from pyFTS.models import pwfts
from pyFTS.partitioners import Grid, Entropy, Util as pUtil
from pyFTS.data import sunspots as DataFrame
from pyFTS.common import Util, Transformations, fts, tree

def pwfts(dataset, trainLength, npart=50):
    fs = Grid.GridPartitioner(data=dataset, npart=50)
    model = pwfts.ProbabilisticWeightedFTS(partitioner=fs)
    model.fit(dataset[:trainLength])
    print(model)
    forecasts = model.predict(dataset[trainLength:trainLength + 200], type='point',
                              steps_ahead=int(dataset.size * 0.2))  # , steps_ahead=int(dataset.size*0.2)
    # forecasts = model.forecast_ahead(dataset[:], trainLength)