tclv

"""
Function that ensures only unique data points get entered
into shared queue on a overlapping window data api. Achieves 
this by keeping 1) a set with data points that have been entered
into the queue 2) a local queue that can be used to ensure that only
the last batch_size are in the set. This gives us constant time membership
checks and bounds the size of the hashset to two times the batch_size
"""
def process_data_to_queue(batch_size):    
    global_queue = Queue.Queue()

tclv

    diff = np.zeros((len(var),))
    

    for i in range(len(var)):
        assert len(test_outputs[i, :]) == window_size
        (test_pass, no_diff) = testmod.kupiec(test_outputs[i, :], var[i])
        diff[i] = no_diff
        print(no_diff)

    print("Mean diff {}".format(np.mean(np.abs(diff))))

tclv

from itertools import cycle

if __name__ == "__main__":
    f1 = open("./fastq1.fq")
    f2 = open("./fastq2.fq")
    reference = cycle([f1, f2])

    for i in range(8):
        print("Checking chunk{}".format(i))
        with open('./chunk{}'.format(i)) as chunkfile:

tclv

\usepackage{ifxetex}

\ifxetex
    \usepackage{fontspec}
    \defaultfontfeatures{Ligatures=TeX} % To support LaTeX quoting style
    \setromanfont{Palatino Linotype} %mijn fonts
    \setmonofont{Source Code Pro for Powerline} %mijn vim font
\else
    \usepackage[T1]{fontenc}
    \usepackage[utf8]{inputenc}