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How to use _create_qual_histogram_helper method in autotest

Best Python code snippet using autotest_python

graphing_utils.py

Source:graphing_utils.py

...536    bucket: tuple containing the (low, high) values of the target bucket537    """538    return [hostname for hostname, pass_rate in hist_data539            if bucket[0] <= pass_rate < bucket[1]]540def _create_qual_histogram_helper(plot_info, extra_text=None):541    """\542    Create a machine qualification histogram of the given data.543    plot_info: a QualificationHistogram544    extra_text: text to show at the upper-left of the graph545    TODO(showard): move much or all of this into methods on546    QualificationHistogram547    """548    cursor = readonly_connection.cursor()549    cursor.execute(plot_info.query)550    if not cursor.rowcount:551        raise NoDataError('query did not return any data')552    # Lists to store the plot data.553    # hist_data store tuples of (hostname, pass_rate) for machines that have554    #     pass rates between 0 and 100%, exclusive.555    # no_tests is a list of machines that have run none of the selected tests556    # no_pass is a list of machines with 0% pass rate557    # perfect is a list of machines with a 100% pass rate558    hist_data = []559    no_tests = []560    no_pass = []561    perfect = []562    # Construct the lists of data to plot563    for hostname, total, good in cursor.fetchall():564        if total == 0:565            no_tests.append(hostname)566            continue567        if good == 0:568            no_pass.append(hostname)569        elif good == total:570            perfect.append(hostname)571        else:572            percentage = 100.0 * good / total573            hist_data.append((hostname, percentage))574    interval = plot_info.interval575    bins = range(0, 100, interval)576    if bins[-1] != 100:577        bins.append(bins[-1] + interval)578    figure, height = _create_figure(_SINGLE_PLOT_HEIGHT)579    subplot = figure.add_subplot(1, 1, 1)580    # Plot the data and get all the bars plotted581    _,_, bars = subplot.hist([data[1] for data in hist_data],582                         bins=bins, align='left')583    bars += subplot.bar([-interval], len(no_pass),584                    width=interval, align='center')585    bars += subplot.bar([bins[-1]], len(perfect),586                    width=interval, align='center')587    bars += subplot.bar([-3 * interval], len(no_tests),588                    width=interval, align='center')589    buckets = [(bin, min(bin + interval, 100)) for bin in bins[:-1]]590    # set the x-axis range to cover all the normal bins plus the three "special"591    # ones - N/A (3 intervals left), 0% (1 interval left) ,and 100% (far right)592    subplot.set_xlim(-4 * interval, bins[-1] + interval)593    subplot.set_xticks([-3 * interval, -interval] + bins + [100 + interval])594    subplot.set_xticklabels(['N/A', '0%'] +595                        ['%d%% - <%d%%' % bucket for bucket in buckets] +596                        ['100%'], rotation=90, size='small')597    # Find the coordinates on the image for each bar598    x = []599    y = []600    for bar in bars:601        x.append(bar.get_x())602        y.append(bar.get_height())603    f = subplot.plot(x, y, linestyle='None')[0]604    upper_left_coords = f.get_transform().transform(zip(x, y))605    bottom_right_coords = f.get_transform().transform(606        [(x_val + interval, 0) for x_val in x])607    # Set the title attributes608    titles = ['%d%% - <%d%%: %d machines' % (bucket[0], bucket[1], y_val)609              for bucket, y_val in zip(buckets, y)]610    titles.append('0%%: %d machines' % len(no_pass))611    titles.append('100%%: %d machines' % len(perfect))612    titles.append('N/A: %d machines' % len(no_tests))613    # Get the hostnames for each bucket in the histogram614    names_list = [_get_hostnames_in_bucket(hist_data, bucket)615                  for bucket in buckets]616    names_list += [no_pass, perfect]617    if plot_info.filter_string:618        plot_info.filter_string += ' AND '619    # Construct the list of drilldown parameters to be passed when the user620    # clicks on the bar.621    params = []622    for names in names_list:623        if names:624            hostnames = ','.join(_quote(hostname) for hostname in names)625            hostname_filter = 'hostname IN (%s)' % hostnames626            full_filter = plot_info.filter_string + hostname_filter627            params.append({'type': 'normal',628                           'filterString': full_filter})629        else:630            params.append({'type': 'empty'})631    params.append({'type': 'not_applicable',632                   'hosts': '<br />'.join(no_tests)})633    area_data = [dict(left=ulx, top=height - uly,634                      right=brx, bottom=height - bry,635                      title=title, callback=plot_info.drilldown_callback,636                      callback_arguments=param_dict)637                 for (ulx, uly), (brx, bry), title, param_dict638                 in zip(upper_left_coords, bottom_right_coords, titles, params)]639    # TODO(showard): extract these magic numbers to named constants640    if extra_text:641        figure.text(.1, .95, extra_text, size='xx-small')642    return (figure, area_data)643def create_qual_histogram(query, filter_string, interval, drilldown_callback,644                          extra_text=None):645    plot_info = QualificationHistogram(query, filter_string, interval,646                                       drilldown_callback)647    figure, area_data = _create_qual_histogram_helper(plot_info, extra_text)648    return _create_image_html(figure, area_data, plot_info)649def create_embedded_plot(model, update_time):650    """\651    Given an EmbeddedGraphingQuery object, generate the PNG image for it.652    model: EmbeddedGraphingQuery object653    update_time: 'Last updated' time654    """655    params = pickle.loads(model.params)656    extra_text = 'Last updated: %s' % update_time657    if model.graph_type == 'metrics':658        plot_info = MetricsPlot(query_dict=params['queries'],659                                plot_type=params['plot'],660                                inverted_series=params['invert'],661                                normalize_to=None,662                                drilldown_callback='')663        figure, areas_unused = _create_metrics_plot_helper(plot_info,664                                                           extra_text)665    elif model.graph_type == 'qual':666        plot_info = QualificationHistogram(667            query=params['query'], filter_string=params['filter_string'],668            interval=params['interval'], drilldown_callback='')669        figure, areas_unused = _create_qual_histogram_helper(plot_info,670                                                             extra_text)671    else:672        raise ValueError('Invalid graph_type %s' % model.graph_type)673    image, bounding_box_unused = _create_png(figure)674    return image675_cache_timeout = global_config.global_config.get_config_value(676    'AUTOTEST_WEB', 'graph_cache_creation_timeout_minutes')677def handle_plot_request(id, max_age):678    """\679    Given the embedding id of a graph, generate a PNG of the embedded graph680    associated with that id.681    id: id of the embedded graph682    max_age: maximum age, in minutes, that a cached version should be held683    """...

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