SciDAVis - Improvements SciDAVis Copy

Merged all changes made in the LapPlot SVN repos up to rev 58.
The changes relevant to SciDAVis are:
- new accessor macros
- new project properties adopted from LabPlot
- several missing "const"s added
- fixed undo for cell editing (validity is now correctly undone)
- fixed a couple of compiler warnings
- merged improved table menus and table normalization method
from 0.2.x branch
- several other minor changes

Fixed parameter substitution into formulas of fit curves.

Fixed a minor syntactic error.

- Fixed estimation of parameter errors in case of Nelder-Mead Simplex fitting
with unknown Y errors.

- Fixed FFT filters - cutoffs could fall between real and imaginary part of a
Fourier component, so that this component would (a) have its amplitude
reduced (but not set to zero) and (b) have its phase modified.

pics for manual version 0.2

final structure for manual version 0.2 (no more "dialog" chapter)

Merged r992:993 from current_stable.

- Fixed fix of estimation of parameter errors.
- Added fit plugins I used to verify fitting code against Misra1a and Chwirut1
datasets from NIST StRD.

Fixed some serious bugs in the curve fitting code, which would cause incorrect
computation results.

- bug #2102708: Weighted linear and polynomial fits required actual weights
(1/sigma^2) to be specified in place of standard errors, while all others
(as well as error bar plots) needed the standard errors themselves.
Solution: Switched everything to using standard errors, eliminating the term
"weighting" from the GUI and most of the source code.
Rationale: Avoid confusion for users, especially given the previous
inconsistent treatment of the matter. Avoid confusion for
devs. Arbitrary weights don't work naturally with non-linear fits;
and they almost certainly lead to nonsensical error estimates of
results (unless you _really_ know what you're doing, in which case
you can simply specify 1/sqrt(weight) as standard error).

- Fixed estimation of parameter errors in case of (scaled) Levenberg-Marquardt
fitting with unknown Y errors. See
http://www.gnu.org/software/gsl/manual/html_node/Computing-the-covariance-matrix-of-best-fit-parameters.html

- Fixed computation of R^2 in case of known Y errors.

Fixed some serious bugs in the curve fitting code, which would cause incorrect
computation results.

- bug #2102708: Weighted linear and polynomial fits required actual weights
(1/sigma^2) to be specified in place of standard errors, while all others
(as well as error bar plots) needed the standard errors themselves.
Solution: Switched everything to using standard errors, eliminating the term
"weighting" from the GUI and most of the source code.
Rationale: Avoid confusion for users, especially given the previous
inconsistent treatment of the matter. Avoid confusion for
devs. Arbitrary weights don't work naturally with non-linear fits;
and they almost certainly lead to nonsensical error estimates of
results (unless you _really_ know what you're doing, in which case
you can simply specify 1/sqrt(weight) as standard error).

- Fixed estimation of parameter errors in case of (scaled) Levenberg-Marquardt
fitting with unknown Y errors. See
http://www.gnu.org/software/gsl/manual/html_node/Computing-the-covariance-matrix-of-best-fit-parameters.html

- Fixed computation of R^2 in case of known Y errors.