From 4b0df8e7baea755e2e1a1c27a7707fb0a3f28b6e Mon Sep 17 00:00:00 2001 From: Tibor Frank Date: Mon, 25 Jun 2018 12:48:43 +0200 Subject: CSIT-1124: Support multi-sample tests + Store parsed MRR results as AvgStdevMetadata + Modify tables and plots to use AvgStdevMetadata Change-Id: I29bb1e492a664544e63a180055f66bb0eecfb957 Signed-off-by: Tibor Frank --- resources/tools/presentation/utils.py | 8 ++++---- 1 file changed, 4 insertions(+), 4 deletions(-) (limited to 'resources/tools/presentation/utils.py') diff --git a/resources/tools/presentation/utils.py b/resources/tools/presentation/utils.py index a2aa0dc071..2cc85c24d1 100644 --- a/resources/tools/presentation/utils.py +++ b/resources/tools/presentation/utils.py @@ -217,13 +217,13 @@ def classify_anomalies(data): the first value of changed average as a regression, or a progression. :param data: Full data set with unavailable samples replaced by nan. - :type data: pandas.Series + :type data: OrderedDict :returns: Classification and trend values :rtype: 2-tuple, list of strings and list of floats """ # Nan mean something went wrong. # Use 0.0 to cause that being reported as a severe regression. - bare_data = [0.0 if np.isnan(sample) else sample + bare_data = [0.0 if np.isnan(sample.avg) else sample for _, sample in data.iteritems()] # TODO: Put analogous iterator into jumpavg library. groups = BitCountingClassifier().classify(bare_data) @@ -234,9 +234,9 @@ def classify_anomalies(data): values_left = 0 avg = 0.0 for _, sample in data.iteritems(): - if np.isnan(sample): + if np.isnan(sample.avg): classification.append("outlier") - avgs.append(sample) + avgs.append(sample.avg) continue if values_left < 1 or active_group is None: values_left = 0 -- cgit 1.2.3-korg