qiskit/visualization/circuit_visualization.py
def _matplotlib_circuit_drawer(circuit,
                               scale=0.7,
                               filename=None,
                               style=None,
                               plot_barriers=True,
                               reverse_bits=False,
                               justify=None):
    """Draw a quantum circuit based on matplotlib.
    If `%matplotlib inline` is invoked in a Jupyter notebook, it visualizes a circuit inline.
    We recommend `%config InlineBackend.figure_format = 'svg'` for the inline visualization.

    Args:
        circuit (QuantumCircuit): a quantum circuit
        scale (float): scaling factor
        filename (str): file path to save image to
        style (dict or str): dictionary of style or file name of style file
        reverse_bits (bool): When set to True reverse the bit order inside
            registers for the output visualization.
        plot_barriers (bool): Enable/disable drawing barriers in the output
            circuit. Defaults to True.
        justify (str) : `left`, `right` or `none`. Defaults to `left`. Says how
            the circuit should be justified.


    Returns:
        matplotlib.figure: a matplotlib figure object for the circuit diagram
    """

    qregs, cregs, ops = utils._get_layered_instructions(circuit,
                                                        reverse_bits=reverse_bits,
                                                        justify=justify)
    qcd = _matplotlib.MatplotlibDrawer(qregs, cregs, ops, scale=scale, style=style,
                                       plot_barriers=plot_barriers,
                                       reverse_bits=reverse_bits)
    return qcd.draw(filename)
def _matplotlib_circuit_drawer(circuit,
                               scale=0.7,
                               filename=None,
                               style=None,
                               plot_barriers=True,
                               reverse_bits=False,
                               justify=None):
    qregs, cregs, ops = utils._get_layered_instructions(circuit,
                                                        reverse_bits=reverse_bits,
                                                        justify=justify)
    qcd = _matplotlib.MatplotlibDrawer(qregs, cregs, ops, scale=scale, style=style,
                                       plot_barriers=plot_barriers,
                                       reverse_bits=reverse_bits)
    return qcd.draw(filename)
def _matplotlib_circuit_drawer ( circuit , scale = 0.7 , filename = None , style = None , plot_barriers = True , reverse_bits = False , justify = None ) : qregs , cregs , ops = utils . _get_layered_instructions ( circuit , reverse_bits = reverse_bits , justify = justify ) qcd = _matplotlib . MatplotlibDrawer ( qregs , cregs , ops , scale = scale , style = style , plot_barriers = plot_barriers , reverse_bits = reverse_bits ) return qcd . draw ( filename )
Draw a quantum circuit based on matplotlib.
    If `%matplotlib inline` is invoked in a Jupyter notebook, it visualizes a circuit inline.
    We recommend `%config InlineBackend.figure_format = 'svg'` for the inline visualization.

    Args:
        circuit (QuantumCircuit): a quantum circuit
        scale (float): scaling factor
        filename (str): file path to save image to
        style (dict or str): dictionary of style or file name of style file
        reverse_bits (bool): When set to True reverse the bit order inside
            registers for the output visualization.
        plot_barriers (bool): Enable/disable drawing barriers in the output
            circuit. Defaults to True.
        justify (str) : `left`, `right` or `none`. Defaults to `left`. Says how
            the circuit should be justified.


    Returns:
        matplotlib.figure: a matplotlib figure object for the circuit diagram
Draw a quantum circuit based on matplotlib . If %matplotlib inline is invoked in a Jupyter notebook it visualizes a circuit inline . We recommend %config InlineBackend . figure_format = svg for the inline visualization .