# this is the template for Lab #3, Task #1
import numpy
import matplotlib.pyplot as p
import lab3
reload(lab3)

p.ion()

def sample_stats(samples,samples_per_bit=4,vth=0.5):
    # reshape array into samples_per_bit columns by as many
    # rows as we need.  Each column represents one of the
    # sample times in a bit period.
    bins = numpy.reshape(samples,(-1,samples_per_bit))

    # now compute statistics each column
    stats = []
    for i in xrange(samples_per_bit):
        column = bins[:,i]
        dist = column - vth  # subtract vth from each sample
        min_dist = ??? # Your code here
        avg_dist = ??? # Your code here
        avg_squared_dist = ??? # Your code here
        stats.append((min_dist,avg_dist,avg_squared_dist))

    return stats  # return collected statistics

if __name__ == '__main__':
    stats = sample_stats(lab3.channel_data)
    for i in xrange(len(stats)):
        min,avg,avgsq = stats[i]
        print "sample %d: min_dist=%6.3f, avg_dist=%6.3f, " \
              "avg_squared_dist=%6.3f" % (i,min,avg,avgsq)

    # when ready for checkoff, enable the following line
    #lab3.checkoff(sample_stats,'L3_1')