qiskit/visualization/interactive/iplot_qsphere.py
def iplot_state_qsphere(rho, figsize=None):
    """ Create a Q sphere representation.

        Graphical representation of the input array, using a Q sphere for each
        eigenvalue.

        Args:
            rho (array): State vector or density matrix.
            figsize (tuple): Figure size in pixels.
    """

    # HTML
    html_template = Template("""
    <p>
        <div id="content_$divNumber" style="position: absolute; z-index: 1;">
            <div id="qsphere_$divNumber"></div>
        </div>
    </p>
    """)

    # JavaScript
    javascript_template = Template("""
    <script>
        requirejs.config({
            paths: {
                qVisualization: "https://qvisualization.mybluemix.net/q-visualizations"
            }
        });
        require(["qVisualization"], function(qVisualizations) {
            data = $data;
            qVisualizations.plotState("qsphere_$divNumber",
                                      "qsphere",
                                      data,
                                      $options);
        });
    </script>

    """)
    rho = _validate_input_state(rho)
    if figsize is None:
        options = {}
    else:
        options = {'width': figsize[0], 'height': figsize[1]}

    qspheres_data = []
    # Process data and execute
    num = int(np.log2(len(rho)))

    # get the eigenvectors and eigenvalues
    weig, stateall = linalg.eigh(rho)

    for _ in range(2**num):
        # start with the max
        probmix = weig.max()
        prob_location = weig.argmax()
        if probmix > 0.001:
            # print("The " + str(k) + "th eigenvalue = " + str(probmix))
            # get the max eigenvalue
            state = stateall[:, prob_location]
            loc = np.absolute(state).argmax()
            # get the element location closes to lowest bin representation.
            for j in range(2**num):
                test = np.absolute(np.absolute(state[j]) -
                                   np.absolute(state[loc]))
                if test < 0.001:
                    loc = j
                    break
            # remove the global phase
            angles = (np.angle(state[loc]) + 2 * np.pi) % (2 * np.pi)
            angleset = np.exp(-1j*angles)
            state = angleset*state
            state.flatten()

            spherepoints = []
            for i in range(2**num):
                # get x,y,z points

                element = bin(i)[2:].zfill(num)
                weight = element.count("1")

                number_of_divisions = n_choose_k(num, weight)
                weight_order = bit_string_index(element)

                angle = weight_order * 2 * np.pi / number_of_divisions

                zvalue = -2 * weight / num + 1
                xvalue = np.sqrt(1 - zvalue**2) * np.cos(angle)
                yvalue = np.sqrt(1 - zvalue**2) * np.sin(angle)

                # get prob and angle - prob will be shade and angle color
                prob = np.real(np.dot(state[i], state[i].conj()))
                angles = (np.angle(state[i]) + 2 * np.pi) % (2 * np.pi)
                qpoint = {
                    'x': xvalue,
                    'y': yvalue,
                    'z': zvalue,
                    'prob': prob,
                    'phase': angles
                }
                spherepoints.append(qpoint)

            # Associate all points to one sphere
            sphere = {
                'points': spherepoints,
                'eigenvalue': probmix
            }

            # Add sphere to the spheres array
            qspheres_data.append(sphere)
            weig[prob_location] = 0

    div_number = str(time.time())
    div_number = re.sub('[.]', '', div_number)

    html = html_template.substitute({
        'divNumber': div_number
    })

    javascript = javascript_template.substitute({
        'data': qspheres_data,
        'divNumber': div_number,
        'options': options
    })

    display(HTML(html + javascript))
def iplot_state_qsphere(rho, figsize=None):
    """ Create a Q sphere representation.

        Graphical representation of the input array, using a Q sphere for each
        eigenvalue.

        Args:
            rho (array): State vector or density matrix.
            figsize (tuple): Figure size in pixels.
    """

    # HTML
    html_template = Template("""
    <p>
        <div id="content_$divNumber" style="position: absolute; z-index: 1;">
            <div id="qsphere_$divNumber"></div>
        </div>
    </p>
    """)

    # JavaScript
    javascript_template = Template("""
    <script>
        requirejs.config({
            paths: {
                qVisualization: "https://qvisualization.mybluemix.net/q-visualizations"
            }
        });
        require(["qVisualization"], function(qVisualizations) {
            data = $data;
            qVisualizations.plotState("qsphere_$divNumber",
                                      "qsphere",
                                      data,
                                      $options);
        });
    </script>

    """)
    rho = _validate_input_state(rho)
    if figsize is None:
        options = {}
    else:
        options = {'width': figsize[0], 'height': figsize[1]}

    qspheres_data = []
    # Process data and execute
    num = int(np.log2(len(rho)))

    # get the eigenvectors and eigenvalues
    weig, stateall = linalg.eigh(rho)

    for _ in range(2**num):
        # start with the max
        probmix = weig.max()
        prob_location = weig.argmax()
        if probmix > 0.001:
            # print("The " + str(k) + "th eigenvalue = " + str(probmix))
            # get the max eigenvalue
            state = stateall[:, prob_location]
            loc = np.absolute(state).argmax()
            # get the element location closes to lowest bin representation.
            for j in range(2**num):
                test = np.absolute(np.absolute(state[j]) -
                                   np.absolute(state[loc]))
                if test < 0.001:
                    loc = j
                    break
            # remove the global phase
            angles = (np.angle(state[loc]) + 2 * np.pi) % (2 * np.pi)
            angleset = np.exp(-1j*angles)
            state = angleset*state
            state.flatten()

            spherepoints = []
            for i in range(2**num):
                # get x,y,z points

                element = bin(i)[2:].zfill(num)
                weight = element.count("1")

                number_of_divisions = n_choose_k(num, weight)
                weight_order = bit_string_index(element)

                angle = weight_order * 2 * np.pi / number_of_divisions

                zvalue = -2 * weight / num + 1
                xvalue = np.sqrt(1 - zvalue**2) * np.cos(angle)
                yvalue = np.sqrt(1 - zvalue**2) * np.sin(angle)

                # get prob and angle - prob will be shade and angle color
                prob = np.real(np.dot(state[i], state[i].conj()))
                angles = (np.angle(state[i]) + 2 * np.pi) % (2 * np.pi)
                qpoint = {
                    'x': xvalue,
                    'y': yvalue,
                    'z': zvalue,
                    'prob': prob,
                    'phase': angles
                }
                spherepoints.append(qpoint)

            # Associate all points to one sphere
            sphere = {
                'points': spherepoints,
                'eigenvalue': probmix
            }

            # Add sphere to the spheres array
            qspheres_data.append(sphere)
            weig[prob_location] = 0

    div_number = str(time.time())
    div_number = re.sub('[.]', '', div_number)

    html = html_template.substitute({
        'divNumber': div_number
    })

    javascript = javascript_template.substitute({
        'data': qspheres_data,
        'divNumber': div_number,
        'options': options
    })

    display(HTML(html + javascript))
Create a Q sphere representation.

        Graphical representation of the input array, using a Q sphere for each
        eigenvalue.

        Args:
            rho (array): State vector or density matrix.
            figsize (tuple): Figure size in pixels.