AIPS HELP file for RM in 31DEC18
As of Mon Oct 22 1:21:09 2018
RM: Task to calculate rotation measure and magnetic field
INNAME Input image name (name)
INCLASS Input image name (class)
INSEQ 0.0 9999.0 Input image name (seq. #)
INDISK 0.0 9.0 Input image disk drive #
IN2NAME Noise image name (name)
IN2CLASS Noise image name (class)
IN2SEQ 0.0 9999.0 Noise image name (seq. #)
IN2DISK 0.0 9.0 Noise image disk drive #
BLC 0.0 4096.0 Bottom Left corner of fit
TRC 0.0 4096.0 Top Right corner of fit
OUTNAME Output image name (name)
OUTCLASS Output image name (class)
(NOT USED AT PRESENT)
OUTSEQ -1.0 9999.0 Output image name (seq. #)
OUTDISK 0.0 9.0 Output disk drive #
APARM (1) begin channel
(2) end channel
(3) initial guess of RM
(4) max expected |RM|
(5) > 0 use noise image
(6) blanking method
(7) blanking level
SEE HELP re 4, 6, 7
SCALR1 -1.0 1.0 <= 0 => Output normal map
> 0 => Output error on map
Use: RM is a task which calculates rotation measure and intrinsic
magnetic field from a set of (at least three) position angle
maps made at different frequencies. The current version can
accept a maximum of 65536 frequencies. The algorithm will do
an unweighted or weighted fit of the position angle to the
wavelength squared. In the latter case, sigma (error) maps must
also be supplied. These error maps must be made with the task
RM outputs both a map of the rotation measure, and a map of the
intrinsic magnetic field. Various blanking options are supplied
and it is vigorously suggested that one of them be used.
BLC, TRC values:
BLC(1-6) : TRC(1-6) apply to axes 2 - 7 of the input
cube. In other words, they are the desired OUTPUT
window rather than the input window. APARM(1), APARM(2),
and APARM(8) control the input window on the first
(actually frequency) axis of the cube.
(1): First frequency channel to use in fit, 0 -> 1
(2): Last frequency channel to use in fit, 0 -> N
(3): The initial guess for the rotation measure. Use the integrated
values if nothing else is known. UNITS are RADIANS per METER
(4): If > 0, use a method due to F. Zhou to search a wide range of
lobe ambiguities, based on APARM(4) as the maximum expected RM
in absolute value.
(5): Solution type. <= 0 => Unweighted fit
>0 => Weight fit by errors in IN2NAME et al.
(6): Blanking type. 0 => No blanking
1 => Blank both output maps if corr. coeff. < APARM(7).
2 => Blank both maps only if sigma of RM exceeds APARM(7)
3 => Blank both maps only if sigma of B > APARM(7) (degrees)
4 => Blank both maps if rms dev. per point from best fit line
exceeds APARM(7) (degrees)
5 => Blank both output maps if in input error of any input map
value exceeds APARM(7). THIS IS THE RECOMMENDED WAY.
(7): The blanking level. See APARM(6).
To run RM, the best thing to do is to start with a cube image (from
IMAGR and COMB) or build a cube image either with MCUBE (regularly
spaced frequencies) or FQUBE (irregularly spaced frequencies). Then
tranpose the cube with TRANSCOD = '312' to make the FREQ or FQID axis
be the first axis. Then run RM.
Ancient intructions to run RM say that you must follow these steps:
1) Run AXDEFINE for each p.a. map and each sigma map (if you
wish weighted fits), and change the 3rd axis (frequency)
to an arbitrary unit (i.e. 'PERLEYS'), whose values
increase uniformly from map to map. Although the order of
the frequencies is not critical, the program stands the
best chance of working properly if the 3rd axis increases
with frequency. It is important that the two frequencies
closest in wavelength have the 3rd axes set to 1 and 2.
Set the third axis of the position angle maps from 1 to
N, where N is the number of frequencies, then set the
position angle error maps to have the third axis run from N+1
to 2N, keeping the same frequency order as the position
angle maps. (If you do not intend to weight by fit, you need
not include the error maps). When running AXDEFINE, set
AXINC = 1 and AXREF = 1 also.
2) Run RENAME for each map to make the name and class of each
the same. Make the sequence number of each map the same as
the new "frequency" value (i.e. from 1 to N for the position
angle maps, and N+1 to 2N for the error maps.)
3) Run MCUBE and assemble these N (or 2N if you want a weighted
fit) maps into a data cube.
4) Run TRANS and transpose the cube. Make the initial first
axis ('LL') the second, the initial second ('MM') the third,
and the initial third (frequency in units of 'PERLEYS' or
whatever) the first. That is, the new order is '312'.
5) Run RM ! INNAME is the transposed cube. Only the OUTNAME
is used, OUTCLASS is pre-set to 'ROTMES' and 'BFIELD'.