NAME
mintegrate - evaluate average/sum/integral of 1-d numerical data
SYNOPSIS
mintegrate [OPTION]... [FILE]
DESCRIPTION
mintegrate is a program to compute averages, sums or integrals of 1-d
data in situations where ultimate numerical precision is not needed.
OPTIONS
-a compute mean value (arithmetic average) and standard deviation
-d <float>
compute integral on open x-data interval with the specified dx
-c compute integral on closed x-data interval; In this case dx
specified by the ’-d’ flag is ignored - data are supposed to be
from an irregular x-grid, dx is computed separately for every
x-interval, and the integral is computed by the trapezoidal
rule.
-x <int>
x-data column (default is 1). If 0, the x-range is an index;
-y <int>
y-data column, where y=f(x) (default is 1)
-r x_0:x_1
x-data range to consider
-s print out accumulated y_i sums: x_i versus accumulated f(x_i);
In the case of a closed integral you have to specify also the
x-data resolution dx (see ’-d’ above).
-S compute the accumulated y_i-sums and add it to the output
-p <str>
print format of the result ("%.6g" is default)
-t <str>
output text in front of the result (invalid with ’-s’ or ’-S’);
A blank can be printed by using a double underscore character
’__’.
-V print version number
--version
output version and license message
--help|-H
display help
-h display short help (options summary)
If none of the options ’-a’, ’-d’, or ’-c’ is used, then the sum of the
provided data will be computed. Empty lines or lines starting with ’#’
are skipped.
This program is perfectly suitable as a basic tool for initial data
analysis and will meet the expected accuracy of a numerical solution
for the most demanding computer users and professionals. Yet be aware
that, although the computations are carried with double floating
precision, the computational techniques used for evaluating an integral
or a standard deviation are analytically low-order approximations, and
thus not intended to be used for numerical computations in engineering
or mathematical sciences for cases where an ultimate numerical
precision is a must. For deeper understanding of the topic see
http://de.wikipedia.org/wiki/Numerical_Recipes.
COPYRIGHT
Copyright © 1997, 2001, 2006, 2007, 2009 Dimitar Ivanov
License: GNU GPL version 3 or later <http://gnu.org/licenses/gpl.html>
This is free software: you are free to change and redistribute it.
There is NO WARRANTY, to the extent permitted by law.