MONOTONE-VIZ(1) User Commands MONOTONE-VIZ(1)NAME
monotone-viz - visualize a monotone repository
SYNOPSIS
monotone-viz [OPTION]... [DB [BRANCH [REVISION]]]
DESCRIPTION
View the monotone repository, DB, at the specified BRANCH and REVISION. DB, BRANCH, and REVISION default to the values in MT/options and
MT/revision.
-noaa don't use an anti-aliased canvas
--help display this help and exit
--version
output version information and exit
FILES
MT/options
The default database and branch are stored in this file.
MT/revision
The default revision is stored in this file.
COPYRIGHT
Copyright 2006 Olivier Andrieu
AUTHOR
Written by Olivier Andrieu <oandrieu@nerim.net>.
This manual page was written by Shaun Jackman <sjackman@debian.org> for the Debian system.
REPORTING BUGS
Report bugs to <monotone-devel@nongnu.org>.
SEE ALSO monotone(1)
http://oandrieu.nerim.net/monotone-viz/
monotone-viz 0.14 March 2006 MONOTONE-VIZ(1)
Check Out this Related Man Page
SPLINE(1G)SPLINE(1G)NAME
spline - interpolate smooth curve
SYNOPSIS
spline [ option ] ...
DESCRIPTION
Spline takes pairs of numbers from the standard input as abcissas and ordinates of a function. It produces a similar set, which is approx-
imately equally spaced and includes the input set, on the standard output. The cubic spline output (R. W. Hamming, Numerical Methods for
Scientists and Engineers, 2nd ed., 349ff) has two continuous derivatives, and sufficiently many points to look smooth when plotted, for
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The following options are recognized, each as a separate argument.
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argument is not a number.
-k The constant k used in the boundary value computation
(2nd deriv. at end) = k*(2nd deriv. next to end)
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-n Space output points so that approximately n intervals occur between the lower and upper x limits. (Default n = 100.)
-p Make output periodic, i.e. match derivatives at ends. First and last input values should normally agree.
-x Next 1 (or 2) arguments are lower (and upper) x limits. Normally these limits are calculated from the data. Automatic abcissas start
at lower limit (default 0).
SEE ALSO graph(1)DIAGNOSTICS
When data is not strictly monotone in x, spline reproduces the input without interpolating extra points.
BUGS
A limit of 1000 input points is enforced silently.
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