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PIFTS - Density forecasts

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Petrônio Cândido de Lima e Silva 2016-11-07 09:18:24 -02:00
parent d27141df81
commit c0342f5684
1 changed files with 10 additions and 8 deletions
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18
pifts.py
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@ -166,7 +166,7 @@ class ProbabilisticIntervalFTS(ifts.IntervalFTS):
def forecastAhead(self,data,steps): def forecastAhead(self,data,steps):
ret = [[data[k],data[k]] for k in np.arange(len(data)-self.order,len(data))] ret = [[data[k],data[k]] for k in np.arange(len(data)-self.order,len(data))]
for k in np.arange(self.order,steps): for k in np.arange(self.order,steps):
if ret[-1][0] <= self.sets[0].lower and ret[-1][0] >= self.sets[-1].upper: if ret[-1][0] <= self.sets[0].lower and ret[-1][1] >= self.sets[-1].upper:
ret.append(ret[-1]) ret.append(ret[-1])
else: else:
lower = self.forecast( [ret[x][0] for x in np.arange(k-self.order,k)] ) lower = self.forecast( [ret[x][0] for x in np.arange(k-self.order,k)] )
@ -197,14 +197,16 @@ class ProbabilisticIntervalFTS(ifts.IntervalFTS):
for k in np.arange(self.order,steps): for k in np.arange(self.order,steps):
grid = self.getGridClean(resolution) grid = self.getGridClean(resolution)
qt1st = self.forecast([intervals[x][0] + (intervals[x][1]-intervals[x][0])/4 for x in np.arange(k-self.order,k)] )
qt2nd = self.forecast([intervals[x][0] + (intervals[x][1]-intervals[x][0])/2 for x in np.arange(k-self.order,k)] )
qt3rd = self.forecast([intervals[x][1] - (intervals[x][1]-intervals[x][0])/4 for x in np.arange(k-self.order,k)] )
grid = self.gridCount(grid,resolution, intervals[k]) grid = self.gridCount(grid,resolution, intervals[k])
grid = self.gridCount(grid,resolution, np.ravel(qt1st))
grid = self.gridCount(grid,resolution, np.ravel(qt2nd)) for qt in np.arange(1,50,2):
grid = self.gridCount(grid,resolution, np.ravel(qt3rd)) #print(qt)
qtle_lower = self.forecast([intervals[x][0] + qt*(intervals[x][1]-intervals[x][0])/100 for x in np.arange(k-self.order,k)] )
grid = self.gridCount(grid,resolution, np.ravel(qtle_lower))
qtle_upper = self.forecast([intervals[x][1] - qt*(intervals[x][1]-intervals[x][0])/100 for x in np.arange(k-self.order,k)] )
grid = self.gridCount(grid,resolution, np.ravel(qtle_upper))
qtle_mid = self.forecast([intervals[x][0] + (intervals[x][1]-intervals[x][0])/2 for x in np.arange(k-self.order,k)] )
grid = self.gridCount(grid,resolution, np.ravel(qtle_mid))
tmp = np.array([ grid[k] for k in sorted(grid) ]) tmp = np.array([ grid[k] for k in sorted(grid) ])