HistPlot

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

Bases: PlotAction

Make an N-panel plot with a configurable number of histograms displayed in each panel. Reference lines showing values of interest may also be added to each histogram. Panels are configured using the HistPanel class.

Attributes Summary

cmap	Color map used for histogram lines.
panels	A configurable dict describing the panels to be plotted, and the histograms for each panel.

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])	Make an N-panel plot with a user-configurable number of histograms displayed in each panel.

Attributes Documentation

cmap

Color map used for histogram lines. All types available via plt.cm may be used. A number of custom color maps are also defined: newtab10, bright, vibrant. (str, default 'newtab10')

panels

A configurable dict describing the panels to be plotted, and the histograms for each panel. (ConfigDict, default {})

Methods Documentation

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

Call self as a function.

getInputSchema() → 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: MutableMapping[str, ndarray[Any, dtype[_ScalarType_co]] | Scalar | HealSparseMap | Tensor | Mapping], plotInfo: Mapping[str, str] = None, **kwargs) → Figure

Make an N-panel plot with a user-configurable number of histograms displayed in each panel.

Parameters:

datapandas.core.frame.DataFrame

The catalog to plot the points from.

plotInfodict

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

"run"

Output run for the plots (str).

"tractTableType"

Table from which results are taken (str).

"plotName"

Output plot name (str)

"SN"

The global signal-to-noise data threshold (float)

"skymap"

The type of skymap used for the data (str).

"tract"

The tract that the data comes from (int).

"bands"

The bands used for this data (str or list).

"visit"

The visit that the data comes from (int)

Returns:

figmatplotlib.figure.Figure

The resulting figure.

Examples

An example histogram plot may be seen below:

For further details on how to generate a plot, please refer to the getting started guide.