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Distribution of a value in 2D qubit lattice as a color map.
cirq.Heatmap(
value_map: Union[Mapping[QubitTuple, SupportsFloat], Mapping[grid_qubit.GridQubit,
SupportsFloat]],
**kwargs
)
Used in the notebooks
Used in the tutorials |
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Args | |
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value_map
|
A dictionary of qubits or QubitTuples as keys and corresponding magnitude as float values. It corresponds to the data which should be plotted as a heatmap. |
**kwargs
|
Optional kwargs including
title: str, default = None
plot_colorbar: bool, default = True
annotation_map: dictionary, A dictionary of QubitTuples as keys and corresponding annotation str as values. It corresponds to the text that should be added on top of each heatmap polygon unit. annotation_format: str, default = '.2g' Formatting string using which annotation_map will be implicitly constructed by applying format(value, annotation_format) for each key in value_map. This is ignored if annotation_map is explicitly specified. annotation_text_kwargs: Matplotlib Text **kwargs, colorbar_position: {'right', 'left', 'top', 'bottom'}, default = 'right' colorbar_size: str, default = '5%' colorbar_pad: str, default = '2%' colorbar_options: Matplotlib colorbar **kwargs, default = None, collection_options: Matplotlib PolyCollection **kwargs, default {"cmap" : "viridis"} vmin, vmax: colormap scaling floats, default = None |
Methods
plot
plot(
ax: Optional[plt.Axes] = None, **kwargs
) -> Tuple[plt.Axes, mpl_collections.Collection]
Plots the heatmap on the given Axes.
Args | |
---|---|
ax
|
the Axes to plot on. If not given, a new figure is created, plotted on, and shown. |
kwargs
|
The optional keyword arguments are used to temporarily override the values present in the heatmap config. See init for more details on the allowed arguments. |
Returns | |
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A 2-tuple (ax, collection) . ax is the plt.Axes that
is plotted on. collection is the collection of paths drawn and filled.
|
update_config
update_config(
**kwargs
) -> 'Heatmap'
Add/Modify **kwargs args passed during initialisation.