The SPFIT/SPCAT program suite of Pickett (available from JPL Molecular Spectroscopy) is currently the most widely used tool for analysis of high-resolution spectra and for their prediction, most notably for spectroscopy databases for atmospheric and astrophysical applications. The appeal of the package lies in flexible construction of the molecular Hamiltonian and in very efficient internal matrix factorization. This allows a single package to deal with widely varying molecular problems and for very fast operation. The package is well known for its steep learning curve so that various help documents (such as this one) are available.
of the programs have been published by HMP since these notes
started. Some comments may therefore have been superseded by
developments, and may not apply to the latest program versions. The
doublet PI subroutine set has not yet been used and statistical weights
on intensities have generally been disregarded. Many years have passed since these note were started and I currently find that I most often tend to jump directly to the Constants and
their names section. I also recommend the Notes and hints on SPFIT and Notes and hints on SPCAT, since these cover points that regularly pose difficulties to users.
SPFIT in the 1994 version worked only for J up to 100, since the March1997 version the J limits are (-270,369) for SPCAT, (-99,999) for SPFIT
Third line in the .par file (single quadrupolar nucleus, I=3/2):
s -4 1 0 ,0 , , , , , , ,
(three quadrupolar nuclei, I1=3/2, I2=1, I3=1, and F1,F2,F coupling):
s -334 1 0 ,0 , , , , , , ,
(three quadrupolar nuclei, I1=3/2, I2=1, I3=1, and I,I1,F coupling):
s -334 1 0 ,0 , , -1 , , , , ,
Remember to set KNMAX explicitly to zero. Also in case of symmetry equivalent nuclei use WTPL and WTML. For example for A1 and A2 states of 14N2...H2O the third lines of the .par file are:
s -33 1 0 , 0 , , -1 , 1. , 0. ,,,,,,,,,,, <---- A1
100 B or
Note that other similar fitted constants (i.e. those that have identical values by symmetry) all have to be declared in this way. If this is not done the resulting constant will be equal to the conventional value multiplied by its degeneracy. For spin-rotation, for example, use
In case of coupled constants the deviation of the second constant gives the overall deviation for both constants in the fit i.e. the deviation and value of constant 100 is the same as that of -30000 if the pair (20000, -30000) is used; since the Dec1996 version only the combined deviation is printed for both constants.
Line in the .lin file (single quadrupolar nucleus):
J' F' J'' F'' 0 0 0 0 0 0 0 0 freq error weight
Third line in the .par file(-1 defines symmetric top, 1 is for prolate symmetry, change to -1 for oblate top):
s -1 1 0 ,,,,,,,,,,,,,,,,,,
Important constants (prolate):
1000 A-B :prolate
Line in the .lin file:
J' K' J'' K'' 0 0 0 0 0 0 0 0 freq error weight
Note that K=3 (K=6 etc.) doublets are to be specified as
J+1 -3 J 3 0 0 0 0 0 0 0 0
The sign of K alternates between odd and even values of J. For a positive value of h3 and even J it is the K= −3 ← 3 component in SPFIT that is the higher frequency component, and 3 ← −3 is the higher frequency component for odd J. Also note that due to this cross type of declaration it is necessary to explicitly declare both components of unresolved K=3, K=6 doublets earlier than in other programs.
l-doubled v=1 states became possible in the March1997
version of the program. The declaration for this problem has evolved
with SPFIT and is currently (2008) somewhat different than originally
used. The key change is that many different tops are recognised
and a C3v top is now declared by using IAX=6.
s -1, 3, , , , 6, 2, 2, -1, 1, 1, ; this is the g.s.
s -1,-3, , , , 6, 2, 2, -1, 1, 1,
Note that the diagonalization option DIAG (twelfth parameter on the first of these lines) is to be set to 1 i.e. for a full projection assignment. Of the pair of doubled states the diagonal constants are to be declared only for the state EWT1=1 and the relevant constants are then:
1011 A-B 3011 B-C
200011 -2 A zeta.EE 600011 -2 C zeta.EE
for off-diagonal elements in the form 0.25[q-qJ J(J+1)..]. The second definition for q involves much more diagonalization and is therefore not recommended.
Transitions which are normally degenerate are best specified by using positive K. Those for l=+1 are declared as state EWT1=1, while those for l=−1 as EWT1=2. The K=0 (Kl−1=−1) is EWT1=2. The two K=l=±1 doublets are both EWT1=1 and their K assignment alternates with parity of J:
Prolate (positive q and Aζ) and EVEN J'':
J' -1 1 J'' 1 1 ....... A+ i.e. upper freq. component
Prolate (positive q and Aζ) and ODD J'':
J' 1 1 J'' -1 1 ....... A+ i.e. upper freq. component
Oblate (positive q, negative Cζ):
J' -1 1 J'' -1 1 ....... A+
Oblate (positive q, positive Cζ):
J' -1 1 J'' -1 1 ....... A-
If the E-symmetry states declared as v=1 and v=2 undergo Coriolis coupling with the A-symmetry state declared as v=0 then connecting constants are:
600001 200001 w = 2 root2 Omega B zeta.EA
where Ω = [sqrt(ωa/ωe)
sqrt(ωe/ωa)]/2 and ζEA
is the Coriolis constant
connecting the E and A states. The oblate
case has been extensively tested in Kisiel et al. J.Mol.Spectrosc. 251(2008)235-240, which contains a
more extensive table of parameter identifiers and their translation
into Hamiltonian terms.
Third line in the .par file:
Reduction-A, prolate (representation Ir):
a 1 1 0 ,,,,,,,,,,,,,,,,,,
Reduction-A, oblate (representation IIIl):
a 1 -1 0 ,,,,,,,,,,,,,,,,,,
Reduction-S, prolate (representation Ir):
s 1 1 0 ,,,,,,,,,,,,,,,,,,
Reduction-S, oblate (representation IIIl):
s 1 -1 0 ,,,,,,,,,,,,,,,,,,
Standard constants are as given in APPENDIX I. The difference in the third .par line between the use of A- and S-reductions is only in declaring different .nam files for constant names (and these files are currently optional). It is also possible to fit linear combinations of constants such as prolate (B+C), (B−C) declared using:
20000 value /(B+C)/2
or, in an alternative way, using:
20000 value /(B+C)/2
which is analogous to the way nuclear quadrupole coupling
constants are declared in the 'simple examples' at the end of SPINV.PDF.
type of declaration is possible since values from successive
instances of a parameter with the same index are additive.
10000 value /(A0+A1)/2
Line in the .lin file:
J' K-1' K+1' J'' K-1'' K+1'' 0 0 0 0 0 0 freq error weight
The lower of the two levels is to be given the identifier v=0, the upper v=1. The constants are then:
10000 A rotational constant for state v=0 etc.
Third line in the .par file (A-type, prolate):
a 1 2 0 ,,,,,,,,,,,,,,,,,,
Line in the .lin file:
J' K-1' K+1' v' J'' K-1'' K+1'' v'' 0 0 0 0 freq error weight
Specification is identical to the case above with the exception that only v''=0 to v'=1 transitions are specified (for absorption) and of the coupling terms only the energy difference term:
11 Delta E
is used. Transition frequency and its error can be specified in cm-1 if the error is made negative.
Three states need to be specified, ground state v=0, and the two excited states v=1 and v=2. The third line in the .par file is then
a 1 3 0 ,,,,,,,,,,,,,,,,,,
and some pertinent constants are:
20000 B for the ground state etc.
Values of the spin quantum number have to be rounded up to the nearest integer, so that the odd half integral spins are declared as: 1/2→1, 3/2→2, etc. The independent quadrupolar constants are specified as:
110010000 1.5 Chi.aa :Prolate
110030000 1.5 Chi.cc :Oblate
110610000 Chi.ab :Prolate and oblate
Third line in the .par file (A-type, prolate, spin 3/2):
a 4 1 0 ,,,,,,,,,,,,,,,,,,
Third line in the .par file (S-type, oblate, spin 3/2):
s 4 -1 0 ,,,,,,,,,,,,,,,,,,
Line in the .lin file:
J' K-1' K+1' F' J'' K-1'' K+1'' F'' 0 0 0 0 freq error weight
Notes from the single nucleus case above are applicable. Prolate rotor constants:
110010000 1.5 Chi.aa \
Third line in the .par file (A-type, prolate, spin1=3/2, spin2=1, and I,F coupling):
a 34 1 0 , , , -1 ,,,,,,,,,,,,,,,
Line in the .lin file (for I,F coupling):
J' K-1' K+1' I' F' J'' K-1'' K+1'' I'' F'' 0 0 freq error weight
The D coefficients are for Hss = I1.D.I2 and are (prolate):
120010000 1.5 D.aa
The first two digits define interacting nuclei. Note that the constant c3 for diatomics in Landolt-Bornstein vol.II/6,table 126.96.36.199 is Dbb=−(1/2) Daa, as only Dbb is spectroscopically determinable for linear and diatomic molecules.
The M coefficients are for Hsr = + I.M.J and thus:
10010000 M.aa for nucleus 1
For linear molecules the use of:
10000000 M for nucleus 1
is equivalent to the declaration:
10020000 M.bb for nucleus 1
Note that, following Flygare, a reverse Hamiltonian definition is often used i.e. Hsr = −I.M.J and the resulting M's have reversed signs relative to those above.
There are two relatively subtle points associated with understanding the errors in fitted parameters that are printed by SPFIT when you use the default FRAC=1 parameter (the seventh parameter in the second line of the .par file). These points are primarily of relevance for small datasets, and diminish in importance for large datasets fitted to close to RMS deviation of 1. Nevertheless if one wants to obtain exact correspondence between the results of SPFIT and those from other fitting programs then some corrections may be necessary.
Since weighted least-squares fitting programs all use the same basic statistical treatment it is useful to refer to the seminal paper on the subject (referred to below as ASZ):
D.L.Albritton, A.L.Schmeltekopf, R.N.Zare, "An introduction to the Least-Squares Fitting of Spectroscopic Data", in Molecular Spectroscopy: Modern Research, Ed. K.N.Rao, Academic Press, 1976, Chapter.1, p.1-67.
The two RMS quantities in the .fit output of SPFIT are:
(MICROWAVE RMS) = sqrt ( Sum[(obs-calc)**2]/Nlines )
Thus the deviations are worked out on the basis of a straightforward number of lines in the dataset, Nlines, and not the degrees of freedom Ndegf=Nlines-Nconst, where Nconst is the number of fitted constants. In ASZ, say Eq.31, the degrees of freedom, (n-m), are used. As a consequence, the deviations evaluated for small datasets by using Nlines instead of Ndegf may differ appreciably. Of course, as HMP points out, one can readily construct data sets with pathologies that make the assumption Ndegf=Nlines-Nconst inadequate, but it is nonetheless an assumption that is generally made. Even more suspicious is the statistics of relatively small numbers when Ndegf/Nlines is significantly less than unity, but this has never stopped spectroscopists from working in that regime!
In the standard application of weighted least-squares (section E5 of ASZ) only relative values of assumed experimental errors are of importance, and the estimated errors on parameters of fit (square roots of diagonal elements of the variance-covariance matrix Eq.33 ASZ) are insensitive to multiplication of assumed measurement errors by a constant factor c. If statistics are sufficient then the errors are standard errors (i.e. for 67% confidence level). For a fit with equal weights (same assumed error for all frequencies) you should get the same result irrespective of the value of the assumed error. This is not the case for SPFIT in which:
"The printed error in fitted constants is at the level of confidence assumed in declaring the uncertainties in experimental measurements in the .lin file".
In this case the absolute, and not only relative values of such measurement errors are of importance, and the printed errors cannot be automatically assumed to be standard errors. The choice made in SPFIT has been to forego the σ2 term in Eq.32 of ASZ. This has the consequence that even for an equally weighted fit changes in the values of the assumed measurement error will lead to changes in evaluated parameter errors.
The two points above are illustrated by fits made for D2S, where the results from the original publication (as reproduced in Table 8.24 of the 3rd Edition of the Gordy&Cook textbook) are used as the basis for the comparison. In the original work the cited errors are at the 95% confidence level, and were obtained by straightforward doubling of the derived standard errors. Those numbers can be seen to be in good correspondence with doubled errors from the ASFIT fit, which returns standard errors. The comparison is not exactly 100% only due to different rounding at the last digit and the possibility of typos (such as in the published error on C: 71 instead of possibly 61). On the other hand you can see that the SPFIT errors are directly dependent on the assumed measurement error even for (as in this case) equally weighted lines. The primary data files are collected in this archive. A similar exercise with an even more exact correspondence with the published data is possible for T2O, for which Ndegf/Nlines is even more pathological.
What you can see is that with SPFIT the values of assumed measurement errors are more important than with many other fitting programs, in which only relative magnitudes of such errors are relevant. In addition, once RMS ERROR deviates significantly from unity, you have to think about what is the confidence interval that the errors correspond to. Fortunately, if you were to care about actual standard errors then it is very easy to apply a suitable correction, see below.
What you can do:
1/ If you want to cite standard (1*sigma = 67% confidence level) errors on parameters fitted as a result of running SPFIT then you need to multiply the printed errors in parameters by
(RMS ERROR)*SQRT( N.lines/ (N.lines-N.fittedconsts) )
This can be done automatically with program PIFORM, which reformats the .fit output and, among other things, converts SPFIT errors to standard errors.
2/ An equivalent procedure is to multiply the assumed errors in frequencies by the same factor as above and to refit, whence you will obtain RMS ERROR of
SQRT( (N.lines-N.fittedconsts)/N.lines )
which will be equivalent to RMS error of unity if Ndegf was used in the statistics. The printed errors on fitted parameters will then be standard (67%) errors. If the dataset is large and the fitting model adequate then this procedure is in fact the way to establish the experimental error of the spectrometer used to make the measurements, and the RMS error will approach unity. For the D2S example with 0.2 MHz errors on frequencies, this procedure will correspond to resetting the measurement errors to:
0.2 * 0.46794 sqrt(66/44) = 1.14602
resulting in SPFIT RMS ERROR of
sqrt(44/66) = 0.81650
3/ For large datasets you may just set the FRAC parameter (the seventh parameter in the second line of the .par file) to the RMS ERROR from a converged fit and then refit. The resulting parameter errors will only differ from standard errors by the factor SQRT(Ndegf/Nlines). You can of course also account for this factor in FRAC and for the D2S example with 0.1 MHz errors on frequencies you will obtain actual standard errors by setting
FRAC = 0.93588 / sqrt(44/66) = 1.14602.
This procedure, as well as point (2), allow you to obtain standard errors on transition frequencies calculated by SPCAT, as printed in the second column of the .cat file. On the other hand, you have to take care, since it might be rather easy to forget that FRAC was set to some nonstandard value that was only valid for a specific fit.
4/ As of
July 2007 you can use negative values of the FRAC parameter in
SPFIT, in which case parameter errors will be equal to the multiple of
standard error that corresponds to the magnitude of FRAC. Hence FRAC=-1 will rescale
SPFIT errors internally using the relationship in point (1) above, so
that you will now get standard errors in the .fit output. Similarly FRAC=-2
will produce 2sigma (95% errors) and FRAC=-3 will lead
to 3sigma (99%) errors. Furthermore, the use of FRAC=-1, for
example, ensures that the errors in frequencies calculated by SPCAT
will also be standard errors etc.
WARNING: It has been discovered (March2016) that the negative FRAC mechanism, such as FRAC=-1, is not without some issues that are relevant to small datasets. In fact, the values of NDFREE in the multiplier
- - -
The bottom line is that whatever you do: "Do not automatically assume that the parameter errors printed by SPFIT are standard errors, especially when your RMS > 1, since you are then in danger of seriously underestimating your actual errors".
- - -
TRAP 1 results
specific meaning of the parameter errors obtained from the fit and the
associated subtleties are discussed in the section immediately
- - -
TRAP 2 is due
to the premature
assumption that a fit has converged. Note that a given fit can be
considered to be properly converged only if two
conditions are satisfied:
1/ The current and the predicted values of the RMS ERROR
are identical and you get screen output terminating in something
2/ The THRESH
parameter (the fifth parameter in the second line of the .par file) is zero. When the fit is properly converged
SPFIT will normally reset THRESH to 0.0000E+000.
this is not the case then you can try zeroing this parameter by
A confident sign of final convergence is that the fit terminates in one iteration and THRESH=0.0000E+000, irrespective of the number of iterations declared in the parameter NITR in the second line of the .par file.
- - -TRAP 3 is posed by the use of a priori parameter uncertainties, ERPAR, as declared next to the parameter values in the .par file. In some situations, like cases with strong intercorrelations between several constants, it is useful to reduce the search range for selected parameters with suitably chosen values of ERPAR. Nevertheless, in the final fit such errors should be reset to be at least an order of magnitude greater than the resulting errors in the fitted constants. Otherwise the solution may be artificially constrained and appear more precise than it really is.
- - -TRAP 4 results from the fact that almost all quartic centrifugal distortion constants in the .par file are negative relative to the usual convention, as you can check in this table. The only exception are the two off-diagonal S-reduction constants, d1 and d2. The recommended solution is to write the parameter descriptions explicitly in the .par file:
200 -5.007436030889545E-004 1.00000000E+000 /-DJ
1100 -3.854253318510433E-003 1.00000000E+000 /-DJK
2000 -9.473858803517874E-003 1.00000000E+000 /-DK
40100 -9.570171396103077E-005 1.00000000E+000 /d1
50000 -1.774207632318250E-005 1.00000000E+000 /d2
You can then optionally use the program PIFORM to automatically recover the values of fitted parameters and of their errors in the form normally used for publication.
- - -TRAP 5 is associated with impoper use of the DIAG parameter (twelfth parameter in third line of .par). The use of a suitable value of DIAG is crucial when there is a high density of states and complex quantisation. There is, regrettably, no universal solution and for this reason there are many alternative settings of DIAG. Conversely, the use of an inapropriate DIAG , especially in simple cases, may lead to spurious quantisation and spurious (sometimes very strong) transition series. It is usually best to commence a new problem with DIAG=0.
If the fit goes haywire make sure to recover the original .par by copying from the .bak version automatically saved by SPFIT at the beginning of this fitting run, using the command: copy xxx.bak xxx.par. It is also good practice to keep good .par and .fit files under different names such as xxx.good.par
In order to fix a value of a constant set its a priori error
to well below the least significant digit of the constant. The
smallest value that can be used is 1.E-37.
also possible to actually zero the value of a constant by using the
following for the value and
the error (PAR
In order to omit a line from the fit or to predict a line carrying zero frequency:
It is possible to assign a zero error to a line and such a line will most of the time be rejected from the fit. This mechanism is not safe, however, since if accidentally the obs-calc deviation for this line falls below a certain threshold (of the order of 0.001) then this line can be captured into the fit and in consequence will distort it.
To run a prediction from known constants but without any lines set up a dummy .lin file with just one line carrying legal quantum numbers and fix all constants in the .par file. Then run SPFIT, which will generate .bin and .var files, so that SPCAT can then be run.
The .lin file is, in the current program version, read either to the number of lines declared in the .par file or to the first blank line, whichever comes first. There is thus no need to count the number of lines manually: just set an excessively large number in the .par file.
Uncertain lines/additional information can be kept at the end of the .lin file, after at least one blank line, and will not interfere with running of the program. Furthermore, it is possible to place comments at the end of each line, and this is used for example in the annotation scheme used by the PIFORM program.
The .par file is acted on up to the number of declared parameters, or to
the first blank line, whichever comes first. However, if there are
non-blank lines after the declared parameters, then those will be
echoed to the .par file resulting from the fit. This mechanism provides a very useful way of keeping an annotated history of fits in
the .par file, including previous versions of this
file. There is a limitation in that
only the first 80 columns of such lines are copied over.
SPFIT no longer requires access to descriptive names of constants that were taken from the .nam files. It is sufficient to place an appropriate alphanumeric comment at the end of the parameter declaration line and this will be carried over to resulting .par files. Note that this comment has to be separated by a space and a slash, and cannot be longer than 10 characters:
1200 2.095827797711319E-007 1.00000000E+000 /HJK
The use of a negative parameter identifier in the .par file has, as the primary function, the declaration of a parameter for which the value follows that of an immediately preceding parameter by a constant ratio.
A second feature is that it is also possible to construct a dependent parameter in such a way that it is a linear combination of independent parameters. This is because the values corresponding to the same negative parameter identifier following several different positive identifiers are additive. An example of this is given by HMP in his documentation, as the last of the 'simple examples'.
In fitting of problems with strong intercorrelations between several constants it is useful to reduce their search range with suitably chosen a priori errors. WARNING: in the final fit such errors should be at least an order of magnitude greater than the errors in the fitted constants. Otherwise the solution may be artificially constrained and appear more precise than it really is.
Compilation with NDP-F-486 3.1:
mf77 -exp -phar2 -OLM -onrc -nomap calfit.for subfit.for
The dimensioning in the top PARAMETER statement in CALFIT may be changed as required, and the original versions of routines ULIB, SLIB, SPINV which contain SAVE calls by name of COMMON block are necessary.
Compilation with SG Fortran:
f77 -O2 -static -o spfit calfit.for subfit.for ulib.for blas.for
Compilation with MS Power-Fortran:
fl32 -G4 -Ox calfit.for subfit.for ulib.for blas.for slib.for
The .int file requires the rotational partition function Qr which should by default be calculated for 300K. Intensities for other temperatures such as those of supersonic expansion could earlier only be recalculated externally, which can be done with PISORT. It is now also possible to calculate intensities for a specified temperature with SPCAT, but remember that, apart from specifying the temperature in the .int file, it is also necessary to calculate Qr for this temperature. Some commonly used approximations for Qr are given below.
For a linear top (Gordy & Cook, ed.3 p.57, Eq.3.64):
Qr = kT/(hB) = 2.0837x104 T/B ; B/MHz, T/K
For a (prolate) symmetric top (G&C, Eq.3.68):
Qr = 5.3311x106 (T 3/(B 2 A))1/2 /sigma ; A,B/MHz, T/K
For an asymmetric top (G&C, Eq.3.69):
Qr = 5.3311x106 (T 3/(A B C))1/2 /sigma ; A,B,C/MHz, T/K
The line intensity (i.e. LGSTR.) tabulated in the SPCAT output is the logarithm of intensity Iba(T) as defined in Eq.(1,2) of the catdoc.pdf documentation file for the jpl catalogue, and is in units of nm2MHz. Conversion to peak absorption coefficient αmax in cm-1 is made with Eq.(5) of the documentation, i.e.
αmax = 102.458 xIba(T)/Δν,
where Δν is the HWHH in MHz at 1 Torr pressure. If the symmetry factor σ and the nuclear spin weight gI are both unity then Iba(T) is a factor of (102.458/20)x0.95=4.87 smaller than αmax calculated by ASROT, which uses Eq.7.73, p.263 G&C, and assumes Δν=20MHz, Fv=0.95. For prediction of intensities for a vibrational state with Fv lower than 1, use Qr/Fv for Qr.
Dipole moments are to be specified as:
1 x.xxx mua/D for state v=0
Since it is the .var file and not the .par file that is used by SPCAT it is possible to change predictions by editing some control parameters in the .var file without the need for a new fit.
Partition function, hyperfine structure and state multiplicity:
The SPFIT/SPCAT package provides several ways of dealing with predictions for higher-J transitions for a molecule with a quadrupolar atom. The lowest-J rotational transitions will show nuclear quadrupole hyperfine structure, but in higher-J transitions this will be completely collapsed and is usually ignored. Databases set up for astrophysicists use several possible approaches so it is useful to discuss the differences. The HCCCN molecule is used as an example, and it contains a single 14N nucleus, nuclear spin I=1. The various possibilities for generating line lists are:
CASE 2: Hyperfine structure is implicit, as treated in the 51001 species entry in the jpl database. Explicit nuclear spin is ignored as in CASE 1, so that spin degeneracy SPIND
is also declared as 1. But each rotational level is declared to be triply degenerate, using WTPL=3, WTMN=3. In consequence, there are three times more levels to be counted in evaluation of the partition function and its room temperature value required in the .int file is therefore Q(300K)=4124.495. Nevertheless, the calculated transition intensities as given by the LGINT values in the .cat file are identical to those from CASE 1.
Compilation with NDP-F-486 3.1:
mf77 -exp -phar2 -OLM -onrc -nomap calcat.for ulib.for
Compilation with MS-Power Fortran:
fl32 -G4 -Ox calcat.for ulib.for blas.for slib.for spinv.for
The dimensioning in the top PARAMETER statement in CALCAT may be changed as required and other notes for compilation of SPFIT are also applicable.
projection type TYP_ _KSQ = power of K^2
10000 A 10000 A spin 1: 11 E1
500 PJ 500 PJ
Windows Vista introduced a new protective software layer called User Account Control (UAC). Under default settings the launching of some programs triggers UAC and you are asked to explicitly confirm that they are bona fide, even if you are an administrator. Large (but not small) runs of SPFIT/SPCAT trigger UAC. The problem is that you do not get the chance to do anything and the programs either hang up or crash. Both SPFIT and SPCAT are subject to this, and the objectionable action seems to be the generation of a scratch memory area for larger sorting operations:
SPFIT: crashes while reading in the .LIN file with the console message "scratch file write error"
SPCAT: hangs after the final "STARTING QUANTUM xx" message at the stage when it would commence sorting the .CAT file in frequency
Switching off UAC altogether cures this problem but it is not recommended. There are various ways of dealing with the problem at the system configuration level, but those also depend on which version of Vista you might have. The simplest and noninvasive way of circumventing this problem is to:
Launching of this "Command Prompt" window still requires one confirmatory click from UAC, but any programs run from within this window will not be subject to further UAC scrutiny. This special window is identified by the word "Administrator:" at the beginning of the text on the top bar. The same technique should work also for programs that use SPFIT/SPCAT in some batch mode, or you can just run such programs from the prepared "Command Prompt" window.
If you run your programs from a file manager, such as Total Commander, then an even better solution is to launch the file manager itself in the "Run as administrator" mode. You can read more about UAC here and here.
(none of this should be necessary with C-versions of the programs although the largest cases dealt with using the manually extended versions did not want to run with those)
With standard parameter values (i.e. program with dimensioning as obtained in 1994 from H.M.Pickett) there was a diagnostic
"spin states truncated in SETSP 18 36"
and for I,F double quadrupole formulation the energy levels for F<I were not calculated.
--> this diagnostic was traced to limit on parameter NX which was set to NX=17 in several parameter statements in SPINV.FOR. When this was changed to NX=36 there was a diagnostic
"total number of sub-blocks per F is too large"
--> this was identified to be associated with MAXQ=100 in several parameter statements in SPINV. On change to MAXQ=200 there was a diagnostic
"GETQQ: too many subblocks 36"
--> this was associated with the limit MAXS=36 in several parameter statements in SPINV. On change to MAXS=72 the predictive calculation for CH2I2 went without hiccups up to J=9. Maximum dimension of hamiltonian=576,J=10 (@ HEAPLN=550000), calc. taking over 1 hour on 486/33+NDP Fortran. However J=10 was not calculated.
--> this was caused by insufficient value of NDMX in SPINV. On change from NDMX=350 to NDMX=700 in SPINV and also on change in CALCAT.FOR from NDEGY=350 to NDEGY=700 and to HEAPLN=1500000 then calculation for CH2I2 appeared possible up to at least J=18.
--> In routine FILGET in SLIB.FOR change
so that programs can be used by opening branches for molecules in the program catalogue and no other subdirs are necessary