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include "ms.h"
# FIT_AND_CLEAN -- Iteratively fit profile scales using banded matrix method
# and remove deviant pixels.
#
# The profile fitting and cleaning are combined in order to minimize
# the calculations in re-evaluating the least squares fit after rejecting
# deviant pixels.
#
# The sigma of the fit is calculated and deviant pixels are those whose
# residual is more than +-sigma_cut * sigma.
# The maximum number of pixels to be replaced is max_replace.
# If max_replace is zero then only the model fitting is performed.
#
# The output of this routine are the cleaned data profiles and the
# least-square fitted model profiles. Return the number of pixels replaced.
procedure fit_and_clean (ms, data, model, ranges, profiles, len_line,
len_profile, nspectra, nparams)
pointer ms # MULTISPEC data structure
real data[len_line] # Input data to be fit
real model[len_line] # Output model line
real ranges[nspectra, LEN_RANGES, 3] # Profile ranges
real profiles[len_profile, nspectra, nparams, 3] # Model profiles
int len_line # Length of data/model line
int len_profile # Length of each profile
int nspectra # Number of spectra
int nparams # Number model parameters
int max_iterate # Maximum number of iterations
int max_replace # Maximum number of bad pixels
real sigma_cut # Rejection cutoff
int fit_type # Type of I0 fitting
bool ex_model # Extract model?
bool exmod
int i_max, nmax, option, npts
int i, iteration, n_total, n_reject
real sigma, lower, upper, residual, resid_min, resid_max
begin
# Initialize the model and I0 parameters to zero.
call aclrr (PARAMETER(ms,I0,1), nspectra)
call aclrr (model, len_line)
# Loop until no further deviant pixels are found.
n_total = 0
do iteration = 1, imax {
# Determine I0 for each profile.
switch (option) {
case 1:
call full_solution (ms, data, model, ranges, profiles,
len_line, len_profile, nspectra, nparams)
case 2:
call quick_solution (ms, data, ranges, profiles, len_line,
len_profile, nspectra)
}
# Set the model to be used to compare against the data.
call set_model (ms, model, profiles, ranges, len_line, len_profile,
nspectra)
# If number of pixels to reject is zero then skip below.
n_reject = 0
if (n_total == nmax)
break
# Compute sigma of fit.
sigma = 0.
npts = 0
do i = 1, len_line {
if ((model[i] > 0.) && (!IS_INDEFR (data[i]))) {
sigma = sigma + (data[i] - model[i]) ** 2
npts = npts + 1
}
}
sigma = sqrt (sigma / npts)
resid_min = -lower * sigma
resid_max = upper * sigma
# Compare each pixel against the model and set deviant pixels
# to INDEFR. If the number of pixels replaced is equal to the
# maximum allowed stop cleaning. Ignore points with model <= 0.
# Thus, points outside the spectra will not be cleaned.
# Ignore INDEFR pixels.
do i = 1, len_line {
if (n_total == nmax)
break
if ((model[i] <= 0.) || (IS_INDEFR (data[i])))
next
# Determine deviant pixels.
residual = data[i] - model[i]
if ((residual < resid_min) || (residual > resid_max)) {
# Flag deviant pixel.
data[i] = INDEFR
n_total = n_total + 1
n_reject = n_reject + 1
}
}
if (n_reject == 0)
break
}
# Refit model if a model extraction is desired and bad pixels were
# in the last fit.
if (exmod && n_reject != 0) {
switch (option) {
case 1:
call full_solution (ms, data, model, ranges, profiles,
len_line, len_profile, nspectra, nparams)
case 2:
call quick_solution (ms, data, ranges, profiles, len_line,
len_profile, nspectra)
}
}
# Scale profiles to form model profiles.
do i = 1, nspectra
call amulkr (profiles[1,i,I0_INDEX,1], PARAMETER(ms,I0,i),
profiles[1,i,I0_INDEX,1], len_profile)
# Replace deviant or INDEF pixels by model values.
# Even if no cleaning was done there may have been some INDEF points
# in the input data line.
do i = 1, len_line {
if (IS_INDEFR (data[i]))
data[i] = model[i]
}
# Print the number of pixels replaced and return.
call ex_prnt3 (n_total)
return
# SET_FIT_AND_CLEAN -- Set the fitting and cleaning parameters.
entry set_fit_and_clean (max_iterate, max_replace, sigma_cut, fit_type,
ex_model)
imax = max_iterate
nmax = max_replace
lower = sigma_cut
upper = sigma_cut
option = fit_type
exmod = ex_model
return
end
procedure full_solution (ms, data, model, ranges, profiles, len_line,
len_profile, nspectra, nparams)
pointer ms # MULTISPEC data structure
real data[len_line] # Input data to be fit
real model[len_line] # Output model line
real ranges[nspectra, LEN_RANGES, 3] # Profile ranges
real profiles[len_profile, nspectra, nparams, 3] # Model profiles
int len_line # Length of data/model line
int len_profile # Length of each profile
int nspectra # Number of spectra
int nparams # Number model parameters
real rnorm
pointer sp, fitparams, solution, offset
begin
# Initialize fitparams and ranges arrays.
call smark (sp)
call salloc (fitparams, nspectra * nparams, TY_REAL)
call salloc (solution, nspectra * nparams, TY_REAL)
offset = (I0_INDEX - 1) * nspectra
call amovki (NO, Memr[fitparams], nspectra * nparams)
call amovki (YES, Memr[fitparams + offset], nspectra)
# Do least squares banded matrix solution for I0 parameters.
# The solution vector contains the least square fit values which
# must be copied to the I0 parameter vector.
call solve (ms, data, model, Memr[fitparams], profiles, ranges,
len_line, len_profile, nspectra, nparams, Memr[solution], rnorm)
call aaddr (PARAMETER(ms, I0, 1), Memr[solution + offset],
PARAMETER(ms, I0, 1), nspectra)
call sfree (sp)
end
# QUICK_SOLUTION -- Quick determination of profile scaling parameters.
procedure quick_solution (ms, data, ranges, profiles, len_line, len_profile,
nspectra)
pointer ms # MULTISPEC data structure
real data[len_line] # Input data to be fit
real ranges[nspectra, LEN_RANGES] # Profile ranges
real profiles[len_profile, nspectra, ARB] # Model profiles
int len_line # Length of data/model line
int len_profile # Length of each profile
int nspectra # Number of spectra
int i, ic, j, n, spectrum, xc
real i0[3]
begin
ic = len_profile / 2
# Determine a value for I0 for each spectrum which is in the image.
do spectrum = 1, nspectra {
n = 0
# Check each profile point from ic on until n = 2.
do i = ic, len_profile - 1 {
xc = ranges[spectrum, X_START] + i
if ((xc < 1) || (xc > len_line))
next
if (IS_INDEFR (data[xc]))
next
j = i + 1
if (profiles[j, spectrum, I0_INDEX] <= 0)
next
n = n + 1
i0[n] = data[xc] / profiles[j, spectrum, I0_INDEX]
if (n >= 2)
break
}
# Check each profile point from ic - 1 and less until n = 3.
do i = ic - 1, 0, -1 {
xc = ranges[spectrum, X_START] + i
if ((xc < 1) || (xc > len_line))
next
if (IS_INDEFR (data[xc]))
next
j = i + 1
if (profiles[j, spectrum, I0_INDEX] <= 0)
next
n = n + 1
i0[n] = data[xc] / profiles[j, spectrum, I0_INDEX]
break
}
# Determine I0.
switch (n) {
case 3: # Use median I0
call asrtr (i0, i0, n)
PARAMETER(ms, I0, spectrum) = i0[2]
case 2: # Use mean I0
PARAMETER(ms, I0, spectrum) = (i0[1] + i0[2]) / 2
case 1: # Use only value
PARAMETER(ms, I0, spectrum) = i0[1]
}
}
end
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