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Solve the following problem using Python, implementing the functions described below, one line at a time
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Description:
 def calc_nfalse(d):
 """ Calculate the number of thermal-noise false positives per segment. """


    dtfactor = n.sum([1./i for i in d['dtarr']])    # assumes dedisperse-all algorithm
    ntrials = d['readints'] * dtfactor * len(d['dmarr']) * d['npixx'] * d['npixy']
    qfrac = 1 - (erf(d['sigma_image1']/n.sqrt(2)) + 1)/2.
    nfalse = int(qfrac*ntrials)
    return nfalse