import numpy as np
from pyFTS import *

def differential(original):
    n = len(original)
    diff = [ original[t-1]-original[t] for t in np.arange(1,n) ]
    diff.insert(0,0)
    return np.array(diff)

def trimf(x,parameters):
	if(x < parameters[0]):
		return 0
	elif(x >= parameters[0] and x < parameters[1]):
		return (x-parameters[0])/(parameters[1]-parameters[0])
	elif(x >= parameters[1] and x <= parameters[2]):
		return (parameters[2]-x)/(parameters[2]-parameters[1])
	else: 
		return 0

def trapmf(x, parameters):
		if(x < parameters[0]):
			return 0
		elif(x >= parameters[0] and x < parameters[1]):
			return (x-parameters[0])/(parameters[1]-parameters[0])
		elif(x >= parameters[1] and x <= parameters[2]):
			return 1
		elif(x >= parameters[2] and x <= parameters[3]):
			return (parameters[3]-x)/(parameters[3]-parameters[2])
		else: 
			return 0

def gaussmf(x,parameters):
		return math.exp(-0.5*((x-parameters[0]) / parameters[1] )**2)


def bellmf(x,parameters):
		return 1 / (1 + abs((xx - parameters[2])/parameters[0])**(2*parameters[1]))


def sigmf(x,parameters):
		return 1 / (1 + math.exp(-parameters[0] * (x - parameters[1])))


class FuzzySet:

	def __init__(self,name,mf,parameters,centroid):
		self.name = name
		self.mf = mf
		self.parameters = parameters
		self.centroid = centroid
        
	def membership(self,x):
		return self.mf(x,self.parameters)
    
	def __str__(self):
		return self.name + ": " + str(self.mf) + "(" + str(self.parameters) + ")"
    
    
def GridPartitionerTrimf(data,npart,names = None,prefix = "A"):
	sets = []
	dmax = max(data)
	dmin = min(data)
	dlen = dmax - dmin
	partlen = dlen / npart
	partition = dmin
	for c in range(npart):
		sets.append( FuzzySet(prefix+str(c),trimf,[partition-partlen, partition, partition+partlen], partition ) )
		partition = partition + partlen
		
	return sets