generate_side_by_side.py [509:558]:
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):
    base_btime_id = ""
    base_min_idx = None

    # Recalculate median for all values, then find the new video
    # by searching in the list for it (use index) to determine
    # the matching video.
    replicates = []
    for retrigger in base_vismet:
        replicates.extend(retrigger["replicates"])
    median_value = np.median(replicates)

    # Find the video which most closely matches the average
    diff = [abs(replicate - median_value) for replicate in replicates]
    min_diff = min(diff)
    base_min_idx = diff.index(min_diff)

    print(
        "BASE: metric=%s prefix=%s mean=%d closest=%d index=%d"
        % (
            metric,
            prefix,
            median_value,
            min_diff,
            base_min_idx,
        )
    )

    replicates = []
    for retrigger in new_vismet:
        replicates.extend(retrigger["replicates"])
    median_value = np.median(replicates)

    # Find the video which most closely matches the average
    diff = [abs(replicate - median_value) for replicate in replicates]
    min_diff = min(diff)
    new_min_idx = diff.index(min_diff)

    print(
        "NEW: metric=%s prefix=%s mean=%d closest=%d index=%d"
        % (
            metric,
            prefix,
            median_value,
            min_diff,
            new_min_idx,
        )
    )

    oldvid = base_videos[base_min_idx]
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mozperftest_tools/mozperftest_tools/side_by_side.py [335:384]:
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    ):
        base_btime_id = ""
        base_min_idx = None

        # Recalculate median for all values, then find the new video
        # by searching in the list for it (use index) to determine
        # the matching video.
        replicates = []
        for retrigger in base_vismet:
            replicates.extend(retrigger["replicates"])
        median_value = np.median(replicates)

        # Find the video which most closely matches the average
        diff = [abs(replicate - median_value) for replicate in replicates]
        min_diff = min(diff)
        base_min_idx = diff.index(min_diff)

        print(
            "BASE: metric=%s prefix=%s mean=%d closest=%d index=%d"
            % (
                metric,
                prefix,
                median_value,
                min_diff,
                base_min_idx,
            )
        )

        replicates = []
        for retrigger in new_vismet:
            replicates.extend(retrigger["replicates"])
        median_value = np.median(replicates)

        # Find the video which most closely matches the average
        diff = [abs(replicate - median_value) for replicate in replicates]
        min_diff = min(diff)
        new_min_idx = diff.index(min_diff)

        print(
            "NEW: metric=%s prefix=%s mean=%d closest=%d index=%d"
            % (
                metric,
                prefix,
                median_value,
                min_diff,
                new_min_idx,
            )
        )

        oldvid = base_videos[base_min_idx]
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