treeherder/perf/migrations/0057_performancealert_confidence_and_more.py [267:396]: - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - fields=[ ("id", models.AutoField(primary_key=True, serialize=False)), ("is_regression", models.BooleanField()), ("starred", models.BooleanField(default=False)), ("created", models.DateTimeField(auto_now_add=True, null=True)), ("first_triaged", models.DateTimeField(default=None, null=True)), ("last_updated", models.DateTimeField(auto_now=True, null=True)), ( "status", models.IntegerField( choices=[ (0, "Untriaged"), (1, "Downstream"), (2, "Reassigned"), (3, "Invalid"), (4, "Acknowledged"), ], default=0, ), ), ( "amount_pct", models.FloatField( help_text="Amount in percentage that series has changed" ), ), ( "amount_abs", models.FloatField( help_text="Absolute amount that series has changed" ), ), ( "prev_value", models.FloatField( help_text="Previous value of series before change" ), ), ( "new_value", models.FloatField(help_text="New value of series after change"), ), ( "t_value", models.FloatField( help_text="t value out of analysis indicating confidence that change is 'real'", null=True, ), ), ( "confidence", models.FloatField( help_text="A value that indicates the confidence of the alert (specific to the detection method used)", null=True, ), ), ("detection_method", models.CharField(max_length=100, null=True)), ( "noise_profile", models.CharField( choices=[ ( "SKEWED", "Samples are heavily found on one side of the mean.", ), ( "OUTLIERS", "There are more outliers than should be expected from a normal distribution.", ), ( "MODAL", "There are multiple areas where most values are found rather than only one.", ), ("OK", "No issues were found."), ("N/A", "Could not compute a noise profile."), ], default="N/A", help_text="The noise profile of the data which precedes this alert.", max_length=30, ), ), ("manually_created", models.BooleanField(default=False)), ("sustained", models.BooleanField(default=False)), ("direction", models.CharField(max_length=100, null=True)), ( "prev_median", models.FloatField( help_text="Previous median value of series before change" ), ), ( "new_median", models.FloatField( help_text="New median value of series after change" ), ), ( "prev_p90", models.FloatField( help_text="Previous P90 value of series before change" ), ), ( "new_p90", models.FloatField(help_text="New P90 value of series after change"), ), ( "prev_p95", models.FloatField( help_text="Previous P95 value of series before change" ), ), ( "new_p95", models.FloatField(help_text="New P95 value of series after change"), ), ( "classifier", models.ForeignKey( null=True, on_delete=django.db.models.deletion.CASCADE, to=settings.AUTH_USER_MODEL, ), ), ( "related_summary", models.ForeignKey( null=True, on_delete=django.db.models.deletion.CASCADE, related_name="related_alerts", - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - treeherder/perf/migrations/0057_performancealert_confidence_and_more.py [423:552]: - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - fields=[ ("id", models.AutoField(primary_key=True, serialize=False)), ("is_regression", models.BooleanField()), ("starred", models.BooleanField(default=False)), ("created", models.DateTimeField(auto_now_add=True, null=True)), ("first_triaged", models.DateTimeField(default=None, null=True)), ("last_updated", models.DateTimeField(auto_now=True, null=True)), ( "status", models.IntegerField( choices=[ (0, "Untriaged"), (1, "Downstream"), (2, "Reassigned"), (3, "Invalid"), (4, "Acknowledged"), ], default=0, ), ), ( "amount_pct", models.FloatField( help_text="Amount in percentage that series has changed" ), ), ( "amount_abs", models.FloatField( help_text="Absolute amount that series has changed" ), ), ( "prev_value", models.FloatField( help_text="Previous value of series before change" ), ), ( "new_value", models.FloatField(help_text="New value of series after change"), ), ( "t_value", models.FloatField( help_text="t value out of analysis indicating confidence that change is 'real'", null=True, ), ), ( "confidence", models.FloatField( help_text="A value that indicates the confidence of the alert (specific to the detection method used)", null=True, ), ), ("detection_method", models.CharField(max_length=100, null=True)), ( "noise_profile", models.CharField( choices=[ ( "SKEWED", "Samples are heavily found on one side of the mean.", ), ( "OUTLIERS", "There are more outliers than should be expected from a normal distribution.", ), ( "MODAL", "There are multiple areas where most values are found rather than only one.", ), ("OK", "No issues were found."), ("N/A", "Could not compute a noise profile."), ], default="N/A", help_text="The noise profile of the data which precedes this alert.", max_length=30, ), ), ("manually_created", models.BooleanField(default=False)), ("sustained", models.BooleanField(default=False)), ("direction", models.CharField(max_length=100, null=True)), ( "prev_median", models.FloatField( help_text="Previous median value of series before change" ), ), ( "new_median", models.FloatField( help_text="New median value of series after change" ), ), ( "prev_p90", models.FloatField( help_text="Previous P90 value of series before change" ), ), ( "new_p90", models.FloatField(help_text="New P90 value of series after change"), ), ( "prev_p95", models.FloatField( help_text="Previous P95 value of series before change" ), ), ( "new_p95", models.FloatField(help_text="New P95 value of series after change"), ), ( "classifier", models.ForeignKey( null=True, on_delete=django.db.models.deletion.CASCADE, to=settings.AUTH_USER_MODEL, ), ), ( "related_summary", models.ForeignKey( null=True, on_delete=django.db.models.deletion.CASCADE, related_name="related_alerts", - 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