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============================================
Visualizations (:mod:`qiskit.visualization`)
============================================
.. currentmodule:: qiskit.visualization
The visualization module contain functions that visualizes measurement outcome counts, quantum
states, circuits, devices and more.
To use visualization functions, you are required to install visualization optionals to your
development environment:
.. code-block:: bash
pip install 'qiskit[visualization]'
Common Keyword Arguments
========================
Many of the figures created by visualization functions in this module are created by `Matplotlib
`_ and accept a subset of the following common arguments. Consult the
individual documentation for exact details.
* ``title`` (``str``): a text string to use for the plot title.
* ``legend`` (``list``): a list of strings to use for labels of the data.
* ``figsize`` (``tuple``): figure size in inches .
* ``color`` (``list``): a list of strings for plotting.
* ``ax`` (`matplotlib.axes.Axes `_): An optional
``Axes`` object to be used for the visualization output. If none is specified a new
`matplotlib.figure.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.
The following example demonstrates the common usage of these arguments:
.. plot::
:alt: Output from the previous code.
:include-source:
from qiskit.visualization import plot_histogram
counts1 = {'00': 499, '11': 501}
counts2 = {'00': 511, '11': 489}
data = [counts1, counts2]
plot_histogram(data)
You can specify ``legend``, ``title``, ``figsize`` and ``color`` by passing to the kwargs.
.. plot::
:alt: Output from the previous code.
:include-source:
:context: reset
from qiskit.visualization import plot_histogram
counts1 = {'00': 499, '11': 501}
counts2 = {'00': 511, '11': 489}
data = [counts1, counts2]
legend = ['First execution', 'Second execution']
title = 'New histogram'
figsize = (10,10)
color=['crimson','midnightblue']
plot_histogram(data, legend=legend, title=title, figsize=figsize, color=color)
You can save the figure to file either by passing the file name to ``filename`` kwarg or use
`matplotlib.figure.Figure.savefig
`_ method.
.. code-block:: python
plot_histogram(data, filename='new_hist.png')
hist = plot_histogram(data)
hist.savefig('new_hist.png')
Counts Visualizations
=====================
This section contains functions that visualize measurement outcome counts.
.. autosummary::
:toctree: ../stubs/
plot_histogram
Example Usage
-------------
Here is an example of using :func:`plot_histogram` to visualize measurement outcome counts:
.. plot::
:alt: Output from the previous code.
:include-source:
from qiskit.visualization import plot_histogram
counts = {"00": 501, "11": 499}
plot_histogram(counts)
The data can be a dictionary with bit string as key and counts as value, or more commonly a
:class:`~qiskit.result.Counts` object obtained from :meth:`~qiskit.result.Result.get_counts`.
Distribution Visualizations
===========================
This section contains functions that visualize sampled distributions.
.. autosummary::
:toctree: ../stubs/
plot_distribution
State Visualizations
====================
This section contains functions that visualize quantum states.
.. autosummary::
:toctree: ../stubs/
plot_bloch_vector
plot_bloch_multivector
plot_state_city
plot_state_hinton
plot_state_paulivec
plot_state_qsphere
Example Usage
-------------
Here is an example of using :func:`plot_state_city` to visualize a quantum state:
.. plot::
:alt: Output from the previous code.
:include-source:
from qiskit.visualization import plot_state_city
state = [[ 0.75 , 0.433j],
[-0.433j, 0.25 ]]
plot_state_city(state)
The state can be array-like list of lists, ``numpy.array``, or more commonly
:class:`~qiskit.quantum_info.Statevector` or :class:`~qiskit.quantum_info.DensityMatrix` objects
obtained from a :class:`~qiskit.circuit.QuantumCircuit`:
.. plot::
:alt: Output from the previous code.
:include-source:
from qiskit import QuantumCircuit
from qiskit.quantum_info import Statevector
from qiskit.visualization import plot_state_city
qc = QuantumCircuit(2)
qc.h(0)
qc.cx(0,1)
# plot using a Statevector
state = Statevector(qc)
plot_state_city(state)
.. plot::
:alt: Output from the previous code.
:include-source:
from qiskit import QuantumCircuit
from qiskit.quantum_info import DensityMatrix
from qiskit.visualization import plot_state_city
qc = QuantumCircuit(2)
qc.h(0)
qc.cx(0,1)
# plot using a DensityMatrix
state = DensityMatrix(qc)
plot_state_city(state)
You can find code examples for each visualization functions on the individual function API page.
Device Visualizations
=====================
.. autosummary::
:toctree: ../stubs/
plot_gate_map
plot_error_map
plot_circuit_layout
plot_coupling_map
Circuit Visualizations
======================
.. autosummary::
:toctree: ../stubs/
circuit_drawer
DAG Visualizations
==================
.. autosummary::
:toctree: ../stubs/
dag_drawer
Pass Manager Visualizations
===========================
.. autosummary::
:toctree: ../stubs/
pass_manager_drawer
Timeline Visualizations
=======================
.. autosummary::
:toctree: ../stubs/
timeline_drawer
Single Qubit State Transition Visualizations
============================================
.. autosummary::
:toctree: ../stubs/
visualize_transition
Array/Matrix Visualizations
===========================
.. autosummary::
:toctree: ../stubs/
array_to_latex
Exceptions
==========
.. autoexception:: VisualizationError
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