How to use the pygtftk.cmd_object.CmdObject function in pygtftk

#mk_matrix: test orientation
        @test "mk_matrix_14" {
         result=`rm -Rf simple_mat*; cat simple.gtf  |gtftk mk_matrix -u 5 -d 5 -t transcript -w 5  -o simple_mat -c simple.chromInfo -V 1 -zn   -y simple.bw  ; unzip -u  simple_mat.zip &>/dev/null; cat simple_mat| grep G0005T001 simple_mat| cut -f8-12| perl -npe 's/\\t/|/g' | sed 's/0000000005//g' | sed 's/69999999995/7/g'`
          [ "$result" = "2.0|3.333333|3.333333|2.0|2.666667" ]
        }
        
        #mk_matrix: test NO orientation (-nst)
        @test "mk_matrix_15" {
         result=`rm -Rf simple_mat*; cat simple.gtf  |gtftk mk_matrix -nst -u 5 -d 5 -t transcript -w 5  -o simple_mat -c simple.chromInfo -V 1 -zn   -y simple.bw  ; unzip -u  simple_mat.zip &>/dev/null; cat simple_mat| grep G0005T001 simple_mat| cut -f8-12| perl -npe 's/\\t/|/g' | sed 's/0000000005//g' | sed 's/69999999995/7/g'`
          [ "$result" = "2.666667|2.0|3.333333|3.333333|2.0" ]
        }
      
    '''

    CmdObject(name="mk_matrix",
              message="Compute a coverage matrix (see profile).",
              parser=make_parser(),
              fun=os.path.abspath(__file__),
              group="coverage",
              updated=__updated__,
              desc=__doc__,
              notes=__notes__,
              test=test)

test = '''
    #control_list
    @test "control_list_1" {
      result=`gtftk control_list -i pygtftk/data/control_list/control_list_data.txt -r pygtftk/data/control_list/control_list_reference.txt -D ; cat control_list/control_list.txt | cut -f2| perl -npe 's/\\n/,/'`
      [ "$result" = "V1,2.02,4.04,6.06," ]
    }
    
    #control_list
    @test "control_list_2" {
      result=` rm -Rf control_list`
      [ "$result" = "" ]
    }
            
    '''

    cmd = CmdObject(name="control_list",
                    message="Returns a list of gene matched for expression based on reference values.",
                    parser=make_parser(),
                    fun=control_list,
                    desc=__doc__,
                    updated=__updated__,
                    notes=__notes__,
                    group="miscellaneous",
                    test=test,
                    rlib=R_LIB)

#bed_to_gtf: test stdin and ine number
    @test "bed_to_gtf_1" {
     result=`gtftk select_by_key -i simple.gtf -k feature -v transcript| gtftk convert -f bed | gtftk bed_to_gtf | wc -l`
      [ "$result" -eq 15 ]
    }
    
    #bed_to_gtf: test column number
    @test "bed_to_gtf_2" {
     result=`gtftk select_by_key -i simple.gtf -k feature -v transcript| gtftk convert -f bed | gtftk bed_to_gtf | awk 'BEGIN{FS="\\t"}{print NF}' | sort | uniq`
      [ "$result" -eq 9 ]
    }

    """

    CMD = CmdObject(name="bed_to_gtf",
                    message="Convert a bed file to a gtf but with lots of empty fields...",
                    parser=make_parser(),
                    fun=os.path.abspath(__file__),
                    updated=__updated__,
                    desc=__doc__,
                    group="conversion",
                    test=test)

}
    
    #divergent: the number of exons is as expected.
    @test "divergent_4" {
     result=`gtftk divergent -i simple.gtf -c simple.chromInfo -u 4 -d 4 | awk '$3=="exon"'| wc -l`
      [ "$result" -eq 25 ]
    }
    
    #divergent: this region contains 4 divergent tx
    @test "divergent_5" {
     result=`gtftk divergent -u 18 -d 18 -c simple.chromInfo -i simple.gtf |  gtftk select_by_key -k feature -v  transcript| grep "dist_to_divergent \\"[0-9]"| gtftk tabulate -H -k transcript_id,dist_to_divergent,divergent| wc -l`
      [ "$result" -eq 4 ]
    }
    
    """
    CmdObject(name="divergent",
              message="Find transcripts with divergent promoters.",
              parser=make_parser(),
              fun=os.path.abspath(__file__),
              desc=__doc__,
              updated=__updated__,
              group="annotation",
              notes=__notes__,
              test=test)

#col_from_tab
    @test "col_from_tab_2" {
     result=`gtftk get_example | gtftk tabulate -k all -x |gtftk col_from_tab -H -c start,end,seqid| wc -l`
      [ "$result" -eq 70 ]
    }
    
    #col_from_tab
    @test "col_from_tab_3" {
     result=`gtftk get_example | gtftk tabulate -k all -x |gtftk col_from_tab -c start,end,seqid| awk 'BEGIN{FS=OFS="\\t"}{print NF}'| sort | uniq`
      [ "$result" -eq 3 ]
    }
    
    """
    from pygtftk.cmd_object import CmdObject

    CmdObject(name="col_from_tab",
              message="Select columns from a tabulated file based on their names.",
              parser=make_parser(),
              fun=os.path.abspath(__file__),
              updated=__updated__,
              desc=__doc__,
              group="miscellaneous",
              test=test)

# Check that the md5 -r signature is the same after regenerating...
    @test "convert_ensembl_11" {
     result=`gtftk get_example | grep -v "gene.*gene_id.*G0010"| gtftk convert_ensembl | md5 -r | sed 's/ .*//'`
      [ "$result" = "679aa6be7ee8d8402f4d05e05d2b49d5" ]
    }
           
    # Delete all genes and transcripts, regenerate, check md5 -r...
    @test "convert_ensembl_12" {
     result=`gtftk get_example | awk '$3 != "transcript"' | awk '$3 != "gene"' | gtftk convert_ensembl  | md5 -r | sed 's/ .*//'`
      [ "$result" = "679aa6be7ee8d8402f4d05e05d2b49d5" ]
    }
        
            
    """

    CMD = CmdObject(name="convert_ensembl",
                    message="Convert the GTF file to ensembl format. Essentially add 'transcript'/'gene' features.",
                    parser=make_parser(),
                    fun=os.path.abspath(__file__),
                    updated=__updated__,
                    notes=__notes__,
                    desc=__doc__,
                    group="conversion",
                    test=test)

result=`gtftk get_example -d mini_real | gtftk alt_prom H3K4me3_cond_1.bed H3K4me3_cond_2.bed| awk 'BEGIN{FS=OFS="\t"}$3=="CRMP1"||NR==1'| grep ENST00000513911 | grep ENST00000324989 | cut -f 25`
      [ "$result" = "1" ]
    }

    @test "alt_prom_2" {
     result=`gtftk get_example -d mini_real | gtftk alt_prom H3K4me3_cond_1.bed H3K4me3_cond_3.bed| awk 'BEGIN{FS=OFS="\t"}$3=="CRMP1"||NR==1'| grep ENST00000513911 | grep ENST00000324989 | cut -f 24`
      [ "$result" = "1" ]
    }

    @test "alt_prom_3" {
     result=`gtftk get_example -d mini_real | gtftk alt_prom H3K4me3_cond_2.bed H3K4me3_cond_3.bed| awk 'BEGIN{FS=OFS="\t"}$3=="CRMP1"||NR==1'| grep ENST00000513911 | grep ENST00000324989 | cut -f 24`
      [ "$result" = "1" ]
    }
    """

    CmdObject(name='alt_prom',
              message='Search for genes with alternative promoters.',
              parser=make_parser(),
              fun=alt_prom,
              desc=__doc__,
              notes=__notes__,
              updated=__updated__,
              group="annotation",
              test=test)

# should be the same as 'cat expected_sequence_minus_rv.fa | md5 -r'
    @test "get_tx_seq_20" {
     result=`gtftk get_tx_seq -i ids_minus.gtf -g chr1_hg38_10M.fa -l transcript_id | perl -ne 'print uc $_'> observed_sequence_minus_rv.fa; cat observed_sequence_minus_rv.fa | md5 -r | sed 's/ .*//'`
      [ "$result" = "6f40e63555a4bb6f849261b0fe9e928c" ]
    } 

    # Check the sequence of tx on minus strand compared to ensembl (no rev_comp). 
    # should be the same as 'cat expected_sequence_minus_no_rv.fa | md5 -r'
    @test "get_tx_seq_21" {
     result=`gtftk get_tx_seq -i ids_minus.gtf -g chr1_hg38_10M.fa -l transcript_id -n | perl -ne 'print uc $_'> observed_sequence_minus_no_rv.fa; cat observed_sequence_minus_no_rv.fa | md5 -r | sed 's/ .*//'`
      [ "$result" = "87c15b230b6057be091566ac29ada7a1" ]
    } 
        
    """

    CmdObject(name="get_tx_seq",
              message="Get transcript sequences in fasta format.",
              parser=make_parser(),
              fun=os.path.abspath(__file__),
              group="sequences",
              desc=__doc__,
              notes=__notes__,
              test=test)

#profile: create dataset
    @test "profile_21" {
     result=`gtftk profile -D -i mini_real_promoter_pr.zip -g bwig -f chrom  -o profile_prom_5  -ph 15 -c "#66C2A5,#FC8D62,#8DA0CB,#6734AF"   -pf png -if example_09.png`
      [ -s "example_09.png" ]
    }
     
    #profile: create dataset
    @test "profile_22" {
     result=`gtftk profile -th classic -D -i mini_real_promoter_pr.zip -g bwig -f chrom  -o profile_prom_5  -ph 15 -c "#66C2A5,#FC8D62,#8DA0CB,#6734AF"   -pf png -if example_09b.png`
      [ -s "example_09b.png" ]
    }
    

    '''
    cmd = CmdObject(name="profile",
                    message="Create coverage profile using a bigWig as input.",
                    parser=make_parser(),
                    fun=draw_profile,
                    desc=__doc__,
                    updated=__updated__,
                    notes=__notes__,
                    references=__references__,
                    group="coverage",
                    test=test,
                    rlib=R_LIB)

[ "$result" -eq 3 ]
    }
    
    # Convert: check zero based (bed6)
    @test "convert_4" {
     result=`gtftk convert -i simple.gtf -n gene_id,transcript_id,start | cut -f2| head -n 1`
      [ "$result" -eq 124 ]
    }
    # Convert: check zero based (bed3)
    @test "convert_4" {
     result=`gtftk convert -i simple.gtf -f bed3 | cut -f2| head -n 1`
      [ "$result" -eq 124 ]
    }
    '''

    CmdObject(name="convert",
              message="Convert a GTF to various format including bed.",
              parser=make_parser(),
              fun=os.path.abspath(__file__),
              updated=__updated__,
              desc=__doc__,
              group="conversion",
              test=test)