prediction_generation/old-code/cpdbench_mozilla_rep copy.py [281:343]:
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        for prev, cur in zip(analyzed_series, analyzed_series[1:]):
            if cur.change_detected:
                prev_value = cur.historical_stats["avg"]
                new_value = cur.forward_stats["avg"]
                alert_properties = get_alert_properties(
                    prev_value, new_value, signature.lower_is_better
                )
                noise_profile = "N/A"
                try:
                    # Gather all data up to the current data point that
                    # shows the regression and obtain a noise profile on it.
                    # This helps us to ignore this alert and others in the
                    # calculation that could influence the profile.
                    noise_data = []
                    for point in analyzed_series:
                        if point == cur:
                            break
                        noise_data.append(geomean(point.values))

                    noise_profile, _ = moz_measure_noise.deviance(noise_data)
                    if not isinstance(noise_profile, str):
                        raise Exception(
                            f"Expecting a string as a noise profile, got: {type(noise_profile)}"
                        )
                except Exception:
                    # Fail without breaking the alert computation
                    newrelic.agent.notice_error()
                    logger.error("Failed to obtain a noise profile.")

                # ignore regressions below the configured regression
                # threshold

                # ALERT_PCT, ALERT_ABS, and ALERT_CHANGE_TYPES come from the PerformanceSignature class in the Treeherder code
                ALERT_PCT = 0
                ALERT_ABS = 1
                ALERT_CHANGE_TYPES = ((ALERT_PCT, "percentage"), (ALERT_ABS, "absolute"))
                if (
                    (
                        signature.alert_change_type is None
                        or signature.alert_change_type == ALERT_PCT
                    )
                    and alert_properties.pct_change < alert_threshold
                ) or (
                    signature.alert_change_type == ALERT_ABS
                    and abs(alert_properties.delta) < alert_threshold
                ):
                    continue
                # summary, _ = PerformanceAlertSummary.objects.get_or_create(
                #     repository=signature.repository,
                #     framework=signature.framework,
                #     push_id=cur.push_id,
                #     prev_push_id=prev.push_id,
                #     defaults={
                #         "manually_created": False,
                #         "created": datetime.utcfromtimestamp(cur.push_timestamp),
                #     },
                # )

                # django/mysql doesn't understand "inf", so just use some
                # arbitrarily high value for that case
                t_value = cur.t
                if t_value == float("inf"):
                    t_value = 1000
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prediction_generation/old-code/cpdbench_mozilla_rep_with_restart_on_alert.py [283:334]:
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        for prev, cur in zip(analyzed_series, analyzed_series[1:]):
            if cur.change_detected:
                prev_value = cur.historical_stats["avg"]
                new_value = cur.forward_stats["avg"]
                alert_properties = get_alert_properties(
                    prev_value, new_value, signature.lower_is_better
                )
                noise_profile = "N/A"
                try:
                    # Gather all data up to the current data point that
                    # shows the regression and obtain a noise profile on it.
                    # This helps us to ignore this alert and others in the
                    # calculation that could influence the profile.
                    noise_data = []
                    for point in analyzed_series:
                        if point == cur:
                            break
                        noise_data.append(geomean(point.values))

                    noise_profile, _ = moz_measure_noise.deviance(noise_data)
                    if not isinstance(noise_profile, str):
                        raise Exception(
                            f"Expecting a string as a noise profile, got: {type(noise_profile)}"
                        )
                except Exception:
                    # Fail without breaking the alert computation
                    newrelic.agent.notice_error()
                    logger.error("Failed to obtain a noise profile.")

                # ignore regressions below the configured regression threshold

                # ALERT_PCT, ALERT_ABS, and ALERT_CHANGE_TYPES come from the PerformanceSignature class in the Treeherder code
                ALERT_PCT = 0
                ALERT_ABS = 1
                ALERT_CHANGE_TYPES = ((ALERT_PCT, "percentage"), (ALERT_ABS, "absolute"))
                if (
                    (
                        signature.alert_change_type is None
                        or signature.alert_change_type == ALERT_PCT
                    )
                    and alert_properties.pct_change < alert_threshold
                ) or (
                    signature.alert_change_type == ALERT_ABS
                    and abs(alert_properties.delta) < alert_threshold
                ):
                    continue

                # django/mysql doesn't understand "inf", so just use some
                # arbitrarily high value for that case
                t_value = cur.t
                if t_value == float("inf"):
                    t_value = 1000
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