def get_multiline_stat_object(name, list_value, labels=None):
"""
Create multiline object from list of values. It outputs mulitline from values and legends is index of the values - i.e. 0, 1, ..
:param name: Name of stat
:param list_value: list of values to embed in multiline value.
:return: MLOps Multiline Value object, timeseries stat category
"""
if isinstance(list_value, list) or isinstance(list_value, np.ndarray):
category = StatCategory.TIME_SERIES
# if labels are not provided then it will be 0, 1, .. length of list - 1
if labels is None:
labels = range(len(list_value))
labels = list(map(lambda x: str(x).strip(), labels))
if (len(labels) == len(list_value)):
multiline_object = MultiLineGraph() \
.name(name) \
.labels(labels)
multiline_object.data(list(list_value))
return multiline_object, category
else:
raise MLOpsStatisticsException(
"size of labels associated with list of values to get does not match. {}!={}"
.format(len(labels), len(list_value)))
else:
raise MLOpsStatisticsException(
"list_value has to be of type list or nd array but got {}".
format(type(list_value)))
def _set_classification_stat(self, name, data, model_id, timestamp,
**kwargs):
mlops_stat_object = None
category = StatCategory.TIME_SERIES
self._logger.debug(
"{} predefined stat called: name: {} data_type: {}".format(
Constants.OFFICIAL_NAME, name, type(data)))
mlops_stat_object, category = \
ClassificationStatObjectFactory.get_stat_object(name, data=data, **kwargs)
if mlops_stat_object is not None:
self.set_stat(
name=name,
data=mlops_stat_object,
model_id=model_id,
# type of stat will be time series by default
category=category,
timestamp=timestamp,
**kwargs)
else:
error = "{} predefined stat cannot be output as error happened in creating mlops stat object from {}" \
.format(name, data)
raise MLOpsStatisticsException(error)
def get_mlops_classification_report_stat_object(**kwargs):
"""
Method creates MLOps table value stat object from classification report string.
It is not recommended to access this method without understanding single value data structure that it is returning.
:param kwargs: classification report string.
:return: Table Value stat object which has classification report embedded inside
"""
cr = kwargs.get('data', None)
if cr is not None:
if isinstance(cr, string_types):
try:
array_report = list()
for row in cr.split("\n"):
parsed_row = [x for x in row.split(" ") if len(x) > 0]
if len(parsed_row) > 0:
array_report.append(parsed_row)
first_header_should_be = [
'precision', 'recall', 'f1-score', 'support'
]
table_object, category = MLStatObjectCreator \
.get_table_value_stat_object(name=ClassificationMetrics.CLASSIFICATION_REPORT.value,
list_2d=array_report,
match_header_pattern=first_header_should_be)
return table_object, category
except Exception as e:
raise MLOpsStatisticsException(
"error happened while outputting classification report as table. Got classification string {}.\n error: {}"
.format(cr, e))
else:
raise MLOpsStatisticsException(
"type of classification should be of string, but received {}"
.format(type(cr)))
else:
raise MLOpsStatisticsException \
("cr object for outputting classification report cannot be None.")