NAME

       ea_non_iid - Run Non-IID tests for entropy assesment

SYNOPSIS

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

DESCRIPTION

       Run Non-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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ea_non_iid 1.1.5                                   April 2023                                      EA_NON_IID(1)