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