FilledContourPlot

class metpy.plots.FilledContourPlot(*args, **kwargs)[source]

Make color-filled contours plots by defining appropriate traits.

Attributes Summary

clabels

A boolean (True/False) on whether to plot contour labels.

colorbar

A string (horizontal/vertical) on whether to add a colorbar to the plot.

colormap

The string name for a Matplolib or MetPy colormap.

contours

A list of values to contour or an integer number of contour levels.

cross_validation_lock

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

data

Xarray dataset that contains the field to be plotted.

field

Name of the field to be plotted.

griddata

Return the internal cached data.

image_range

A tuple of min and max values that represent the range of values to color the rasterized image.

level

The level of the field to be plotted.

name

Generate a name for the plot.

parent

A trait whose value must be an instance of a specified class.

plotdata

Return the data for plotting.

time

Set the valid time to be plotted as a datetime object.

Methods Summary

__init__(*args, **kwargs)

Initialize self.

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.

clear()

Clear the plot.

clear_collections()

Clear the handle collections to the plot instance.

clear_handle()

Clear the handle to the plot instance.

draw()

Draw the plot.

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)

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.

set_trait(name, value)

Forcibly sets trait attribute, including read-only attributes.

setup_instance(*args, **kwargs)

This is called before self.__init__ is called.

trait_events([name])

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

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.

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

clabels

A boolean (True/False) on whether to plot contour labels.

To plot contour labels set this trait to True, the default value is False.

colorbar

A string (horizontal/vertical) on whether to add a colorbar to the plot.

To add a colorbar associated with the plot, set the trait to horizontal or vertical,specifying the orientation of the produced colorbar. The default value is None.

colormap

The string name for a Matplolib or MetPy colormap.

For example, the Blue-Purple colormap from Matplotlib can be accessed using ‘BuPu’.

contours

A list of values to contour or an integer number of contour levels.

This parameter sets contour or colorfill values for a plot. Values can be entered either as a list of values or as an integer with the number of contours to be plotted (as per matplotlib documentation). A list can be generated by using square brackets or creating a numpy 1D array and converting it to a list with the tolist method.

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.

data

Xarray dataset that contains the field to be plotted.

field

Name of the field to be plotted.

This is the name of the variable from the dataset that is to be plotted. An example, from a model grid file that uses the THREDDS convention for naming would be Geopotential_height_isobaric or Temperature_isobaric. For GOES-16/17 satellite data it might be Sectorized_CMI. To check for the variables available within a dataset, list the variables with the following command assuming the dataset was read using xarray as ds, list(ds)

griddata

Return the internal cached data.

image_range

A tuple of min and max values that represent the range of values to color the rasterized image.

The min and max values entered as a tuple will be converted to a matplotlib.colors.Normalize instance for plotting.

level

The level of the field to be plotted.

This is a value with units to choose the desired plot level. For example, selecting the 850-hPa level, set this parameter to 850 * units.hPa

name

Generate a name for the plot.

parent

A trait whose value must be an instance of a specified class.

The value can also be an instance of a subclass of the specified class.

Subclasses can declare default classes by overriding the klass attribute

plotdata

Return the data for plotting.

The data array, x coordinates, and y coordinates.

time

Set the valid time to be plotted as a datetime object.

If a forecast hour is to be plotted the time should be set to the valid future time, which can be done using the datetime and timedelta objects from the Python standard library.

Methods Documentation

__init__(*args, **kwargs)

Initialize self. See help(type(self)) for accurate signature.

add_traits(**traits)

Dynamically add trait attributes to the HasTraits instance.

classmethod class_own_trait_events(name)

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)

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)

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)

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.

clear()

Clear the plot.

Resets all internal state and sets need for redraw.

clear_collections()

Clear the handle collections to the plot instance.

clear_handle()

Clear the handle to the plot instance.

draw()

Draw the plot.

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.

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)
observe(handler, names=traitlets.All, type='change')

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=None, name=None, remove=False)

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.

set_trait(name, value)

Forcibly sets trait attribute, including read-only attributes.

setup_instance(*args, **kwargs)

This is called before self.__init__ is called.

classmethod trait_events(name=None)

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_metadata(traitname, key, default=None)

Get metadata values for trait by key.

trait_names(**metadata)

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

traits(**metadata)

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, names=traitlets.All, type='change')

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=traitlets.All)

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