### Fixed mass estimation of C1 (information dimension)

`c1 -d# -m# -M# -t# -n# [-## -K# -o `*outfile*` -l# -x# -c#[,#] -V# -h] `* file*

` -d `delay

` -m `minimal embedding dimension

` -M `maximal embedding dimension (at least 2)

` -t `minimal time separation

` -n `minimal number of center points

` -# `resolution, values per octave (2)

` -K `maximal number of neighbours (100)

` -l `number of values to be read (all)

` -x `number of values to be skipped (0)

` -c `column(s) to be read (1 or *file*,#)

` -o `output file name, just ` -o `means *file*`_c1`

` -V `verbosity level (0 = only fatal errors)

` -h `show this message

Computes curves for the fixed mass computation of the information dimension.
The output is written to a
file named *file*`_c1`,
containing as two columns the
necessary radius and the `mass'. Although the `mass' is the independent
quantity here, this is to conform with the output of c2naive and d2.
A logarithmic range of masses between 1/N and 1 is realised by varying
the neighbour order k as well as the subsequence length n. For a given mass
k/n, n is chosen as small is possible as long as k is not smaller than the
value specified by ` -K `.

The number of reference points has to be selected by specifying
` -n `. That number of points are selected
at random from all time indices.

It is possible to use multivariate data, also with mixed embeddings.
Contrary to the convention, the embedding dimension here specifies the total
number of phase space coordinates. The number of components of the time series
to be considered can only be given by explicit enumeration with the option
` -c `.

**Note:**
You will probably use the auxiliary programs
c2d or c2t
to process the output further. The formula used for the Gaussian kernel
correlation sum does not apply to the information dimension.
See also the example below.

### Usage example

Try also just running: `gnuplot c1.gnu` in the
`examples` directory.

> `henon -l10000 > data`
> `c1 -m2 -M6 -d1 -t50 -n500 data `
gnuplot> `set logscale x`
gnuplot> `set yrange [0:3]`
gnuplot> `plot '< c2d -a2 data_c1', 1.2 `

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