purpose only.

execute_EndScan(subarray_id: int) → ska_tango_base.type_hints.TaskFunctionType

Execute the EndScan command as a long-running task.

Parameters:

subarray_id – the subarray for which the command applies

Returns:

A tuple containing a return code and a string message indicating status. The message is for information purpose only.

execute_Off() → ska_tango_base.type_hints.TaskFunctionType

Turn the station on.

Returns:

A tuple containing a return code and a string message indicating status. The message is for information purpose only.

execute_On() → ska_tango_base.type_hints.TaskFunctionType

Turn the station on.

Returns:

A tuple containing a return code and a string message indicating status. The message is for information purpose only.

execute_TriggerAdcEqualisation(target_adc: float, **kwargs: Any) → ska_tango_base.type_hints.TaskFunctionType

Execute the TriggerAdcEqualisation command as a long-running task.

Parameters:

• target_adc – target value for ADC gain.

• kwargs – optional parameters include bias.

Returns:

The task to be submitted as a LRC.

failedPointingUpdates() → str

Return the tracking beams which are currently unlocked.

Returns:

the tracking beams which are currently unlocked.

healthModelParams(argin: str) → None

Set the params for health transition rules.

Parameters:

argin – JSON-string of dictionary of health states

healthReport() → str

Get the health report.

Returns:

the health report.

healthThresholds(argin: str) → None

Set the params for health transition rules.

Default health thresholds:

“antennas”: (f2f, d2f, d2d),

tuple(int, int, int): Number of antennas failed before health failed,

Number of antennas degraded before health failed, Number of antennas degraded before health degraded

Parameters:

argin – JSON-string of dictionary of health thresholds

inactiveBankCalibrationId() → str

Return the calibration id of the inactive bank.

Returns:

Return the inactive bank calibration id

init_device() → None

Initialise the device.

isCalibrated() → bool

Return a flag indicating whether this station is currently calibrated or not.

Returns:

a flag indicating whether this station is currently calibrated or not.

isConfigured() → bool

Return a flag indicating whether this station is currently configured or not.

Returns:

a flag indicating whether this station is currently configured or not.

isInitialised() → bool

Return true if all tiles in the SpsStation are initialised.

Returns:

true if all tiles in the SpsStation are initialised.

isSynchronised() → bool

Return true if all tiles in the SpsStation are synchronised.

Returns:

true if all tiles in the SpsStation are synchronised.

lastPointingDelays() → str

Return last pointing delays applied to the tiles.

Values are initialised to 0.0 if they haven’t been set. These values are in antenna EEP order.

Returns:

last pointing delays applied to the tiles.

latestPreferredJobId() → str

Return the user_friendly_name of the most recent preferred calibration job.

Returns:

the user_friendly_name of the most recent preferred job, or an empty string if none exists.

numberOfChannels() → int

Return the total number of channels in the beamformer.

Returns:

the total number of channels

outsideTemperature() → float | None

Return the OutsideTemperature.

Returns:

the OutsideTemperature.

pointingUpdateTimingHistory(history_size: int) → None

Set the number of pointing update timing records to keep in history.

Parameters:

history_size – Number of timing records to keep (must be > 0)

refHeight() → float

Return the refHeight attribute.

Returns:

the ellipsoidal height of the station reference position

refLatitude() → float

Return the refLatitude attribute.

Returns:

the WGS84 Latitude of the station reference position

refLongitude() → float

Return the refLongitude attribute.

Returns:

the WGS84 Longitude of the station reference position

staticDelays() → list[float]

Report the static delays in use for this station.

Returns:

list of static delays.

stationID() → int

Return the station ID.

Returns:

the numerical station ID.

trackingStatus() → str

Return the tracking status of currently active PointingRequests.

Beam IDs not listed have no active PointingRequest.

Returns:

Tracking status of active PointingRequests.

transientBufferTrl() → str

Return the TRL of the TANGO device that managers the transient buffer.

Returns:

the TRL of the TANGO device that managers the transient buffer

useNewHealthModel(argin: bool) → None

Set a flag indicating whether this station is using the new health model.

Parameters:

argin – a flag indicating whether this station is currently using the new health model.

main(*args: str, **kwargs: str) → int

Entry point for module.

Parameters:

• args – positional arguments

• kwargs – named arguments

Returns:

exit code