DewPointDepression#

class lsst.ts.watcher.rules.DewPointDepression(config, log=None)#

Bases: PollingRule

Check the dew point depression.

This rule only reads ESS telemetry topics.

Parameters:

config (types.SimpleNamespace) – Rule configuration, as validated by the schema.
log (logging.Logger, optional) – Parent logger.

Notes

The alarm name is f”DewPointDepression.{name}”.

Like most rules based on data from the ESS CSC: this uses FilteredTopicField and its ilk, because a given topic may be output for more than one sensor (e.g. there may be two humidity sensors or two 4-channel temperature sensors connected to the same CSC) where the data is differentiated by the value of the sensorName field.

Methods Summary

`compute_alarm_severity`()	Compute and set alarm severity and reason.
`get_schema`()	Return a jsonschema as a `dict`, to validate configuration.
`setup`(model)	Create filtered topic wrappers

Methods Documentation

compute_alarm_severity()#

Compute and set alarm severity and reason.

Parameters:

**kwargs (dict [str, typing.Any]) –

Keyword arguments. If triggered by TopicCallback calling update_alarm_severity, the arguments will be as follows:

data : salobj.BaseMsgType Message from the topic described by topic_callback.
topic_callback : TopicCallback Topic callback wrapper.

Returns:

None, if no change or unknown, or a tuple of two values
severity (lsst.ts.xml.enums.Watcher.AlarmSeverity) – The new alarm severity.
reason (str) – Detailed reason for the severity, e.g. a string describing what value is out of range, and what the range is. If severity is NONE then this value is ignored (but still required) and the old reason is retained until the alarm is reset to nominal state.

Notes

You may return NoneNoReason if the alarm state is NONE.

classmethod get_schema()#

Return a jsonschema as a dict, to validate configuration.

Notes

Please provide default values for all fields for which defaults make sense. This makes watcher configuration files easier to write.

If your rule has no configuration then return None.

We recommend that you write the schema as yaml, for compactness, then use yaml.safe_load to convert it to a dict. For example:

schema_yaml = """
    $schema: http://json-schema.org/draft-07/schema#
    description: Configuration for MyRule
    type: object
    properties:
    ...
    required: [...]
    additionalProperties: false
"""
return yaml.safe_load(schema_yaml)

setup(model)#

Create filtered topic wrappers

Parameters:: model (Model) – The watcher model.