Python analytics

These use the numpy library, I believe. I adapted them to work in a more vanilla python way as I could not get my head around numpy.

Exponential moving average

def ema(s, n):
    """
    returns an n period exponential moving average for
    the time series s

    s is a list ordered from oldest (index 0) to most recent
    (index -1) n is an integer

    returns a numeric array of the exponential moving average
    """
    s = array(s)
    ema = []
    j = 1
    #get n sma first and calculate the next n period ema
    sma = sum(s[:n]) / n
    multiplier = 2 / float(1 + n)
    ema.append(sma)
    #EMA(current) = ( (Price(current) - EMA(prev) ) xMultiplier) + EMA(prev)
    ema.append(( (s[n] - sma) * multiplier) + sma)
    #now calculate the rest of the values
    for i in s[n+1:]:
        tmp = ( (i - ema[j]) * multiplier) + ema[j]
        j = j + 1
        ema.append(tmp)
    return ema

Simple moving average

def movavg(s, n):
    """
    returns an n period moving average for the time series s
       
    s is a list ordered from oldest (index 0) to most recent (index -1)
    n is an integer

        returns a numeric array of the moving average

    See also ema in this module for the exponential moving average.
    """
    s = array(s)
    c = cumsum(s)
    return (c[n-1:] - c[:-n+1]) / float(n-1)