CompletenessHist

class lsst.analysis.tools.actions.plot.CompletenessHist(*args, **kw)

Bases: PlotAction

Makes plots of completeness and purity.

Attributes Summary

action	Action to compute completeness/purity (CalcCompletenessHistogramAction, default <class 'lsst.analysis.tools.actions.keyedData.calcCompletenessHistogram.CalcCompletenessHistogramAction'>)
color_counts	Color for the line showing object counts (str, default '#029E73')
color_right	Color for the line showing the correctly classified fraction (str, default '#949494')
color_wrong	Color for the line showing the wrongly classified fraction (str, default '#DE8F05')
label_shift	Fraction of plot width to shift completeness/purity labels by.Ignored if percentiles_style is not 'below_line' (float, default -0.1)
legendLocation	Legend position within main plot (str, default 'lower left')
mag_ref_label	Label for the completeness x axis.
mag_target_label	Label for the purity x axis.
object_label	Label for measured objects (str, default 'Object')
percentiles_style	Style and locations for completeness threshold percentile labels (str, default 'below_line')
publicationStyle	Make a publication-style of plot (bool, default False)
reference_label	Label for reference objects (str, default 'Reference')
show_purity	Whether to include a purity plot below completness (bool, default True)

Methods Summary

__call__(data, **kwargs)	Call self as a function.
getInputSchema()	Return the schema an AnalysisAction expects to be present in the arguments supplied to the __call__ method.
makePlot(data, plotInfo, **kwargs)	Makes a plot showing the fraction of injected sources recovered by input magnitude.

Attributes Documentation

action

Action to compute completeness/purity (CalcCompletenessHistogramAction, default <class 'lsst.analysis.tools.actions.keyedData.calcCompletenessHistogram.CalcCompletenessHistogramAction'>)

color_counts

Color for the line showing object counts (str, default '#029E73')

color_right

Color for the line showing the correctly classified fraction (str, default '#949494')

color_wrong

Color for the line showing the wrongly classified fraction (str, default '#DE8F05')

label_shift

Fraction of plot width to shift completeness/purity labels by.Ignored if percentiles_style is not ‘below_line’ (float, default -0.1)

legendLocation

Legend position within main plot (str, default 'lower left')

mag_ref_label

Label for the completeness x axis. (str, default '{band}-band Reference Magnitude')

mag_target_label

Label for the purity x axis. (str, default '{band}-band Measured Magnitude')

object_label

Label for measured objects (str, default 'Object')

percentiles_style

Style and locations for completeness threshold percentile labels (str, default 'below_line')

Allowed values:

'above_plot'

Labels in a semicolon-separated list above plot

'below_line'

Labels under the horizontal part of each line

'None'

Field is optional

publicationStyle

Make a publication-style of plot (bool, default False)

reference_label

Label for reference objects (str, default 'Reference')

show_purity

Whether to include a purity plot below completness (bool, default True)

Methods Documentation

__call__(data: MutableMapping[str, ndarray[tuple[Any, ...], dtype[_ScalarT]] | Scalar | HealSparseMap | Tensor | Mapping], **kwargs) → Mapping[str, Figure] | Figure

Call self as a function.

getInputSchema() → Iterable[tuple[str, type[numpy.ndarray[tuple[Any, ...], numpy.dtype[_ScalarT]]] | type[lsst.analysis.tools.interfaces._interfaces.Scalar] | type[healsparse.healSparseMap.HealSparseMap] | type[lsst.analysis.tools.interfaces._interfaces.Tensor] | type[Mapping]]]

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

Returns:

resultKeyedDataSchema

The schema this action requires to be present when calling this action, keys are unformatted.

makePlot(data, plotInfo, **kwargs)

Makes a plot showing the fraction of injected sources recovered by input magnitude.

The behavior of this plot is controlled by self.action. This action must be added to a struct (usually self.process.calculateActions) by the tool that calls this plot.

Parameters:

dataKeyedData

All the data

plotInfodict

A dictionary of information about the data being plotted with keys: camera

The camera used to take the data (lsst.afw.cameraGeom.Camera)

"cameraName"

The name of camera used to take the data (str).

"filter"

The filter used for this data (str).

"ccdKey"

The ccd/dectector key associated with this camera (str).

"visit"

The visit of the data; only included if the data is from a single epoch dataset (str).

"patch"

The patch that the data is from; only included if the data is from a coadd dataset (str).

"tract"

The tract that the data comes from (str).

"photoCalibDataset"

The dataset used for the calibration, e.g. “jointcal” or “fgcm” (str).

"skyWcsDataset"

The sky Wcs dataset used (str).

"rerun"

The rerun the data is stored in (str).

Returns

——

``fig``

The figure to be saved (matplotlib.figure.Figure).

Notes

The behaviour of this plot is largel

Examples

An example of the plot produced from this code from tract 3828 of the DC2 simulations is here: