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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 e-mail programs:

-as a self-installing 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 2nd degree equation with graph—useful in analyzing 2nd 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 publication-quality. 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 Gauss-Newton nonlinear solver with the Levenberg--Marquart 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 (N-2) 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.