Bugfix on partitioner base class: the number of partitions is updated after the set construction
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@ -67,6 +67,8 @@ class Partitioner(object):
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self.sets = self.build(ndata)
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self.sets = self.build(ndata)
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self.partitions = len(self.sets)
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if self.ordered_sets is None and self.setnames is not None:
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if self.ordered_sets is None and self.setnames is not None:
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self.ordered_sets = self.setnames[:len(self.sets)]
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self.ordered_sets = self.setnames[:len(self.sets)]
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else:
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else:
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@ -18,19 +18,27 @@ from pyFTS.fcm import fts, common, GA
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from pyFTS.data import Enrollments, TAIEX
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from pyFTS.data import Enrollments, TAIEX
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import pandas as pd
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x = [k for k in np.arange(-2*np.pi, 2*np.pi, 0.15)]
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df = pd.read_csv('https://query.data.world/s/7zfy4d5uep7wbgf56k4uu5g52dmvap', sep=';')
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y = [np.sin(k) for k in x]
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data = df['glo_avg'].values[:12000]
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from pyFTS.models import hofts
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from pyFTS.partitioners import Grid, FCM, CMeans, Entropy
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from pyFTS.benchmarks import Measures
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fs = Grid.GridPartitioner(data=data, npart=35, func=Membership.trimf)
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metodos = [FCM.FCMPartitioner]
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k = 35
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GA.parameters['num_concepts'] = 35
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rows = []
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GA.parameters['order'] = 2
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GA.parameters['partitioner'] = fs
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GA.execute('TAIEX', data)
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for contador, metodo in enumerate(metodos):
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print(metodo)
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part = metodo(data=y, npart=k)
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model = hofts.HighOrderFTS(order=2, partitioner=part)
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model.fit(y)
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forecasts = model.predict(y)
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for o in range(model.order):
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forecasts.insert(0, None)
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'''
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'''
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