float_conversion

Module: missions.nodes.type_manipulation.float_conversion

Convert different non-float entries to float

Inheritance diagram for pySPACE.missions.nodes.type_manipulation.float_conversion:

Inheritance diagram of pySPACE.missions.nodes.type_manipulation.float_conversion

Class Summary

Int2FloatNode([type]) Converts all the entries in the data set to either
NaN2NumberNode(\*\*kwargs) Converts all the NaN enetries in the data set to 0.0

Classes

Int2FloatNode

class pySPACE.missions.nodes.type_manipulation.float_conversion.Int2FloatNode(type='float64', **kwargs)[source]

Bases: pySPACE.missions.nodes.base_node.BaseNode

Converts all the entries in the data set to either a double or longdouble precision

Parameters

type:String that can be either “float32”, “float64” or “float128”

(optional, default:”float64”)

Exemplary Call

-
    node : Int2FloatNode
    parameters :
        type : "float64"
Author:

Andrei Ignat(andrei_cristian.ignat@dfki.de)
Created:

2014/08/14
POSSIBLE NODE NAMES:
 
  • Int2FloatNode
  • Int2Float
POSSIBLE INPUT TYPES:
 
  • TimeSeries
  • FeatureVector

Class Components Summary

_execute(data)
feature_vector_conversion(data)
input_types
time_series_conversion(data)
input_types = ['TimeSeries', 'FeatureVector']
__init__(type='float64', **kwargs)[source]
_execute(data)[source]
time_series_conversion(data)[source]
feature_vector_conversion(data)[source]

NaN2NumberNode

class pySPACE.missions.nodes.type_manipulation.float_conversion.NaN2NumberNode(**kwargs)[source]

Bases: pySPACE.missions.nodes.base_node.BaseNode

Converts all the NaN enetries in the data set to 0.0 This node should not be abused in usage but rather used as a fail safe in case one of the entries is NaN

Exemplary Call

-
    node : NaN2NumberNode
Author:

Andrei Ignat(andrei_cristian.ignat@dfki.de)
Created:

2014/08/14
POSSIBLE NODE NAMES:
 
  • NaN2NumberNode
  • NaN2Number
POSSIBLE INPUT TYPES:
 
  • TimeSeries
  • FeatureVector

Class Components Summary

_execute(data)
feature_vector_conversion(data)
input_types
time_series_conversion(data)
input_types = ['TimeSeries', 'FeatureVector']
__init__(**kwargs)[source]
_execute(data)[source]
time_series_conversion(data)[source]
feature_vector_conversion(data)[source]