PanelContainer#

class metpy.plots.PanelContainer(**kwargs: Any)[source]#

Collects panels and set complete figure related settings (e.g., size).

Attributes Summary

cross_validation_lock

A contextmanager for running a block with our cross validation lock set to True.

figure

Provide access to the underlying figure object.

mpl_args

Supply a dictionary of valid Matplotlib keyword arguments to modify how the plot variable is drawn.

panel

Provide simple access for a single panel.

panels

A list of panels to plot on the figure.

size

This trait takes a tuple of (width, height) to set the size of the figure.

Methods Summary

__init__(*args, **kwargs)

add_traits(**traits)

Dynamically add trait attributes to the HasTraits instance.

class_own_trait_events(name)

Get a dict of all event handlers defined on this class, not a parent.

class_own_traits(**metadata)

Get a dict of all the traitlets defined on this class, not a parent.

class_trait_names(**metadata)

Get a list of all the names of this class' traits.

class_traits(**metadata)

Get a dict of all the traits of this class.

copy()

Return a copy of the panel container.

draw()

Draw the collection of panels.

has_trait(name)

Returns True if the object has a trait with the specified name.

hold_trait_notifications()

Context manager for bundling trait change notifications and cross validation.

notify_change(change)

Notify observers of a change event

observe(handler[, names, type])

Setup a handler to be called when a trait changes.

on_trait_change([handler, name, remove])

DEPRECATED: Setup a handler to be called when a trait changes.

refresh(_)

Refresh the rendering of all panels.

save(*args, **kwargs)

Save the constructed graphic as an image file.

set_trait(name, value)

Forcibly sets trait attribute, including read-only attributes.

setup_instance(**kwargs)

This is called before self.__init__ is called.

show()

Show the constructed graphic on the screen.

trait_defaults(*names, **metadata)

Return a trait's default value or a dictionary of them

trait_events([name])

Get a dict of all the event handlers of this class.

trait_has_value(name)

Returns True if the specified trait has a value.

trait_metadata(traitname, key[, default])

Get metadata values for trait by key.

trait_names(**metadata)

Get a list of all the names of this class' traits.

trait_values(**metadata)

A dict of trait names and their values.

traits(**metadata)

Get a dict of all the traits of this class.

unobserve(handler[, names, type])

Remove a trait change handler.

unobserve_all([name])

Remove trait change handlers of any type for the specified name.

Attributes Documentation

cross_validation_lock#

A contextmanager for running a block with our cross validation lock set to True.

At the end of the block, the lock’s value is restored to its value prior to entering the block.

figure[source]#

Provide access to the underlying figure object.

mpl_args#

Supply a dictionary of valid Matplotlib keyword arguments to modify how the plot variable is drawn.

Using this attribute you must choose the appropriate keyword arguments (kwargs) based on what you are plotting (e.g., contours, color-filled contours, image plot, etc.). This is available for all plot types (ContourPlot, FilledContourPlot, RasterPlot, ImagePlot, BarbPlot, ArrowPlot, PlotGeometry, and PlotObs). For PlotObs, the kwargs are those to specify the StationPlot object. NOTE: Setting the mpl_args trait will override any other trait that corresponds to a specific kwarg for the particular plot type (e.g., linecolor, linewidth).

panel[source]#

Provide simple access for a single panel.

panels#

A list of panels to plot on the figure.

This trait must contain at least one panel to plot on the figure.

size#

This trait takes a tuple of (width, height) to set the size of the figure.

This trait defaults to None and will assume the default matplotlib.pyplot.figure size.

Methods Documentation

__init__(*args: Any, **kwargs: Any) None#
add_traits(**traits: Any) None#

Dynamically add trait attributes to the HasTraits instance.

classmethod class_own_trait_events(name: str) dict[str, EventHandler]#

Get a dict of all event handlers defined on this class, not a parent.

Works like event_handlers, except for excluding traits from parents.

classmethod class_own_traits(**metadata: Any) dict[str, TraitType[Any, Any]]#

Get a dict of all the traitlets defined on this class, not a parent.

Works like class_traits, except for excluding traits from parents.

classmethod class_trait_names(**metadata: Any) list[str]#

Get a list of all the names of this class’ traits.

This method is just like the trait_names() method, but is unbound.

classmethod class_traits(**metadata: Any) dict[str, TraitType[Any, Any]]#

Get a dict of all the traits of this class. The dictionary is keyed on the name and the values are the TraitType objects.

This method is just like the traits() method, but is unbound.

The TraitTypes returned don’t know anything about the values that the various HasTrait’s instances are holding.

The metadata kwargs allow functions to be passed in which filter traits based on metadata values. The functions should take a single value as an argument and return a boolean. If any function returns False, then the trait is not included in the output. If a metadata key doesn’t exist, None will be passed to the function.

copy()[source]#

Return a copy of the panel container.

draw()[source]#

Draw the collection of panels.

has_trait(name: str) bool#

Returns True if the object has a trait with the specified name.

hold_trait_notifications() Any#

Context manager for bundling trait change notifications and cross validation.

Use this when doing multiple trait assignments (init, config), to avoid race conditions in trait notifiers requesting other trait values. All trait notifications will fire after all values have been assigned.

notify_change(change: Bunch) None#

Notify observers of a change event

observe(handler: Callable[[...], Any], names: Sentinel | str | Iterable[Sentinel | str] = traitlets.All, type: Sentinel | str = 'change') None#

Setup a handler to be called when a trait changes.

This is used to setup dynamic notifications of trait changes.

Parameters:
  • handler (callable) – A callable that is called when a trait changes. Its signature should be handler(change), where change is a dictionary. The change dictionary at least holds a ‘type’ key. * type: the type of notification. Other keys may be passed depending on the value of ‘type’. In the case where type is ‘change’, we also have the following keys: * owner : the HasTraits instance * old : the old value of the modified trait attribute * new : the new value of the modified trait attribute * name : the name of the modified trait attribute.

  • names (list, str, All) – If names is All, the handler will apply to all traits. If a list of str, handler will apply to all names in the list. If a str, the handler will apply just to that name.

  • type (str, All (default: 'change')) – The type of notification to filter by. If equal to All, then all notifications are passed to the observe handler.

on_trait_change(handler: EventHandler | None = None, name: Sentinel | str | None = None, remove: bool = False) None#

DEPRECATED: Setup a handler to be called when a trait changes.

This is used to setup dynamic notifications of trait changes.

Static handlers can be created by creating methods on a HasTraits subclass with the naming convention ‘_[traitname]_changed’. Thus, to create static handler for the trait ‘a’, create the method _a_changed(self, name, old, new) (fewer arguments can be used, see below).

If remove is True and handler is not specified, all change handlers for the specified name are uninstalled.

Parameters:
  • handler (callable, None) – A callable that is called when a trait changes. Its signature can be handler(), handler(name), handler(name, new), handler(name, old, new), or handler(name, old, new, self).

  • name (list, str, None) – If None, the handler will apply to all traits. If a list of str, handler will apply to all names in the list. If a str, the handler will apply just to that name.

  • remove (bool) – If False (the default), then install the handler. If True then unintall it.

refresh(_)[source]#

Refresh the rendering of all panels.

save(*args, **kwargs)[source]#

Save the constructed graphic as an image file.

This method takes a string for saved file name. Additionally, the same arguments and keyword arguments that matplotlib.pyplot.savefig does.

set_trait(name: str, value: Any) None#

Forcibly sets trait attribute, including read-only attributes.

setup_instance(**kwargs: Any) None#

This is called before self.__init__ is called.

show()[source]#

Show the constructed graphic on the screen.

trait_defaults(*names: str, **metadata: Any) dict[str, Any] | Sentinel#

Return a trait’s default value or a dictionary of them

Notes

Dynamically generated default values may depend on the current state of the object.

classmethod trait_events(name: str | None = None) dict[str, EventHandler]#

Get a dict of all the event handlers of this class.

Parameters:

name (str (default: None)) – The name of a trait of this class. If name is None then all the event handlers of this class will be returned instead.

Returns:

The event handlers associated with a trait name, or all event handlers.

trait_has_value(name: str) bool#

Returns True if the specified trait has a value.

This will return false even if getattr would return a dynamically generated default value. These default values will be recognized as existing only after they have been generated.

Example

class MyClass(HasTraits):
    i = Int()


mc = MyClass()
assert not mc.trait_has_value("i")
mc.i  # generates a default value
assert mc.trait_has_value("i")
trait_metadata(traitname: str, key: str, default: Any = None) Any#

Get metadata values for trait by key.

trait_names(**metadata: Any) list[str]#

Get a list of all the names of this class’ traits.

trait_values(**metadata: Any) dict[str, Any]#

A dict of trait names and their values.

The metadata kwargs allow functions to be passed in which filter traits based on metadata values. The functions should take a single value as an argument and return a boolean. If any function returns False, then the trait is not included in the output. If a metadata key doesn’t exist, None will be passed to the function.

Returns:

A dict of trait names and their values.

Notes

Trait values are retrieved via getattr, any exceptions raised by traits or the operations they may trigger will result in the absence of a trait value in the result dict.

traits(**metadata: Any) dict[str, TraitType[Any, Any]]#

Get a dict of all the traits of this class. The dictionary is keyed on the name and the values are the TraitType objects.

The TraitTypes returned don’t know anything about the values that the various HasTrait’s instances are holding.

The metadata kwargs allow functions to be passed in which filter traits based on metadata values. The functions should take a single value as an argument and return a boolean. If any function returns False, then the trait is not included in the output. If a metadata key doesn’t exist, None will be passed to the function.

unobserve(handler: Callable[[...], Any], names: Sentinel | str | Iterable[Sentinel | str] = traitlets.All, type: Sentinel | str = 'change') None#

Remove a trait change handler.

This is used to unregister handlers to trait change notifications.

Parameters:
  • handler (callable) – The callable called when a trait attribute changes.

  • names (list, str, All (default: All)) – The names of the traits for which the specified handler should be uninstalled. If names is All, the specified handler is uninstalled from the list of notifiers corresponding to all changes.

  • type (str or All (default: 'change')) – The type of notification to filter by. If All, the specified handler is uninstalled from the list of notifiers corresponding to all types.

unobserve_all(name: str | Any = traitlets.All) None#

Remove trait change handlers of any type for the specified name. If name is not specified, removes all trait notifiers.

Examples using metpy.plots.PanelContainer#

Simple Plotting

Simple Plotting

Raster Plots using Declarative Syntax

Raster Plots using Declarative Syntax

NOAA SPC Convective Outlook

NOAA SPC Convective Outlook

Combined Plotting

Combined Plotting

Surface Analysis using Declarative Syntax

Surface Analysis using Declarative Syntax

Upper Air Analysis using Declarative Syntax

Upper Air Analysis using Declarative Syntax

NOAA NHC Wind Speed Probabilities

NOAA NHC Wind Speed Probabilities

Using Predefined Areas with MetPy

Using Predefined Areas with MetPy

MetPy Declarative Syntax Tutorial

MetPy Declarative Syntax Tutorial