diff options
Diffstat (limited to 'resources/tools/presentation/generator_CPTA.py')
| -rw-r--r-- | resources/tools/presentation/generator_CPTA.py | 74 |
1 files changed, 33 insertions, 41 deletions
diff --git a/resources/tools/presentation/generator_CPTA.py b/resources/tools/presentation/generator_CPTA.py index 40fed8be78..d4ac06d09f 100644 --- a/resources/tools/presentation/generator_CPTA.py +++ b/resources/tools/presentation/generator_CPTA.py @@ -27,7 +27,7 @@ import pandas as pd from collections import OrderedDict from datetime import datetime -from utils import split_outliers, archive_input_data, execute_command,\ +from utils import archive_input_data, execute_command, \ classify_anomalies, Worker @@ -87,24 +87,22 @@ def generate_cpta(spec, data): return ret_code -def _generate_trending_traces(in_data, job_name, build_info, moving_win_size=10, +def _generate_trending_traces(in_data, job_name, build_info, show_trend_line=True, name="", color=""): """Generate the trending traces: - samples, - - trimmed moving median (trending line) - outliers, regress, progress + - average of normal samples (trending line) :param in_data: Full data set. :param job_name: The name of job which generated the data. :param build_info: Information about the builds. - :param moving_win_size: Window size. :param show_trend_line: Show moving median (trending plot). :param name: Name of the plot :param color: Name of the color for the plot. :type in_data: OrderedDict :type job_name: str :type build_info: dict - :type moving_win_size: int :type show_trend_line: bool :type name: str :type color: str @@ -132,16 +130,14 @@ def _generate_trending_traces(in_data, job_name, build_info, moving_win_size=10, data_pd = pd.Series(data_y, index=xaxis) - t_data, outliers = split_outliers(data_pd, outlier_const=1.5, - window=moving_win_size) - anomaly_classification = classify_anomalies(t_data, window=moving_win_size) + anomaly_classification, avgs = classify_anomalies(data_pd) anomalies = pd.Series() anomalies_colors = list() + anomalies_avgs = list() anomaly_color = { - "outlier": 0.0, - "regression": 0.33, - "normal": 0.66, + "regression": 0.0, + "normal": 0.5, "progression": 1.0 } if anomaly_classification: @@ -152,7 +148,8 @@ def _generate_trending_traces(in_data, job_name, build_info, moving_win_size=10, index=[item[0], ])) anomalies_colors.append( anomaly_color[anomaly_classification[idx]]) - anomalies_colors.extend([0.0, 0.33, 0.66, 1.0]) + anomalies_avgs.append(avgs[idx]) + anomalies_colors.extend([0.0, 0.5, 1.0]) # Create traces @@ -176,9 +173,25 @@ def _generate_trending_traces(in_data, job_name, build_info, moving_win_size=10, ) traces = [trace_samples, ] + if show_trend_line: + trace_trend = plgo.Scatter( + x=xaxis, + y=avgs, + mode='lines', + line={ + "shape": "linear", + "width": 1, + "color": color, + }, + showlegend=False, + legendgroup=name, + name='{name}-trend'.format(name=name) + ) + traces.append(trace_trend) + trace_anomalies = plgo.Scatter( x=anomalies.keys(), - y=anomalies.values, + y=anomalies_avgs, mode='markers', hoverinfo="none", showlegend=False, @@ -188,13 +201,11 @@ def _generate_trending_traces(in_data, job_name, build_info, moving_win_size=10, "size": 15, "symbol": "circle-open", "color": anomalies_colors, - "colorscale": [[0.00, "grey"], - [0.25, "grey"], - [0.25, "red"], - [0.50, "red"], - [0.50, "white"], - [0.75, "white"], - [0.75, "green"], + "colorscale": [[0.00, "red"], + [0.33, "red"], + [0.33, "white"], + [0.66, "white"], + [0.66, "green"], [1.00, "green"]], "showscale": True, "line": { @@ -209,8 +220,8 @@ def _generate_trending_traces(in_data, job_name, build_info, moving_win_size=10, "size": 14 }, "tickmode": 'array', - "tickvals": [0.125, 0.375, 0.625, 0.875], - "ticktext": ["Outlier", "Regression", "Normal", "Progression"], + "tickvals": [0.167, 0.500, 0.833], + "ticktext": ["Regression", "Normal", "Progression"], "ticks": "", "ticklen": 0, "tickangle": -90, @@ -220,24 +231,6 @@ def _generate_trending_traces(in_data, job_name, build_info, moving_win_size=10, ) traces.append(trace_anomalies) - if show_trend_line: - data_trend = t_data.rolling(window=moving_win_size, - min_periods=2).median() - trace_trend = plgo.Scatter( - x=data_trend.keys(), - y=data_trend.tolist(), - mode='lines', - line={ - "shape": "spline", - "width": 1, - "color": color, - }, - showlegend=False, - legendgroup=name, - name='{name}-trend'.format(name=name) - ) - traces.append(trace_trend) - if anomaly_classification: return traces, anomaly_classification[-1] else: @@ -312,7 +305,6 @@ def _generate_all_charts(spec, input_data): test_data, job_name=job_name, build_info=build_info, - moving_win_size=win_size, name='-'.join(test_name.split('-')[3:-1]), color=COLORS[index]) traces.extend(trace) |