azure.ai.anomalydetector.models package¶
-
class
azure.ai.anomalydetector.models.AlignPolicy(*, align_mode: Union[str, AlignMode, None] = None, fill_na_method: Union[str, FillNAMethod, None] = None, padding_value: Optional[int] = None, **kwargs)[source]¶ AlignPolicy.
- Parameters
align_mode (str or AlignMode) – An optional field, indicates how we align different variables into the same time-range which is required by the model.{Inner, Outer}. Possible values include: “Inner”, “Outer”.
fill_na_method (str or FillNAMethod) – An optional field, indicates how missed values will be filled with. Can not be set to NotFill, when alignMode is Outer.{Previous, Subsequent, Linear, Zero, Fix, NotFill}. Possible values include: “Previous”, “Subsequent”, “Linear”, “Zero”, “Pad”, “NotFill”.
padding_value (int) – optional field, only be useful if FillNAMethod is set to Pad.
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as_dict(keep_readonly=True, key_transformer=<function attribute_transformer>, **kwargs)¶ Return a dict that can be JSONify using json.dump.
Advanced usage might optionaly use a callback as parameter:
Key is the attribute name used in Python. Attr_desc is a dict of metadata. Currently contains ‘type’ with the msrest type and ‘key’ with the RestAPI encoded key. Value is the current value in this object.
The string returned will be used to serialize the key. If the return type is a list, this is considered hierarchical result dict.
See the three examples in this file:
attribute_transformer
full_restapi_key_transformer
last_restapi_key_transformer
If you want XML serialization, you can pass the kwargs is_xml=True.
- Parameters
key_transformer (function) – A key transformer function.
- Returns
A dict JSON compatible object
- Return type
-
classmethod
deserialize(data, content_type=None)¶ Parse a str using the RestAPI syntax and return a model.
-
classmethod
enable_additional_properties_sending()¶
-
classmethod
from_dict(data, key_extractors=None, content_type=None)¶ Parse a dict using given key extractor return a model.
By default consider key extractors (rest_key_case_insensitive_extractor, attribute_key_case_insensitive_extractor and last_rest_key_case_insensitive_extractor)
-
classmethod
is_xml_model()¶
-
serialize(keep_readonly=False, **kwargs)¶ Return the JSON that would be sent to azure from this model.
This is an alias to as_dict(full_restapi_key_transformer, keep_readonly=False).
If you want XML serialization, you can pass the kwargs is_xml=True.
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class
azure.ai.anomalydetector.models.AnomalyContributor(*, contribution_score: Optional[float] = None, variable: Optional[str] = None, **kwargs)[source]¶ AnomalyContributor.
- Parameters
-
as_dict(keep_readonly=True, key_transformer=<function attribute_transformer>, **kwargs)¶ Return a dict that can be JSONify using json.dump.
Advanced usage might optionaly use a callback as parameter:
Key is the attribute name used in Python. Attr_desc is a dict of metadata. Currently contains ‘type’ with the msrest type and ‘key’ with the RestAPI encoded key. Value is the current value in this object.
The string returned will be used to serialize the key. If the return type is a list, this is considered hierarchical result dict.
See the three examples in this file:
attribute_transformer
full_restapi_key_transformer
last_restapi_key_transformer
If you want XML serialization, you can pass the kwargs is_xml=True.
- Parameters
key_transformer (function) – A key transformer function.
- Returns
A dict JSON compatible object
- Return type
-
classmethod
deserialize(data, content_type=None)¶ Parse a str using the RestAPI syntax and return a model.
-
classmethod
enable_additional_properties_sending()¶
-
classmethod
from_dict(data, key_extractors=None, content_type=None)¶ Parse a dict using given key extractor return a model.
By default consider key extractors (rest_key_case_insensitive_extractor, attribute_key_case_insensitive_extractor and last_rest_key_case_insensitive_extractor)
-
classmethod
is_xml_model()¶
-
serialize(keep_readonly=False, **kwargs)¶ Return the JSON that would be sent to azure from this model.
This is an alias to as_dict(full_restapi_key_transformer, keep_readonly=False).
If you want XML serialization, you can pass the kwargs is_xml=True.
-
class
azure.ai.anomalydetector.models.AnomalyDetectorError(*, code: Union[str, AnomalyDetectorErrorCodes, None] = None, message: Optional[str] = None, **kwargs)[source]¶ Error information returned by the API.
- Parameters
code (str or AnomalyDetectorErrorCodes) – The error code. Possible values include: “InvalidCustomInterval”, “BadArgument”, “InvalidGranularity”, “InvalidPeriod”, “InvalidModelArgument”, “InvalidSeries”, “InvalidJsonFormat”, “RequiredGranularity”, “RequiredSeries”.
message (str) – A message explaining the error reported by the service.
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as_dict(keep_readonly=True, key_transformer=<function attribute_transformer>, **kwargs)¶ Return a dict that can be JSONify using json.dump.
Advanced usage might optionaly use a callback as parameter:
Key is the attribute name used in Python. Attr_desc is a dict of metadata. Currently contains ‘type’ with the msrest type and ‘key’ with the RestAPI encoded key. Value is the current value in this object.
The string returned will be used to serialize the key. If the return type is a list, this is considered hierarchical result dict.
See the three examples in this file:
attribute_transformer
full_restapi_key_transformer
last_restapi_key_transformer
If you want XML serialization, you can pass the kwargs is_xml=True.
- Parameters
key_transformer (function) – A key transformer function.
- Returns
A dict JSON compatible object
- Return type
-
classmethod
deserialize(data, content_type=None)¶ Parse a str using the RestAPI syntax and return a model.
-
classmethod
enable_additional_properties_sending()¶
-
classmethod
from_dict(data, key_extractors=None, content_type=None)¶ Parse a dict using given key extractor return a model.
By default consider key extractors (rest_key_case_insensitive_extractor, attribute_key_case_insensitive_extractor and last_rest_key_case_insensitive_extractor)
-
classmethod
is_xml_model()¶
-
serialize(keep_readonly=False, **kwargs)¶ Return the JSON that would be sent to azure from this model.
This is an alias to as_dict(full_restapi_key_transformer, keep_readonly=False).
If you want XML serialization, you can pass the kwargs is_xml=True.
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class
azure.ai.anomalydetector.models.AnomalyState(*, timestamp: datetime.datetime, value: Optional[AnomalyValue] = None, errors: Optional[List[ErrorResponse]] = None, **kwargs)[source]¶ AnomalyState.
All required parameters must be populated in order to send to Azure.
- Parameters
timestamp (datetime) – Required. timestamp.
value (AnomalyValue) –
errors (list[ErrorResponse]) – Error message when inference this timestamp.
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as_dict(keep_readonly=True, key_transformer=<function attribute_transformer>, **kwargs)¶ Return a dict that can be JSONify using json.dump.
Advanced usage might optionaly use a callback as parameter:
Key is the attribute name used in Python. Attr_desc is a dict of metadata. Currently contains ‘type’ with the msrest type and ‘key’ with the RestAPI encoded key. Value is the current value in this object.
The string returned will be used to serialize the key. If the return type is a list, this is considered hierarchical result dict.
See the three examples in this file:
attribute_transformer
full_restapi_key_transformer
last_restapi_key_transformer
If you want XML serialization, you can pass the kwargs is_xml=True.
- Parameters
key_transformer (function) – A key transformer function.
- Returns
A dict JSON compatible object
- Return type
-
classmethod
deserialize(data, content_type=None)¶ Parse a str using the RestAPI syntax and return a model.
-
classmethod
enable_additional_properties_sending()¶
-
classmethod
from_dict(data, key_extractors=None, content_type=None)¶ Parse a dict using given key extractor return a model.
By default consider key extractors (rest_key_case_insensitive_extractor, attribute_key_case_insensitive_extractor and last_rest_key_case_insensitive_extractor)
-
classmethod
is_xml_model()¶
-
serialize(keep_readonly=False, **kwargs)¶ Return the JSON that would be sent to azure from this model.
This is an alias to as_dict(full_restapi_key_transformer, keep_readonly=False).
If you want XML serialization, you can pass the kwargs is_xml=True.
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class
azure.ai.anomalydetector.models.AnomalyValue(*, is_anomaly: bool, severity: float, contributors: Optional[List[AnomalyContributor]] = None, score: Optional[float] = None, **kwargs)[source]¶ AnomalyValue.
All required parameters must be populated in order to send to Azure.
- Parameters
contributors (list[AnomalyContributor]) – If current timestamp is an anomaly, contributors will show potential root cause for thus anomaly. Contributors can help us understand why current timestamp has been detected as an anomaly.
is_anomaly (bool) – Required. To indicate whether current timestamp is anomaly or not.
severity (float) – Required. anomaly score of the current timestamp, the more significant an anomaly is, the higher the score will be.
score (float) – anomaly score of the current timestamp, the more significant an anomaly is, the higher the score will be, score measures global significance.
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as_dict(keep_readonly=True, key_transformer=<function attribute_transformer>, **kwargs)¶ Return a dict that can be JSONify using json.dump.
Advanced usage might optionaly use a callback as parameter:
Key is the attribute name used in Python. Attr_desc is a dict of metadata. Currently contains ‘type’ with the msrest type and ‘key’ with the RestAPI encoded key. Value is the current value in this object.
The string returned will be used to serialize the key. If the return type is a list, this is considered hierarchical result dict.
See the three examples in this file:
attribute_transformer
full_restapi_key_transformer
last_restapi_key_transformer
If you want XML serialization, you can pass the kwargs is_xml=True.
- Parameters
key_transformer (function) – A key transformer function.
- Returns
A dict JSON compatible object
- Return type
-
classmethod
deserialize(data, content_type=None)¶ Parse a str using the RestAPI syntax and return a model.
-
classmethod
enable_additional_properties_sending()¶
-
classmethod
from_dict(data, key_extractors=None, content_type=None)¶ Parse a dict using given key extractor return a model.
By default consider key extractors (rest_key_case_insensitive_extractor, attribute_key_case_insensitive_extractor and last_rest_key_case_insensitive_extractor)
-
classmethod
is_xml_model()¶
-
serialize(keep_readonly=False, **kwargs)¶ Return the JSON that would be sent to azure from this model.
This is an alias to as_dict(full_restapi_key_transformer, keep_readonly=False).
If you want XML serialization, you can pass the kwargs is_xml=True.
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class
azure.ai.anomalydetector.models.ChangePointDetectRequest(*, series: List[TimeSeriesPoint], granularity: Union[str, TimeGranularity], custom_interval: Optional[int] = None, period: Optional[int] = None, stable_trend_window: Optional[int] = None, threshold: Optional[float] = None, **kwargs)[source]¶ ChangePointDetectRequest.
All required parameters must be populated in order to send to Azure.
- Parameters
series (list[TimeSeriesPoint]) – Required. Time series data points. Points should be sorted by timestamp in ascending order to match the change point detection result.
granularity (str or TimeGranularity) – Required. Can only be one of yearly, monthly, weekly, daily, hourly, minutely or secondly. Granularity is used for verify whether input series is valid. Possible values include: “yearly”, “monthly”, “weekly”, “daily”, “hourly”, “minutely”, “secondly”, “microsecond”, “none”.
custom_interval (int) – Custom Interval is used to set non-standard time interval, for example, if the series is 5 minutes, request can be set as {“granularity”:”minutely”, “customInterval”:5}.
period (int) – Optional argument, periodic value of a time series. If the value is null or does not present, the API will determine the period automatically.
stable_trend_window (int) – Optional argument, advanced model parameter, a default stableTrendWindow will be used in detection.
threshold (float) – Optional argument, advanced model parameter, between 0.0-1.0, the lower the value is, the larger the trend error will be which means less change point will be accepted.
-
as_dict(keep_readonly=True, key_transformer=<function attribute_transformer>, **kwargs)¶ Return a dict that can be JSONify using json.dump.
Advanced usage might optionaly use a callback as parameter:
Key is the attribute name used in Python. Attr_desc is a dict of metadata. Currently contains ‘type’ with the msrest type and ‘key’ with the RestAPI encoded key. Value is the current value in this object.
The string returned will be used to serialize the key. If the return type is a list, this is considered hierarchical result dict.
See the three examples in this file:
attribute_transformer
full_restapi_key_transformer
last_restapi_key_transformer
If you want XML serialization, you can pass the kwargs is_xml=True.
- Parameters
key_transformer (function) – A key transformer function.
- Returns
A dict JSON compatible object
- Return type
-
classmethod
deserialize(data, content_type=None)¶ Parse a str using the RestAPI syntax and return a model.
-
classmethod
enable_additional_properties_sending()¶
-
classmethod
from_dict(data, key_extractors=None, content_type=None)¶ Parse a dict using given key extractor return a model.
By default consider key extractors (rest_key_case_insensitive_extractor, attribute_key_case_insensitive_extractor and last_rest_key_case_insensitive_extractor)
-
classmethod
is_xml_model()¶
-
serialize(keep_readonly=False, **kwargs)¶ Return the JSON that would be sent to azure from this model.
This is an alias to as_dict(full_restapi_key_transformer, keep_readonly=False).
If you want XML serialization, you can pass the kwargs is_xml=True.
-
class
azure.ai.anomalydetector.models.ChangePointDetectResponse(*, is_change_point: Optional[List[bool]] = None, confidence_scores: Optional[List[float]] = None, **kwargs)[source]¶ ChangePointDetectResponse.
Variables are only populated by the server, and will be ignored when sending a request.
- Variables
period (int) – Frequency extracted from the series, zero means no recurrent pattern has been found.
- Parameters
is_change_point (list[bool]) – isChangePoint contains change point properties for each input point. True means an anomaly either negative or positive has been detected. The index of the array is consistent with the input series.
confidence_scores (list[float]) – the change point confidence of each point.
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as_dict(keep_readonly=True, key_transformer=<function attribute_transformer>, **kwargs)¶ Return a dict that can be JSONify using json.dump.
Advanced usage might optionaly use a callback as parameter:
Key is the attribute name used in Python. Attr_desc is a dict of metadata. Currently contains ‘type’ with the msrest type and ‘key’ with the RestAPI encoded key. Value is the current value in this object.
The string returned will be used to serialize the key. If the return type is a list, this is considered hierarchical result dict.
See the three examples in this file:
attribute_transformer
full_restapi_key_transformer
last_restapi_key_transformer
If you want XML serialization, you can pass the kwargs is_xml=True.
- Parameters
key_transformer (function) – A key transformer function.
- Returns
A dict JSON compatible object
- Return type
-
classmethod
deserialize(data, content_type=None)¶ Parse a str using the RestAPI syntax and return a model.
-
classmethod
enable_additional_properties_sending()¶
-
classmethod
from_dict(data, key_extractors=None, content_type=None)¶ Parse a dict using given key extractor return a model.
By default consider key extractors (rest_key_case_insensitive_extractor, attribute_key_case_insensitive_extractor and last_rest_key_case_insensitive_extractor)
-
classmethod
is_xml_model()¶
-
serialize(keep_readonly=False, **kwargs)¶ Return the JSON that would be sent to azure from this model.
This is an alias to as_dict(full_restapi_key_transformer, keep_readonly=False).
If you want XML serialization, you can pass the kwargs is_xml=True.
-
class
azure.ai.anomalydetector.models.DetectRequest(*, series: List[TimeSeriesPoint], granularity: Union[str, TimeGranularity, None] = None, custom_interval: Optional[int] = None, period: Optional[int] = None, max_anomaly_ratio: Optional[float] = None, sensitivity: Optional[int] = None, **kwargs)[source]¶ DetectRequest.
All required parameters must be populated in order to send to Azure.
- Parameters
series (list[TimeSeriesPoint]) – Required. Time series data points. Points should be sorted by timestamp in ascending order to match the anomaly detection result. If the data is not sorted correctly or there is duplicated timestamp, the API will not work. In such case, an error message will be returned.
granularity (str or TimeGranularity) – Optional argument, can be one of yearly, monthly, weekly, daily, hourly, minutely, secondly, microsecond or none. If granularity is not present, it will be none by default. If granularity is none, the timestamp property in time series point can be absent. Possible values include: “yearly”, “monthly”, “weekly”, “daily”, “hourly”, “minutely”, “secondly”, “microsecond”, “none”.
custom_interval (int) – Custom Interval is used to set non-standard time interval, for example, if the series is 5 minutes, request can be set as {“granularity”:”minutely”, “customInterval”:5}.
period (int) – Optional argument, periodic value of a time series. If the value is null or does not present, the API will determine the period automatically.
max_anomaly_ratio (float) – Optional argument, advanced model parameter, max anomaly ratio in a time series.
sensitivity (int) – Optional argument, advanced model parameter, between 0-99, the lower the value is, the larger the margin value will be which means less anomalies will be accepted.
-
as_dict(keep_readonly=True, key_transformer=<function attribute_transformer>, **kwargs)¶ Return a dict that can be JSONify using json.dump.
Advanced usage might optionaly use a callback as parameter:
Key is the attribute name used in Python. Attr_desc is a dict of metadata. Currently contains ‘type’ with the msrest type and ‘key’ with the RestAPI encoded key. Value is the current value in this object.
The string returned will be used to serialize the key. If the return type is a list, this is considered hierarchical result dict.
See the three examples in this file:
attribute_transformer
full_restapi_key_transformer
last_restapi_key_transformer
If you want XML serialization, you can pass the kwargs is_xml=True.
- Parameters
key_transformer (function) – A key transformer function.
- Returns
A dict JSON compatible object
- Return type
-
classmethod
deserialize(data, content_type=None)¶ Parse a str using the RestAPI syntax and return a model.
-
classmethod
enable_additional_properties_sending()¶
-
classmethod
from_dict(data, key_extractors=None, content_type=None)¶ Parse a dict using given key extractor return a model.
By default consider key extractors (rest_key_case_insensitive_extractor, attribute_key_case_insensitive_extractor and last_rest_key_case_insensitive_extractor)
-
classmethod
is_xml_model()¶
-
serialize(keep_readonly=False, **kwargs)¶ Return the JSON that would be sent to azure from this model.
This is an alias to as_dict(full_restapi_key_transformer, keep_readonly=False).
If you want XML serialization, you can pass the kwargs is_xml=True.
-
class
azure.ai.anomalydetector.models.DetectionRequest(*, source: str, start_time: datetime.datetime, end_time: datetime.datetime, **kwargs)[source]¶ Request to submit a detection.
All required parameters must be populated in order to send to Azure.
- Parameters
source (str) – Required. source file link of the input variables, each variable will be a csv with two columns, the first column will be timestamp, the second column will be value.Besides these variable csv files, a extra meta.json can be included in th zip file if you would like to rename a variable.Be default, the file name of the variable will be used as the variable name. The variables used in detection should be consistent with variables in the model used for detection.
start_time (datetime) – Required. A require field, start time of data be used for detection, should be date-time.
end_time (datetime) – Required. A require field, end time of data be used for detection, should be date-time.
-
as_dict(keep_readonly=True, key_transformer=<function attribute_transformer>, **kwargs)¶ Return a dict that can be JSONify using json.dump.
Advanced usage might optionaly use a callback as parameter:
Key is the attribute name used in Python. Attr_desc is a dict of metadata. Currently contains ‘type’ with the msrest type and ‘key’ with the RestAPI encoded key. Value is the current value in this object.
The string returned will be used to serialize the key. If the return type is a list, this is considered hierarchical result dict.
See the three examples in this file:
attribute_transformer
full_restapi_key_transformer
last_restapi_key_transformer
If you want XML serialization, you can pass the kwargs is_xml=True.
- Parameters
key_transformer (function) – A key transformer function.
- Returns
A dict JSON compatible object
- Return type
-
classmethod
deserialize(data, content_type=None)¶ Parse a str using the RestAPI syntax and return a model.
-
classmethod
enable_additional_properties_sending()¶
-
classmethod
from_dict(data, key_extractors=None, content_type=None)¶ Parse a dict using given key extractor return a model.
By default consider key extractors (rest_key_case_insensitive_extractor, attribute_key_case_insensitive_extractor and last_rest_key_case_insensitive_extractor)
-
classmethod
is_xml_model()¶
-
serialize(keep_readonly=False, **kwargs)¶ Return the JSON that would be sent to azure from this model.
This is an alias to as_dict(full_restapi_key_transformer, keep_readonly=False).
If you want XML serialization, you can pass the kwargs is_xml=True.
-
class
azure.ai.anomalydetector.models.DetectionResult(*, result_id: str, summary: azure.ai.anomalydetector.models._models_py3.DetectionResultSummary, results: List[AnomalyState], **kwargs)[source]¶ Anomaly Response of one detection corresponds to a resultId.
All required parameters must be populated in order to send to Azure.
- Parameters
result_id (str) – Required.
summary (DetectionResultSummary) – Required. Multivariate anomaly detection status.
results (list[AnomalyState]) – Required. anomaly status of each timestamp.
-
as_dict(keep_readonly=True, key_transformer=<function attribute_transformer>, **kwargs)¶ Return a dict that can be JSONify using json.dump.
Advanced usage might optionaly use a callback as parameter:
Key is the attribute name used in Python. Attr_desc is a dict of metadata. Currently contains ‘type’ with the msrest type and ‘key’ with the RestAPI encoded key. Value is the current value in this object.
The string returned will be used to serialize the key. If the return type is a list, this is considered hierarchical result dict.
See the three examples in this file:
attribute_transformer
full_restapi_key_transformer
last_restapi_key_transformer
If you want XML serialization, you can pass the kwargs is_xml=True.
- Parameters
key_transformer (function) – A key transformer function.
- Returns
A dict JSON compatible object
- Return type
-
classmethod
deserialize(data, content_type=None)¶ Parse a str using the RestAPI syntax and return a model.
-
classmethod
enable_additional_properties_sending()¶
-
classmethod
from_dict(data, key_extractors=None, content_type=None)¶ Parse a dict using given key extractor return a model.
By default consider key extractors (rest_key_case_insensitive_extractor, attribute_key_case_insensitive_extractor and last_rest_key_case_insensitive_extractor)
-
classmethod
is_xml_model()¶
-
serialize(keep_readonly=False, **kwargs)¶ Return the JSON that would be sent to azure from this model.
This is an alias to as_dict(full_restapi_key_transformer, keep_readonly=False).
If you want XML serialization, you can pass the kwargs is_xml=True.
-
class
azure.ai.anomalydetector.models.DetectionResultSummary(*, status: Union[str, DetectionStatus], setup_info: azure.ai.anomalydetector.models._models_py3.DetectionRequest, errors: Optional[List[ErrorResponse]] = None, variable_states: Optional[List[VariableState]] = None, **kwargs)[source]¶ DetectionResultSummary.
All required parameters must be populated in order to send to Azure.
- Parameters
status (str or DetectionStatus) – Required. Multivariate anomaly detection status. Possible values include: “CREATED”, “RUNNING”, “READY”, “FAILED”.
errors (list[ErrorResponse]) – Error message when creating or training model fails.
variable_states (list[VariableState]) –
setup_info (DetectionRequest) – Required. Request when creating the model.
-
as_dict(keep_readonly=True, key_transformer=<function attribute_transformer>, **kwargs)¶ Return a dict that can be JSONify using json.dump.
Advanced usage might optionaly use a callback as parameter:
Key is the attribute name used in Python. Attr_desc is a dict of metadata. Currently contains ‘type’ with the msrest type and ‘key’ with the RestAPI encoded key. Value is the current value in this object.
The string returned will be used to serialize the key. If the return type is a list, this is considered hierarchical result dict.
See the three examples in this file:
attribute_transformer
full_restapi_key_transformer
last_restapi_key_transformer
If you want XML serialization, you can pass the kwargs is_xml=True.
- Parameters
key_transformer (function) – A key transformer function.
- Returns
A dict JSON compatible object
- Return type
-
classmethod
deserialize(data, content_type=None)¶ Parse a str using the RestAPI syntax and return a model.
-
classmethod
enable_additional_properties_sending()¶
-
classmethod
from_dict(data, key_extractors=None, content_type=None)¶ Parse a dict using given key extractor return a model.
By default consider key extractors (rest_key_case_insensitive_extractor, attribute_key_case_insensitive_extractor and last_rest_key_case_insensitive_extractor)
-
classmethod
is_xml_model()¶
-
serialize(keep_readonly=False, **kwargs)¶ Return the JSON that would be sent to azure from this model.
This is an alias to as_dict(full_restapi_key_transformer, keep_readonly=False).
If you want XML serialization, you can pass the kwargs is_xml=True.
-
class
azure.ai.anomalydetector.models.DiagnosticsInfo(*, model_state: Optional[ModelState] = None, variable_states: Optional[List[VariableState]] = None, **kwargs)[source]¶ DiagnosticsInfo.
- Parameters
model_state (ModelState) –
variable_states (list[VariableState]) –
-
as_dict(keep_readonly=True, key_transformer=<function attribute_transformer>, **kwargs)¶ Return a dict that can be JSONify using json.dump.
Advanced usage might optionaly use a callback as parameter:
Key is the attribute name used in Python. Attr_desc is a dict of metadata. Currently contains ‘type’ with the msrest type and ‘key’ with the RestAPI encoded key. Value is the current value in this object.
The string returned will be used to serialize the key. If the return type is a list, this is considered hierarchical result dict.
See the three examples in this file:
attribute_transformer
full_restapi_key_transformer
last_restapi_key_transformer
If you want XML serialization, you can pass the kwargs is_xml=True.
- Parameters
key_transformer (function) – A key transformer function.
- Returns
A dict JSON compatible object
- Return type
-
classmethod
deserialize(data, content_type=None)¶ Parse a str using the RestAPI syntax and return a model.
-
classmethod
enable_additional_properties_sending()¶
-
classmethod
from_dict(data, key_extractors=None, content_type=None)¶ Parse a dict using given key extractor return a model.
By default consider key extractors (rest_key_case_insensitive_extractor, attribute_key_case_insensitive_extractor and last_rest_key_case_insensitive_extractor)
-
classmethod
is_xml_model()¶
-
serialize(keep_readonly=False, **kwargs)¶ Return the JSON that would be sent to azure from this model.
This is an alias to as_dict(full_restapi_key_transformer, keep_readonly=False).
If you want XML serialization, you can pass the kwargs is_xml=True.
-
class
azure.ai.anomalydetector.models.EntireDetectResponse(*, period: int, expected_values: List[float], upper_margins: List[float], lower_margins: List[float], is_anomaly: List[bool], is_negative_anomaly: List[bool], is_positive_anomaly: List[bool], **kwargs)[source]¶ EntireDetectResponse.
All required parameters must be populated in order to send to Azure.
- Parameters
period (int) – Required. Frequency extracted from the series, zero means no recurrent pattern has been found.
expected_values (list[float]) – Required. ExpectedValues contain expected value for each input point. The index of the array is consistent with the input series.
upper_margins (list[float]) – Required. UpperMargins contain upper margin of each input point. UpperMargin is used to calculate upperBoundary, which equals to expectedValue + (100 - marginScale)*upperMargin. Anomalies in response can be filtered by upperBoundary and lowerBoundary. By adjusting marginScale value, less significant anomalies can be filtered in client side. The index of the array is consistent with the input series.
lower_margins (list[float]) – Required. LowerMargins contain lower margin of each input point. LowerMargin is used to calculate lowerBoundary, which equals to expectedValue - (100 - marginScale)*lowerMargin. Points between the boundary can be marked as normal ones in client side. The index of the array is consistent with the input series.
is_anomaly (list[bool]) – Required. IsAnomaly contains anomaly properties for each input point. True means an anomaly either negative or positive has been detected. The index of the array is consistent with the input series.
is_negative_anomaly (list[bool]) – Required. IsNegativeAnomaly contains anomaly status in negative direction for each input point. True means a negative anomaly has been detected. A negative anomaly means the point is detected as an anomaly and its real value is smaller than the expected one. The index of the array is consistent with the input series.
is_positive_anomaly (list[bool]) – Required. IsPositiveAnomaly contain anomaly status in positive direction for each input point. True means a positive anomaly has been detected. A positive anomaly means the point is detected as an anomaly and its real value is larger than the expected one. The index of the array is consistent with the input series.
-
as_dict(keep_readonly=True, key_transformer=<function attribute_transformer>, **kwargs)¶ Return a dict that can be JSONify using json.dump.
Advanced usage might optionaly use a callback as parameter:
Key is the attribute name used in Python. Attr_desc is a dict of metadata. Currently contains ‘type’ with the msrest type and ‘key’ with the RestAPI encoded key. Value is the current value in this object.
The string returned will be used to serialize the key. If the return type is a list, this is considered hierarchical result dict.
See the three examples in this file:
attribute_transformer
full_restapi_key_transformer
last_restapi_key_transformer
If you want XML serialization, you can pass the kwargs is_xml=True.
- Parameters
key_transformer (function) – A key transformer function.
- Returns
A dict JSON compatible object
- Return type
-
classmethod
deserialize(data, content_type=None)¶ Parse a str using the RestAPI syntax and return a model.
-
classmethod
enable_additional_properties_sending()¶
-
classmethod
from_dict(data, key_extractors=None, content_type=None)¶ Parse a dict using given key extractor return a model.
By default consider key extractors (rest_key_case_insensitive_extractor, attribute_key_case_insensitive_extractor and last_rest_key_case_insensitive_extractor)
-
classmethod
is_xml_model()¶
-
serialize(keep_readonly=False, **kwargs)¶ Return the JSON that would be sent to azure from this model.
This is an alias to as_dict(full_restapi_key_transformer, keep_readonly=False).
If you want XML serialization, you can pass the kwargs is_xml=True.
-
class
azure.ai.anomalydetector.models.ErrorResponse(*, code: str, message: str, **kwargs)[source]¶ ErrorResponse.
All required parameters must be populated in order to send to Azure.
- Parameters
-
as_dict(keep_readonly=True, key_transformer=<function attribute_transformer>, **kwargs)¶ Return a dict that can be JSONify using json.dump.
Advanced usage might optionaly use a callback as parameter:
Key is the attribute name used in Python. Attr_desc is a dict of metadata. Currently contains ‘type’ with the msrest type and ‘key’ with the RestAPI encoded key. Value is the current value in this object.
The string returned will be used to serialize the key. If the return type is a list, this is considered hierarchical result dict.
See the three examples in this file:
attribute_transformer
full_restapi_key_transformer
last_restapi_key_transformer
If you want XML serialization, you can pass the kwargs is_xml=True.
- Parameters
key_transformer (function) – A key transformer function.
- Returns
A dict JSON compatible object
- Return type
-
classmethod
deserialize(data, content_type=None)¶ Parse a str using the RestAPI syntax and return a model.
-
classmethod
enable_additional_properties_sending()¶
-
classmethod
from_dict(data, key_extractors=None, content_type=None)¶ Parse a dict using given key extractor return a model.
By default consider key extractors (rest_key_case_insensitive_extractor, attribute_key_case_insensitive_extractor and last_rest_key_case_insensitive_extractor)
-
classmethod
is_xml_model()¶
-
serialize(keep_readonly=False, **kwargs)¶ Return the JSON that would be sent to azure from this model.
This is an alias to as_dict(full_restapi_key_transformer, keep_readonly=False).
If you want XML serialization, you can pass the kwargs is_xml=True.
-
class
azure.ai.anomalydetector.models.LastDetectResponse(*, period: int, suggested_window: int, expected_value: float, upper_margin: float, lower_margin: float, is_anomaly: bool, is_negative_anomaly: bool, is_positive_anomaly: bool, **kwargs)[source]¶ LastDetectResponse.
All required parameters must be populated in order to send to Azure.
- Parameters
period (int) – Required. Frequency extracted from the series, zero means no recurrent pattern has been found.
suggested_window (int) – Required. Suggested input series points needed for detecting the latest point.
expected_value (float) – Required. Expected value of the latest point.
upper_margin (float) – Required. Upper margin of the latest point. UpperMargin is used to calculate upperBoundary, which equals to expectedValue + (100 - marginScale)*upperMargin. If the value of latest point is between upperBoundary and lowerBoundary, it should be treated as normal value. By adjusting marginScale value, anomaly status of latest point can be changed.
lower_margin (float) – Required. Lower margin of the latest point. LowerMargin is used to calculate lowerBoundary, which equals to expectedValue - (100 - marginScale)*lowerMargin.
is_anomaly (bool) – Required. Anomaly status of the latest point, true means the latest point is an anomaly either in negative direction or positive direction.
is_negative_anomaly (bool) – Required. Anomaly status in negative direction of the latest point. True means the latest point is an anomaly and its real value is smaller than the expected one.
is_positive_anomaly (bool) – Required. Anomaly status in positive direction of the latest point. True means the latest point is an anomaly and its real value is larger than the expected one.
-
as_dict(keep_readonly=True, key_transformer=<function attribute_transformer>, **kwargs)¶ Return a dict that can be JSONify using json.dump.
Advanced usage might optionaly use a callback as parameter:
Key is the attribute name used in Python. Attr_desc is a dict of metadata. Currently contains ‘type’ with the msrest type and ‘key’ with the RestAPI encoded key. Value is the current value in this object.
The string returned will be used to serialize the key. If the return type is a list, this is considered hierarchical result dict.
See the three examples in this file:
attribute_transformer
full_restapi_key_transformer
last_restapi_key_transformer
If you want XML serialization, you can pass the kwargs is_xml=True.
- Parameters
key_transformer (function) – A key transformer function.
- Returns
A dict JSON compatible object
- Return type
-
classmethod
deserialize(data, content_type=None)¶ Parse a str using the RestAPI syntax and return a model.
-
classmethod
enable_additional_properties_sending()¶
-
classmethod
from_dict(data, key_extractors=None, content_type=None)¶ Parse a dict using given key extractor return a model.
By default consider key extractors (rest_key_case_insensitive_extractor, attribute_key_case_insensitive_extractor and last_rest_key_case_insensitive_extractor)
-
classmethod
is_xml_model()¶
-
serialize(keep_readonly=False, **kwargs)¶ Return the JSON that would be sent to azure from this model.
This is an alias to as_dict(full_restapi_key_transformer, keep_readonly=False).
If you want XML serialization, you can pass the kwargs is_xml=True.
-
class
azure.ai.anomalydetector.models.Model(*, model_id: str, created_time: datetime.datetime, last_updated_time: datetime.datetime, model_info: Optional[ModelInfo] = None, **kwargs)[source]¶ Response of get model.
All required parameters must be populated in order to send to Azure.
- Parameters
-
as_dict(keep_readonly=True, key_transformer=<function attribute_transformer>, **kwargs)[source]¶ Return a dict that can be JSONify using json.dump.
Advanced usage might optionaly use a callback as parameter:
Key is the attribute name used in Python. Attr_desc is a dict of metadata. Currently contains ‘type’ with the msrest type and ‘key’ with the RestAPI encoded key. Value is the current value in this object.
The string returned will be used to serialize the key. If the return type is a list, this is considered hierarchical result dict.
See the three examples in this file:
attribute_transformer
full_restapi_key_transformer
last_restapi_key_transformer
If you want XML serialization, you can pass the kwargs is_xml=True.
- Parameters
key_transformer (function) – A key transformer function.
- Returns
A dict JSON compatible object
- Return type
-
classmethod
deserialize(data, content_type=None)[source]¶ Parse a str using the RestAPI syntax and return a model.
-
classmethod
from_dict(data, key_extractors=None, content_type=None)[source]¶ Parse a dict using given key extractor return a model.
By default consider key extractors (rest_key_case_insensitive_extractor, attribute_key_case_insensitive_extractor and last_rest_key_case_insensitive_extractor)
-
class
azure.ai.anomalydetector.models.ModelInfo(*, source: str, start_time: datetime.datetime, end_time: datetime.datetime, sliding_window: Optional[int] = None, align_policy: Optional[AlignPolicy] = None, display_name: Optional[str] = None, **kwargs)[source]¶ Train result of a model including status, errors and diagnose info for model and variables.
Variables are only populated by the server, and will be ignored when sending a request.
All required parameters must be populated in order to send to Azure.
- Parameters
sliding_window (int) – An optional field, indicates how many history points will be used to determine the anomaly score of one subsequent point.
align_policy (AlignPolicy) – An optional field, since those multivariate need to be aligned in the same timestamp before starting the detection.
source (str) – Required. source file link of the input variables, each variable will be a csv with two columns, the first column will be timestamp, the second column will be value.Besides these variable csv files, an extra meta.json can be included in th zip file if you would like to rename a variable.Be default, the file name of the variable will be used as the variable name.
start_time (datetime) – Required. require field, start time of data be used for generating multivariate anomaly detection model, should be data-time.
end_time (datetime) – Required. require field, end time of data be used for generating multivariate anomaly detection model, should be data-time.
display_name (str) – optional field, name of the model.
- Variables
status (str or ModelStatus) – Model training status. Possible values include: “CREATED”, “RUNNING”, “READY”, “FAILED”.
errors (list[ErrorResponse]) – Error message when fails to create a model.
diagnostics_info (DiagnosticsInfo) – Used for deep analysis model and variables.
-
as_dict(keep_readonly=True, key_transformer=<function attribute_transformer>, **kwargs)¶ Return a dict that can be JSONify using json.dump.
Advanced usage might optionaly use a callback as parameter:
Key is the attribute name used in Python. Attr_desc is a dict of metadata. Currently contains ‘type’ with the msrest type and ‘key’ with the RestAPI encoded key. Value is the current value in this object.
The string returned will be used to serialize the key. If the return type is a list, this is considered hierarchical result dict.
See the three examples in this file:
attribute_transformer
full_restapi_key_transformer
last_restapi_key_transformer
If you want XML serialization, you can pass the kwargs is_xml=True.
- Parameters
key_transformer (function) – A key transformer function.
- Returns
A dict JSON compatible object
- Return type
-
classmethod
deserialize(data, content_type=None)¶ Parse a str using the RestAPI syntax and return a model.
-
classmethod
enable_additional_properties_sending()¶
-
classmethod
from_dict(data, key_extractors=None, content_type=None)¶ Parse a dict using given key extractor return a model.
By default consider key extractors (rest_key_case_insensitive_extractor, attribute_key_case_insensitive_extractor and last_rest_key_case_insensitive_extractor)
-
classmethod
is_xml_model()¶
-
serialize(keep_readonly=False, **kwargs)¶ Return the JSON that would be sent to azure from this model.
This is an alias to as_dict(full_restapi_key_transformer, keep_readonly=False).
If you want XML serialization, you can pass the kwargs is_xml=True.
-
class
azure.ai.anomalydetector.models.ModelList(*, models: List[ModelSnapshot], current_count: int, max_count: int, next_link: Optional[str] = None, **kwargs)[source]¶ Response to the list models operation.
All required parameters must be populated in order to send to Azure.
- Parameters
models (list[ModelSnapshot]) – Required. List of models.
current_count (int) – Required. Current count of trained multivariate models.
max_count (int) – Required. Max number of models that can be trained for this subscription.
next_link (str) – next link to fetch more models.
-
as_dict(keep_readonly=True, key_transformer=<function attribute_transformer>, **kwargs)¶ Return a dict that can be JSONify using json.dump.
Advanced usage might optionaly use a callback as parameter:
Key is the attribute name used in Python. Attr_desc is a dict of metadata. Currently contains ‘type’ with the msrest type and ‘key’ with the RestAPI encoded key. Value is the current value in this object.
The string returned will be used to serialize the key. If the return type is a list, this is considered hierarchical result dict.
See the three examples in this file:
attribute_transformer
full_restapi_key_transformer
last_restapi_key_transformer
If you want XML serialization, you can pass the kwargs is_xml=True.
- Parameters
key_transformer (function) – A key transformer function.
- Returns
A dict JSON compatible object
- Return type
-
classmethod
deserialize(data, content_type=None)¶ Parse a str using the RestAPI syntax and return a model.
-
classmethod
enable_additional_properties_sending()¶
-
classmethod
from_dict(data, key_extractors=None, content_type=None)¶ Parse a dict using given key extractor return a model.
By default consider key extractors (rest_key_case_insensitive_extractor, attribute_key_case_insensitive_extractor and last_rest_key_case_insensitive_extractor)
-
classmethod
is_xml_model()¶
-
serialize(keep_readonly=False, **kwargs)¶ Return the JSON that would be sent to azure from this model.
This is an alias to as_dict(full_restapi_key_transformer, keep_readonly=False).
If you want XML serialization, you can pass the kwargs is_xml=True.
-
class
azure.ai.anomalydetector.models.ModelSnapshot(*, model_id: str, created_time: datetime.datetime, last_updated_time: datetime.datetime, variables_count: int, display_name: Optional[str] = None, **kwargs)[source]¶ ModelSnapshot.
Variables are only populated by the server, and will be ignored when sending a request.
All required parameters must be populated in order to send to Azure.
- Parameters
- Variables
status (str or ModelStatus) – Required. Model training status. Possible values include: “CREATED”, “RUNNING”, “READY”, “FAILED”.
-
as_dict(keep_readonly=True, key_transformer=<function attribute_transformer>, **kwargs)¶ Return a dict that can be JSONify using json.dump.
Advanced usage might optionaly use a callback as parameter:
Key is the attribute name used in Python. Attr_desc is a dict of metadata. Currently contains ‘type’ with the msrest type and ‘key’ with the RestAPI encoded key. Value is the current value in this object.
The string returned will be used to serialize the key. If the return type is a list, this is considered hierarchical result dict.
See the three examples in this file:
attribute_transformer
full_restapi_key_transformer
last_restapi_key_transformer
If you want XML serialization, you can pass the kwargs is_xml=True.
- Parameters
key_transformer (function) – A key transformer function.
- Returns
A dict JSON compatible object
- Return type
-
classmethod
deserialize(data, content_type=None)¶ Parse a str using the RestAPI syntax and return a model.
-
classmethod
enable_additional_properties_sending()¶
-
classmethod
from_dict(data, key_extractors=None, content_type=None)¶ Parse a dict using given key extractor return a model.
By default consider key extractors (rest_key_case_insensitive_extractor, attribute_key_case_insensitive_extractor and last_rest_key_case_insensitive_extractor)
-
classmethod
is_xml_model()¶
-
serialize(keep_readonly=False, **kwargs)¶ Return the JSON that would be sent to azure from this model.
This is an alias to as_dict(full_restapi_key_transformer, keep_readonly=False).
If you want XML serialization, you can pass the kwargs is_xml=True.
-
class
azure.ai.anomalydetector.models.ModelState(*, epoch_ids: Optional[List[int]] = None, train_losses: Optional[List[float]] = None, validation_losses: Optional[List[float]] = None, latencies_in_seconds: Optional[List[float]] = None, **kwargs)[source]¶ ModelState.
- Parameters
-
as_dict(keep_readonly=True, key_transformer=<function attribute_transformer>, **kwargs)¶ Return a dict that can be JSONify using json.dump.
Advanced usage might optionaly use a callback as parameter:
Key is the attribute name used in Python. Attr_desc is a dict of metadata. Currently contains ‘type’ with the msrest type and ‘key’ with the RestAPI encoded key. Value is the current value in this object.
The string returned will be used to serialize the key. If the return type is a list, this is considered hierarchical result dict.
See the three examples in this file:
attribute_transformer
full_restapi_key_transformer
last_restapi_key_transformer
If you want XML serialization, you can pass the kwargs is_xml=True.
- Parameters
key_transformer (function) – A key transformer function.
- Returns
A dict JSON compatible object
- Return type
-
classmethod
deserialize(data, content_type=None)¶ Parse a str using the RestAPI syntax and return a model.
-
classmethod
enable_additional_properties_sending()¶
-
classmethod
from_dict(data, key_extractors=None, content_type=None)¶ Parse a dict using given key extractor return a model.
By default consider key extractors (rest_key_case_insensitive_extractor, attribute_key_case_insensitive_extractor and last_rest_key_case_insensitive_extractor)
-
classmethod
is_xml_model()¶
-
serialize(keep_readonly=False, **kwargs)¶ Return the JSON that would be sent to azure from this model.
This is an alias to as_dict(full_restapi_key_transformer, keep_readonly=False).
If you want XML serialization, you can pass the kwargs is_xml=True.
-
class
azure.ai.anomalydetector.models.TimeSeriesPoint(*, value: float, timestamp: Optional[datetime.datetime] = None, **kwargs)[source]¶ TimeSeriesPoint.
All required parameters must be populated in order to send to Azure.
- Parameters
-
as_dict(keep_readonly=True, key_transformer=<function attribute_transformer>, **kwargs)¶ Return a dict that can be JSONify using json.dump.
Advanced usage might optionaly use a callback as parameter:
Key is the attribute name used in Python. Attr_desc is a dict of metadata. Currently contains ‘type’ with the msrest type and ‘key’ with the RestAPI encoded key. Value is the current value in this object.
The string returned will be used to serialize the key. If the return type is a list, this is considered hierarchical result dict.
See the three examples in this file:
attribute_transformer
full_restapi_key_transformer
last_restapi_key_transformer
If you want XML serialization, you can pass the kwargs is_xml=True.
- Parameters
key_transformer (function) – A key transformer function.
- Returns
A dict JSON compatible object
- Return type
-
classmethod
deserialize(data, content_type=None)¶ Parse a str using the RestAPI syntax and return a model.
-
classmethod
enable_additional_properties_sending()¶
-
classmethod
from_dict(data, key_extractors=None, content_type=None)¶ Parse a dict using given key extractor return a model.
By default consider key extractors (rest_key_case_insensitive_extractor, attribute_key_case_insensitive_extractor and last_rest_key_case_insensitive_extractor)
-
classmethod
is_xml_model()¶
-
serialize(keep_readonly=False, **kwargs)¶ Return the JSON that would be sent to azure from this model.
This is an alias to as_dict(full_restapi_key_transformer, keep_readonly=False).
If you want XML serialization, you can pass the kwargs is_xml=True.
-
class
azure.ai.anomalydetector.models.VariableState(*, variable: Optional[str] = None, filled_na_ratio: Optional[float] = None, effective_count: Optional[int] = None, start_time: Optional[datetime.datetime] = None, end_time: Optional[datetime.datetime] = None, errors: Optional[List[ErrorResponse]] = None, **kwargs)[source]¶ VariableState.
- Parameters
variable (str) – Variable name.
filled_na_ratio (float) – Merged NA ratio of a variable.
effective_count (int) – Effective time-series points count.
start_time (datetime) – Start time of a variable.
end_time (datetime) – End time of a variable.
errors (list[ErrorResponse]) – Error message when parse variable.
-
as_dict(keep_readonly=True, key_transformer=<function attribute_transformer>, **kwargs)¶ Return a dict that can be JSONify using json.dump.
Advanced usage might optionaly use a callback as parameter:
Key is the attribute name used in Python. Attr_desc is a dict of metadata. Currently contains ‘type’ with the msrest type and ‘key’ with the RestAPI encoded key. Value is the current value in this object.
The string returned will be used to serialize the key. If the return type is a list, this is considered hierarchical result dict.
See the three examples in this file:
attribute_transformer
full_restapi_key_transformer
last_restapi_key_transformer
If you want XML serialization, you can pass the kwargs is_xml=True.
- Parameters
key_transformer (function) – A key transformer function.
- Returns
A dict JSON compatible object
- Return type
-
classmethod
deserialize(data, content_type=None)¶ Parse a str using the RestAPI syntax and return a model.
-
classmethod
enable_additional_properties_sending()¶
-
classmethod
from_dict(data, key_extractors=None, content_type=None)¶ Parse a dict using given key extractor return a model.
By default consider key extractors (rest_key_case_insensitive_extractor, attribute_key_case_insensitive_extractor and last_rest_key_case_insensitive_extractor)
-
classmethod
is_xml_model()¶
-
serialize(keep_readonly=False, **kwargs)¶ Return the JSON that would be sent to azure from this model.
This is an alias to as_dict(full_restapi_key_transformer, keep_readonly=False).
If you want XML serialization, you can pass the kwargs is_xml=True.
-
class
azure.ai.anomalydetector.models.AlignMode[source]¶ An optional field, indicates how we align different variables into the same time-range which is required by the model.{Inner, Outer}
-
INNER= 'Inner'¶
-
OUTER= 'Outer'¶
-
-
class
azure.ai.anomalydetector.models.AnomalyDetectorErrorCodes[source]¶ The error code.
-
BAD_ARGUMENT= 'BadArgument'¶
-
INVALID_CUSTOM_INTERVAL= 'InvalidCustomInterval'¶
-
INVALID_GRANULARITY= 'InvalidGranularity'¶
-
INVALID_JSON_FORMAT= 'InvalidJsonFormat'¶
-
INVALID_MODEL_ARGUMENT= 'InvalidModelArgument'¶
-
INVALID_PERIOD= 'InvalidPeriod'¶
-
INVALID_SERIES= 'InvalidSeries'¶
-
REQUIRED_GRANULARITY= 'RequiredGranularity'¶
-
REQUIRED_SERIES= 'RequiredSeries'¶
-
-
class
azure.ai.anomalydetector.models.DetectionStatus[source]¶ Multivariate anomaly detection status
-
CREATED= 'CREATED'¶
-
FAILED= 'FAILED'¶
-
READY= 'READY'¶
-
RUNNING= 'RUNNING'¶
-
-
class
azure.ai.anomalydetector.models.FillNAMethod[source]¶ An optional field, indicates how missed values will be filled with. Can not be set to NotFill, when alignMode is Outer.{Previous, Subsequent, Linear, Zero, Fix, NotFill}
-
LINEAR= 'Linear'¶
-
NOT_FILL= 'NotFill'¶
-
PAD= 'Pad'¶
-
PREVIOUS= 'Previous'¶
-
SUBSEQUENT= 'Subsequent'¶
-
ZERO= 'Zero'¶
-
-
class
azure.ai.anomalydetector.models.ModelStatus[source]¶ Model training status.
-
CREATED= 'CREATED'¶
-
FAILED= 'FAILED'¶
-
READY= 'READY'¶
-
RUNNING= 'RUNNING'¶
-
-
class
azure.ai.anomalydetector.models.TimeGranularity[source]¶ Optional argument, can be one of yearly, monthly, weekly, daily, hourly, minutely, secondly, microsecond or none. If granularity is not present, it will be none by default. If granularity is none, the timestamp property in time series point can be absent.
-
DAILY= 'daily'¶
-
HOURLY= 'hourly'¶
-
MICROSECOND= 'microsecond'¶
-
MONTHLY= 'monthly'¶
-
NONE= 'none'¶
-
PER_MINUTE= 'minutely'¶
-
PER_SECOND= 'secondly'¶
-
WEEKLY= 'weekly'¶
-
YEARLY= 'yearly'¶
-