Bugfixes due to circular imports

This commit is contained in:
Petrônio Cândido 2021-01-13 15:31:59 -03:00
parent 8bf3f7b1e9
commit 5b2b983619
2 changed files with 4 additions and 5 deletions

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@ -2,9 +2,8 @@
Kohonen Self Organizing Maps for Fuzzy Time Series
"""
import pandas as pd
from pyFTS.models.multivariate import wmvfts
#from pyFTS.models.multivariate import wmvfts
from typing import Tuple
from pyFTS.common.Transformations import Transformation
from typing import List
from pyFTS.common.transformations.transformation import Transformation

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@ -12,7 +12,7 @@ import pandas as pd
from pyFTS.partitioners import Grid #, Entropy, Util as pUtil, Simple
#from pyFTS.benchmarks import benchmarks as bchmk, Measures
#from pyFTS.models import chen, yu, cheng, ismailefendi, hofts, pwfts, tsaur, song, sadaei, ifts
from pyFTS.models import pwfts, hofts, chen
from pyFTS.models import pwfts, hofts
#from pyFTS.models.ensemble import ensemble
from pyFTS.common import Transformations, Membership, Util
#from pyFTS.benchmarks import arima, quantreg #BSTS, gaussianproc, knn
@ -38,8 +38,8 @@ l = len(dados)
particionador = Grid.GridPartitioner(data = dados, npart = 10, func = Membership.trimf)
#modelo = pwfts.ProbabilisticWeightedFTS(partitioner = particionador, order = 1)
modelo = hofts.WeightedHighOrderFTS(partitioner = particionador, order = 1, standard_horizon=1, lags=[2])
modelo = pwfts.ProbabilisticWeightedFTS(partitioner = particionador, order = 1)
#modelo = hofts.WeightedHighOrderFTS(partitioner = particionador, order = 1, standard_horizon=1, lags=[2])
#modelo = chen.ConventionalFTS(partitioner = particionador, standard_horizon=3)
modelo.fit(dados)