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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 convertloc(candsfile, candloc, memory_limit):
 """ For given state and location that are too bulky, calculate new location given memory_limit. """


    scan, segment, candint, dmind, dtind, beamnum = candloc

    # set up state and find absolute integration of candidate
    d0 = pickle.load(open(candsfile, 'r'))
    filename = os.path.basename(d0['filename'])
    readints0 = d0['readints']
    nskip0 = (24*3600*(d0['segmenttimes'][segment, 0]
                      - d0['starttime_mjd'])
             / d0['inttime']).astype(int)
    candint_abs = nskip0 + candint

    logger.debug('readints0 {} nskip0 {}, candint_abs {}'.format(readints0, nskip0, candint_abs))

    # clean up d0 and resubmit to set_pipeline
    params = pp.Params()
    for key in d0.keys():
        if not hasattr(params, key):
            _ = d0.pop(key)
    d0['logfile'] = False
    d0['npix'] = 0
    d0['uvres'] = 0
    d0['nsegments'] = 0
    d0['memory_limit'] = memory_limit
    d = rt.set_pipeline(os.path.basename(filename), scan, **d0)

    # find best segment for new state
    readints = d['readints']
    nskips = [(24*3600*(d['segmenttimes'][segment, 0]
                        - d['starttime_mjd']) / d['inttime']).astype(int)
              for segment in range(d['nsegments'])]

    posind = [i for i in range(len(nskips)) if candint_abs - nskips[i] > 0]
    segment_new = [seg for seg in posind if candint_abs - nskips[seg] == min([candint_abs - nskips[i] for i in posind])][0]
    candint_new = candint_abs - nskips[segment_new]

    logger.debug('nskips {}, segment_new {}'.format(nskips, segment_new))

    return [scan, segment_new, candint_new, dmind, dtind, beamnum]