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
Color map used for histogram lines.
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.
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]] | Scalar | HealSparseMap], **kwargs) Mapping[str, Figure] | Figure ¶
Call self as a function.
- getInputSchema() HealSparseMap]]] ¶
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.
- result
- makePlot(data: MutableMapping[str, ndarray[Any, dtype[ScalarType]] | Scalar | HealSparseMap], plotInfo: Mapping[str, str] | None = None, **kwargs) Figure ¶
Make an N-panel plot with a user-configurable number of histograms displayed in each panel.
- Parameters:
- data
pandas.core.frame.DataFrame
The catalog to plot the points from.
- plotInfo
dict
- 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"
"visit"
The visit that the data comes from (
int
)
- data
- Returns:
- fig
matplotlib.figure.Figure
The resulting figure.
- fig
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.