qiskit.visualization.plot_distribution#
- qiskit.visualization.plot_distribution(data, figsize=(7, 5), color=None, number_to_keep=None, sort='asc', target_string=None, legend=None, bar_labels=True, title=None, ax=None, filename=None)[ソース]#
Plot a distribution from input sampled data.
- パラメータ:
data (list or dict) – This is either a list of dictionaries or a single dict containing the values to represent (ex {『001』: 130})
figsize (tuple) – Figure size in inches.
color (list or str) – String or list of strings for distribution bar colors.
number_to_keep (int) – The number of terms to plot per dataset. The rest is made into a single bar called 『rest』. If multiple datasets are given, the
number_to_keep
applies to each dataset individually, which may result in more bars thannumber_to_keep + 1
. Thenumber_to_keep
applies to the total values, rather than the x-axis sort.sort (string) – Could be 『asc』, 『desc』, 『hamming』, 『value』, or 『value_desc』. If set to 『value』 or 『value_desc』 the x axis will be sorted by the maximum probability for each bitstring. Defaults to 『asc』.
target_string (str) – Target string if 『sort』 is a distance measure.
legend (list) – A list of strings to use for labels of the data. The number of entries must match the length of data (if data is a list or 1 if it’s a dict)
bar_labels (bool) – Label each bar in histogram with probability value.
title (str) – A string to use for the plot title
ax (matplotlib.axes.Axes) – An optional Axes object to be used for the visualization output. If none is specified a new matplotlib Figure will be created and used. Additionally, if specified there will be no returned Figure since it is redundant.
filename (str) – file path to save image to.
- 戻り値:
A figure for the rendered distribution, if the
ax
kwarg is not set.- 戻り値の型:
matplotlib.Figure
- 例外:
MissingOptionalLibraryError – Matplotlib not available.
VisualizationError – When legend is provided and the length doesn’t match the input data.
サンプル
# Plot two counts in the same figure with legends and colors specified. from qiskit.visualization import plot_distribution counts1 = {'00': 525, '11': 499} counts2 = {'00': 511, '11': 514} legend = ['First execution', 'Second execution'] plot_distribution([counts1, counts2], legend=legend, color=['crimson','midnightblue'], title="New Distribution") # You can sort the bitstrings using different methods. counts = {'001': 596, '011': 211, '010': 50, '000': 117, '101': 33, '111': 8, '100': 6, '110': 3} # Sort by the counts in descending order dist1 = plot_distribution(counts, sort='value_desc') # Sort by the hamming distance (the number of bit flips to change from # one bitstring to the other) from a target string. dist2 = plot_distribution(counts, sort='hamming', target_string='001')