import pandas as pd
from collections import OrderedDict
-from utils import find_outliers, archive_input_data, execute_command
+from utils import split_outliers, archive_input_data, execute_command
# Command to build the html format of the report
data_pd = pd.Series(data_y, index=data_x)
- t_data, outliers = find_outliers(data_pd, outlier_const=1.5)
+ t_data, outliers = split_outliers(data_pd, outlier_const=1.5,
+ window=moving_win_size)
results = _evaluate_results(data_pd, t_data, window=moving_win_size)
anomalies = pd.Series()
y=anomalies.values,
mode='markers',
hoverinfo="none",
- showlegend=False,
+ showlegend=True,
legendgroup=name,
name="{name}: outliers".format(name=name),
marker={