def report(niter=3, **kwargs):

    kwargs = {'s': 0, 'n': 300, 'p': 20, 'signal': 7, 'split_frac': 0.8}
    split_report = reports.reports['test_split_compare']
    screened_results = reports.collect_multiple_runs(split_report['test'],
                                                     split_report['columns'],
                                                     niter,
                                                     reports.summarize_all,
                                                     **kwargs)

    fig = reports.boot_clt_plot(screened_results, inactive=True, active=False)
    fig.savefig('split_compare_pivots.pdf') # will have both bootstrap and CLT on plot
Beispiel #2
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def report(niter=50, **kwargs):

    split_report = reports.reports['test_split_compare']
    screened_results = reports.collect_multiple_runs(split_report['test'],
                                                     split_report['columns'],
                                                     niter,
                                                     reports.summarize_all,
                                                     **kwargs)

    fig = reports.boot_clt_plot(screened_results,
                                color='b',
                                inactive=True,
                                active=False)
    fig.savefig(
        'split_compare_pivots.pdf')  # will have both bootstrap and CLT on plot
Beispiel #3
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def report(niter=10, **kwargs):

    kwargs = {
        's': 0,
        'n': 300,
        'p': 10,
        'signal': 7,
        'nviews': 3,
        'intervals': 'old'
    }
    split_report = reports.reports['test_multiple_queries']
    screened_results = reports.collect_multiple_runs(split_report['test'],
                                                     split_report['columns'],
                                                     niter,
                                                     reports.summarize_all,
                                                     **kwargs)

    fig = reports.boot_clt_plot(screened_results, inactive=True, active=False)
    fig.savefig(
        'multiple_queries_CI.pdf')  # will have both bootstrap and CLT on plot