NAME

       ea_iid - Run IID tests for entropy assesment

SYNOPSIS

       ea_iid [-i|-c] [-a|-t] [-v] [-q] [-l <index>,<samples> ] <file_name> [bits_per_symbol]

DESCRIPTION

       Run IID tests for entropy assesment.

       <file_name>:  Must  be  relative  path  to  a  binary file with at least 1 million entries
              (samples).

       [bits_per_symbol]: Must be between 1-8, inclusive. By default this value is inferred  from
              the data.

       [-i|-c]:  '-i'  for  initial  entropy  estimate,  '-c'  for conditioned sequential dataset
              entropy estimate. The initial entropy estimate is the default.

       [-a|-t]: '-a' produces the 'H_bitstring' assessment using all read  bits,  '-t'  truncates
              the  bitstring  used  to produce the `H_bitstring` assessment to 1000000 bits. Test
              all data by default.

              Note: When testing binary data, no `H_bitstring` assessment  is  produced,  so  the
              `-a` and `-t` options produce the same results for the initial assessment of binary
              data.

       -v: Optional verbosity flag for more output. Can be used multiple times.

       -q: Quiet mode, less output to screen. This will override any verbose flags.

       -l <index>,<samples>   Read the <index> substring of length <samples>.

              Samples are assumed to be packed into 8-bit values,  where  the  least  significant
              'bits_per_symbol' bits constitute the symbol.

       -i: Initial Entropy Estimate (Section 3.1.3)

              Computes  the  initial  entropy  estimate  H_I  as  described in Section 3.1.3 (not
              accounting for H_submitter) using the entropy estimators specified in Section  6.3.
              If  'bits_per_symbol'  is  greater  than  1,  the  samples  are  also  converted to
              bitstrings and assessed to create H_bitstring; for multi-bit symbols,  two  entropy
              estimates  are  computed:  H_original  and  H_bitstring.   Returns  min(H_original,
              bits_per_symbol X H_bitstring). The initial entropy estimate H_I = min(H_submitter,
              H_original, bits_per_symbol X H_bitstring).

       -c: Conditioned Sequential Dataset Entropy Estimate (Section 3.1.5.2)

              Computes  the entropy estimate per bit h' for the conditioned sequential dataset if
              the conditioning function is non-vetted. The samples are converted to a  bitstring.
              Returns h' = min(H_bitstring).

       -o: Set Output Type to JSON

              Changes the output format to JSON and sets the file location for the output file.

       --version: Prints tool version information

COPYRIGHT

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