pyFTS.models.nonstationary package

Submodules

pyFTS.models.nonstationary.common module

Non Stationary Fuzzy Sets

GARIBALDI, Jonathan M.; JAROSZEWSKI, Marcin; MUSIKASUWAN, Salang. Nonstationary fuzzy sets. IEEE Transactions on Fuzzy Systems, v. 16, n. 4, p. 1072-1086, 2008.

class pyFTS.models.nonstationary.common.FuzzySet(name, mf, parameters, **kwargs)

Bases: pyFTS.common.FuzzySet.FuzzySet

Non Stationary Fuzzy Sets

get_lower(t)

get_midpoint(t)

get_upper(t)

location

Pertubation function that affects the location of the membership function

location_params

Parameters for location pertubation function

membership(x, t)

Calculate the membership value of a given input

Parameters

• x – input value

• t – time displacement or perturbation parameters

Returns

membership value of x at this fuzzy set

noise

Pertubation function that adds noise on the membership function

noise_params

Parameters for noise pertubation function

perform_location(t, param)

perform_width(t, param)

perturbate_parameters(t)

width

Pertubation function that affects the width of the membership function

width_params

Parameters for width pertubation function

pyFTS.models.nonstationary.common.check_bounds(data, partitioner, t)

pyFTS.models.nonstationary.common.check_bounds_index(data, partitioner, t)

pyFTS.models.nonstationary.common.fuzzify(inst, t, fuzzySets)

Calculate the membership values for a data point given nonstationary fuzzy sets

Parameters

• inst – data points

• t – time displacement of the instance

• fuzzySets – list of fuzzy sets

Returns

array of membership values

pyFTS.models.nonstationary.common.fuzzySeries(data, fuzzySets, ordered_sets, window_size=1, method='fuzzy', const_t=None)

pyFTS.models.nonstationary.common.window_index(t, window_size)

pyFTS.models.nonstationary.cvfts module

pyFTS.models.nonstationary.flrg module

class pyFTS.models.nonstationary.flrg.NonStationaryFLRG(LHS, **kwargs)

Bases: pyFTS.common.flrg.FLRG

get_key()

Returns a unique identifier for this FLRG

get_lower(*args)

Returns the lower bound value for the RHS fuzzy sets

Parameters

sets – fuzzy sets

Returns

lower bound value

get_membership(data, *args)

Returns the membership value of the FLRG for the input data

Parameters

• data – input data

• sets – fuzzy sets

Returns

the membership value

get_midpoint(*args)

Returns the midpoint value for the RHS fuzzy sets

Parameters

sets – fuzzy sets

Returns

the midpoint value

get_upper(*args)

Returns the upper bound value for the RHS fuzzy sets

Parameters

sets – fuzzy sets

Returns

upper bound value

unpack_args(*args)

pyFTS.models.nonstationary.honsfts module

pyFTS.models.nonstationary.nsfts module

pyFTS.models.nonstationary.partitioners module

class pyFTS.models.nonstationary.partitioners.PolynomialNonStationaryPartitioner(data, part, **kwargs)

Bases: pyFTS.partitioners.partitioner.Partitioner

Non Stationary Universe of Discourse Partitioner

build(data)

Perform the partitioning of the Universe of Discourse

Parameters

data – training data

Returns

get_polynomial_perturbations(data, **kwargs)

poly_width(par1, par2, rng, deg)

scale_down(x, pct)

scale_up(x, pct)

class pyFTS.models.nonstationary.partitioners.SimpleNonStationaryPartitioner(data, part, **kwargs)

Bases: pyFTS.partitioners.partitioner.Partitioner

Non Stationary Universe of Discourse Partitioner

build(data)

Perform the partitioning of the Universe of Discourse

Parameters

data – training data

Returns

pyFTS.models.nonstationary.partitioners.simplenonstationary_gridpartitioner_builder(data, npart, transformation)

pyFTS.models.nonstationary.perturbation module

Pertubation functions for Non Stationary Fuzzy Sets

pyFTS.models.nonstationary.perturbation.exponential(x, parameters)

pyFTS.models.nonstationary.perturbation.linear(x, parameters)

pyFTS.models.nonstationary.perturbation.periodic(x, parameters)

pyFTS.models.nonstationary.perturbation.polynomial(x, parameters)

pyFTS.models.nonstationary.util module

Module contents

Fuzzy time series with nonstationary fuzzy sets, for heteroskedastic data