diff options
Diffstat (limited to 'resources/tools/presentation/generator_CPTA.py')
| -rw-r--r-- | resources/tools/presentation/generator_CPTA.py | 16 |
1 files changed, 9 insertions, 7 deletions
diff --git a/resources/tools/presentation/generator_CPTA.py b/resources/tools/presentation/generator_CPTA.py index 3a8ea93e0a..066bfbddc8 100644 --- a/resources/tools/presentation/generator_CPTA.py +++ b/resources/tools/presentation/generator_CPTA.py @@ -164,19 +164,21 @@ def _evaluate_results(in_data, trimmed_data, window=10): if len(in_data) > 2: win_size = in_data.size if in_data.size < window else window - results = [0.0, ] * win_size + results = [0.0, ] median = in_data.rolling(window=win_size).median() stdev_t = trimmed_data.rolling(window=win_size, min_periods=2).std() m_vals = median.values s_vals = stdev_t.values d_vals = in_data.values - for day in range(win_size, in_data.size): - if np.isnan(m_vals[day - 1]) or np.isnan(s_vals[day - 1]): + for day in range(1, in_data.size): + if np.isnan(m_vals[day]) \ + or np.isnan(s_vals[day]) \ + or np.isnan(d_vals[day]): results.append(0.0) - elif d_vals[day] < (m_vals[day - 1] - 3 * s_vals[day - 1]): + elif d_vals[day] < (m_vals[day] - 3 * s_vals[day]): results.append(0.33) - elif (m_vals[day - 1] - 3 * s_vals[day - 1]) <= d_vals[day] <= \ - (m_vals[day - 1] + 3 * s_vals[day - 1]): + elif (m_vals[day] - 3 * s_vals[day]) <= d_vals[day] <= \ + (m_vals[day] + 3 * s_vals[day]): results.append(0.66) else: results.append(1.0) @@ -244,7 +246,7 @@ def _generate_trending_traces(in_data, build_info, period, moving_win_size=10, data_y = [val for val in in_data.values()] data_pd = pd.Series(data_y, index=data_x) - t_data, outliers = find_outliers(data_pd) + t_data, outliers = find_outliers(data_pd, outlier_const=1.5) results = _evaluate_results(data_pd, t_data, window=moving_win_size) |