def write_geno(data, sidx):
    """
    write the geno output formerly used by admixture, still supported by 
    adegenet, perhaps. Also, sNMF still likes .geno.
    """

    ## grab snp and bis data from tmparr
    start = time.time()
    tmparrs = os.path.join(data.dirs.outfiles, "tmp-{}.h5".format(data.name)) 
    with h5py.File(tmparrs, 'r') as io5:
        snparr = io5["snparr"]
        bisarr = io5["bisarr"]

        ## trim to size b/c it was made longer than actual
        bend = np.where(np.all(bisarr[:] == "", axis=0))[0]
        if np.any(bend):
            bend = bend.min()
        else:
            bend = bisarr.shape[1]        

        send = np.where(np.all(snparr[:] == "", axis=0))[0]       
        if np.any(send):
            send = send.min()
        else:
            send = snparr.shape[1]        

        ## get most common base at each SNP as a pseudo-reference
        ## and record 0,1,2 or missing=9 for counts of the ref allele
        snpref = reftrick(snparr[:, :send].view(np.int8), GETCONS).view("S1")
        bisref = reftrick(bisarr[:, :bend].view(np.int8), GETCONS).view("S1")

        ## geno matrix to fill (9 is empty)
        snpgeno = np.zeros((snparr.shape[0], send), dtype=np.uint8)
        snpgeno.fill(9)
        bisgeno = np.zeros((bisarr.shape[0], bend), dtype=np.uint8)
        bisgeno.fill(9)

        ##--------------------------------------------------------------------
        ## fill in complete hits (match to first column ref base)
        mask2 = np.array(snparr[:, :send] == snpref[:, 0])
        snpgeno[mask2] = 2

        ## fill in single hits (heteros) match to hetero of first+second column
        ambref = np.apply_along_axis(lambda x: TRANSFULL[tuple(x)], 1, snpref[:, :2])
        mask1 = np.array(snparr[:, :send] == ambref)
        snpgeno[mask1] = 1

        ## fill in zero hits, meaning a perfect match to the second column base
        ## anything else is left at 9 (missing), b/c it's either missing or it
        ## is not bi-allelic. 
        mask0 = np.array(snparr[:, :send] == snpref[:, 1])
        snpgeno[mask0] = 0

        ##--------------------------------------------------------------------

        ## fill in complete hits
        mask2 = np.array(bisarr[:, :bend] == bisref[:, 0])
        bisgeno[mask2] = 2

        ## fill in single hits (heteros)
        ambref = np.apply_along_axis(lambda x: TRANSFULL[tuple(x)], 1, bisref[:, :2])
        mask1 = np.array(bisarr[:, :bend] == ambref)
        bisgeno[mask1] = 1

        ## fill in zero hits (match to second base)
        mask0 = np.array(bisarr[:, :bend] == bisref[:, 1])
        bisgeno[mask0] = 0

        ##---------------------------------------------------------------------
        ## print to files
        np.savetxt(data.outfiles.geno, snpgeno.T, delimiter="", fmt="%d")
        np.savetxt(data.outfiles.ugeno, bisgeno.T, delimiter="", fmt="%d")
    LOGGER.debug("finished writing geno in: %s", time.time() - start)
def write_geno(data, sidx):
    """
    write the geno output formerly used by admixture, still supported by 
    adegenet, perhaps. Also, sNMF still likes .geno.
    """

    ## grab snp and bis data from tmparr
    start = time.time()
    tmparrs = os.path.join(data.dirs.outfiles, "tmp-{}.h5".format(data.name)) 
    with h5py.File(tmparrs, 'r') as io5:
        snparr = io5["snparr"]
        bisarr = io5["bisarr"]

        ## trim to size b/c it was made longer than actual
        bend = np.where(np.all(bisarr[:] == "", axis=0))[0]
        if np.any(bend):
            bend = bend.min()
        else:
            bend = bisarr.shape[1]        

        send = np.where(np.all(snparr[:] == "", axis=0))[0]       
        if np.any(send):
            send = send.min()
        else:
            send = snparr.shape[1]        

        ## get most common base at each SNP as a pseudo-reference
        ## and record 0,1,2 or missing=9 for counts of the ref allele
        snpref = reftrick(snparr[:, :send].view(np.int8), GETCONS).view("S1")
        bisref = reftrick(bisarr[:, :bend].view(np.int8), GETCONS).view("S1")

        ## geno matrix to fill (9 is empty)
        snpgeno = np.zeros((snparr.shape[0], send), dtype=np.uint8)
        snpgeno.fill(9)
        bisgeno = np.zeros((bisarr.shape[0], bend), dtype=np.uint8)
        bisgeno.fill(9)

        ##--------------------------------------------------------------------
        ## fill in complete hits (match to first column ref base)
        mask2 = np.array(snparr[:, :send] == snpref[:, 0])
        snpgeno[mask2] = 2

        ## fill in single hits (heteros) match to hetero of first+second column
        ambref = np.apply_along_axis(lambda x: TRANSFULL[tuple(x)], 1, snpref[:, :2])
        mask1 = np.array(snparr[:, :send] == ambref)
        snpgeno[mask1] = 1

        ## fill in zero hits, meaning a perfect match to the second column base
        ## anything else is left at 9 (missing), b/c it's either missing or it
        ## is not bi-allelic. 
        mask0 = np.array(snparr[:, :send] == snpref[:, 1])
        snpgeno[mask0] = 0

        ##--------------------------------------------------------------------

        ## fill in complete hits
        mask2 = np.array(bisarr[:, :bend] == bisref[:, 0])
        bisgeno[mask2] = 2

        ## fill in single hits (heteros)
        ambref = np.apply_along_axis(lambda x: TRANSFULL[tuple(x)], 1, bisref[:, :2])
        mask1 = np.array(bisarr[:, :bend] == ambref)
        bisgeno[mask1] = 1

        ## fill in zero hits (match to second base)
        mask0 = np.array(bisarr[:, :bend] == bisref[:, 1])
        bisgeno[mask0] = 0

        ##---------------------------------------------------------------------
        ## print to files
        np.savetxt(data.outfiles.geno, snpgeno.T, delimiter="", fmt="%d")
        np.savetxt(data.outfiles.ugeno, bisgeno.T, delimiter="", fmt="%d")
    LOGGER.debug("finished writing geno in: %s", time.time() - start)
def write_geno ( data , sidx ) : ## grab snp and bis data from tmparr start = time . time ( ) tmparrs = os . path . join ( data . dirs . outfiles , "tmp-{}.h5" . format ( data . name ) ) with h5py . File ( tmparrs , 'r' ) as io5 : snparr = io5 [ "snparr" ] bisarr = io5 [ "bisarr" ] ## trim to size b/c it was made longer than actual bend = np . where ( np . all ( bisarr [ : ] == "" , axis = 0 ) ) [ 0 ] if np . any ( bend ) : bend = bend . min ( ) else : bend = bisarr . shape [ 1 ] send = np . where ( np . all ( snparr [ : ] == "" , axis = 0 ) ) [ 0 ] if np . any ( send ) : send = send . min ( ) else : send = snparr . shape [ 1 ] ## get most common base at each SNP as a pseudo-reference ## and record 0,1,2 or missing=9 for counts of the ref allele snpref = reftrick ( snparr [ : , : send ] . view ( np . int8 ) , GETCONS ) . view ( "S1" ) bisref = reftrick ( bisarr [ : , : bend ] . view ( np . int8 ) , GETCONS ) . view ( "S1" ) ## geno matrix to fill (9 is empty) snpgeno = np . zeros ( ( snparr . shape [ 0 ] , send ) , dtype = np . uint8 ) snpgeno . fill ( 9 ) bisgeno = np . zeros ( ( bisarr . shape [ 0 ] , bend ) , dtype = np . uint8 ) bisgeno . fill ( 9 ) ##-------------------------------------------------------------------- ## fill in complete hits (match to first column ref base) mask2 = np . array ( snparr [ : , : send ] == snpref [ : , 0 ] ) snpgeno [ mask2 ] = 2 ## fill in single hits (heteros) match to hetero of first+second column ambref = np . apply_along_axis ( lambda x : TRANSFULL [ tuple ( x ) ] , 1 , snpref [ : , : 2 ] ) mask1 = np . array ( snparr [ : , : send ] == ambref ) snpgeno [ mask1 ] = 1 ## fill in zero hits, meaning a perfect match to the second column base ## anything else is left at 9 (missing), b/c it's either missing or it ## is not bi-allelic.  mask0 = np . array ( snparr [ : , : send ] == snpref [ : , 1 ] ) snpgeno [ mask0 ] = 0 ##-------------------------------------------------------------------- ## fill in complete hits mask2 = np . array ( bisarr [ : , : bend ] == bisref [ : , 0 ] ) bisgeno [ mask2 ] = 2 ## fill in single hits (heteros) ambref = np . apply_along_axis ( lambda x : TRANSFULL [ tuple ( x ) ] , 1 , bisref [ : , : 2 ] ) mask1 = np . array ( bisarr [ : , : bend ] == ambref ) bisgeno [ mask1 ] = 1 ## fill in zero hits (match to second base) mask0 = np . array ( bisarr [ : , : bend ] == bisref [ : , 1 ] ) bisgeno [ mask0 ] = 0 ##--------------------------------------------------------------------- ## print to files np . savetxt ( data . outfiles . geno , snpgeno . T , delimiter = "" , fmt = "%d" ) np . savetxt ( data . outfiles . ugeno , bisgeno . T , delimiter = "" , fmt = "%d" ) LOGGER . debug ( "finished writing geno in: %s" , time . time ( ) - start )
write the geno output formerly used by admixture, still supported by 
    adegenet, perhaps. Also, sNMF still likes .geno.
write the geno output formerly used by admixture still supported by adegenet perhaps . Also sNMF still likes . geno .