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1997-07-08
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WELCOME TO THE MATHEMATICS AND STATISTICS DEMO
IDL's mathematics and statistics tools are designed
for use in a wide variety of disciplines. This demo
introduces 6 features.
MENU OPTIONS
------------
File Menu:
Select "Quit" to exit the Mathematics and
Statistics Demo and return to the IDL Demo
main screen.
About Menu:
Select "About mathematics and statistics" for
information about the Mathematics and Statistics
Demo.
FEATURES
--------
<<Integration>> radio button
The INT_TABULATED function uses a fifth-order
Newton-Cotes integration formula and
neighborhood spline curve-fitting to produce
integrations of tabulated data (discrete
points). This is one of the most accurate
integration techniques available.
area = INT_TABULATED(time, amplitude)
You can also use IDL to integrate functions
that have algebraic singularities and asymptotic
behavior.
<<Generate new data>> button
Creates a new set of data.
<<Solving Equations>> radio button
Dozens of "Numerical Recipes" library routines
for performing complex mathematical computations
are integrated into IDL.
For example, the NR_NEWT function solves systems
of non-linear equations. Multiple solutions can
be found by starting the NR_NEWT algorithm at
different initial values. The black markers show
the locations of the initial guesses. The white
markers show the solutions to the non-linear
system of equations. The solutions lie on the
intersection of the three surfaces:
z = -(x*x - y - 4) (Bottom surface - blue)
z = 0 (Middle surface - green)
z = x*x + y*y - 8 (Top surface - red)
The Numerical Recipes algorithms are used by
permission and are taken from the book
"Numerical Recipes in C, The Art of Scientific
Computing" (second edition) by: William H. Press,
Saul A. Teukolsky, William T. Vetterling, and
Brian P. Flannery.
<<Minimization>> radio button
The IDL Numerical Recipies routine NR_POWELL can
be used to find the local minimum of a function
of 'n' variables. In this demo, clicking on the
plot identifies the nearest local minimum of the
function:
y=SIN(SIN(x^2)-COS(x))+COS(SIN(x)+SIN(x)^2)']
<<Linear regression>> radio button
The "Method of Least Absolute Deviation" (the
plot on the right) is used to accurately fit a
curve through data. This curve fitting method,
unlike "least-square" fitting (the plot on the
left) is not adversely affected by outlying
points.
<<Number of Points Above>> slider
Sets the number of outliers above the
main cluster.
<<Number of Points Below>> slider
Sets the number of outliers below the
main cluster.
<<Polynomial Fit>> radio button
The "POLY_FIT" function fits a least-square
polynomial curve through scattered data points.
<<Number of points>> slider
Sets the number of data points.
<<Degree>> slider
Sets the polynomial degree.
<<Surface Fit>> radio button
The MIN_CURVE_SURF function can be used to fit a
minimum curvature surface through irregularly-
gridded 3D data.
<<Number of Points>>
Sets the number of data points.