qiskit/visualization/interactive/iplot_histogram.py
def iplot_histogram(data, figsize=None, number_to_keep=None,
                    sort='asc', legend=None):
    """ Create a histogram representation.

        Graphical representation of the input array using a vertical bars
        style graph.

        Args:
            data (list or dict):  This is either a list of dicts or a single
                dict containing the values to represent (ex. {'001' : 130})
            figsize (tuple): Figure size in pixels.
            number_to_keep (int): The number of terms to plot and
                rest is made into a single bar called other values
            sort (string): Could be 'asc' or 'desc'
            legend (list): A list of strings to use for labels of the data.
                The number of entries must match the length of data.
        Raises:
            VisualizationError: When legend is provided and the length doesn't
                match the input data.
    """

    # HTML
    html_template = Template("""
    <p>
        <div id="histogram_$divNumber"></div>
    </p>
    """)

    # JavaScript
    javascript_template = Template("""
    <script>
        requirejs.config({
            paths: {
                qVisualization: "https://qvisualization.mybluemix.net/q-visualizations"
            }
        });

        require(["qVisualization"], function(qVisualizations) {
            qVisualizations.plotState("histogram_$divNumber",
                                      "histogram",
                                      $executions,
                                      $options);
        });
    </script>
    """)

    # Process data and execute
    div_number = str(time.time())
    div_number = re.sub('[.]', '', div_number)

    # set default figure size if none provided
    if figsize is None:
        figsize = (7, 5)

    options = {'number_to_keep': 0 if number_to_keep is None else number_to_keep,
               'sort': sort,
               'show_legend': 0,
               'width': int(figsize[0]),
               'height': int(figsize[1])}
    if legend:
        options['show_legend'] = 1

    data_to_plot = []
    if isinstance(data, dict):
        data = [data]

    if legend and len(legend) != len(data):
        raise VisualizationError("Length of legendL (%s) doesn't match number "
                                 "of input executions: %s" %
                                 (len(legend), len(data)))

    for item, execution in enumerate(data):
        exec_data = process_data(execution, options['number_to_keep'])
        out_dict = {'data': exec_data}
        if legend:
            out_dict['name'] = legend[item]
        data_to_plot.append(out_dict)

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

    javascript = javascript_template.substitute({
        'divNumber': div_number,
        'executions': data_to_plot,
        'options': options
    })

    display(HTML(html + javascript))
def iplot_histogram(data, figsize=None, number_to_keep=None,
                    sort='asc', legend=None):
    """ Create a histogram representation.

        Graphical representation of the input array using a vertical bars
        style graph.

        Args:
            data (list or dict):  This is either a list of dicts or a single
                dict containing the values to represent (ex. {'001' : 130})
            figsize (tuple): Figure size in pixels.
            number_to_keep (int): The number of terms to plot and
                rest is made into a single bar called other values
            sort (string): Could be 'asc' or 'desc'
            legend (list): A list of strings to use for labels of the data.
                The number of entries must match the length of data.
        Raises:
            VisualizationError: When legend is provided and the length doesn't
                match the input data.
    """

    # HTML
    html_template = Template("""
    <p>
        <div id="histogram_$divNumber"></div>
    </p>
    """)

    # JavaScript
    javascript_template = Template("""
    <script>
        requirejs.config({
            paths: {
                qVisualization: "https://qvisualization.mybluemix.net/q-visualizations"
            }
        });

        require(["qVisualization"], function(qVisualizations) {
            qVisualizations.plotState("histogram_$divNumber",
                                      "histogram",
                                      $executions,
                                      $options);
        });
    </script>
    """)

    # Process data and execute
    div_number = str(time.time())
    div_number = re.sub('[.]', '', div_number)

    # set default figure size if none provided
    if figsize is None:
        figsize = (7, 5)

    options = {'number_to_keep': 0 if number_to_keep is None else number_to_keep,
               'sort': sort,
               'show_legend': 0,
               'width': int(figsize[0]),
               'height': int(figsize[1])}
    if legend:
        options['show_legend'] = 1

    data_to_plot = []
    if isinstance(data, dict):
        data = [data]

    if legend and len(legend) != len(data):
        raise VisualizationError("Length of legendL (%s) doesn't match number "
                                 "of input executions: %s" %
                                 (len(legend), len(data)))

    for item, execution in enumerate(data):
        exec_data = process_data(execution, options['number_to_keep'])
        out_dict = {'data': exec_data}
        if legend:
            out_dict['name'] = legend[item]
        data_to_plot.append(out_dict)

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

    javascript = javascript_template.substitute({
        'divNumber': div_number,
        'executions': data_to_plot,
        'options': options
    })

    display(HTML(html + javascript))
Create a histogram representation.

        Graphical representation of the input array using a vertical bars
        style graph.

        Args:
            data (list or dict):  This is either a list of dicts or a single
                dict containing the values to represent (ex. {'001' : 130})
            figsize (tuple): Figure size in pixels.
            number_to_keep (int): The number of terms to plot and
                rest is made into a single bar called other values
            sort (string): Could be 'asc' or 'desc'
            legend (list): A list of strings to use for labels of the data.
                The number of entries must match the length of data.
        Raises:
            VisualizationError: When legend is provided and the length doesn't
                match the input data.