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style(detect): add code annotation

This commit is contained in:
lxd1190 2018-11-09 15:55:49 +08:00
parent a9348864e0
commit 3c46aa7282
1 changed files with 20 additions and 4 deletions
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24
time_series_detector/detect.py
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@ -61,9 +61,18 @@ class Detect(object):
def value_predict(self, data):
"""
Predict the data
Predict if the latest value is an outlier or not.
:param data: the time series to detect of
:param data: The attributes are:
'window', the length of window,
'taskId', the id of detect model,
'dataC', a piece of data to learn,
'dataB', a piece of data to learn,
'dataA', a piece of data to learn and the latest value to be detected.
:type data: Dictionary-like object
:return: The attributes are:
'p', the class probability,
'ret', the result of detect(1 denotes normal, 0 denotes abnormal).
"""
ret_code, ret_data = self.__check_param(data)
if ret_code != TSD_OP_SUCCESS:
@ -94,9 +103,16 @@ class Detect(object):
def rate_predict(self, data):
"""
Predict the data
Predict if the latest value is an outlier or not.
:param data: the time series to detect of
:param data: The attributes are:
'dataC', a piece of data to learn,
'dataB', a piece of data to learn,
'dataA', a piece of data to learn and the latest value to be detected.
:type data: Dictionary-like object
:return: The attributes are:
'p', the class probability,
'ret', the result of detect(1 denotes normal, 0 denotes abnormal).
"""
combined_data = data["dataC"] + "," + data["dataB"] + "," + data["dataA"]
time_series = map(float, combined_data.split(','))