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ent - pseudorandom number sequence test


ent [options] [file]


ENT Logo

ent performs a variety of tests on the stream of bytes in file (or standard input if no
file is specified) and produces output on standard output; for example:

Entropy = 7.980627 bits per character.

Optimum compression would reduce the size
of this 51768 character file by 0 percent.

Chi square distribution for 51768 samples is 1542.26, and randomly
would exceed this value 0.01 percent of the times.

Arithmetic mean value of data bytes is 125.93 (127.5 = random).
Monte Carlo value for Pi is 3.169834647 (error 0.90 percent).
Serial correlation coefficient is 0.004249 (totally uncorrelated = 0.0).

The values calculated are as follows:

The information density of the contents of the file, expressed as a number of bits per
character. The results above, which resulted from processing an image file compressed with
JPEG, indicate that the file is extremely dense in information—essentially random. Hence,
compression of the file is unlikely to reduce its size. By contrast, the C source code of
the program has entropy of about 4.9 bits per character, indicating that optimal
compression of the file would reduce its size by 38%. [Hamming, pp. 104-108]

The chi-square test is the most commonly used test for the randomness of data, and is
extremely sensitive to errors in pseudorandom sequence generators. The chi-square
distribution is calculated for the stream of bytes in the file and expressed as an
absolute number and a percentage which indicates how frequently a truly random sequence
would exceed the value calculated. We interpret the percentage as the degree to which the
sequence tested is suspected of being non-random. If the percentage is greater than 99% or
less than 1%, the sequence is almost certainly not random. If the percentage is between
99% and 95% or between 1% and 5%, the sequence is suspect. Percentages between 90% and
95% and 5% and 10% indicate the sequence is "almost suspect". Note that our JPEG file,
while very dense in information, is far from random as revealed by the chi-square test.

Applying this test to the output of various pseudorandom sequence generators is
interesting. The low-order 8 bits returned by the standard Unix rand(1) function, for
example, yields:

Chi square distribution for 500000 samples is 0.01, and randomly
would exceed this value 99.99 percent of the times.

While an improved generator [Park & Miller] reports:

Chi square distribution for 500000 samples is 212.53, and randomly
would exceed this value 95.00 percent of the times.

Thus, the standard Unix generator (or at least the low-order bytes it returns) is
unacceptably non-random, while the improved generator is much better but still
sufficiently non-random to cause concern for demanding applications. Contrast both of
these software generators with the chi-square result of a genuine random sequence created
by timing radioactive decay events[1]:

Chi square distribution for 32768 samples is 237.05, and randomly
would exceed this value 75.00 percent of the times.

See [Knuth, pp. 35-40] for more information on the chi-square test. An interactive chi-
square calculator[2] is available at this site.

This is simply the result of summing all the bytes (bits if the -b option is specified) in
the file and dividing by the file length. If the data are close to random, this should be
about 127.5 (0.5 for -b option output). If the mean departs from this value, the values
are consistently high or low.

Each successive sequence of six bytes is used as 24 bit X and Y coordinates within a
square. If the distance of the randomly-generated point is less than the radius of a
circle inscribed within the square, the six-byte sequence is considered a "hit". The
percentage of hits can be used to calculate the value of Pi. For very large streams (this
approximation converges very slowly), the value will approach the correct value of Pi if
the sequence is close to random. A 32768 byte file created by radioactive decay yielded:

Monte Carlo value for Pi is 3.139648438 (error 0.06 percent).

This quantity measures the extent to which each byte in the file depends upon the previous
byte. For random sequences, this value (which can be positive or negative) will, of
course, be close to zero. A non-random byte stream such as a C program will yield a serial
correlation coefficient on the order of 0.5. Wildly predictable data such as uncompressed
bitmaps will exhibit serial correlation coefficients approaching 1. See [Knuth, pp. 64-65]
for more details.


-b The input is treated as a stream of bits rather than of 8-bit bytes. Statistics
reported reflect the properties of the bitstream.

-c Print a table of the number of occurrences of each possible byte (or bit, if the -b
option is also specified) value, and the fraction of the overall file made up by
that value. Printable characters in the ISO-8859-1 (Latin-1) character set are
shown along with their decimal byte values. In non-terse output mode, values with
zero occurrences are not printed.

-f Fold upper case letters to lower case before computing statistics. Folding is done
based on the ISO-8859-1 (Latin-1) character set, with accented letters correctly

-t Terse mode: output is written in Comma Separated Value (CSV) format, suitable for
loading into a spreadsheet and easily read by any programming language. See Terse
Mode Output Format below for additional details.

-u Print how-to-call information.

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