Contents

# Basis

For those who do not follow this site, GKPlot is a plotting program which, in the contrary of Excel, allows plotting data to publishable quality within minute. The program has been heavily updated since July and comes now to completion. This must be tried out.

GKPlot has been written in Java using the processing software. Processing is not originally used for programming this type of application but its ease of use and the possibility of making quick animations made it appealing.

# Videos

# Screenshots

RGA analysis of a spectrum acquired by an SRS Mass spectrometer

Excel like data handling, several functions available.

XPS spectrum acquired using an Omicron EA125

Data Import window allows the importation of any ASCII file

Peak Fitting using a GLT function of a TOF spectrum

Linear Peak fitting

Shirley Background Correction

# Features

- Fresh new look with dark theme 3d buttons and menus.
- New RGA, XPS, data menu.
- New import window which enable easily import from ASCII data or even SRS, MKS, CSV, OmicronDAT125 files.
- RGA menu with a new RGA library which is shown directly on the spectrum.
- XPS menu with a possibility of correcting spectrum with a linear or shirley background. Also FWHM, intensity and position of peaks are available.
- Peak Fitting using Gaussian, Lorentzian or even GLT just like casaXPS
- Data menu with several data handling options available.
- Smooth moving menu which is not affected by the amount of data even when handling 40000 data points.
- Drag the plot using the left mouse click
- Zoom in to the area of your choice by right click and dragging from left to right and bottom to top
- Zoom in to the maximum and minimum by right clicking only
- Use the buttons above (minX, min Y…) to fine tune the graph
- Save the data to a CSV file and save a config file for used parameters
- Export to PDF and JPG
- 6 different views available: Properties, Labels, Fitting, RGA, XPS, Plot views
- logarithmic / Linear scale
- General and scientific text
- Linear & Log curve fit. Equations used are explained below

# Download

Download Windows 32 / 64

DownloadLinux 32 / 64

DownloadMac

# Other Images

# History Log

Version 0.6

- New menu added
- Zoom out works for all 8 dataY.
- Gaussian peak fitting added
- Lorentz peak fitting added
- Gaussian X Lorentz + tail peak fitting added
- Only peak fitting for 1 peak but will be expanded in the future.

Version 0.5

- Fresh new look with dark theme 3d buttons and menus.
- New RGA, XPS, data menu.
- New import window which enable easily import from ASCII data or even SRS, MKS, CSV files.
- RGA menu with a new RGA library which is shown directly on the spectrum.
- XPS menu with a possibility of correcting spectrum with a linear or shirley background. Also FWHM, intensity and position of peaks is available.
- Data menu with several data handling options available.
- Smooth moving menu which is not affected by the amount of data even when handling 40000 data points.

Version 0.4

- Data window allowing the view and changes of data value.
- RGA library for RGA analysis
- Open RGA text files from the SRS supplier
- Export to PDF and JPG
- RGA view available
- graph data with points, lines and now with area

Version 0.3

- New set of good looking buttons
- Rolling Menu
- Save the data in a CSV file and the parameters used in a config file
- Open CSV data and previous parameters used by a config file. See Example in the Zip file
- Fit Log data
- Delete unwanted data
- Legend moveable around the screen
- Export PDF to a location of your choice

Version 0.2

- logarithmic / Linear scale
- General and scientific text
- Linear curve fit with equations explained in a previous post
- X, Y positions shown at the bottom
- More precise plot dragging

Version 0.1

- Drag the plot using the left mouse click
- Zoom in to the area of your choice by right click and dragging from left to right and bottom to top
- Zoom in to the maximum and minimum by right clicking only
- Use the buttons above (minX, min Y…) to fine tune the graph
- open CSV files
- Export to PDF. This export for now in the same folder as the executable.
- 2 different views are available

# Curve Fitting Explained

## Linear Curve fitting

With the data points in the form of

,

,

with a straight line fit is of the form:

To find the error using the least square method approach, one must calculate the square of the difference between each data point. For one datapoint , this will be of the form:

The least square approach requires to minimise the sum of the least square:

To minimise the error with respect to a or b, one must derivate it.

The equations above can be re-written as:

In a Matrix form this gives:

Which is also equal to:

Knowing that:

We can obtain for the equation above:

Therefore:

,

and

## Log Curve fitting

For functions of the form:

These can be transformed as follow:

,

which is equal to:

.

The solution from the linear fitting can now be used as this is equal to Y = ax+ c with Y = log(y) and b = log(c).

The Matrix form is as follow:

with the solutions to be:

,

or

.

,

and

# Shirley background explained

In most cases, XPS spectra require a background correction before peak fitting can be carried out. There are 3 different types of background corrections: Linear, Shirley and tougaard. The most widely used is the Shirley background as it is more or less accurate and somehow easy to compute. The essential feature of the algorithm is the iterative determination of the background using the areas A1 and A2 to compute the background intensity SB(E) :

where k is the step in the background and is the difference between I1 and I2. The calculation of the shirley is an iterative procedure as initially A1(E) and A2(E) are unknown and have to approximated using e.g. a linear correction of the background.

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