AnalysisTool¶

class lsst.analysis.tools.AnalysisTool¶

Bases: lsst.analysis.tools.AnalysisAction

A tool which which calculates a single type of analysis on input data, though it may return more than one result.

AnalysisTools should be used though one of its sub-classes, either an AnalysisMetric or an AnalysisPlot.

Although AnalysisTools are considered a single type of analysis, the classes themselves can be thought of as a container. AnalysisTools are aggregations of AnalysisActions to form prep, process, and produce stages. These stages allow better reuse of individual AnalysisActions and easier introspection in contexts such as a notebook or interprepter.

An AnalysisTool can be thought of an an individual configuration that specifies which AnalysisAction should run for each stage.

The stages themselves are also configurable, allowing control over various aspects of the individual AnalysisActions.

Attributes Summary

`applyContext`
`history`
`identity`
`parameterizedBand`	Specifies if an `AnalysisTool` may parameterize a band within any field in any stage, or if the set of bands is already uniquely determined though configuration.
`prep`	Action to run to prepare inputs (`KeyedDataAction`, default `<class 'lsst.analysis.tools.interfaces.KeyedDataAction'>`)
`process`	Action to process data into intended form (`AnalysisAction`, default `<class 'lsst.analysis.tools.interfaces.AnalysisAction'>`)
`produce`	Action to perform any finalization steps (`AnalysisAction`, default `<class 'lsst.analysis.tools.interfaces.AnalysisAction'>`)

Methods Summary

`__call__`(data, numpy.ndarray[typing.Any, …)	Call self as a function.
`addInputSchema`(inputSchema, …)	Add the supplied inputSchema argument to the class such that it will be returned along side any other arguments in a call to `getInputSchema`.
`compare`(other[, shortcut, rtol, atol, output])	Compare this configuration to another `Config` for equality.
`formatHistory`(name, **kwargs)	Format a configuration field’s history to a human-readable format.
`freeze`()	Make this config, and all subconfigs, read-only.
`getFormattedInputSchema`(**kwargs)	Return input schema, with keys formatted with any arguments supplied by kwargs passed to this method.
`getInputSchema`()	Return the schema an `AnalysisAction` expects to be present in the arguments supplied to the __call__ method.
`getOutputSchema`()	Return the schema an `AnalysisAction` will produce, if the `__call__` method returns `KeyedData`, otherwise this may return None.
`items`()	Get configurations as `(field name, field value)` pairs.
`keys`()	Get field names.
`load`(filename[, root])	Modify this config in place by executing the Python code in a configuration file.
`loadFromStream`(stream[, root, filename])	Modify this Config in place by executing the Python code in the provided stream.
`loadFromString`(code[, root, filename])	Modify this Config in place by executing the Python code in the provided string.
`names`()	Get all the field names in the config, recursively.
`populatePrepFromProcess`()	Add additional inputs to the prep stage if supported.
`save`(filename[, root])	Save a Python script to the named file, which, when loaded, reproduces this config.
`saveToStream`(outfile[, root, skipImports])	Save a configuration file to a stream, which, when loaded, reproduces this config.
`saveToString`([skipImports])	Return the Python script form of this configuration as an executable string.
`setDefaults`()	Subclass hook for computing defaults.
`toDict`()	Make a dictionary of field names and their values.
`update`(**kw)	Update values of fields specified by the keyword arguments.
`validate`()	Validate the Config, raising an exception if invalid.
`values`()	Get field values.

Attributes Documentation

applyContext¶

history¶

identity = None¶

parameterizedBand = True¶: Specifies if an AnalysisTool may parameterize a band within any field in any stage, or if the set of bands is already uniquely determined though configuration. I.e. can this AnalysisTool be automatically looped over to produce a result for multiple bands.

prep¶: Action to run to prepare inputs (KeyedDataAction, default <class 'lsst.analysis.tools.interfaces.KeyedDataAction'>)

process¶: Action to process data into intended form (AnalysisAction, default <class 'lsst.analysis.tools.interfaces.AnalysisAction'>)

produce¶: Action to perform any finalization steps (AnalysisAction, default <class 'lsst.analysis.tools.interfaces.AnalysisAction'>)

Methods Documentation

__call__(data: MutableMapping[str, numpy.ndarray[typing.Any, numpy.dtype[+ScalarType]] | lsst.analysis.tools.interfaces.Scalar[numpy.ndarray[Any, numpy.dtype[ScalarType]], lsst.analysis.tools.interfaces.Scalar]], **kwargs) → Union[Mapping[str, matplotlib.figure.Figure], matplotlib.figure.Figure, Mapping[str, lsst.verify.measurement.Measurement], lsst.verify.measurement.Measurement]¶: Call self as a function.

addInputSchema(inputSchema: Iterable[Tuple[str, Union[Type[numpy.ndarray[Any, numpy.dtype[ScalarType]]], Type[numbers.Number], Type[numpy.number]]]]) → None¶

Add the supplied inputSchema argument to the class such that it will be returned along side any other arguments in a call to getInputSchema.

Parameters:	inputSchema : `KeyedDataSchema` A schema that is to be merged in with any existing schema when a call to `getInputSchema` is made.

compare(other, shortcut=True, rtol=1e-08, atol=1e-08, output=None)¶

Compare this configuration to another Config for equality.

Parameters:

other : lsst.pex.config.Config: Other Config object to compare against this config.
shortcut : bool, optional: If True, return as soon as an inequality is found. Default is True.
rtol : float, optional: Relative tolerance for floating point comparisons.
atol : float, optional: Absolute tolerance for floating point comparisons.
output : callable, optional: A callable that takes a string, used (possibly repeatedly) to report inequalities.

Returns:

isEqual : bool: True when the two lsst.pex.config.Config instances are equal. False if there is an inequality.

See also

lsst.pex.config.compareConfigs

Notes

Unselected targets of RegistryField fields and unselected choices of ConfigChoiceField fields are not considered by this method.

Floating point comparisons are performed by numpy.allclose.

formatHistory(name, **kwargs)¶

Format a configuration field’s history to a human-readable format.

Parameters:	name : `str` Name of a `Field` in this config. kwargs Keyword arguments passed to `lsst.pex.config.history.format`.
Returns:	history : `str` A string containing the formatted history.

See also

lsst.pex.config.history.format

freeze()¶: Make this config, and all subconfigs, read-only.

getFormattedInputSchema(**kwargs) → Iterable[Tuple[str, Union[Type[numpy.ndarray[Any, numpy.dtype[ScalarType]]], Type[numbers.Number], Type[numpy.number]]]]¶

Return input schema, with keys formatted with any arguments supplied by kwargs passed to this method.

Returns:	result : `KeyedDataSchema` The schema this action requires to be present when calling this action, formatted with any input arguments (e.g. band=’i’)

getInputSchema() → Iterable[Tuple[str, Union[Type[numpy.ndarray[Any, numpy.dtype[ScalarType]]], Type[numbers.Number], Type[numpy.number]]]]¶

Return the schema an AnalysisAction expects to be present in the arguments supplied to the __call__ method.

Returns:	result : `KeyedDataSchema` The schema this action requires to be present when calling this action, keys are unformatted.

getOutputSchema() → Optional[Iterable[Tuple[str, Union[Type[numpy.ndarray[Any, numpy.dtype[ScalarType]]], Type[numbers.Number], Type[numpy.number]]]], None]¶

Return the schema an AnalysisAction will produce, if the __call__ method returns KeyedData, otherwise this may return None.

Returns:	result : `KeyedDataSchema` or None The schema this action will produce when returning from call. This will be unformatted if any templates are present. Should return None if action does not return `KeyedData`.

items()¶

Get configurations as (field name, field value) pairs.

Returns:	items : `dict_items` Iterator of tuples for each configuration. Tuple items are: Field name. Field value.

keys()¶

Get field names.

Returns:	names : `dict_keys` List of `lsst.pex.config.Field` names.

See also

lsst.pex.config.Config.iterkeys

load(filename, root='config')¶

Modify this config in place by executing the Python code in a configuration file.

Parameters:	filename : `str` Name of the configuration file. A configuration file is Python module. root : `str`, optional Name of the variable in file that refers to the config being overridden. For example, the value of root is `"config"` and the file contains: config.myField = 5 Then this config’s field `myField` is set to `5`.

See also

lsst.pex.config.Config.loadFromStream
lsst.pex.config.Config.loadFromString
lsst.pex.config.Config.save
lsst.pex.config.Config.saveToStream
lsst.pex.config.Config.saveToString

loadFromStream(stream, root='config', filename=None)¶

Modify this Config in place by executing the Python code in the provided stream.

Parameters:

stream : file-like object, str, bytes, or compiled string

Stream containing configuration override code. If this is a code object, it should be compiled with mode="exec".

root : str, optional

Name of the variable in file that refers to the config being overridden.

For example, the value of root is "config" and the file contains:

config.myField = 5

Then this config’s field myField is set to 5.

filename : str, optional

Name of the configuration file, or None if unknown or contained in the stream. Used for error reporting.

See also

lsst.pex.config.Config.load
lsst.pex.config.Config.loadFromString
lsst.pex.config.Config.save
lsst.pex.config.Config.saveToStream
lsst.pex.config.Config.saveToString

Notes

For backwards compatibility reasons, this method accepts strings, bytes and code objects as well as file-like objects. New code should use loadFromString instead for most of these types.

loadFromString(code, root='config', filename=None)¶

Modify this Config in place by executing the Python code in the provided string.

Parameters:

code : str, bytes, or compiled string

Stream containing configuration override code.

root : str, optional

Name of the variable in file that refers to the config being overridden.

For example, the value of root is "config" and the file contains:

config.myField = 5

Then this config’s field myField is set to 5.

filename : str, optional

Name of the configuration file, or None if unknown or contained in the stream. Used for error reporting.

See also

lsst.pex.config.Config.load
lsst.pex.config.Config.loadFromStream
lsst.pex.config.Config.save
lsst.pex.config.Config.saveToStream
lsst.pex.config.Config.saveToString

names()¶

Get all the field names in the config, recursively.

Returns:	names : `list` of `str` Field names.

populatePrepFromProcess()¶

Add additional inputs to the prep stage if supported.

If the configured prep action supports adding to it’s input schema, attempt to add the required inputs schema from the process stage to the prep stage.

This method will be a no-op if the prep action does not support this feature.

save(filename, root='config')¶

Save a Python script to the named file, which, when loaded, reproduces this config.

Parameters:	filename : `str` Desination filename of this configuration. root : `str`, optional Name to use for the root config variable. The same value must be used when loading (see `lsst.pex.config.Config.load`).

See also

lsst.pex.config.Config.saveToStream
lsst.pex.config.Config.saveToString
lsst.pex.config.Config.load
lsst.pex.config.Config.loadFromStream
lsst.pex.config.Config.loadFromString

saveToStream(outfile, root='config', skipImports=False)¶

Save a configuration file to a stream, which, when loaded, reproduces this config.

Parameters:

outfile : file-like object: Destination file object write the config into. Accepts strings not bytes.
root: Name to use for the root config variable. The same value must be used when loading (see lsst.pex.config.Config.load).
skipImports : bool, optional: If True then do not include import statements in output, this is to support human-oriented output from pipetask where additional clutter is not useful.

See also

lsst.pex.config.Config.save
lsst.pex.config.Config.saveToString
lsst.pex.config.Config.load
lsst.pex.config.Config.loadFromStream
lsst.pex.config.Config.loadFromString

saveToString(skipImports=False)¶

Return the Python script form of this configuration as an executable string.

Parameters:	skipImports : `bool`, optional If `True` then do not include `import` statements in output, this is to support human-oriented output from `pipetask` where additional clutter is not useful.
Returns:	code : `str` A code string readable by `loadFromString`.

See also

lsst.pex.config.Config.save
lsst.pex.config.Config.saveToStream
lsst.pex.config.Config.load
lsst.pex.config.Config.loadFromStream
lsst.pex.config.Config.loadFromString

setDefaults()¶

Subclass hook for computing defaults.

Notes

Derived Config classes that must compute defaults rather than using the Field instances’s defaults should do so here. To correctly use inherited defaults, implementations of setDefaults must call their base class’s setDefaults.

toDict()¶

Make a dictionary of field names and their values.

Returns:	dict_ : `dict` Dictionary with keys that are `Field` names. Values are `Field` values.

See also

lsst.pex.config.Field.toDict

Notes

This method uses the toDict method of individual fields. Subclasses of Field may need to implement a toDict method for this method to work.

update(**kw)¶

Update values of fields specified by the keyword arguments.

Parameters:	kw Keywords are configuration field names. Values are configuration field values.

Notes

The __at and __label keyword arguments are special internal keywords. They are used to strip out any internal steps from the history tracebacks of the config. Do not modify these keywords to subvert a Config instance’s history.

Examples

This is a config with three fields:

>>> from lsst.pex.config import Config, Field
>>> class DemoConfig(Config):
...     fieldA = Field(doc='Field A', dtype=int, default=42)
...     fieldB = Field(doc='Field B', dtype=bool, default=True)
...     fieldC = Field(doc='Field C', dtype=str, default='Hello world')
...
>>> config = DemoConfig()

These are the default values of each field:

>>> for name, value in config.iteritems():
...     print(f"{name}: {value}")
...
fieldA: 42
fieldB: True
fieldC: 'Hello world'

Using this method to update fieldA and fieldC:

>>> config.update(fieldA=13, fieldC='Updated!')

Now the values of each field are:

>>> for name, value in config.iteritems():
...     print(f"{name}: {value}")
...
fieldA: 13
fieldB: True
fieldC: 'Updated!'

validate()¶

Validate the Config, raising an exception if invalid.

Raises:	lsst.pex.config.FieldValidationError Raised if verification fails.

Notes

The base class implementation performs type checks on all fields by calling their validate methods.

Complex single-field validation can be defined by deriving new Field types. For convenience, some derived lsst.pex.config.Field-types (ConfigField and ConfigChoiceField) are defined in lsst.pex.config that handle recursing into subconfigs.

Inter-field relationships should only be checked in derived Config classes after calling this method, and base validation is complete.

values()¶

Get field values.

Returns:	values : `dict_values` Iterator of field values.

Navigation

AnalysisTool¶