Distribution of a value in 2D qubit lattice as a color map.

Used in the notebooks

Used in the tutorials

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



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Plots the heatmap on the given Axes.

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.

A 2-tuple (ax, collection). ax is the plt.Axes that is plotted on. collection is the collection of paths drawn and filled.


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Add/Modify **kwargs args passed during initialisation.