INTERPOLATE  Cubic and Quintic Interpolation
CUBETERP and QUINTERP perform cubic and quintic interpolation of a
known, tabulated function. These routines are different from the many
other interpolation routines fr IDL in that they allow you to choose
the first derivative  and second derivative in the case of QUINTERP
 at each control point. In other words, these are not standard
"natural" splines, but rather smooth polynomials with specified
derivatives at every point. The caller specifies the tabulated values
and derivatives and requested interpolation points, and returns the
interpolated values (and optionally the interpolated derivaties).
If you do not need to specify the derivative values
explicitly, then you likely want to use SPL_INIT/SPL_INTERP
instead.
PHUNWRAP  Phase Unwrapping to Remove Cycle Jumps
PHUNWRAP unwraps a sequence of phases to produce a new series of
cycle counts. Phase jumps due to crossing over the PHASE=0 boundary
are removed by adding an integral number of cycles. The algorithm is
based on the MATLAB "unwrap" function. Users can select the tolerance
used to determine the phase jump, and can also select the definition
of "1 cycle."
QUATERNIONS  Library to Manipulate and Use Quaternions
This library provides routines to manipulate and use quaternions in
IDL. Quaternions are 4vectors that can be used to represent the
orientations of one reference frame with respect to another. In
practical terms, quaternions represent arbitrary three dimensional
rotations. They have many advantages over rotation matrices (i.e.,
direction cosine matrices) and over Euler angles. Quaternions are
used in computer animation to represent the orientation of the camera,
and in spacecraft navigation to represent the body attitude.
The function QTCOMPOSE is used to make a quaternion from a rotation
axis and angle. The functions QTANG and QTAXIS are used to extract
the rotation axis and angle from an existing quaternion. The
functions QTMAT and QTFIND are used to convert to and from the
direction cosine matrix representation. The functions QTERP, QTPOW,
QTLOG and QTEXP are used to perform smooth interpolations between
orientations. The functions QTINV and QTMULT construct the quaternion
inverse and product respectively. The function QTVROT transforms a
3vector according to a quaternion rotation. QTEULER is a convenience
routine to chain together multiple Eulerlike rotations. QTNORMALIZE
normalizes a quaternion to be a unit quaternion and/or enforces other
regularity constraints.
UNITVEC  Manipulate unit vectors and polar angles
These three functions provide ways to manipulate unit vectors as
3vectors and as spherical polar angles. (also known as longitude and
latitude; or longitude and colatitude; or right ascension and
declination)
UNITIZE returns a unit vector for any input vector. The returned
vector has the same direction as the input, but unit magnitude.
ANGUNITVEC and UNITVECANG convert between 3component vector
notation and spherical polar angles. ANGUNITVEC converts from
longitude and (co)latitude (or RA/Dec) to a unit 3vector. UNITVECANG
does the reverse conversion.
QPINT1D  Adaptive Numerical Integration (Quadpack)
QPINT1D adaptively calculates an approximation result to a given
definite integral, hopefully satisfying a constraint on the accuracy
of the solution. QPINT1D is based on the QUADPACK fortran package
originally by Piessens, de Doncker, Ueberhuber and Kahaner (and
implements equivalents to the QAGSE, QAGPE, QAGIE, and DQKxx fortran
routines). All of these specialized integrators are combined into a
single convenient callable IDL procedure.
QPINT1D integrates both IDL functions and IDL expressions. It
handles integrands with known and unknown but integrable
singularities, and also can compute improper integrals (i.e.,
integrals whose limits extend to infinity).
QPINT1D is "adaptive" in the sense that it locates regions of the
integration interval which contain the highest error, and focusses its
efforts on those regions. The algorithm locates these regions by
successively bisecting the starting interval. Each subinterval is
assigned an error estimate, and the region with the largest error
estimate is subdivided further, until each subinterval carries
approximately the same amount of error. Convergence of the procedure
may be accelerated by the Epsilon algorithm due to Wynn.
DDEABM  Integrate Ordinary Differential Equation (AdamsBashforthMoulton)
DDEABM performs integration of a system of one or more ordinary
differential equations (ODEs) using a PredictorCorrector technique.
An adaptive AdamsBashforthMoulton method of variable order between
one and twelve, adaptive stepsize, and error control, is used to
integrate equations of the form:
DF_DT = FUNCT(T, F)
T is the independent variable, F is the (possibly vector) function
value at T, and DF_DT is the derivative of F with respect to T,
evaluated at T. FUNCT is a user function which returns the derivative
of one or more equations.
DDEABM is based on the public domain procedure DDEABM.F written by
L. F. Shampine and M. K. Gordon, and available in the DEPAC package of
solvers within SLATEC library.
DDEABM is used primarily to solve nonstiff and mildly stiff ODE
problems, where evaluation of the user function is expensive, or high
precision is demanded (close to the machine precision).
CHEB  Approximation and interpolation using Chebyshev polynomials
This is a set of three IDL functions, used for the interpolation
and approximation of mathematical functions over finite intervals by
Chebyshev polynomials. The approximating function is:
f(x) = Sum[ c_j T_j(x) ]
where "c_j" are the
Chebyshev coefficients and T_j(x) are the orthogonal Chebyshev
polynomials. By default the interval is [1,1], but this can be
changed with the INTERVAL keyword.
Chebyshev approximations are most appropriate when a known smooth
function is expensive to calculate. With a small number of function
evaluations, the Chebyshev coefficients can be determined once, and
then the Chebyshev series can be subsequently evaluated quickly for
many abcissae.
The approximation method proceeds in two steps. First, the user
must estimate the Chebyshev coefficients. CHEBCOEF is normally used
in this case, for functions which can be evaluated to full machine
precision at arbitrary abcissae. For noisy or tabulated data, users
should use CHEBFIT instead. For data tabulated on a uniform grid, the
CHEBGRID function is appropriate. The result of either of these
functions is an array of coefficients. The second step involves
computing the function value at the desired abcissae, for which the
CHEBEVAL function is used. Several mechanisms are provided to the
user to control the approximation error.
LEGCHEB can estimate the coefficients of the Legendre series
if the Chebyshev series coefficients are already known.
QRFAC  Linear Least Squares Solutions using QR decomposition
Given an MxN matrix A (M>N), the procedure QRFAC computes the QR
decomposition (factorization) of A. This factorization is useful in
least squares applications solving the equation, A ## x = B. Together
with the procedure QRSOLV, this equation can be solved in a least
squares sense.
The QR factorization produces two matrices, Q and R, such that
A = Q ## R
where Q is orthogonal such that TRANSPOSE(Q)##Q equals the identity
matrix, and R is upper triangular. This procedure does not compute Q
directly, but returns the morecompact Householder reflectors, which
QRSOLV applies in constructing the solution.
The solution technique is to first compute the factorization using
QRFAC, which yields the orthogonal matrix Q and the upper triangular
matrix R. Then the solution vector, X, is computed using QRSOLV.
Pivoting can be performed using the PIVOT keyword.
MCHOLDC  Modified Cholesky factorization of a symmetric matrix
Given a symmetric matrix A, the MCHOLDC procedure computes the
factorization:
A + E = TRANSPOSE(U) ## D ## U
where A is the original matrix (optionally permuted if the PIVOT
keyword is set), U is an upper triangular matrix, D is a diagonal
matrix, and E is a diagonal error matrix.
The standard Cholesky factorization is only defined for a positive
definite symmetric matrix (this is true both mathematically, and for
the standard IDL routine CHOLDC). If the input matrix is positive
definite then the error term E will be zero upon output. The user may
in fact test the positivedefiniteness of their matrix by factoring it
and testing that all terms in E are zero.
The decomposition from MCHOLDC can now be used to solve problems
with the builtin IDL function CHOLSOL, if the CHOLSOL keyword is
set.
CROSSPN  Efficient vector cross products of many terms
The function CROSSPN computes the vector cross product (outer
product). The difference between CROSSPN and the IDL library function
CROSSP, is that CROSSPN allows more than one cross product to be
computed at one time (i.e., it is vectorized).
Thus, in the expression "C = CROSSPN(A, B)" the vector cross
product is computed as C = A x B. Because CROSSPN is vectorized, the
vector cross product of any combination of 3vectors and 3xN arrays can
be computed.
ACIRCCIRC  Calculate the area of overlap between two circular regions
ACIRCCIRC computes the overlap area between two circles. The
circles are specified by their radii, R1 and R2, and the distance
between the centers of the circles.
ACIRCCIRC handles cases of partial overlap, as well degenerate
cases of no overlap and circle 1 completely enclosed within circle
2 (or vice versa).
