def build_ui(cls):
# define arguments that behave as function inputs
inputs = []
inputs.append(UISingleItem(
name='input_item1',
datatype=str,
description='String encoded array of sensor readings'
))
inputs.append(UISingleItem(
name='input_item2',
datatype=str,
description='String encoded array of sensor readings'
))
inputs.append(UISingleItem(
name='input_item3',
datatype=str,
description='String encoded array of sensor readings'
))
# define arguments that behave as function outputs
outputs = []
outputs.append(UIFunctionOutSingle(
name='output_item',
datatype=float,
description='L2 norm of the string encoded sensor readings'
))
return (inputs, outputs)
def build_ui(cls):
#define arguments that behave as function inputs
inputs = []
inputs.append(
UIMultiItem(name='feature', datatype=float, required=True))
inputs.append(
UISingleItem(name='target', datatype=float, required=True))
#define arguments that behave as function outputs
outputs = []
outputs.append(
UISingleItem(name='difference', datatype=float, required=True))
return (inputs, outputs)
def build_ui(cls):
inputs = []
inputs.append(
UISingleItem(name='input_item',
datatype=float,
description='Item to base anomaly on'))
inputs.append(
UISingle(
name='factor',
datatype=int,
description=
'Frequency of anomaly e.g. A value of 3 will create anomaly every 3 datapoints',
default=10))
inputs.append(
UISingle(name='width',
datatype=int,
description='Width of the anomaly created',
default=5))
outputs = []
outputs.append(
UIFunctionOutSingle(
name='output_item',
datatype=float,
description='Generated Item With Flatline anomalies'))
return (inputs, outputs)
def build_ui(cls):
inputs = []
inputs.append(
UISingleItem(name='input_item',
datatype=float,
description='Item to base anomaly on'))
inputs.append(
UISingle(
name='factor',
datatype=int,
description=
'Frequency of anomaly e.g. A value of 3 will create anomaly every 3 datapoints',
default=5))
inputs.append(
UISingle(
name='size',
datatype=int,
description=
'Size of extreme anomalies to be created. e.g. 10 will create 10x size extreme \
anomaly compared to the normal variance',
default=10))
outputs = []
outputs.append(
UIFunctionOutSingle(
name='output_item',
datatype=float,
description='Generated Item With Extreme anomalies'))
return (inputs, outputs)
def build_ui(cls):
# define arguments that behave as function inputs
inputs = []
inputs.append(UISingleItem(name='dimension_name', datatype=str))
inputs.append(
UISingle(name='dimension_value',
datatype=str,
description='Dimension Filter Value'))
inputs.append(
UIExpression(
name='expression',
description="Define alert expression using pandas systax. \
Example: df['inlet_temperature']>50. ${pressure} will be substituted \
with df['pressure'] before evaluation, ${} with df[<dimension_name>]"
))
inputs.append(
UISingle(name='pulse_trigger',
description=
"If true only generate alerts on crossing the threshold",
datatype=bool))
# define arguments that behave as function outputs
outputs = []
outputs.append(
UIFunctionOutSingle(name='alert_name',
datatype=bool,
description='Output of alert function'))
outputs.append(
UIFunctionOutSingle(name='alert_end',
datatype=dt.datetime,
description='End of pulse triggered alert'))
return (inputs, outputs)
def build_ui(cls):
# define arguments that behave as function inputs
inputs = []
inputs.append(UISingleItem(
name='input_item',
datatype=str,
description='String encoded array of sensor readings'
))
# define arguments that behave as function outputs
outputs = []
return (inputs, outputs)
def build_ui(cls):
# define arguments that behave as function inputs
inputs = []
inputs.append(UISingleItem(name='dimension_name', datatype=str))
inputs.append(UISingle(name='dimension_value', datatype=str,
description='Dimension Filter Value'))
inputs.append(UIExpression(name='expression',
description="Define alert expression using pandas systax. \
Example: df['inlet_temperature']>50. ${pressure} will be substituted \
with df['pressure'] before evaluation, ${} with df[<dimension_name>]"))
# define arguments that behave as function outputs
outputs = []
outputs.append(UIFunctionOutSingle(name='alert_name', datatype=bool, description='Output of alert function'))
return (inputs, outputs)
def build_ui(cls):
inputs = [
UISingleItem(
name='source',
datatype=None,
description='Choose data item to run data quality checks on'),
UIMulti(name='checks_with_string_output',
datatype=str,
description='Select quality checks '
'to run. These checks return string output ',
values=cls.STR_QUALITY_CHECKS,
required=False),
UIMulti(name='checks_with_numerical_output',
datatype=str,
description='Select quality '
'checks to run. These checks return numerical output ',
values=cls.NUMERICAL_QUALITY_CHECKS,
required=False),
UIMulti(name='checks_with_boolean_output',
datatype=str,
description='Select quality checks '
'to run. These checks return boolean output',
values=cls.BOOLEAN_QUALITY_CHECKS,
required=False)
]
outputs = [
UIFunctionOutMulti(
'name',
cardinality_from='checks_with_string_output',
datatype=str,
description='quality check returns string output'),
UIFunctionOutMulti(
'name',
cardinality_from='checks_with_numerical_output',
datatype=float,
description='quality check returns numerical output'),
UIFunctionOutMulti(
'name',
cardinality_from='checks_with_boolean_output',
datatype=bool,
description='quality check returns boolean output')
]
return inputs, outputs