import pylab as plt
import os
import numpy as np

def main():

    srate = 4000000.0 
    fftsize = 8192
    infiler = 'counts-check.dat' #real samples
    infilei = 'counts-checki.dat' #imag samples

    rsize = os.path.getsize(infiler) / 4
    rshape = (fftsize, rsize/fftsize)

    isize = os.path.getsize(infilei) / 4
    ishape = (fftsize, isize/fftsize)

    x = np.memmap(infiler, dtype='float32', mode = 'r', shape=rshape)  
    y = np.memmap(infilei, dtype='float32', mode = 'r', shape=ishape)

    sum_counts = 0
    i = 0  

    for count1 in range(rsize/fftsize):
        for count2 in range(fftsize):
            sum_counts += (x[count2, count1])#/100.0
            i += 1
        
    avg = float(sum_counts) / float(i)
    #conversion = 0.0196 / avg
    print avg #conversion

    freqPlotx = np.mean(x, axis=0)
    freqPloty = np.mean(y, axis=0)

    plotvals = []

    for f in range(freqPlotx.size):
        val = pow(freqPlotx[f],2) + pow(freqPloty[f],2)
        plotvals.append(val)

    #print freqPlot
    '''fmin = (169010000-(srate/2))/1000000
    fmax = (169010000+(srate/2))/1000000
    fidx = np.linspace(fmin, fmax, freqPlot.size)'''

    plt.plot(plotvals) #fidx, freqPlot
    plt.show()
    

if __name__ == "__main__":
    main()