NAME
    SimilarityMatricesFingerprints.pl - Calculate similarity matrices using
    fingerprints strings data in SD, FP and CSV/TSV text file(s)

SYNOPSIS
    SimilarityMatricesFingerprints.pl SDFile(s) FPFile(s) TextFile(s)...

    SimilarityMatricesFingerprints.pl [--alpha *number*] [--beta *number*]
    [-b, --BitVectorComparisonMode *All | "TanimotoSimilarity,[
    TverskySimilarity, ... ]"*] [-c, --ColMode *ColNum | ColLabel*]
    [--CompoundIDCol *col number | col name*] [--CompoundIDPrefix *text*]
    [--CompoundIDField *DataFieldName*] [--CompoundIDMode *DataField |
    MolName | LabelPrefix | MolNameOrLabelPrefix*] [-d, --detail
    *InfoLevel*] [-f, --fast] [--FingerprintsCol *col number | col name*]
    [--FingerprintsField *FieldLabel*] [-h, --help] [--InDelim *comma |
    semicolon*] [--InputDataMode *LoadInMemory | ScanFile*] [-m, --mode
    *AutoDetect | FingerprintsBitVectorString | FingerprintsVectorString*]
    [--OutDelim *comma | tab | semicolon*] [--OutMatrixFormat
    *RowsAndColumns | IDPairsAndValue*] [--OutMatrixType *FullMatrix |
    UpperTriangularMatrix | LowerTriangularMatrix*] [-o, --overwrite] [-p,
    --precision *number*] [-q, --quote *Yes | No*] [-r, --root *RootName*]
    [-v, --VectorComparisonMode *All | "TanimotoSimilairy, [
    ManhattanDistance, ...]"*] [--VectorComparisonFormulism *All |
    "AlgebraicForm, [BinaryForm, SetTheoreticForm]"*] [-w, --WorkingDir
    dirname] SDFile(s) FPFile(s) TextFile(s)...

DESCRIPTION
    Calculate similarity matrices using fingerprint bit-vector or vector
    strings data in *SD, FP and CSV/TSV* text file(s) and generate CSV/TSV
    text file(s) containing values for specified similarity and distance
    coefficients.

    The scripts SimilarityMatrixSDFiles.pl and SimilarityMatrixTextFiles.pl
    have been removed from the current release of MayaChemTools and their
    functionality merged with this script.

    The valid *SDFile* extensions are *.sdf* and *.sd*. All SD files in a
    current directory can be specified either by **.sdf* or the current
    directory name.

    The valid *FPFile* extensions are *.fpf* and *.fp*. All FP files in a
    current directory can be specified either by **.fpf* or the current
    directory name.

    The valid *TextFile* extensions are *.csv* and *.tsv* for
    comma/semicolon and tab delimited text files respectively. All other
    file names are ignored. All text files in a current directory can be
    specified by **.csv*, **.tsv*, or the current directory name. The
    --indelim option determines the format of *TextFile(s)*. Any file which
    doesn't correspond to the format indicated by --indelim option is
    ignored.

    Example of *FP* file containing fingerprints bit-vector string data:

        #
        # Package = MayaChemTools 7.4
        # ReleaseDate = Oct 21, 2010
        #
        # TimeStamp =  Mon Mar 7 15:14:01 2011
        #
        # FingerprintsStringType = FingerprintsBitVector
        #
        # Description = PathLengthBits:AtomicInvariantsAtomTypes:MinLength1:...
        # Size = 1024
        # BitStringFormat = HexadecimalString
        # BitsOrder = Ascending
        #
        Cmpd1 9c8460989ec8a49913991a6603130b0a19e8051c89184414953800cc21510...
        Cmpd2 000000249400840040100042011001001980410c000000001010088001120...
        ... ...
        ... ..

    Example of *FP* file containing fingerprints vector string data:

        #
        # Package = MayaChemTools 7.4
        # ReleaseDate = Oct 21, 2010
        #
        # TimeStamp =  Mon Mar 7 15:14:01 2011
        #
        # FingerprintsStringType = FingerprintsVector
        #
        # Description = PathLengthBits:AtomicInvariantsAtomTypes:MinLength1:...
        # VectorStringFormat = IDsAndValuesString
        # VectorValuesType = NumericalValues
        #
        Cmpd1 338;C F N O C:C C:N C=O CC CF CN CO C:C:C C:C:N C:CC C:CF C:CN C:
        N:C C:NC CC:N CC=O CCC CCN CCO CNC NC=O O=CO C:C:C:C C:C:C:N C:C:CC...;
        33 1 2 5 21 2 2 12 1 3 3 20 2 10 2 2 1 2 2 2 8 2 5 1 1 1 19 2 8 2 2 2 2
        6 2 2 2 2 2 2 2 2 3 2 2 1 4 1 5 1 1 18 6 2 2 1 2 10 2 1 2 1 2 2 2 2 ...
        Cmpd2 103;C N O C=N C=O CC CN CO CC=O CCC CCN CCO CNC N=CN NC=O NCN O=C
        O C CC=O CCCC CCCN CCCO CCNC CNC=N CNC=O CNCN CCCC=O CCCCC CCCCN CC...;
        15 4 4 1 2 13 5 2 2 15 5 3 2 2 1 1 1 2 17 7 6 5 1 1 1 2 15 8 5 7 2 2 2 2
        1 2 1 1 3 15 7 6 8 3 4 4 3 2 2 1 2 3 14 2 4 7 4 4 4 4 1 1 1 2 1 1 1 ...
        ... ...
        ... ...

    Example of *SD* file containing fingerprints bit-vector string data:

        ... ...
        ... ...
        $$$$
        ... ...
        ... ...
        ... ...
        41 44  0  0  0  0  0  0  0  0999 V2000
         -3.3652    1.4499    0.0000 C   0  0  0  0  0  0  0  0  0  0  0  0
        ... ...
        2  3  1  0  0  0  0
        ... ...
        M  END
        >  <CmpdID>
        Cmpd1

        >  <PathLengthFingerprints>
        FingerprintsBitVector;PathLengthBits:AtomicInvariantsAtomTypes:MinLengt
        h1:MaxLength8;1024;HexadecimalString;Ascending;9c8460989ec8a49913991a66
        03130b0a19e8051c89184414953800cc2151082844a201042800130860308e8204d4028
        00831048940e44281c00060449a5000ac80c894114e006321264401600846c050164462
        08190410805000304a10205b0100e04c0038ba0fad0209c0ca8b1200012268b61c0026a
        aa0660a11014a011d46

        $$$$
        ... ...
        ... ...

    Example of CSV *Text* file containing fingerprints bit-vector string
    data:

        "CompoundID","PathLengthFingerprints"
        "Cmpd1","FingerprintsBitVector;PathLengthBits:AtomicInvariantsAtomTypes
        :MinLength1:MaxLength8;1024;HexadecimalString;Ascending;9c8460989ec8a4
        9913991a6603130b0a19e8051c89184414953800cc2151082844a20104280013086030
        8e8204d402800831048940e44281c00060449a5000ac80c894114e006321264401..."
        ... ...
        ... ...

    The current release of MayaChemTools supports the following types of
    fingerprint bit-vector and vector strings:

        FingerprintsVector;AtomNeighborhoods:AtomicInvariantsAtomTypes:MinRadi
        us0:MaxRadius2;41;AlphaNumericalValues;ValuesString;NR0-C.X1.BO1.H3-AT
        C1:NR1-C.X3.BO3.H1-ATC1:NR2-C.X1.BO1.H3-ATC1:NR2-C.X3.BO4-ATC1 NR0-C.X
        1.BO1.H3-ATC1:NR1-C.X3.BO3.H1-ATC1:NR2-C.X1.BO1.H3-ATC1:NR2-C.X3.BO4-A
        TC1 NR0-C.X2.BO2.H2-ATC1:NR1-C.X2.BO2.H2-ATC1:NR1-C.X3.BO3.H1-ATC1:NR2
        -C.X2.BO2.H2-ATC1:NR2-N.X3.BO3-ATC1:NR2-O.X1.BO1.H1-ATC1 NR0-C.X2.B...

        FingerprintsVector;AtomTypesCount:AtomicInvariantsAtomTypes:ArbitraryS
        ize;10;NumericalValues;IDsAndValuesString;C.X1.BO1.H3 C.X2.BO2.H2 C.X2
        .BO3.H1 C.X3.BO3.H1 C.X3.BO4 F.X1.BO1 N.X2.BO2.H1 N.X3.BO3 O.X1.BO1.H1
        O.X1.BO2;2 4 14 3 10 1 1 1 3 2

        FingerprintsVector;AtomTypesCount:SLogPAtomTypes:ArbitrarySize;16;Nume
        ricalValues;IDsAndValuesString;C1 C10 C11 C14 C18 C20 C21 C22 C5 CS F
        N11 N4 O10 O2 O9;5 1 1 1 14 4 2 1 2 2 1 1 1 1 3 1

        FingerprintsVector;AtomTypesCount:SLogPAtomTypes:FixedSize;67;OrderedN
        umericalValues;IDsAndValuesString;C1 C2 C3 C4 C5 C6 C7 C8 C9 C10 C11 C
        12 C13 C14 C15 C16 C17 C18 C19 C20 C21 C22 C23 C24 C25 C26 C27 CS N1 N
        2 N3 N4 N5 N6 N7 N8 N9 N10 N11 N12 N13 N14 NS O1 O2 O3 O4 O5 O6 O7 O8
        O9 O10 O11 O12 OS F Cl Br I Hal P S1 S2 S3 Me1 Me2;5 0 0 0 2 0 0 0 0 1
        1 0 0 1 0 0 0 14 0 4 2 1 0 0 0 0 0 2 0 0 0 1 0 0 0 0 0 0 1 0 0 0 0...

        FingerprintsVector;EStateIndicies:ArbitrarySize;11;NumericalValues;IDs
        AndValuesString;SaaCH SaasC SaasN SdO SdssC SsCH3 SsF SsOH SssCH2 SssN
        H SsssCH;24.778 4.387 1.993 25.023 -1.435 3.975 14.006 29.759 -0.073 3
        .024 -2.270

        FingerprintsVector;EStateIndicies:FixedSize;87;OrderedNumericalValues;
        ValuesString;0 0 0 0 0 0 0 3.975 0 -0.073 0 0 24.778 -2.270 0 0 -1.435
        4.387 0 0 0 0 0 0 3.024 0 0 0 0 0 0 0 1.993 0 29.759 25.023 0 0 0 0 1
        4.006 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
        0 0 0 0 0 0 0 0 0 0 0 0 0 0

        FingerprintsVector;ExtendedConnectivity:AtomicInvariantsAtomTypes:Radi
        us2;60;AlphaNumericalValues;ValuesString;73555770 333564680 352413391
        666191900 1001270906 1371674323 1481469939 1977749791 2006158649 21414
        08799 49532520 64643108 79385615 96062769 273726379 564565671 85514103
        5 906706094 988546669 1018231313 1032696425 1197507444 1331250018 1338
        532734 1455473691 1607485225 1609687129 1631614296 1670251330 17303...

        FingerprintsVector;ExtendedConnectivityCount:AtomicInvariantsAtomTypes
        :Radius2;60;NumericalValues;IDsAndValuesString;73555770 333564680 3524
        13391 666191900 1001270906 1371674323 1481469939 1977749791 2006158649
        2141408799 49532520 64643108 79385615 96062769 273726379 564565671...;
        3 2 1 1 14 1 2 10 4 3 1 1 1 1 2 1 2 1 1 1 2 3 1 1 2 1 3 3 8 2 2 2 6 2
        1 2 1 1 2 1 1 1 2 1 1 2 1 2 1 1 1 1 1 1 1 1 1 2 1 1

        FingerprintsBitVector;ExtendedConnectivityBits:AtomicInvariantsAtomTyp
        es:Radius2;1024;BinaryString;Ascending;0000000000000000000000000000100
        0000000001010000000110000011000000000000100000000000000000000000100001
        1000000110000000000000000000000000010011000000000000000000000000010000
        0000000000000000000000000010000000000000000001000000000000000000000000
        0000000000010000100001000000000000101000000000000000100000000000000...

        FingerprintsVector;ExtendedConnectivity:FunctionalClassAtomTypes:Radiu
        s2;57;AlphaNumericalValues;ValuesString;24769214 508787397 850393286 8
        62102353 981185303 1231636850 1649386610 1941540674 263599683 32920567
        1 571109041 639579325 683993318 723853089 810600886 885767127 90326012
        7 958841485 981022393 1126908698 1152248391 1317567065 1421489994 1455
        632544 1557272891 1826413669 1983319256 2015750777 2029559552 20404...

        FingerprintsVector;ExtendedConnectivity:EStateAtomTypes:Radius2;62;Alp
        haNumericalValues;ValuesString;25189973 528584866 662581668 671034184
        926543080 1347067490 1738510057 1759600920 2034425745 2097234755 21450
        44754 96779665 180364292 341712110 345278822 386540408 387387308 50430
        1706 617094135 771528807 957666640 997798220 1158349170 1291258082 134
        1138533 1395329837 1420277211 1479584608 1486476397 1487556246 1566...

        FingerprintsBitVector;MACCSKeyBits;166;BinaryString;Ascending;00000000
        0000000000000000000000000000000001001000010010000000010010000000011100
        0100101010111100011011000100110110000011011110100110111111111111011111
        11111111111110111000

        FingerprintsBitVector;MACCSKeyBits;322;BinaryString;Ascending;11101011
        1110011111100101111111000111101100110000000000000011100010000000000000
        0000000000000000000000000000000000000000000000101000000000000000000000
        0000000000000000000000000000000000000000000000000000000000000000000000
        0000000000000000000000000000000000000011000000000000000000000000000000
        0000000000000000000000000000000000000000

        FingerprintsVector;MACCSKeyCount;166;OrderedNumericalValues;ValuesStri
        ng;0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
        0 0 0 0 0 0 0 1 0 0 3 0 0 0 0 4 0 0 2 0 0 0 0 0 0 0 0 2 0 0 2 0 0 0 0
        0 0 0 0 1 1 8 0 0 0 1 0 0 1 0 1 0 1 0 3 1 3 1 0 0 0 1 2 0 11 1 0 0 0
        5 0 0 1 2 0 1 1 0 0 0 0 0 1 1 0 1 1 1 1 0 4 0 0 1 1 0 4 6 1 1 1 2 1 1
        3 5 2 2 0 5 3 5 1 1 2 5 1 2 1 2 4 8 3 5 5 2 2 0 3 5 4 1

        FingerprintsVector;MACCSKeyCount;322;OrderedNumericalValues;ValuesStri
        ng;14 8 2 0 2 0 4 4 2 1 4 0 0 2 5 10 5 2 1 0 0 2 0 5 13 3 28 5 5 3 0 0
        0 4 2 1 1 0 1 1 0 0 2 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 22 5 3 0 0 0 1 0
        0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
        0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 11 0 2 0 0 0 0 0 0 0 0 0
        0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 ...

        FingerprintsBitVector;PathLengthBits:AtomicInvariantsAtomTypes:MinLeng
        th1:MaxLength8;1024;BinaryString;Ascending;001000010011010101011000110
        0100010101011000101001011100110001000010001001101000001001001001001000
        0010110100000111001001000001001010100100100000000011000000101001011100
        0010000001000101010100000100111100110111011011011000000010110111001101
        0101100011000000010001000011000010100011101100001000001000100000000...

        FingerprintsVector;PathLengthCount:AtomicInvariantsAtomTypes:MinLength
        1:MaxLength8;432;NumericalValues;IDsAndValuesPairsString;C.X1.BO1.H3 2
        C.X2.BO2.H2 4 C.X2.BO3.H1 14 C.X3.BO3.H1 3 C.X3.BO4 10 F.X1.BO1 1 N.X
        2.BO2.H1 1 N.X3.BO3 1 O.X1.BO1.H1 3 O.X1.BO2 2 C.X1.BO1.H3C.X3.BO3.H1
        2 C.X2.BO2.H2C.X2.BO2.H2 1 C.X2.BO2.H2C.X3.BO3.H1 4 C.X2.BO2.H2C.X3.BO
        4 1 C.X2.BO2.H2N.X3.BO3 1 C.X2.BO3.H1:C.X2.BO3.H1 10 C.X2.BO3.H1:C....

        FingerprintsVector;PathLengthCount:MMFF94AtomTypes:MinLength1:MaxLengt
        h8;463;NumericalValues;IDsAndValuesPairsString;C5A 2 C5B 2 C=ON 1 CB 1
        8 COO 1 CR 9 F 1 N5 1 NC=O 1 O=CN 1 O=CO 1 OC=O 1 OR 2 C5A:C5B 2 C5A:N
        5 2 C5ACB 1 C5ACR 1 C5B:C5B 1 C5BC=ON 1 C5BCB 1 C=ON=O=CN 1 C=ONNC=O 1
        CB:CB 18 CBF 1 CBNC=O 1 COO=O=CO 1 COOCR 1 COOOC=O 1 CRCR 7 CRN5 1 CR
        OR 2 C5A:C5B:C5B 2 C5A:C5BC=ON 1 C5A:C5BCB 1 C5A:N5:C5A 1 C5A:N5CR ...

        FingerprintsVector;TopologicalAtomPairs:AtomicInvariantsAtomTypes:MinD
        istance1:MaxDistance10;223;NumericalValues;IDsAndValuesString;C.X1.BO1
        .H3-D1-C.X3.BO3.H1 C.X2.BO2.H2-D1-C.X2.BO2.H2 C.X2.BO2.H2-D1-C.X3.BO3.
        H1 C.X2.BO2.H2-D1-C.X3.BO4 C.X2.BO2.H2-D1-N.X3.BO3 C.X2.BO3.H1-D1-...;
        2 1 4 1 1 10 8 1 2 6 1 2 2 1 2 1 2 2 1 2 1 5 1 10 12 2 2 1 2 1 9 1 3 1
        1 1 2 2 1 3 6 1 6 14 2 2 2 3 1 3 1 8 2 2 1 3 2 6 1 2 2 5 1 3 1 23 1...

        FingerprintsVector;TopologicalAtomPairs:FunctionalClassAtomTypes:MinDi
        stance1:MaxDistance10;144;NumericalValues;IDsAndValuesString;Ar-D1-Ar
        Ar-D1-Ar.HBA Ar-D1-HBD Ar-D1-Hal Ar-D1-None Ar.HBA-D1-None HBA-D1-NI H
        BA-D1-None HBA.HBD-D1-NI HBA.HBD-D1-None HBD-D1-None NI-D1-None No...;
        23 2 1 1 2 1 1 1 1 2 1 1 7 28 3 1 3 2 8 2 1 1 1 5 1 5 24 3 3 4 2 13 4
        1 1 4 1 5 22 4 4 3 1 19 1 1 1 1 1 2 2 3 1 1 8 25 4 5 2 3 1 26 1 4 1 ...

        FingerprintsVector;TopologicalAtomTorsions:AtomicInvariantsAtomTypes;3
        3;NumericalValues;IDsAndValuesString;C.X1.BO1.H3-C.X3.BO3.H1-C.X3.BO4-
        C.X3.BO4 C.X1.BO1.H3-C.X3.BO3.H1-C.X3.BO4-N.X3.BO3 C.X2.BO2.H2-C.X2.BO
        2.H2-C.X3.BO3.H1-C.X2.BO2.H2 C.X2.BO2.H2-C.X2.BO2.H2-C.X3.BO3.H1-O...;
        2 2 1 1 2 2 1 1 3 4 4 8 4 2 2 6 2 2 1 2 1 1 2 1 1 2 6 2 4 2 1 3 1

        FingerprintsVector;TopologicalAtomTorsions:EStateAtomTypes;36;Numerica
        lValues;IDsAndValuesString;aaCH-aaCH-aaCH-aaCH aaCH-aaCH-aaCH-aasC aaC
        H-aaCH-aasC-aaCH aaCH-aaCH-aasC-aasC aaCH-aaCH-aasC-sF aaCH-aaCH-aasC-
        ssNH aaCH-aasC-aasC-aasC aaCH-aasC-aasC-aasN aaCH-aasC-ssNH-dssC a...;
        4 4 8 4 2 2 6 2 2 2 4 3 2 1 3 3 2 2 2 1 2 1 1 1 2 1 1 1 1 1 1 1 2 1 1 2

        FingerprintsVector;TopologicalAtomTriplets:AtomicInvariantsAtomTypes:M
        inDistance1:MaxDistance10;3096;NumericalValues;IDsAndValuesString;C.X1
        .BO1.H3-D1-C.X1.BO1.H3-D1-C.X3.BO3.H1-D2 C.X1.BO1.H3-D1-C.X2.BO2.H2-D1
        0-C.X3.BO4-D9 C.X1.BO1.H3-D1-C.X2.BO2.H2-D3-N.X3.BO3-D4 C.X1.BO1.H3-D1
        -C.X2.BO2.H2-D4-C.X2.BO2.H2-D5 C.X1.BO1.H3-D1-C.X2.BO2.H2-D6-C.X3....;
        1 2 2 2 2 2 2 2 8 8 4 8 4 4 2 2 2 2 4 2 2 2 4 2 2 2 2 1 2 2 4 4 4 2 2
        2 4 4 4 8 4 4 2 4 4 4 2 4 4 2 2 2 2 2 2 2 2 1 2 2 2 2 2 2 2 2 2 2 8...

        FingerprintsVector;TopologicalAtomTriplets:SYBYLAtomTypes:MinDistance1
        :MaxDistance10;2332;NumericalValues;IDsAndValuesString;C.2-D1-C.2-D9-C
        .3-D10 C.2-D1-C.2-D9-C.ar-D10 C.2-D1-C.3-D1-C.3-D2 C.2-D1-C.3-D10-C.3-
        D9 C.2-D1-C.3-D2-C.3-D3 C.2-D1-C.3-D2-C.ar-D3 C.2-D1-C.3-D3-C.3-D4 C.2
        -D1-C.3-D3-N.ar-D4 C.2-D1-C.3-D3-O.3-D2 C.2-D1-C.3-D4-C.3-D5 C.2-D1-C.
        3-D5-C.3-D6 C.2-D1-C.3-D5-O.3-D4 C.2-D1-C.3-D6-C.3-D7 C.2-D1-C.3-D7...

        FingerprintsVector;TopologicalPharmacophoreAtomPairs:ArbitrarySize:Min
        Distance1:MaxDistance10;54;NumericalValues;IDsAndValuesString;H-D1-H H
        -D1-NI HBA-D1-NI HBD-D1-NI H-D2-H H-D2-HBA H-D2-HBD HBA-D2-HBA HBA-D2-
        HBD H-D3-H H-D3-HBA H-D3-HBD H-D3-NI HBA-D3-NI HBD-D3-NI H-D4-H H-D4-H
        BA H-D4-HBD HBA-D4-HBA HBA-D4-HBD HBD-D4-HBD H-D5-H H-D5-HBA H-D5-...;
        18 1 2 1 22 12 8 1 2 18 6 3 1 1 1 22 13 6 5 7 2 28 9 5 1 1 1 36 16 10
        3 4 1 37 10 8 1 35 10 9 3 3 1 28 7 7 4 18 16 12 5 1 2 1

        FingerprintsVector;TopologicalPharmacophoreAtomPairs:FixedSize:MinDist
        ance1:MaxDistance10;150;OrderedNumericalValues;ValuesString;18 0 0 1 0
        0 0 2 0 0 1 0 0 0 0 22 12 8 0 0 1 2 0 0 0 0 0 0 0 0 18 6 3 1 0 0 0 1
        0 0 1 0 0 0 0 22 13 6 0 0 5 7 0 0 2 0 0 0 0 0 28 9 5 1 0 0 0 1 0 0 1 0
        0 0 0 36 16 10 0 0 3 4 0 0 1 0 0 0 0 0 37 10 8 0 0 0 0 1 0 0 0 0 0 0
        0 35 10 9 0 0 3 3 0 0 1 0 0 0 0 0 28 7 7 4 0 0 0 0 0 0 0 0 0 0 0 18...

        FingerprintsVector;TopologicalPharmacophoreAtomTriplets:ArbitrarySize:
        MinDistance1:MaxDistance10;696;NumericalValues;IDsAndValuesString;Ar1-
        Ar1-Ar1 Ar1-Ar1-H1 Ar1-Ar1-HBA1 Ar1-Ar1-HBD1 Ar1-H1-H1 Ar1-H1-HBA1 Ar1
        -H1-HBD1 Ar1-HBA1-HBD1 H1-H1-H1 H1-H1-HBA1 H1-H1-HBD1 H1-HBA1-HBA1 H1-
        HBA1-HBD1 H1-HBA1-NI1 H1-HBD1-NI1 HBA1-HBA1-NI1 HBA1-HBD1-NI1 Ar1-...;
        46 106 8 3 83 11 4 1 21 5 3 1 2 2 1 1 1 100 101 18 11 145 132 26 14 23
        28 3 3 5 4 61 45 10 4 16 20 7 5 1 3 4 5 3 1 1 1 1 5 4 2 1 2 2 2 1 1 1
        119 123 24 15 185 202 41 25 22 17 3 5 85 95 18 11 23 17 3 1 1 6 4 ...

        FingerprintsVector;TopologicalPharmacophoreAtomTriplets:FixedSize:MinD
        istance1:MaxDistance10;2692;OrderedNumericalValues;ValuesString;46 106
        8 3 0 0 83 11 4 0 0 0 1 0 0 0 0 0 0 0 0 21 5 3 0 0 1 2 2 0 0 1 0 0 0
        0 0 0 1 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 100 101 18 11 0 0 145 132 26
        14 0 0 23 28 3 3 0 0 5 4 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 61 45 10 4 0
        0 16 20 7 5 1 0 3 4 5 3 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 1 1 0 0 5 ...

OPTIONS
    --alpha *number*
        Value of alpha parameter for calculating *Tversky* similarity
        coefficient specified for -b, --BitVectorComparisonMode option. It
        corresponds to weights assigned for bits set to "1" in a pair of
        fingerprint bit-vectors during the calculation of similarity
        coefficient. Possible values: *0 to 1*. Default value: <0.5>.

    --beta *number*
        Value of beta parameter for calculating *WeightedTanimoto* and
        *WeightedTversky* similarity coefficients specified for -b,
        --BitVectorComparisonMode option. It is used to weight the
        contributions of bits set to "0" during the calculation of
        similarity coefficients. Possible values: *0 to 1*. Default value of
        <1> makes *WeightedTanimoto* and *WeightedTversky* equivalent to
        *Tanimoto* and *Tversky*.

    -b, --BitVectorComparisonMode *All |
    "TanimotoSimilarity,[TverskySimilarity,...]"*
        Specify what similarity coefficients to use for calculating
        similarity matrices for fingerprints bit-vector strings data values
        in *TextFile(s)*: calculate similarity matrices for all supported
        similarity coefficients or specify a comma delimited list of
        similarity coefficients. Possible values: *All |
        "TanimotoSimilarity,[TverskySimilarity,...]*. Default:
        *TanimotoSimilarity*

        *All* uses complete list of supported similarity coefficients:
        *BaroniUrbaniSimilarity, BuserSimilarity, CosineSimilarity,
        DiceSimilarity, DennisSimilarity, ForbesSimilarity,
        FossumSimilarity, HamannSimilarity, JacardSimilarity,
        Kulczynski1Similarity, Kulczynski2Similarity, MatchingSimilarity,
        McConnaugheySimilarity, OchiaiSimilarity, PearsonSimilarity,
        RogersTanimotoSimilarity, RussellRaoSimilarity, SimpsonSimilarity,
        SkoalSneath1Similarity, SkoalSneath2Similarity,
        SkoalSneath3Similarity, TanimotoSimilarity, TverskySimilarity,
        YuleSimilarity, WeightedTanimotoSimilarity,
        WeightedTverskySimilarity*. These similarity coefficients are
        described below.

        For two fingerprint bit-vectors A and B of same size, let:

            Na = Number of bits set to "1" in A
            Nb = Number of bits set to "1" in B
            Nc = Number of bits set to "1" in both A and B
            Nd = Number of bits set to "0" in both A and B

            Nt = Number of bits set to "1" or "0" in A or B (Size of A or B)
            Nt = Na + Nb - Nc + Nd

            Na - Nc = Number of bits set to "1" in A but not in B
            Nb - Nc = Number of bits set to "1" in B but not in A

        Then, various similarity coefficients [ Ref. 40 - 42 ] for a pair of
        bit-vectors A and B are defined as follows:

        *BaroniUrbaniSimilarity*: ( SQRT( Nc * Nd ) + Nc ) / ( SQRT ( Nc *
        Nd ) + Nc + ( Na - Nc ) + ( Nb - Nc ) ) ( same as Buser )

        *BuserSimilarity*: ( SQRT ( Nc * Nd ) + Nc ) / ( SQRT ( Nc * Nd ) +
        Nc + ( Na - Nc ) + ( Nb - Nc ) ) ( same as BaroniUrbani )

        *CosineSimilarity*: Nc / SQRT ( Na * Nb ) (same as Ochiai)

        *DiceSimilarity*: (2 * Nc) / ( Na + Nb )

        *DennisSimilarity*: ( Nc * Nd - ( ( Na - Nc ) * ( Nb - Nc ) ) ) /
        SQRT ( Nt * Na * Nb)

        *ForbesSimilarity*: ( Nt * Nc ) / ( Na * Nb )

        *FossumSimilarity*: ( Nt * ( ( Nc - 1/2 ) ** 2 ) / ( Na * Nb )

        *HamannSimilarity*: ( ( Nc + Nd ) - ( Na - Nc ) - ( Nb - Nc ) ) / Nt

        *JaccardSimilarity*: Nc / ( ( Na - Nc) + ( Nb - Nc ) + Nc ) = Nc / (
        Na + Nb - Nc ) (same as Tanimoto)

        *Kulczynski1Similarity*: Nc / ( ( Na - Nc ) + ( Nb - Nc) ) = Nc / (
        Na + Nb - 2Nc )

        *Kulczynski2Similarity*: ( ( Nc / 2 ) * ( 2 * Nc + ( Na - Nc ) + (
        Nb - Nc) ) ) / ( ( Nc + ( Na - Nc ) ) * ( Nc + ( Nb - Nc ) ) ) = 0.5
        * ( Nc / Na + Nc / Nb )

        *MatchingSimilarity*: ( Nc + Nd ) / Nt

        *McConnaugheySimilarity*: ( Nc ** 2 - ( Na - Nc ) * ( Nb - Nc) ) / (
        Na * Nb )

        *OchiaiSimilarity*: Nc / SQRT ( Na * Nb ) (same as Cosine)

        *PearsonSimilarity*: ( ( Nc * Nd ) - ( ( Na - Nc ) * ( Nb - Nc ) ) /
        SQRT ( Na * Nb * ( Na - Nc + Nd ) * ( Nb - Nc + Nd ) )

        *RogersTanimotoSimilarity*: ( Nc + Nd ) / ( ( Na - Nc) + ( Nb - Nc)
        + Nt) = ( Nc + Nd ) / ( Na + Nb - 2Nc + Nt)

        *RussellRaoSimilarity*: Nc / Nt

        *SimpsonSimilarity*: Nc / MIN ( Na, Nb)

        *SkoalSneath1Similarity*: Nc / ( Nc + 2 * ( Na - Nc) + 2 * ( Nb -
        Nc) ) = Nc / ( 2 * Na + 2 * Nb - 3 * Nc )

        *SkoalSneath2Similarity*: ( 2 * Nc + 2 * Nd ) / ( Nc + Nd + Nt )

        *SkoalSneath3Similarity*: ( Nc + Nd ) / ( ( Na - Nc ) + ( Nb - Nc )
        ) = ( Nc + Nd ) / ( Na + Nb - 2 * Nc )

        *TanimotoSimilarity*: Nc / ( ( Na - Nc) + ( Nb - Nc ) + Nc ) = Nc /
        ( Na + Nb - Nc ) (same as Jaccard)

        *TverskySimilarity*: Nc / ( alpha * ( Na - Nc ) + ( 1 - alpha) * (
        Nb - Nc) + Nc ) = Nc / ( alpha * ( Na - Nb ) + Nb)

        *YuleSimilarity*: ( ( Nc * Nd ) - ( ( Na - Nc ) * ( Nb - Nc ) ) ) /
        ( ( Nc * Nd ) + ( ( Na - Nc ) * ( Nb - Nc ) ) )

        Values of Tanimoto/Jaccard and Tversky coefficients are dependent on
        only those bit which are set to "1" in both A and B. In order to
        take into account all bit positions, modified versions of Tanimoto [
        Ref. 42 ] and Tversky [ Ref. 43 ] have been developed.

        Let:

            Na' = Number of bits set to "0" in A
            Nb' = Number of bits set to "0" in B
            Nc' = Number of bits set to "0" in both A and B

        Tanimoto': Nc' / ( ( Na' - Nc') + ( Nb' - Nc' ) + Nc' ) = Nc' / (
        Na' + Nb' - Nc' )

        Tversky': Nc' / ( alpha * ( Na' - Nc' ) + ( 1 - alpha) * ( Nb' - Nc'
        ) + Nc' ) = Nc' / ( alpha * ( Na' - Nb' ) + Nb')

        Then:

        *WeightedTanimotoSimilarity* = beta * Tanimoto + (1 - beta) *
        Tanimoto'

        *WeightedTverskySimilarity* = beta * Tversky + (1 - beta) * Tversky'

    -c, --ColMode *ColNum | ColLabel*
        Specify how columns are identified in *TextFile(s)*: using column
        number or column label. Possible values: *ColNum or ColLabel*.
        Default value: *ColNum*.

    --CompoundIDCol *col number | col name*
        This value is -c, --ColMode mode specific. It specifies input
        *TextFile(s)* column to use for generating compound ID for
        similarity matrices in output *TextFile(s)*. Possible values: *col
        number or col label*. Default value: *first column containing the
        word compoundID in its column label or sequentially generated IDs*.

    --CompoundIDPrefix *text*
        Specify compound ID prefix to use during sequential generation of
        compound IDs for input *SDFile(s)* and *TextFile(s)*. Default value:
        *Cmpd*. The default value generates compound IDs which look like
        Cmpd<Number>.

        For input *SDFile(s)*, this value is only used during *LabelPrefix |
        MolNameOrLabelPrefix* values of --CompoundIDMode option; otherwise,
        it's ignored.

        Examples for *LabelPrefix* or *MolNameOrLabelPrefix* value of
        --CompoundIDMode:

            Compound

        The values specified above generates compound IDs which correspond
        to Compound<Number> instead of default value of Cmpd<Number>.

    --CompoundIDField *DataFieldName*
        Specify input *SDFile(s)* datafield label for generating compound
        IDs. This value is only used during *DataField* value of
        --CompoundIDMode option.

        Examples for *DataField* value of --CompoundIDMode:

            MolID
            ExtReg

    --CompoundIDMode *DataField | MolName | LabelPrefix |
    MolNameOrLabelPrefix*
        Specify how to generate compound IDs from input *SDFile(s)* for
        similarity matrix CSV/TSV text file(s): use a *SDFile(s)* datafield
        value; use molname line from *SDFile(s)*; generate a sequential ID
        with specific prefix; use combination of both MolName and
        LabelPrefix with usage of LabelPrefix values for empty molname
        lines.

        Possible values: *DataField | MolName | LabelPrefix |
        MolNameOrLabelPrefix*. Default: *LabelPrefix*.

        For *MolNameAndLabelPrefix* value of --CompoundIDMode, molname line
        in *SDFile(s)* takes precedence over sequential compound IDs
        generated using *LabelPrefix* and only empty molname values are
        replaced with sequential compound IDs.

    -d, --detail *InfoLevel*
        Level of information to print about lines being ignored. Default:
        *1*. Possible values: *1, 2 or 3*.

    -f, --fast
        In this mode, fingerprints columns specified using --FingerprintsCol
        for *TextFile(s)* and --FingerprintsField for *SDFile(s)* are
        assumed to contain valid fingerprints data and no checking is
        performed before calculating similarity matrices. By default,
        fingerprints data is validated before computing pairwise similarity
        and distance coefficients.

    --FingerprintsCol *col number | col name*
        This value is -c, --colmode specific. It specifies fingerprints
        column to use during calculation similarity matrices for
        *TextFile(s)*. Possible values: *col number or col label*. Default
        value: *first column containing the word Fingerprints in its column
        label*.

    --FingerprintsField *FieldLabel*
        Fingerprints field label to use during calculation similarity
        matrices for *SDFile(s)*. Default value: *first data field label
        containing the word Fingerprints in its label*

    -h, --help
        Print this help message.

    --InDelim *comma | semicolon*
        Input delimiter for CSV *TextFile(s)*. Possible values: *comma or
        semicolon*. Default value: *comma*. For TSV files, this option is
        ignored and *tab* is used as a delimiter.

    --InputDataMode *LoadInMemory | ScanFile*
        Specify how fingerprints bit-vector or vector strings data from *SD,
        FP and CSV/TSV* fingerprint file(s) is processed: Retrieve, process
        and load all available fingerprints data in memory; Retrieve and
        process data for fingerprints one at a time. Possible values :
        *LoadInMemory | ScanFile*. Default: *LoadInMemory*.

        During *LoadInMemory* value of --InputDataMode, fingerprints
        bit-vector or vector strings data from input file is retrieved,
        processed, and loaded into memory all at once as fingerprints
        objects for generation for similarity matrices.

        During *ScanFile* value of --InputDataMode, multiple passes over the
        input fingerprints file are performed to retrieve and process
        fingerprints bit-vector or vector strings data one at a time to
        generate fingerprints objects used during generation of similarity
        matrices. A temporary copy of the input fingerprints file is made at
        the start and deleted after generating the matrices.

        *ScanFile* value of --InputDataMode allows processing of arbitrary
        large fingerprints files without any additional memory requirement.

    -m, --mode *AutoDetect | FingerprintsBitVectorString |
    FingerprintsVectorString*
        Format of fingerprint strings data in *TextFile(s)*: automatically
        detect format of fingerprints string created by MayaChemTools
        fingerprints generation scripts or explicitly specify its format.
        Possible values: *AutoDetect | FingerprintsBitVectorString |
        FingerprintsVectorString*. Default value: *AutoDetect*.

    --OutDelim *comma | tab | semicolon*
        Delimiter for output CSV/TSV text file(s). Possible values: *comma,
        tab, or semicolon* Default value: *comma*.

    --OutMatrixFormat *RowsAndColumns | IDPairsAndValue*
        Specify how similarity or distance values calculated for
        fingerprints vector and bit-vector strings are written to the output
        CSV/TSV text file(s): Generate text files containing rows and
        columns with their labels corresponding to compound IDs and each
        matrix element value corresponding to similarity or distance between
        corresponding compounds; Generate text files containing rows
        containing compoundIDs for two compounds followed by similarity or
        distance value between these compounds.

        Possible values: *RowsAndColumns, or IDPairsAndValue*. Default
        value: *RowsAndColumns*.

        The value of --OutMatrixFormat in conjunction with --OutMatrixType
        determines type of data written to output files and allows
        generation of up to 6 different output data formats:

            OutMatrixFormat OutMatrixType

            RowsAndColumns  FullMatrix   [ DEFAULT ]
            RowsAndColumns  UpperTriangularMatrix
            RowsAndColumns  LowerTriangularMatrix

            IDPairsAndValue FullMatrix
            IDPairsAndValue UpperTriangularMatrix
            IDPairsAndValue LowerTriangularMatrix

        Example of data in output file for *RowsAndColumns*
        --OutMatrixFormat value for *FullMatrix* valueof --OutMatrixType:

            "","Cmpd1","Cmpd2","Cmpd3","Cmpd4","Cmpd5","Cmpd6",... ...
            "Cmpd1","1","0.04","0.25","0.13","0.11","0.2",... ...
            "Cmpd2","0.04","1","0.06","0.05","0.19","0.07",... ...
            "Cmpd3","0.25","0.06","1","0.12","0.22","0.25",... ...
            "Cmpd4","0.13","0.05","0.12","1","0.11","0.13",... ...
            "Cmpd5","0.11","0.19","0.22","0.11","1","0.17",... ...
            "Cmpd6","0.2","0.07","0.25","0.13","0.17","1",... ...
            ... ... ..
            ... ... ..
            ... ... ..

        Example of data in output file for *RowsAndColumns*
        --OutMatrixFormat value for *UpperTriangularMatrix* value of
        --OutMatrixType:

            "","Cmpd1","Cmpd2","Cmpd3","Cmpd4","Cmpd5","Cmpd6",... ...
            "Cmpd1","1","0.04","0.25","0.13","0.11","0.2",... ...
            "Cmpd2","1","0.06","0.05","0.19","0.07",... ...
            "Cmpd3","1","0.12","0.22","0.25",... ...
            "Cmpd4","1","0.11","0.13",... ...
            "Cmpd5","1","0.17",... ...
            "Cmpd6","1",... ...
            ... ... ..
            ... ... ..
            ... ... ..

        Example of data in output file for *RowsAndColumns*
        --OutMatrixFormat value for *LowerTriangularMatrix* value of
        --OutMatrixType:

            "","Cmpd1","Cmpd2","Cmpd3","Cmpd4","Cmpd5","Cmpd6",... ...
            "Cmpd1","1"
            "Cmpd2","0.04","1"
            "Cmpd3","0.25","0.06","1"
            "Cmpd4","0.13","0.05","0.12","1"
            "Cmpd5","0.11","0.19","0.22","0.11","1"
            "Cmpd6","0.2","0.07","0.25","0.13","0.17","1"
            ... ... ..
            ... ... ..
            ... ... ..

        Example of data in output file for *IDPairsAndValue*
        --OutMatrixFormat value for <FullMatrix> value of OutMatrixType:

            "CmpdID1","CmpdID2","Coefficient Value"
            "Cmpd1","Cmpd1","1"
            "Cmpd1","Cmpd2","0.04"
            "Cmpd1","Cmpd3","0.25"
            "Cmpd1","Cmpd4","0.13"
            ... ... ...
            ... ... ...
            ... ... ...
            "Cmpd2","Cmpd1","0.04"
            "Cmpd2","Cmpd2","1"
            "Cmpd2","Cmpd3","0.06"
            "Cmpd2","Cmpd4","0.05"
            ... ... ...
            ... ... ...
            ... ... ...
            "Cmpd3","Cmpd1","0.25"
            "Cmpd3","Cmpd2","0.06"
            "Cmpd3","Cmpd3","1"
            "Cmpd3","Cmpd4","0.12"
            ... ... ...
            ... ... ...
            ... ... ...

        Example of data in output file for *IDPairsAndValue*
        --OutMatrixFormat value for <UpperTriangularMatrix> value of
        --OutMatrixType:

            "CmpdID1","CmpdID2","Coefficient Value"
            "Cmpd1","Cmpd1","1"
            "Cmpd1","Cmpd2","0.04"
            "Cmpd1","Cmpd3","0.25"
            "Cmpd1","Cmpd4","0.13"
            ... ... ...
            ... ... ...
            ... ... ...
            "Cmpd2","Cmpd2","1"
            "Cmpd2","Cmpd3","0.06"
            "Cmpd2","Cmpd4","0.05"
            ... ... ...
            ... ... ...
            ... ... ...
            "Cmpd3","Cmpd3","1"
            "Cmpd3","Cmpd4","0.12"
            ... ... ...
            ... ... ...
            ... ... ...

        Example of data in output file for *IDPairsAndValue*
        --OutMatrixFormat value for <LowerTriangularMatrix> value of
        --OutMatrixType:

            "CmpdID1","CmpdID2","Coefficient Value"
            "Cmpd1","Cmpd1","1"
            "Cmpd2","Cmpd1","0.04"
            "Cmpd2","Cmpd2","1"
            "Cmpd3","Cmpd1","0.25"
            "Cmpd3","Cmpd2","0.06"
            "Cmpd3","Cmpd3","1"
            "Cmpd4","Cmpd1","0.13"
            "Cmpd4","Cmpd2","0.05"
            "Cmpd4","Cmpd3","0.12"
            "Cmpd4","Cmpd4","1"
            ... ... ...
            ... ... ...
            ... ... ...

    --OutMatrixType *FullMatrix | UpperTriangularMatrix |
    LowerTriangularMatrix*
        Type of similarity or distance matrix to calculate for fingerprints
        vector and bit-vector strings: Calculate full matrix; Calculate
        lower triangular matrix including diagonal; Calculate upper
        triangular matrix including diagonal.

        Possible values: *FullMatrix, UpperTriangularMatrix, or
        LowerTriangularMatrix*. Default value: *FullMatrix*.

        The value of --OutMatrixType in conjunction with --OutMatrixFormat
        determines type of data written to output files.

    -o, --overwrite
        Overwrite existing files

    -p, --precision *number*
        Precision of calculated values in the output file. Default: up to
        *2* decimal places. Valid values: positive integers.

    -q, --quote *Yes | No*
        Put quote around column values in output CSV/TSV text file(s).
        Possible values: *Yes or No*. Default value: *Yes*.

    -r, --root *RootName*
        New file name is generated using the root:
        <Root><BitVectorComparisonMode>.<Ext> or
        <Root><VectorComparisonMode><VectorComparisonFormulism>.<Ext>. The
        csv, and tsv <Ext> values are used for comma/semicolon, and tab
        delimited text files respectively. This option is ignored for
        multiple input files.

    -v, --VectorComparisonMode *All |
    "TanimotoSimilarity,[ManhattanDistance,...]"*
        Specify what similarity or distance coefficients to use for
        calculating similarity matrices for fingerprint vector strings data
        values in *TextFile(s)*: calculate similarity matrices for all
        supported similarity and distance coefficients or specify a comma
        delimited list of similarity and distance coefficients. Possible
        values: *All | "TanimotoSimilairy,[ManhattanDistance,..]"*. Default:
        *TanimotoSimilarity*.

        The value of -v, --VectorComparisonMode, in conjunction with
        --VectorComparisonFormulism, decides which type of similarity and
        distance coefficient formulism gets used.

        *All* uses complete list of supported similarity and distance
        coefficients: *CosineSimilarity, CzekanowskiSimilarity,
        DiceSimilarity, OchiaiSimilarity, JaccardSimilarity,
        SorensonSimilarity, TanimotoSimilarity, CityBlockDistance,
        EuclideanDistance, HammingDistance, ManhattanDistance,
        SoergelDistance*. These similarity and distance coefficients are
        described below.

        FingerprintsVector.pm module, used to calculate similarity and
        distance coefficients, provides support to perform comparison
        between vectors containing three different types of values:

        Type I: OrderedNumericalValues

            . Size of two vectors are same
            . Vectors contain real values in a specific order. For example: MACCS keys
              count, Topological pharmnacophore atom pairs and so on.

        Type II: UnorderedNumericalValues

            . Size of two vectors might not be same
            . Vectors contain unordered real value identified by value IDs. For example:
              Toplogical atom pairs, Topological atom torsions and so on

        Type III: AlphaNumericalValues

            . Size of two vectors might not be same
            . Vectors contain unordered alphanumerical values. For example: Extended
              connectivity fingerprints, atom neighborhood fingerprints.

        Before performing similarity or distance calculations between
        vectors containing UnorderedNumericalValues or AlphaNumericalValues,
        the vectors are transformed into vectors containing unique
        OrderedNumericalValues using value IDs for UnorderedNumericalValues
        and values itself for AlphaNumericalValues.

        Three forms of similarity and distance calculation between two
        vectors, specified using --VectorComparisonFormulism option, are
        supported: *AlgebraicForm, BinaryForm or SetTheoreticForm*.

        For *BinaryForm*, the ordered list of processed final vector values
        containing the value or count of each unique value type is simply
        converted into a binary vector containing 1s and 0s corresponding to
        presence or absence of values before calculating similarity or
        distance between two vectors.

        For two fingerprint vectors A and B of same size containing
        OrderedNumericalValues, let:

            N = Number values in A or B

            Xa = Values of vector A
            Xb = Values of vector B

            Xai = Value of ith element in A
            Xbi = Value of ith element in B

           SUM = Sum of i over N values

        For SetTheoreticForm of calculation between two vectors, let:

            SetIntersectionXaXb = SUM ( MIN ( Xai, Xbi ) )
            SetDifferenceXaXb = SUM ( Xai ) + SUM ( Xbi ) - SUM ( MIN ( Xai, Xbi ) )

        For BinaryForm of calculation between two vectors, let:

            Na = Number of bits set to "1" in A = SUM ( Xai )
            Nb = Number of bits set to "1" in B = SUM ( Xbi )
            Nc = Number of bits set to "1" in both A and B = SUM ( Xai * Xbi )
            Nd = Number of bits set to "0" in both A and B
               = SUM ( 1 - Xai - Xbi + Xai * Xbi)

            N = Number of bits set to "1" or "0" in A or B = Size of A or B = Na + Nb - Nc + Nd

        Additionally, for BinaryForm various values also correspond to:

            Na = | Xa |
            Nb = | Xb |
            Nc = | SetIntersectionXaXb |
            Nd = N - | SetDifferenceXaXb |

            | SetDifferenceXaXb | = N - Nd = Na + Nb - Nc + Nd - Nd = Na + Nb - Nc
                                  =  | Xa | + | Xb | - | SetIntersectionXaXb |

        Various similarity and distance coefficients [ Ref 40, Ref 62, Ref
        64 ] for a pair of vectors A and B in *AlgebraicForm, BinaryForm and
        SetTheoreticForm* are defined as follows:

        CityBlockDistance: ( same as HammingDistance and ManhattanDistance)

        *AlgebraicForm*: SUM ( ABS ( Xai - Xbi ) )

        *BinaryForm*: ( Na - Nc ) + ( Nb - Nc ) = Na + Nb - 2 * Nc

        *SetTheoreticForm*: | SetDifferenceXaXb | - | SetIntersectionXaXb |
        = SUM ( Xai ) + SUM ( Xbi ) - 2 * ( SUM ( MIN ( Xai, Xbi ) ) )

        CosineSimilarity: ( same as OchiaiSimilarityCoefficient)

        *AlgebraicForm*: SUM ( Xai * Xbi ) / SQRT ( SUM ( Xai ** 2) * SUM (
        Xbi ** 2) )

        *BinaryForm*: Nc / SQRT ( Na * Nb)

        *SetTheoreticForm*: | SetIntersectionXaXb | / SQRT ( |Xa| * |Xb| ) =
        SUM ( MIN ( Xai, Xbi ) ) / SQRT ( SUM ( Xai ) * SUM ( Xbi ) )

        CzekanowskiSimilarity: ( same as DiceSimilarity and
        SorensonSimilarity)

        *AlgebraicForm*: ( 2 * ( SUM ( Xai * Xbi ) ) ) / ( SUM ( Xai ** 2) +
        SUM ( Xbi **2 ) )

        *BinaryForm*: 2 * Nc / ( Na + Nb )

        *SetTheoreticForm*: 2 * | SetIntersectionXaXb | / ( |Xa| + |Xb| ) =
        2 * ( SUM ( MIN ( Xai, Xbi ) ) ) / ( SUM ( Xai ) + SUM ( Xbi ) )

        DiceSimilarity: ( same as CzekanowskiSimilarity and
        SorensonSimilarity)

        *AlgebraicForm*: ( 2 * ( SUM ( Xai * Xbi ) ) ) / ( SUM ( Xai ** 2) +
        SUM ( Xbi **2 ) )

        *BinaryForm*: 2 * Nc / ( Na + Nb )

        *SetTheoreticForm*: 2 * | SetIntersectionXaXb | / ( |Xa| + |Xb| ) =
        2 * ( SUM ( MIN ( Xai, Xbi ) ) ) / ( SUM ( Xai ) + SUM ( Xbi ) )

        EuclideanDistance:

        *AlgebraicForm*: SQRT ( SUM ( ( ( Xai - Xbi ) ** 2 ) ) )

        *BinaryForm*: SQRT ( ( Na - Nc ) + ( Nb - Nc ) ) = SQRT ( Na + Nb -
        2 * Nc )

        *SetTheoreticForm*: SQRT ( | SetDifferenceXaXb | - |
        SetIntersectionXaXb | ) = SQRT ( SUM ( Xai ) + SUM ( Xbi ) - 2 * (
        SUM ( MIN ( Xai, Xbi ) ) ) )

        HammingDistance: ( same as CityBlockDistance and ManhattanDistance)

        *AlgebraicForm*: SUM ( ABS ( Xai - Xbi ) )

        *BinaryForm*: ( Na - Nc ) + ( Nb - Nc ) = Na + Nb - 2 * Nc

        *SetTheoreticForm*: | SetDifferenceXaXb | - | SetIntersectionXaXb |
        = SUM ( Xai ) + SUM ( Xbi ) - 2 * ( SUM ( MIN ( Xai, Xbi ) ) )

        JaccardSimilarity: ( same as TanimotoSimilarity)

        *AlgebraicForm*: SUM ( Xai * Xbi ) / ( SUM ( Xai ** 2 ) + SUM ( Xbi
        ** 2 ) - SUM ( Xai * Xbi ) )

        *BinaryForm*: Nc / ( ( Na - Nc ) + ( Nb - Nc ) + Nc ) = Nc / ( Na +
        Nb - Nc )

        *SetTheoreticForm*: | SetIntersectionXaXb | / | SetDifferenceXaXb |
        = SUM ( MIN ( Xai, Xbi ) ) / ( SUM ( Xai ) + SUM ( Xbi ) - SUM ( MIN
        ( Xai, Xbi ) ) )

        ManhattanDistance: ( same as CityBlockDistance and HammingDistance)

        *AlgebraicForm*: SUM ( ABS ( Xai - Xbi ) )

        *BinaryForm*: ( Na - Nc ) + ( Nb - Nc ) = Na + Nb - 2 * Nc

        *SetTheoreticForm*: | SetDifferenceXaXb | - | SetIntersectionXaXb |
        = SUM ( Xai ) + SUM ( Xbi ) - 2 * ( SUM ( MIN ( Xai, Xbi ) ) )

        OchiaiSimilarity: ( same as CosineSimilarity)

        *AlgebraicForm*: SUM ( Xai * Xbi ) / SQRT ( SUM ( Xai ** 2) * SUM (
        Xbi ** 2) )

        *BinaryForm*: Nc / SQRT ( Na * Nb)

        *SetTheoreticForm*: | SetIntersectionXaXb | / SQRT ( |Xa| * |Xb| ) =
        SUM ( MIN ( Xai, Xbi ) ) / SQRT ( SUM ( Xai ) * SUM ( Xbi ) )

        SorensonSimilarity: ( same as CzekanowskiSimilarity and
        DiceSimilarity)

        *AlgebraicForm*: ( 2 * ( SUM ( Xai * Xbi ) ) ) / ( SUM ( Xai ** 2) +
        SUM ( Xbi **2 ) )

        *BinaryForm*: 2 * Nc / ( Na + Nb )

        *SetTheoreticForm*: 2 * | SetIntersectionXaXb | / ( |Xa| + |Xb| ) =
        2 * ( SUM ( MIN ( Xai, Xbi ) ) ) / ( SUM ( Xai ) + SUM ( Xbi ) )

        SoergelDistance:

        *AlgebraicForm*: SUM ( ABS ( Xai - Xbi ) ) / SUM ( MAX ( Xai, Xbi )
        )

        *BinaryForm*: 1 - Nc / ( Na + Nb - Nc ) = ( Na + Nb - 2 * Nc ) / (
        Na + Nb - Nc )

        *SetTheoreticForm*: ( | SetDifferenceXaXb | - | SetIntersectionXaXb
        | ) / | SetDifferenceXaXb | = ( SUM ( Xai ) + SUM ( Xbi ) - 2 * (
        SUM ( MIN ( Xai, Xbi ) ) ) ) / ( SUM ( Xai ) + SUM ( Xbi ) - SUM (
        MIN ( Xai, Xbi ) ) )

        TanimotoSimilarity: ( same as JaccardSimilarity)

        *AlgebraicForm*: SUM ( Xai * Xbi ) / ( SUM ( Xai ** 2 ) + SUM ( Xbi
        ** 2 ) - SUM ( Xai * Xbi ) )

        *BinaryForm*: Nc / ( ( Na - Nc ) + ( Nb - Nc ) + Nc ) = Nc / ( Na +
        Nb - Nc )

        *SetTheoreticForm*: | SetIntersectionXaXb | / | SetDifferenceXaXb |
        = SUM ( MIN ( Xai, Xbi ) ) / ( SUM ( Xai ) + SUM ( Xbi ) - SUM ( MIN
        ( Xai, Xbi ) ) )

    --VectorComparisonFormulism *All |
    "AlgebraicForm,[BinaryForm,SetTheoreticForm]"*
        Specify fingerprints vector comparison formulism to use for
        calculation similarity and distance coefficients during -v,
        --VectorComparisonMode: use all supported comparison formulisms or
        specify a comma delimited. Possible values: *All |
        "AlgebraicForm,[BinaryForm,SetTheoreticForm]"*. Default value:
        *AlgebraicForm*.

        *All* uses all three forms of supported vector comparison formulism
        for values of -v, --VectorComparisonMode option.

        For fingerprint vector strings containing AlphaNumericalValues data
        values - ExtendedConnectivityFingerprints,
        AtomNeighborhoodsFingerprints and so on - all three formulism result
        in same value during similarity and distance calculations.

    -w, --WorkingDir *DirName*
        Location of working directory. Default: current directory.

EXAMPLES
    To generate a similarity matrix corresponding to Tanimoto similarity
    coefficient for fingerprints bit-vector strings data corresponding to
    supported fingerprints in text file present in a column name containing
    Fingerprint substring by loading all fingerprints data into memory and
    create a SampleFPHexTanimotoSimilarity.csv file containing compound IDs
    retrieved from column name containing CompoundID substring, type:

        % SimilarityMatricesFingerprints.pl -o SampleFPHex.csv

    To generate a similarity matrix corresponding to Tanimoto similarity
    coefficient for fingerprints bit-vector strings data corresponding to
    supported fingerprints in SD File present in a data field with
    Fingerprint substring in its label by loading all fingerprints data into
    memory and create a SampleFPHexTanimotoSimilarity.csv file containing
    sequentially generated compound IDs with Cmpd prefix, type:

        % SimilarityMatricesFingerprints.pl -o SampleFPHex.sdf

    To generate a similarity matrix corresponding to Tanimoto similarity
    coefficient for fingerprints bit-vector strings data corresponding to
    supported fingerprints in FP file by loading all fingerprints data into
    memory and create a SampleFPHexTanimotoSimilarity.csv file along with
    compound IDs retrieved from FP file, type:

        % SimilarityMatricesFingerprints.pl -o SampleFPHex.fpf

    To generate a lower triangular similarity matrix corresponding to
    Tanimoto similarity coefficient for fingerprints bit-vector strings data
    corresponding to supported fingerprints in text file present in a column
    name containing Fingerprint substring by loading all fingerprints data
    into memory and create a SampleFPHexTanimotoSimilarity.csv file
    containing compound IDs retrieved from column name containing CompoundID
    substring, type:

        % SimilarityMatricesFingerprints.pl -o --InputDataMode LoadInMemory
          --OutMatrixFormat RowsAndColumns --OutMatrixType LowerTriangularMatrix
          SampleFPHex.csv

    To generate a upper triangular similarity matrix corresponding to
    Tanimoto similarity coefficient for fingerprints bit-vector strings data
    corresponding to supported fingerprints in text file present in a column
    name containing Fingerprint substring by loading all fingerprints data
    into memory and create a SampleFPHexTanimotoSimilarity.csv file in
    IDPairsAndValue format containing compound IDs retrieved from column
    name containing CompoundID substring, type:

        % SimilarityMatricesFingerprints.pl -o --InputDataMode LoadInMemory
          --OutMatrixFormat IDPairsAndValue --OutMatrixType UpperTriangularMatrix
          SampleFPHex.csv

    To generate a full similarity matrix corresponding to Tanimoto
    similarity coefficient for fingerprints bit-vector strings data
    corresponding to supported fingerprints in text file present in a column
    name containing Fingerprint substring by scanning file without loading
    all fingerprints data into memory and create a
    SampleFPHexTanimotoSimilarity.csv file containing compound IDs retrieved
    from column name containing CompoundID substring, type:

        % SimilarityMatricesFingerprints.pl -o --InputDataMode ScanFile
          --OutMatrixFormat RowsAndColumns --OutMatrixType FullMatrix
          SampleFPHex.csv

    To generate a lower triangular similarity matrix corresponding to
    Tanimoto similarity coefficient for fingerprints bit-vector strings data
    corresponding to supported fingerprints in text file present in a column
    name containing Fingerprint substring by scanning file without loading
    all fingerprints data into memory and create a
    SampleFPHexTanimotoSimilarity.csv file in IDPairsAndValue format
    containing compound IDs retrieved from column name containing CompoundID
    substring, type:

        % SimilarityMatricesFingerprints.pl -o --InputDataMode ScanFile
          --OutMatrixFormat IDPairsAndValue --OutMatrixType LowerTriangularMatrix
          SampleFPHex.csv

    To generate a similarity matrix corresponding to Tanimoto similarity
    coefficient using algebraic formulism for fingerprints vector strings
    data corresponding to supported fingerprints in text file present in a
    column name containing Fingerprint substring and create a
    SampleFPCountTanimotoSimilarityAlgebraicForm.csv file containing
    compound IDs retrieved from column name containing CompoundID substring,
    type:

        % SimilarityMatricesFingerprints.pl -o SampleFPCount.csv

    To generate a similarity matrix corresponding to Tanimoto similarity
    coefficient using algebraic formulism for fingerprints vector strings
    data corresponding to supported fingerprints in SD file present in a
    data field with Fingerprint substring in its label and create a
    SampleFPCountTanimotoSimilarityAlgebraicForm.csv file containing
    sequentially generated compound IDs with Cmpd prefix, type:

        % SimilarityMatricesFingerprints.pl -o SampleFPCount.sdf

    To generate a similarity matrix corresponding to Tanimoto similarity
    coefficient using algebraic formulism vector strings data corresponding
    to supported fingerprints in FP file and create a
    SampleFPCountTanimotoSimilarityAlgebraicForm.csv file along with
    compound IDs retrieved from FP file, type:

        % SimilarityMatricesFingerprints.pl -o SampleFPCount.fpf

    To generate a similarity matrix corresponding to Tanimoto similarity
    coefficient for fingerprints bit-vector strings data corresponding to
    supported fingerprints in text file present in a column name containing
    Fingerprint substring and create a SampleFPHexTanimotoSimilarity.csv
    file in IDPairsAndValue format containing compound IDs retrieved from
    column name containing CompoundID substring, type:

        % SimilarityMatricesFingerprints.pl --OutMatrixFormat IDPairsAndValue -o
          SampleFPHex.csv

    To generate a similarity matrix corresponding to Tanimoto similarity
    coefficient for fingerprints bit-vector strings data corresponding to
    supported fingerprints in SD file present in a data field with
    Fingerprint substring in its label and create a
    SampleFPHexTanimotoSimilarity.csv file in IDPairsAndValue format
    containing sequentially generated compound IDs with Cmpd prefix, type:

        % SimilarityMatricesFingerprints.pl --OutMatrixFormat IDPairsAndValue -o
          SampleFPHex.sdf

    To generate a similarity matrix corresponding to Tanimoto similarity
    coefficient for fingerprints bit-vector strings data corresponding to
    supported fingerprints in FP file and create a
    SampleFPHexTanimotoSimilarity.csv file in IDPairsAndValue format along
    with compound IDs retrieved from FP file, type:

        % SimilarityMatricesFingerprints.pl --OutMatrixFormat IDPairsAndValue -o
          SampleFPHex.fpf

    To generate a similarity matrix corresponding to Tanimoto similarity
    coefficient for fingerprints bit-vector strings data corresponding to
    supported fingerprints in SD file present in a data field with
    Fingerprint substring in its label and create a
    SampleFPHexTanimotoSimilarity.csv file containing compound IDs from mol
    name line, type:

        % SimilarityMatricesFingerprints.pl --CompoundIDMode MolName -o
          SampleFPHex.sdf

    To generate a similarity matrix corresponding to Tanimoto similarity
    coefficient for fingerprints bit-vector strings data corresponding to
    supported fingerprints present in a data field with Fingerprint
    substring in its label and create a SampleFPHexTanimotoSimilarity.csv
    file containing compound IDs from data field name Mol_ID, type:

        % SimilarityMatricesFingerprints.pl --CompoundIDMode DataField
          --CompoundIDField Mol_ID -o SampleFPBin.sdf

    To generate similarity matrices corresponding to Buser, Dice and
    Tanimoto similarity coefficient for fingerprints bit-vector strings data
    corresponding to supported fingerprints present in a column name
    containing Fingerprint substring and create
    SampleFPBin[CoefficientName]Similarity.csv files containing compound IDs
    retrieved from column name containing CompoundID substring, type:

        % SimilarityMatricesFingerprints.pl -b "BuserSimilarity,DiceSimilarity,
          TanimotoSimilarity" -o SampleFPBin.csv

    To generate similarity matrices corresponding to Buser, Dice and
    Tanimoto similarity coefficient for fingerprints bit-vector strings data
    corresponding to supported fingerprints present in a data field with
    Fingerprint substring in its label and create
    SampleFPBin[CoefficientName]Similarity.csv files containing sequentially
    generated compound IDs with Cmpd prefix, type:

        % SimilarityMatricesFingerprints.pl -b "BuserSimilarity,DiceSimilarity,
          TanimotoSimilarity" -o SampleFPBin.sdf

    To generate similarity matrices corresponding to CityBlock distance and
    Tanimoto similarity coefficients using algebraic formulism for
    fingerprints vector strings data corresponding to supported fingerprints
    present in a column name containing Fingerprint substring and create
    SampleFPCount[CoefficientName]AlgebraicForm.csv files containing
    compound IDs retrieved from column name containing CompoundID substring,
    type:

        % SimilarityMatricesFingerprints.pl -v "CityBlockDistance,
          TanimotoSimilarity" -o SampleFPCount.csv

    To generate similarity matrices corresponding to CityBlock distance and
    Tanimoto similarity coefficients using algebraic formulism for
    fingerprints vector strings data corresponding to supported fingerprints
    present in a data field with Fingerprint substring in its label and
    create SampleFPCount[CoefficientName]AlgebraicForm.csv files containing
    sequentially generated compound IDs with Cmpd prefix, type:

        % SimilarityMatricesFingerprints.pl -v "CityBlockDistance,
          TanimotoSimilarity" -o SampleFPCount.sdf

    To generate similarity matrices corresponding to CityBlock distance
    Tanimoto similarity coefficients using binary formulism for fingerprints
    vector strings data corresponding to supported fingerprints present in a
    column name containing Fingerprint substring and create
    SampleFPCount[CoefficientName]Binary.csv files containing compound IDs
    retrieved from column name containing CompoundID substring, type:

        % SimilarityMatricesFingerprints.pl -v "CityBlockDistance,
          TanimotoSimilarity" --VectorComparisonFormulism BinaryForm -o
          SampleFPCount.csv

    To generate similarity matrices corresponding to CityBlock distance
    Tanimoto similarity coefficients using binary formulism for fingerprints
    vector strings data corresponding to supported fingerprints present in a
    data field with Fingerprint substring in its label and create
    SampleFPCount[CoefficientName]Binary.csv files containing sequentially
    generated compound IDs with Cmpd prefix, type:

        % SimilarityMatricesFingerprints.pl -v "CityBlockDistance,
          TanimotoSimilarity" --VectorComparisonFormulism BinaryForm -o
          SampleFPCount.sdf

    To generate similarity matrices corresponding to CityBlock distance
    Tanimoto similarity coefficients using all supported comparison
    formulisms for fingerprints vector strings data corresponding to
    supported fingerprints present in a column name containing Fingerprint
    substring and create SampleFPCount[CoefficientName][FormulismName].csv
    files containing compound IDs retrieved from column name containing
    CompoundID substring, type:

        % SimilarityMatricesFingerprints.pl -v "CityBlockDistance,
          TanimotoSimilarity" --VectorComparisonFormulism All -o SampleFPCount.csv

    To generate similarity matrices corresponding to CityBlock distance
    Tanimoto similarity coefficients using all supported comparison
    formulisms for fingerprints vector strings data corresponding to
    supported fingerprints present in a data field with Fingerprint
    substring in its label and create
    SampleFPCount[CoefficientName][FormulismName].csv files containing
    sequentially generated compound IDs with Cmpd prefix, type:

        % SimilarityMatricesFingerprints.pl -v "CityBlockDistance,TanimotoSimilarity"
          --VectorComparisonFormulism All -o SampleFPCount.sdf

    To generate similarity matrices corresponding to all available
    similarity coefficient for fingerprints bit-vector strings data
    corresponding to supported fingerprints present in a column name
    containing Fingerprint substring and create
    SampleFPHex[CoefficientName].csv files containing compound IDs retrieved
    from column name containing CompoundID substring, type:

        % SimilarityMatricesFingerprints.pl -m AutoDetect --BitVectorComparisonMode
          All --alpha 0.5 -beta 0.5 -o SampleFPHex.csv

    To generate similarity matrices corresponding to all available
    similarity coefficient for fingerprints bit-vector strings data
    corresponding to supported fingerprints present in a data field with
    Fingerprint substring in its label and create
    SampleFPHex[CoefficientName].csv files containing sequentially generated
    compound IDs with Cmpd prefix, type

        % SimilarityMatricesFingerprints.pl -m AutoDetect --BitVectorComparisonMode
          All --alpha 0.5 -beta 0.5 -o SampleFPHex.sdf

    To generate similarity matrices corresponding to all available
    similarity and distance coefficients using all comparison formulism for
    fingerprints vector strings data corresponding to supported fingerprints
    present in a column name containing Fingerprint substring and create
    SampleFPCount[CoefficientName][FormulismName].csv files containing
    compound IDs retrieved from column name containing CompoundID substring,
    type:

        % SimilarityMatricesFingerprints.pl -m AutoDetect --VectorComparisonMode
          All --VectorComparisonFormulism All -o SampleFPCount.csv

    To generate similarity matrices corresponding to all available
    similarity and distance coefficients using all comparison formulism for
    fingerprints vector strings data corresponding to supported fingerprints
    present in a data field with Fingerprint substring in its label and
    create SampleFPCount[CoefficientName][FormulismName].csv files
    containing sequentially generated compound IDs with Cmpd prefix, type:

        % SimilarityMatricesFingerprints.pl -m AutoDetect --VectorComparisonMode
          All --VectorComparisonFormulism All -o SampleFPCount.sdf

    To generate a similarity matrix corresponding to Tanimoto similarity
    coefficient for fingerprints bit-vector strings data corresponding to
    supported fingerprints present in a column number 2 and create a
    SampleFPHexTanimotoSimilarity.csv file containing compound IDs retrieved
    column number 1, type:

        % SimilarityMatricesFingerprints.pl --ColMode ColNum --CompoundIDCol 1
          --FingerprintsCol 2 -o SampleFPHex.csv

    To generate a similarity matrix corresponding to Tanimoto similarity
    coefficient for fingerprints bit-vector strings data corresponding to
    supported fingerprints present in a data field name Fingerprints and
    create a SampleFPHexTanimotoSimilarity.csv file containing compound IDs
    present in data field name Mol_ID, type:

        % SimilarityMatricesFingerprints.pl --FingerprintsField Fingerprints
          --CompoundIDMode DataField --CompoundIDField Mol_ID -o SampleFPHex.sdf

    To generate a similarity matrix corresponding to Tversky similarity
    coefficient for fingerprints bit-vector strings data corresponding to
    supported fingerprints present in a column named Fingerprints and create
    a SampleFPHexTverskySimilarity.tsv file containing compound IDs
    retrieved column named CompoundID, type:

        % SimilarityMatricesFingerprints.pl --BitVectorComparisonMode
          TverskySimilarity --alpha 0.5 --ColMode ColLabel --CompoundIDCol
          CompoundID --FingerprintsCol Fingerprints --OutDelim Tab --quote No
          -o SampleFPHex.csv

    To generate a similarity matrix corresponding to Tanimoto similarity
    coefficient for fingerprints bit-vector strings data corresponding to
    supported fingerprints present in a data field with Fingerprint
    substring in its label and create a SampleFPHexTanimotoSimilarity.csv
    file containing compound IDs from molname line or sequentially generated
    compound IDs with Mol prefix, type:

        % SimilarityMatricesFingerprints.pl --CompoundIDMode MolnameOrLabelPrefix
          --CompoundIDPrefix Mol -o SampleFPHex.sdf

    To generate a similarity matrix corresponding to Tanimoto similarity
    coefficient for fingerprints bit-vector strings data corresponding to
    supported fingerprints present in a data field with Fingerprint
    substring in its label and create a SampleFPHexTanimotoSimilarity.tsv
    file containing sequentially generated compound IDs with Cmpd prefix,
    type:

        % SimilarityMatricesFingerprints.pl -OutDelim Tab --quote No -o SampleFPHex.sdf

AUTHOR
    Manish Sud <msud@san.rr.com>

SEE ALSO
    InfoFingerprintsFiles.pl, SimilaritySearchingFingerprints.pl,
    AtomNeighborhoodsFingerprints.pl, ExtendedConnectivityFingerprints.pl,
    MACCSKeysFingerprints.pl, PathLengthFingerprints.pl,
    TopologicalAtomPairsFingerprints.pl,
    TopologicalAtomTorsionsFingerprints.pl,
    TopologicalPharmacophoreAtomPairsFingerprints.pl,
    TopologicalPharmacophoreAtomTripletsFingerprints.pl

COPYRIGHT
    Copyright (C) 2015 Manish Sud. All rights reserved.

    This file is part of MayaChemTools.

    MayaChemTools is free software; you can redistribute it and/or modify it
    under the terms of the GNU Lesser General Public License as published by
    the Free Software Foundation; either version 3 of the License, or (at
    your option) any later version.

