def findDiffSeries(series1,diffInterval=1):
    series1 = smoothArray(series1)
    diffSeries =[]
    lenSeries=len(series1)
    if (diffInterval>lenSeries):
        print "diffInterval can not be greater than the length of series"
        return
    i=diffInterval
    while(i<lenSeries):
        diffSeries.append((i-diffInterval,i,((series1[i]-series1[i-diffInterval])/series1[i-diffInterval])*100))
        i=i+1
    (N,P) = MADThreshold(diffSeries)
    print "N & P ::::::::"+ str(N)+":::"+ str(P)
    return diffSeries
def slopeBasedDetection(series1,smoothed1,series2,smoothed2,next_val_to_consider = 7, default_threshold = True, threshold = 0, what_to_consider = 1):
    if(smoothed1 == False):
        series1 = smoothArray(series1)
    if(smoothed2 == False):
        series2 = smoothArray(series2)
    
    n = len(series1)
    positive_slopes = []
    anomalous_pts = []
    negative_slopes = []
    i = 0
    while(i<(n-next_val_to_consider+1)):
        if((series2[i+next_val_to_consider-1] - series2[i]) == 0):
            i= i+ next_val_to_consider 
            continue
        diff = ((series1[i+next_val_to_consider-1] - series1[i]) * series2[i] )/ ((series2[i+next_val_to_consider-1] - series2[i]) * series1[i])
        if(diff < 0):
            negative_slopes.append((i,i+next_val_to_consider-1,diff))
        else:
            positive_slopes.append((i,i+next_val_to_consider-1,diff))
        i= i+ next_val_to_consider
    
             
    if(default_threshold == True):
        temp = []
        for x in positive_slopes:
            temp.append(x[2])
        if(len(temp)>0):
            (_,positive_threshold) = MADThreshold(temp)
        # print "Positive Threshold Value:" + str(positive_threshold)
        
    if(default_threshold == True):
        temp = []
        for x in negative_slopes:
            temp.append(x[2])
        if(len(temp)>0):
            (negative_threshold,_) = MADThreshold(temp)
        # print "Negative Threshold Value:" + str(negative_threshold)
    
    if(what_to_consider == 1):
        positive_anomalous_pts = []        
        if(default_threshold):
            print "Possitive Threshold of Slope Based : " + str(positive_threshold)
            for i in range(0,len(positive_slopes)):
                if(positive_slopes[i][2] > positive_threshold):
                    positive_anomalous_pts.append(positive_slopes[i])
        else:
            print "Possitive Threshold of Slope Based User Given: " + str(threshold)
            for i in range(0,len(positive_slopes)):
                if(positive_slopes[i][2] > threshold):
                    positive_anomalous_pts.append(positive_slopes[i])
        return positive_anomalous_pts
    elif(what_to_consider == -1):        
        negative_anomalous_pts = []
        if(default_threshold):
            print "Negative Threshold of Slope Based : " + str(negative_threshold)
            for i in range(0,len(negative_slopes)):
                if(negative_slopes[i][2] < negative_threshold):
                    negative_anomalous_pts.append(negative_slopes[i])
        else:
            print "Negative Threshold of Slope Based User Given: " + str(threshold)
            for i in range(0,len(negative_slopes)):
                if(negative_slopes[i][2] < threshold):
                    negative_anomalous_pts.append(negative_slopes[i])
        return negative_anomalous_pts
    elif(what_to_consider == 0):
        if(default_threshold):
            print "Possitive Threshold of Slope Based : " + str(positive_threshold)
            print "Negative Threshold of Slope Based : " + str(negative_threshold)
            positive_anomalous_pts = []
            for i in range(0,len(positive_slopes)):
                if(positive_slopes[i][2] > positive_threshold):
                    positive_anomalous_pts.append(positive_slopes[i])
            negative_anomalous_pts = []
            for i in range(0,len(negative_slopes)):
                if(negative_slopes[i][2] < negative_threshold):
                    negative_anomalous_pts.append(negative_slopes[i])
            anomalous_pts = positive_anomalous_pts  + negative_anomalous_pts
            # Sort array according to start of window
            sorted(anomalous_pts, key=lambda x: x[0])    
            return anomalous_pts
        else:
            print "Threshold of Slope Based User Given: " + str(threshold)
            positive_anomalous_pts = []
            for i in range(0,len(positive_slopes)):
                if(positive_slopes[i][2] > threshold):
                    positive_anomalous_pts.append(positive_slopes[i])
            negative_anomalous_pts = []
            for i in range(0,len(negative_slopes)):
                if(abs(negative_slopes[i][2]) > threshold):
                    negative_anomalous_pts.append(negative_slopes[i])
            anomalous_pts = positive_anomalous_pts  + negative_anomalous_pts
            # Sort array according to start of window
            sorted(anomalous_pts, key=lambda x: x[0])    
            return anomalous_pts
    pass