94 lines
2.1 KiB
Python
94 lines
2.1 KiB
Python
#!/usr/bin/python
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# -*- coding: utf8 -*-
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import numpy as np
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import pandas as pd
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import math
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from operator import itemgetter
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from pyFTS.common import FLR, FuzzySet, SortedCollection
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from pyFTS import fts
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class EnsembleFTS(fts.FTS):
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def __init__(self, name, update=True):
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super(EnsembleFTS, self).__init__("Ensemble FTS")
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self.shortname = "Ensemble FTS " + name
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self.name = "Ensemble FTS"
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self.flrgs = {}
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self.hasPointForecasting = True
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self.hasIntervalForecasting = True
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self.hasDistributionForecasting = True
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self.isHighOrder = True
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self.models = []
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self.parameters = []
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def train(self, data, sets, order=1,parameters=None):
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pass
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def forecast(self, data):
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ndata = np.array(self.doTransformations(data))
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l = len(ndata)
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ret = []
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for k in np.arange(self.order - 1, l):
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pass
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ret = self.doInverseTransformations(ret, params=[data[self.order - 1:]])
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return ret
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def forecastInterval(self, data):
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ndata = np.array(self.doTransformations(data))
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l = len(ndata)
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ret = []
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for k in np.arange(self.order - 1, l):
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pass
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return ret
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def forecastAhead(self, data, steps):
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pass
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def forecastAheadInterval(self, data, steps):
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pass
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def getGridClean(self, resolution):
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grid = {}
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if len(self.transformations) == 0:
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_min = self.sets[0].lower
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_max = self.sets[-1].upper
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else:
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_min = self.original_min
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_max = self.original_max
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for sbin in np.arange(_min,_max, resolution):
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grid[sbin] = 0
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return grid
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def gridCount(self, grid, resolution, index, interval):
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#print(interval)
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for k in index.inside(interval[0],interval[1]):
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#print(k)
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grid[k] += 1
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return grid
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def gridCountPoint(self, grid, resolution, index, point):
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k = index.find_ge(point)
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# print(k)
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grid[k] += 1
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return grid
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def forecastAheadDistribution(self, data, steps, resolution, parameters=2):
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pass
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