def show_summary(trace: ProcessedTrace) -> None:
print(f"{trace.NumberGCs} GCs")
for k, v in trace.number_gcs_in_each_generation.items():
print(f" {k.name}: {v}")
print(f"{trace.HeapCount} heaps")
for m in ("HeapSizeAfterMB_Mean", "HeapSizeAfterMB_Max"):
print(f"{m}: {trace.unwrap_metric_from_name(m)}")
# TODO: how to get mean/max memory load? Is it possible?
metrics: Sequence[str] = ("PauseDurationMSec", "PromotedMBPerSec",
"HeapSizeAfterMB")
num_metrics = len(metrics)
kind_to_metric_to_values: List[List[List[float]]] = [
[[] for _ in range(num_metrics)] for _ in range(4)
]
for gc in trace.gcs:
gc_kind = get_gc_kind(gc)
for metric_index, metric in enumerate(metrics):
metric_index_to_values = kind_to_metric_to_values[enum_value(
gc_kind)]
values = metric_index_to_values[metric_index]
values.append(gc.unwrap_metric_from_name(metric))
for kind in GCKind:
histograms: List[BasicHistogram] = []
for metric_index, metric in enumerate(metrics):
histograms.append(
BasicHistogram(
values=kind_to_metric_to_values[enum_value(kind)]
[metric_index],
name=metric,
x_label=kind.name,
))
basic_chart(histograms)
def _custom_chart() -> None:
xs = tuple(range(8))
basic_chart((
BasicLineChart(
lines=(
BasicLine(name="linear", xs=xs, ys=xs),
BasicLine(name="quadratic", xs=xs, ys=[x**2 for x in xs]),
),
x_label="x",
y_label="y",
),
BasicHistogram(values=[x for n in range(4) for x in repeat(n, n)],
x_label="number"),
))
