def _to_proto(
thresholds: List[float], histogram: calibration_histogram.Histogram
) -> metrics_for_slice_pb2.CalibrationHistogramBuckets:
"""Converts histogram into CalibrationHistogramBuckets proto.
Args:
thresholds: Thresholds associated with histogram buckets.
histogram: Calibration histogram.
Returns:
A histogram in CalibrationHistogramBuckets proto format.
"""
pb = metrics_for_slice_pb2.CalibrationHistogramBuckets()
lower_threshold = float('-inf')
for i, bucket in enumerate(histogram):
if i >= len(thresholds) - 1:
upper_threshold = float('inf')
else:
upper_threshold = thresholds[i + 1]
pb.buckets.add(
lower_threshold_inclusive=lower_threshold,
upper_threshold_exclusive=upper_threshold,
total_weighted_label={'value': bucket.weighted_labels},
total_weighted_refined_prediction={
'value': bucket.weighted_predictions
},
num_weighted_examples={'value': bucket.weighted_examples})
lower_threshold = upper_threshold
return pb
def testSerializePlots(self):
slice_key = _make_slice_key('fruit', 'apple')
plot_key = metric_types.PlotKey(name='calibration_plot',
output_name='output_name')
calibration_plot = text_format.Parse(
"""
buckets {
lower_threshold_inclusive: -inf
upper_threshold_exclusive: 0.0
num_weighted_examples { value: 0.0 }
total_weighted_label { value: 0.0 }
total_weighted_refined_prediction { value: 0.0 }
}
buckets {
lower_threshold_inclusive: 0.0
upper_threshold_exclusive: 0.5
num_weighted_examples { value: 1.0 }
total_weighted_label { value: 1.0 }
total_weighted_refined_prediction { value: 0.3 }
}
buckets {
lower_threshold_inclusive: 0.5
upper_threshold_exclusive: 1.0
num_weighted_examples { value: 1.0 }
total_weighted_label { value: 0.0 }
total_weighted_refined_prediction { value: 0.7 }
}
buckets {
lower_threshold_inclusive: 1.0
upper_threshold_exclusive: inf
num_weighted_examples { value: 0.0 }
total_weighted_label { value: 0.0 }
total_weighted_refined_prediction { value: 0.0 }
}
""", metrics_for_slice_pb2.CalibrationHistogramBuckets())
expected_plots_for_slice = text_format.Parse(
"""
slice_key {
single_slice_keys {
column: 'fruit'
bytes_value: 'apple'
}
}
plot_keys_and_values {
key {
output_name: "output_name"
}
value {
calibration_histogram_buckets {
buckets {
lower_threshold_inclusive: -inf
upper_threshold_exclusive: 0.0
num_weighted_examples { value: 0.0 }
total_weighted_label { value: 0.0 }
total_weighted_refined_prediction { value: 0.0 }
}
buckets {
lower_threshold_inclusive: 0.0
upper_threshold_exclusive: 0.5
num_weighted_examples { value: 1.0 }
total_weighted_label { value: 1.0 }
total_weighted_refined_prediction { value: 0.3 }
}
buckets {
lower_threshold_inclusive: 0.5
upper_threshold_exclusive: 1.0
num_weighted_examples { value: 1.0 }
total_weighted_label { value: 0.0 }
total_weighted_refined_prediction { value: 0.7 }
}
buckets {
lower_threshold_inclusive: 1.0
upper_threshold_exclusive: inf
num_weighted_examples { value: 0.0 }
total_weighted_label { value: 0.0 }
total_weighted_refined_prediction { value: 0.0 }
}
}
}
}
""", metrics_for_slice_pb2.PlotsForSlice())
got = metrics_and_plots_serialization._serialize_plots(
(slice_key, {
plot_key: calibration_plot
}), None)
self.assertProtoEquals(
expected_plots_for_slice,
metrics_for_slice_pb2.PlotsForSlice.FromString(got))