def build_ui(cls):
# define arguments that behave as function inputs
inputs = []
inputs.append(
UIMultiItem(name='features', datatype=float, required=True))
inputs.append(
UIMultiItem(name='targets',
datatype=float,
required=True,
output_item='predictions',
is_output_datatype_derived=True))
return (inputs, [])
def build_ui(cls):
# define arguments that behave as function inputs
inputs = []
inputs.append(UIMultiItem(
name='group1_in',
datatype=None,
description='String encoded array of sensor readings, 15 readings per 5 mins',
output_item='group1_out',
is_output_datatype_derived=True, output_datatype=None
))
inputs.append(UIMultiItem(
name='group2_in',
datatype=None,
description='String encoded array of sensor readings, 5 readings per 5 mins',
output_item='group2_out',
is_output_datatype_derived=True, output_datatype=None
))
# 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(
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(
UIMultiItem(name='source',
datatype=None,
description=('Choose the data items'
' that you would like to'
' aggregate'),
output_item='name',
is_output_datatype_derived=True))
inputs.append(
UIExpression(name='expression',
description='Paste in or type an AS expression'))
return (inputs, [])
def build_ui(cls):
inputs = []
# Input variable name must be kept 'source'
# Output variable name must be kept 'name'
inputs.append(
UIMultiItem(name='source',
datatype=None,
description=('Choose the data items'
' that you would like to'
' aggregate'),
output_item='name',
is_output_datatype_derived=True))
inputs.append(
UIExpression(
name='expression',
description='Use ${GROUP} to reference the current grain.'
'All Pandas Series methods can be used on the grain.'
'For example, ${GROUP}.max() - ${GROUP}.min().'))
return (inputs, [])
def build_ui(cls):
inputs = []
outputs = []
inputs.append(
UIMultiItem(name='input_items',
datatype=None,
description=('Choose the data items'
' that you would like to'
' aggregate'),
output_item='output_items',
is_output_datatype_derived=True))
aggregate_names = list(cls.get_available_methods().keys())
inputs.append(
UISingle(name='aggregation_function',
description='Choose aggregation function',
values=aggregate_names))
return (inputs, outputs)