alm_i2t

This IDL function turns an indexed list of alm (as generated by fits2alm) into a tabular (real or complex) a(l,m) array for easier manipulation

Location in HEALPix directory tree: src/idl/misc/alm_i2t.pro 

FORMAT

IDL> alm_table=alm_i2t(Index, Alm_vec, [/COMPLEX, /HELP, LMAX=, MMAX=])

QUALIFIERS

Index

Integer vector of size ni containing the index i of the of $a_{\ell m}$ coefficients, related to $\{\ell,m\}$ by $i = \ell^2 + \ell + m + 1$

Alm_vec

Array of $a_{\ell m}$ coefficients, with dimension (ni, nalm [,nsig]) where
ni = number of i indices
nalm = 2 for real and imaginary parts of alm coefficients or
4 for above plus corresponding error values
nsig = number of signals (usually 1 for any of T E B or 3 for T,E,B together)

KEYWORDS

/COMPLEX

if set, the output array is complex with dimensions (lmax+1, mmax+1, [nalm/2 , nsig]),
otherwise, the array is real with dimensions (lmax+1, mmax+1, nalm [, nsig]).
lmax and mmax are determined from input Index values, unless set otherwise by user.

/HELP

if set, prints out the help header and exits

LMAX=

lmax to be used in output array, regardless of value found in input index

MMAX=

mmax to be used in output array, regardless of value found in input index

DESCRIPTION

alm_i2t returns a real or complex array, containing the $a_{\ell m}$ with $0 \le \ell \le \ell_{\mathrm{max}}$ and $0 \le m \le m_{\mathrm{max}}$. The negative m are therefore ignored.

RELATED ROUTINES

This section lists the routines related to alm_i2t

idl

version 6.4 or more is necessary to run alm_i2t.

alm_t2i

turns tabular alm's such as those generated by alm_i2t into indexed lists than can written to FITS files with alm2fits

alm2fits, fits2alm

routines to read and write $a_{\ell m}$ indexed lists from and to FITS files.

EXAMPLE:

fits2alm, i1, a1, 'alm1.fits'
ac1 = alm_i2t(i1, a1, /complex, lmax=100, mmax=100)
fits2alm, i2, a2, 'alm2.fits'
ac2 = alm_i2t(i2, a2, /complex, lmax=100, mmax=100)
ac = 0.9*ac1 + 0.1*ac2
alm_t2i, ac, i, a
alm2fits, i, a, 'almsum.fits'

The example above reads 2 sets of $a_{\ell m}$ from FITS files, puts the alm's with $(\ell,m) \le 100$ in tabular arrays, and then make a weighted sum of the alm's. The resulting alm or put back into a indexed list in order to be written to FITS.