ipyrad/assemble/cluster_across.py
def build_tmp_h5(data, samples):
    """ build tmp h5 arrays that can return quick access for nloci"""
    ## get samples and names, sorted
    snames = [i.name for i in samples]
    snames.sort()

    ## Build an array for quickly indexing consens reads from catg files.
    ## save as a npy int binary file.
    uhandle = os.path.join(data.dirs.across, data.name+".utemp.sort")
    bseeds = os.path.join(data.dirs.across, data.name+".tmparrs.h5")

    ## send as first async1 job
    get_seeds_and_hits(uhandle, bseeds, snames)
def build_tmp_h5(data, samples):
    """ build tmp h5 arrays that can return quick access for nloci"""
    ## get samples and names, sorted
    snames = [i.name for i in samples]
    snames.sort()

    ## Build an array for quickly indexing consens reads from catg files.
    ## save as a npy int binary file.
    uhandle = os.path.join(data.dirs.across, data.name+".utemp.sort")
    bseeds = os.path.join(data.dirs.across, data.name+".tmparrs.h5")

    ## send as first async1 job
    get_seeds_and_hits(uhandle, bseeds, snames)
def build_tmp_h5 ( data , samples ) : ## get samples and names, sorted snames = [ i . name for i in samples ] snames . sort ( ) ## Build an array for quickly indexing consens reads from catg files. ## save as a npy int binary file. uhandle = os . path . join ( data . dirs . across , data . name + ".utemp.sort" ) bseeds = os . path . join ( data . dirs . across , data . name + ".tmparrs.h5" ) ## send as first async1 job get_seeds_and_hits ( uhandle , bseeds , snames )
build tmp h5 arrays that can return quick access for nloci
build tmp h5 arrays that can return quick access for nloci