Helper Modules
The helper modules collected for you by Edit Associates are intended to make authoring easier, by putting on your desktop graphing and calculation utilities necessary in processing and presenting your experimental data.
For reasons of avoiding clashes with your antivirus program, most of the modules write on disk and not in memory, so we advise NOT to place these modules in the Program Files folder, where the writing is usually supervised by the antivirus programs.
None of these modules will harm your computer and the package may be uninstalled easily.
This is a free service, and of course there is no obligation to use our editing services, but we would be happy to assist you.
You
can select how you want to use these modules according to the
settings of your download and email programs:
as
a selfinstalling archive http://www.editassociates.com/EA_Helpers_setup.exe
as
a zip archive of the above cabinet, http://www.editassociates.com/EA_Helpers_setup.zip
as
an archive of the “Edit Associates Helpers” folder http://www.editassociates.com/EA_Helpers_folder.zip
For this option you should unpack the archive and copy this folder
on an external drive (such as an USB stick) of your convenience. You
should place the link and the icon on your desktop manually.
The modules are listed below.

The Student
distribution
variable t
is
obtained for a given confidence interval
P and
a number of degrees of freedom v
. Such calculations enter in the confidence analysis of repeated measurements, mostly in Analytical Chemistry. Note that the results of your calculation do not disappear as you change the variables but are kept in the list box of the module for further reference 

A
handy periodic table of the elements, along with physical
constants and some atomic data. Again, the results of your queries are not deleted but kept in the list box below the Table. 

A
mathematical expression evaluator, including an advanced error
analysis, (thanks to Mark Morley (morley
at camosun.bc.ca command line parser). Again, the results of your queries are not deleted but kept in the list box below the edit line. 

A
2^{nd}
degree equation with graph—useful in analyzing 2^{nd} degree polynomial models. Again, the results of your queries are not deleted but kept in the list box below the edit lines. 

Solving
a linear system of equations and inverting a matrix are made
easier by using this module based on Gauss elimination. A
relevant example is provided. 

Eigenvalues
and eigenvectors of real symmetric matrices are a basic procedure
in Quantum Chemistry. Here the procedures from the Eispack/Slatec
package are implemented in a convenient way for easy handling of
such problems. A relevant example is provided for the Huckel method in Organic Chemistry. 

The
DatView module is helpful in visualizing results from batch
processing of data located in the same folder. Text
and tabular data formatted in two columns (raw data) and three
columns (raw vs. refined) may be visualized. Zooming
is available through the left mouse button. Unzoom is available
through the right zoom button. Relevant examples are provided. 
The
scientific programming needs are met by this module, where the GNU
FORTRAN 77 compiler (www.gnu.org) is enriched with the SLATEC
scientific library and Dislin7 scientific plotting facility. The SLATEC library contains numerical methods at the highest standard of the American Mathematical Society. The SLATEC library is in the public domain for this version of the GNU compiler. The Dislin library contains 2D plotting facilities producing graphs of publicationquality. The Dislin 7 library is also free for this version of the GNU compiler. Relevant
examples are provided. 

Unfolding
(deconvolution) of experimental peaks enables closer analysis of
overlapped peaks and of their tail details . Unfolding of experimental peaks is performed by using Fourier transforms of the experimental data and of the kernel, which can be chosen as Lorentzian or Gaussian line shapes. Tikhonov
regularisation based filtering is used. The width of the kernel lines may be selected with the spinner in the bottom right of the window. For closer examination a logarithmic scale may be used. Relevant examples are provided. The results may be saved. 


Smoothing of experimental data is frequently needed. With this module you have the possibility of repeating smoothing interactively. Zooming
and panning of the experimental pattern are available. Relevant
examples are provided. The results may be saved. 

This
module performs the least squares fit of a quadrupolar splitting
in Mossbauer spectra, or any other absorbtion spectrum consisting
in 2 peaks with Lorentzian line shape. A GaussNewton nonlinear solver with the LevenbergMarquart parameter is implemented. The results of successive fitting sessions are available in the list box below the fitted spectrum. Relevant examples are provided. The results may be saved. 

The
linear regression method frequently enters in such delicate tasks
as calibrations. Apart of the least squares parameters of the fitted line, the Student variable and confidence intervals are calculated for the (N2) degrees of freedom of the experimental data. The results may be saved. 

In absence
of experimental errors, the low degree polynomial is revealed, but
this is no more possible when noise is present. In presence
of experimental errors, the polynomial regression is an unstable
numerical procedure. The
module allows progressive application of the polynomial model with
increasing degrees, in order to avoid spurious description of
the data. Relevant examples are provided. The results may be saved. 

PrestoPlot, by Prof. David Shalloway at Cornell University not only plots publication quality graphs but also allows non linear least squares fitting of the data. The program is freeware and can be downloaded at ccl.net also. 

Tracer
by Marcus Karolewki at MIT ( karolewski at alumn.mit.edu) is
providing a convenient way to recover data from older plots made
on paper that have no digital equivalent available. This program is freeware. 
ImageJ,
by Wayne Rusband of the National Institutes of Health (nih.gov) is
the de facto standard in professional image processing. The
program is in the public domain. The present module is implementing an embedded variation of the program for your convenience. 