PVL Randlsq Parameter File Format

Written by Ben Atkin
June 15, 2005
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The randlsq parameter format is the format understood by the perl script, runrandlsq. runrandlsq reads it in, generates an old-style parameter file that the Fortran program, randlsq, can understand, and runs randlsq.

File Contents

  - Any combination of: latitude, longitude, radius, alpha_angle,
        delta_angle, kappa_angle, right_ascension, declination, and
        rotation_rate.
  - In ellipsoidal solutions, axis_a, axis_b, axis_c, and long_offset
        are also options.
  - For focal length solutions, there is a focal_length option.

Formatting

Comments

# This is a comment

Key = Value Pairs

Keys and values (except for filenames) are not case sensitive.

Key = Value

Lists

A special type of value is a list. Valid lists:

FIX_LATITUDE = {}
FIX_LONGITUDE = { 1001 }

FIX_LATITUDE = { A0004, A0005 }
FIX_LONGITUDE = { A0004,
  A0005
}

Note: The opening curly brace must appear on the same line as the key and equals sign.

Sample Data

# randlsq parameter file

# Target body
target = Titan

# Target definition
targdef = /targets/titan.def.1

# Longitude type (east, west, or tdef)
longitude_type = tdef

# Use planet angles? (yes/no)
use_planet_angles = no

# Type of solution (general, ellipsoid, or focal_length)
solution_type = general

# Variables to solve for.
#   - Any combination of: latitude, longitude, radius, alpha_angle,
#         delta_angle, kappa_angle, right_ascension, declination, and
#         rotation_rate.
#   - In ellipsoidal solutions, axis_a, axis_b, axis_c, and long_offset
#         are also options.
#   - For focal length solutions, there is a focal_length option.
solve_for = (latitude, longitude, alpha_angle, delta_angle, kappa_angle)

# Lists are comma-separated

# Points to fix (point id's)
fix_latitude  = { }
fix_longitude = { }

# Images to fix (fsc's)
fix_alpha = { }
fix_delta = { }
fix_kappa = { }

# Solution method (matrix_inversion or conjugate_gradient)
solution_method = matrix_inversion

# Compute uncertainties?  (only available with matrix_inversion)
compute_uncertainties = yes

# Number of iterations
iterations = 10
conjugate_gradient_iterations = 1834